Work Zone Road User Costs - Concepts and Applications

Chapter 2. Work Zone Road User Costs

2.1 Definition of Work Zone Road User Cost

A work zone is defined in the Highway Capacity Manual (HCM) as a segment of highway in which maintenance and construction operations impinge on the number of lanes available to traffic or affect the operational characteristics of traffic flowing through the segment. (Highway Capacity Manual 2000, Transportation Research Board, Washington, DC, 2000.)

A work zone is defined in the Manual on Uniform Traffic Control Devices (MUTCD) as an area of a highway with construction, maintenance, or utility work activities. A work zone typically is marked by signs, channelizing devices, barriers, pavement markings, and/or work vehicles. It extends from the first warning sign or high-intensity rotating, flashing, oscillating, or strobe lights on a vehicle to the END ROAD WORK sign or the last temporary traffic control device. (Manual on Uniform Traffic Control Devices for Streets and Highways, 2009 Edition, Federal Highway Administration, Washington, DC, 2009.)

Work zone road user cost is defined as the additional costs borne by motorists and the community at-large as a result of work zone activity.

Within the context of this document, WZ RUC primarily refers to the monetized components of work zone impacts, such as the user delay costs, vehicle operating costs (VOC), crash costs and emission costs. Increasingly, other off-site components such as noise, business and local community impacts are being utilized in WZ RUC applications. These off-site impacts are hard to monetize since the factors that influence their computation are often site-specific and no generalized method or tool is yet available to determine them. In this document, these off-site impacts are either considered as quantitative /non-monetary (e.g. noise) or qualitative (e.g. inconvenience to local community) factors. The components of WZ RUC are illustrated in Figure 1 and discussed in greater detail in the sections that follow. The practitioners can use their discretion in selecting appropriate work zone impacts to be used in WZ RUC analysis.

Figure 1. Road user cost components.

The WZ RUC computation process is based on the assessment of mobility, safety, environmental, business, and local community impacts resulting from the work zone activities of a roadway project. The WZ RUC computation along with the work zone impacts assessment evolves through various stages of the project development process from planning through construction. The precision of WZ RUC estimate and, the type and level of detail of impacts assessment vary depending upon the project development stage. (Sankar, P., K. Jeannotte, J. P. Arch, M. Romero, and J. E. Bryden, Work Zone Impacts Assessment – An Approach to Assess and Manage Work Zone Safety and Mobility Impacts of Road Projects, Report No. FHWA-HOP-05-068, Office of Operations, Federal Highway Administration, Washington, DC, 2006.) For example, in the project scoping stage, a conceptual estimation or qualitative information of WZ RUC may be used in identifying the significance of potential impacts; and during preliminary engineering a rough estimation of WZ RUC will be determined for use in MOT strategy selection; whereas, in the 90 percent design stage, a precise estimate will be determined for use in setting the contract provisions such as lane rental fee and incentives/disincentives.

The WZ RUC computation process involves the following key steps:

• Data gathering for work zone impact assessment.
• Estimation of work zone impacts.
• Computation of unit costs for each impact type.
• Estimation of WZ RUC components.

This chapter presents a detailed discussion of the key concepts of quantifiable monetary impacts. The process involved in deriving the monetary components and their unit costs is illustrated using step-by-step procedures. A less-rigorous discussion of non-monetary and qualitative factors is also presented. Later sections of this chapter focus on data requirements for mobility analysis and computation tools available for WZ RUC estimation.

2.2 Travel Delay Costs

Travel delay costs are calculated by multiplying the estimated delays to personal travel, truck travel, and freight inventory caused by the work zone by the unit cost ($/hr) of travel time. Figure 2 presents the computation of travel delay costs schematically.

2.2.1 Delay Time

Delay time is the additional travel time necessary to traverse the work zone or to detour around it. Delay time is an aggregation of the following components:

• Speed change delay is the additional time necessary to decelerate from the upstream approach speed to the work zone speed and then to accelerate back to the initial approach speed after traversing the work zone under unrestricted (free) traffic flow.
• Reduced speed delay is the additional time necessary to traverse the work zone at the lower posted speed; it depends on the upstream and work zone speed differential and length of the work zone under both unrestricted and restricted (forced) traffic flow.
• Detour delay is the additional time necessary to travel the excess distance by selecting a detour route.

Figure 2. Schematic illustrating the components of travel delay costs.

• Stopping delay is the additional time necessary to come to a complete stop from the upstream approach speed (instead of just slowing to the work zone speed) and the additional time to accelerate back to the approach speed after traversing the work zone under restricted traffic flow.
• Queue delay is the additional time necessary to creep through the queue under restricted traffic flow.

Work zone traffic delay time estimates can be obtained using mobility impact analysis methods such as demand-capacity analysis and simulation methods. The inputs required for mobility analysis are discussed in section 2.8. A discussion of various tools readily available for delay time estimation and WZ RUC computation is presented in section 2.9. Note that the estimated mobility parameters may change based on the selected tool, as the methodologies utilized in these tools may be different. Delay time during construction also can be estimated using the floating-car technique, where a test car is driven by an observer along the work zone section a number of times to measure the travel time.

2.2.2 Monetary Value of Travel Time

Like goods and services, time spent traveling in a vehicle is a resource with economic value. The monetary value of travel time is based on the concept that time spent traveling otherwise would have been spent productively, whether for remunerative work or recreation. The United States Department of Transportation (USDOT) Office of the Secretary of Transportation (OST) provides guidelines and procedures for calculating the value of travel time saved or lost by road users. (USDOT, Valuation of Travel Time in Economic Analysis-Revised Departmental Guidance, Memorandum, Office of the Secretary of Transportation, U.S. Department of Transportation, Washington, DC. 2003.) (The value of travel time can be established using the wage rate method or road users’ stated/revealed preference. The OST guidance is based on the wage rate method. Under the stated/revealed preference method, the information on road users’ alternative choice of route or travel mode is gathered through surveys or polling. Based on the collected information, the associated travel time and cost differentials between the baseline and the preferred alternative choices are used in establishing the value of travel time through statistical modeling.)

Monetary value of travel time is a sum of:

• Dollar value of personal travel time (only passenger cars).
• Dollar value of business travel time (only passenger cars).
• Value of truck travel time (only trucks).
• Cost of freight inventory delay (only trucks).
• Cost of vehicle depreciation (all vehicles).

Note that the available unit cost data used in the computation of these monetary components may not reflect current or most recent year statistics. Practitioners are advised to adjust the existing year data to current year data using appropriate adjustment factors mentioned herein. In addition, the highway agencies can use their discretion in combining or eliminating smaller cost components as deemed appropriate.

2.2.2.1 Monetary Value of Personal Travel Time

The hourly dollar value of road users’ personal travel time is estimated based on some percentage of their wages. The steps involved in monetizing the personal travel delay time are enumerated as follows.

Step 1. Determine the proportion of passenger cars on personal travel. This proportion may vary with the type of travel: local or intercity. The number of person miles reported in the National Household Transportation Survey (NHTS) is used in determining the proportion of passenger cars on personal travel. Travel patterns reported in the NHTS and the Nationwide Personal Transportation Survey (NPTS) over the past 20 years are summarized in Table 1.

Table 1. Ratio of personal and business travel.

Study	Travel Type	Personal	Business
1990 NPTS (Hu, P. S. and J. Young, 1990 Nationwide Personal Transportation Survey (NPTS) Databook, Report No. FHWA-PL-94-010A, Prepared by Oak Ridge National Laboratory, Submitted to the Office of Highway Information Management, Federal Highway Administration, Washington, DC, November 1993.)	Local (Reported in 1990 NPTS Databook, Vol. I, Table 4.41, page 4-72.)	95.8%	4.2%
	Intercity (Reported in 1990 NPTS Databook, Vol. II, Table 8.13, page 8-22.)	95.0%	5.0%
1995 NPTS (Oak Ridge National Laboratory, 1995 Nationwide Personal Transportation Survey (NPTS) Databook, Report No. ORNL/TM-2001/248, Prepared for FHWA Office of Highway Information Management, Oak Ridge National Laboratory, Oak Ridge, TN, October, 2001.)	Not Specified	94.2%	5.8%
2001 NHTS (Hu, P. S. and T. R. Reuscher, Summary of Travel Trends, 2001 National Household Travel Survey, Prepared by Oak Ridge National Laboratory, Submitted to the Federal Highway Administration, Washington, DC, November 2004.)	Not Specified	91.9%	8.1%
2009 NHTS (Obtained from NHTS Online Analysis Tools - Table Designer using the variables: 1990 Trip Purpose and the annual person miles of travel (for Step 4)/ average vehicle occupancy (for Step 5).)	Not Specified	93.7%	6.3%

Step 2. Establish the average vehicle occupancy (AVO) of passenger cars. The AVO is the ratio of person-miles of travel and vehicle-miles of travel by trip type. (Obtained from NHTS Online Analysis Tools - Table Designer using the variables: 1990 Trip Purpose and the annual person miles of travel (for Step 4)/ average vehicle occupancy (for Step 5).) Refer to Table 2 for the recent NHTS estimates of AVO values. The average AVO for personal travel was 1.67 in 2009. The AVO of intercity personal travel is higher than that of local personal travel. Estimates of 1990 NPTS (Vol. 2, Table 8.15, of the NPTS report) indicate that the AVO factor for intercity travel was 2.30, whereas the AVO for local travel was 1.66. By selecting an appropriate AVO, the delay time can be converted from person-hours to vehicle-hours or vice-versa.

Table 2. HTS estimates of average vehicle occupancy factors of personal and business travel.

Purpose of Trip (1990 definition)		1995	2001	2009
Work-related business		1.20	1.22	1.24
Personal	To or from work	1.14	1.14	1.13
	Shopping	1.74	1.77	1.78
	Other family /personal business	1.78	1.85	1.84
	School/church	1.68	1.76	1.77
	Doctor/dentist	1.51	1.64	1.59
	Vacation	2.33	2.42	2.7
	Visit friends or relatives	1.83	1.88	2.08
	Other social or recreational	2.18	2.09	2.2
	Other	1.82	1.89	1.96
	Not ascertained	2.39	1.65	1.93
	Overall personal	1.67	1.75	1.67
All travel		1.59	1.63	1.67

Source: NHTS Online Analysis Tools

Step 3. Estimate per hour monetary value of travel time for a person on personal travel. The dollar value of personal travel time (per person –hr) is estimated using the median annual income for all U.S. households reported by the U.S. Census Bureau, in accordance with the OST guidelines (see Table 3). (Median Household Income reported by US Census Bureau.)

Table 3. OST guidelines for calculating value of personal travel time.

Travel Type	Per Person-Hour as a percent of Wage Rate	Data Source
Local	50% (35-60%)	Median annual income for all U.S. households divided by 2080 hours. Reported in U.S. Census Bureau. State or local income data can be substituted in lieu of national statistics.
Intercity	70% (60-90%)	Median annual income for all U.S. households divided by 2080 hours. Reported in U.S. Census Bureau. State or local income data can be substituted in lieu of national statistics.

Hourly value of personal travel time per person is calculated as:

For local personal travel,

Hourly value of personal travel time per person = 50% of median annual household income ÷ 2080 hours.
Median annual income for all U.S. households = $49,445 (for 2010). (DeNavas-Walt, C., B. D. Proctor, J. C. Smith, Income, Poverty, and Health Insurance Coverage in the United States: 2010, Report No. P60-239, US Census Bureau, September 2011.)
Hourly value of personal travel time = 0.5* $49,445/2080 = $11.89/person -hr

For intercity personal travel,

Hourly value of personal travel time per person = 70% of median annual household income ÷ 2080 hours.
Median annual income for all U.S. households = $49,445 (for 2010)
Hourly value of personal travel time = 0.7* $49,445 /2080 = $16.64/person –hr

Step 4. Compute per hour monetary value of travel time for a vehicle on personal travel. The dollar value of personal travel time for all occupants in a vehicle, in terms of dollar/vehicle-hr, is computed by multiplying the dollar value of hourly travel time per person with an appropriate AVO factor. In other words, the hourly travel time per person is converted to hourly travel time per vehicle to estimate delay time costs based on the number of vehicles (instead of the number of persons) traveling on the roadway.

For local personal travel,

Hourly value of a person’s travel time in a vehicle= $11.89/person -hr
Average vehicle occupancy = 1.67 persons per vehicle
Hourly travel time value of all occupants in a vehicle or the hourly value of a vehicle on personal travel = $11.89 * 1.67 = $19.85/vehicle-hr

The hourly travel time value of a vehicle on personal travel is same as the vehicle’s delay time costs.

For intercity personal travel,

Hourly value of travel time = $16.75/person -hr
Average vehicle occupancy = 2.30 persons per vehicle
Hourly value of vehicle delay time = $16.64 * 2.30 = $38.27/vehicle-hr

Step 5. Compute travel delay costs for passenger cars on personal travel. Multiply the hourly dollar value of vehicle delay time with the delay time of passenger cars on personal travel. For local or personal travel,

Total delay time for passenger cars on personal travel = Average delay time* Number of passenger car vehicles on personal travel (and)
Travel delay costs for passenger cars on personal travel = Total delay time for passenger cars on personal travel * hourly $ value of vehicle delay time

2.2.2.2 Monetary Value of Business Travel Time

The hourly dollar value of road users’ business travel time is estimated based on the employer’s costs of employees that include both wages and benefits. The steps involved in calculating the cost component of the business travel time are enumerated as follows:

Step 1. Determine the proportion of passenger cars on business travel. The number of person miles reported in the NHTS is used in determining the proportion of passenger cars on business travel (see Table 1).

Step 2. Establish the AVO of passenger cars. As shown in Table 2, the average AVO for business travel was 1.24 in 2009. Alternatively, agency-specific travel behavior statistics can be used to reflect local trends.

Step 3. Estimate per hour monetary value of travel time for a person on business travel. Hourly dollar value of a person’s time on business travel is estimated using the OST guidelines presented in Table 4. Total hourly wages and benefits of all civilian workers reported in the Bureau of Labor Statistics (BLS) Employer Costs for Employee Compensation (ECEC) are used. For current year estimates, the ECEC data released every quarter can be used for computations, or adjustments can be made using the BLS Employment Cost Index (ECI) data.

For both local and intercity business travel,

Hourly value of a person’s time on business travel = 100% of median hourly wages plus benefits.
Hourly employment cost = $29.75 (December, 2010)
Hourly value of a person’s time on business travel = $29.75/person –hr.

Table 4. OST guidelines for calculating value of business travel time.

Travel Type	Per Person-Hour as a percent of Wage Rate	Data Source
Local	100% (80-120%)	Total compensation (wages and benefits) cost per hour. Reported in Bureau of Labor Statistics, Employer Costs for Employee Compensation
Intercity	100% (80-120%)	Total compensation (wages and benefits) cost per hour. Reported in Bureau of Labor Statistics, Employer Costs for Employee Compensation

Step 4. Compute per hour monetary value of travel time for a vehicle on business travel. Multiply the hourly value of a person’s time on business travel with the AVO factor. Note that the AVO is assumed to be the same for passenger cars on business travel for both local and intercity travel.

Hourly value of a person’s time on business travel = $29.75/person -hr
Average vehicle occupancy = 1.24 persons per vehicle
Hourly time value of a vehicle on business travel = $29.75 * 1.24 = $36.89/veh-hr

Step 5. Compute travel delay costs for passenger cars on business travel. Multiply the hourly dollar value of vehicle delay time with the delay time of passenger cars on business travel.

For business travel,

Total delay time for passenger cars on business travel = Average delay time* Number of passenger car vehicles on business travel (and)
Travel delay costs for passenger cars on business travel = Total delay time for passenger cars on business travel * hourly $ value of vehicle delay time

2.2.2.3 Monetary Value of Truck Travel Time

Hourly dollar value of truck travel time is estimated based on the compensation costs of truck drivers that include both wages and benefits. The steps involved in calculating the cost component of the truck travel time are enumerated as follows:

Step 1. Determine the average vehicle occupancy of trucks. NHTS data provide AVO values only for cars and light-duty trucks. There are no national averages or sources for AVO values of trucks. Agencies can use region-specific data, if available. In the absence of national or region-specific values, the truck AVOs recommended in the Highway Economic Requirement System (HERS)-ST Technical Report can be utilized. (FHWA, Highway Economic Requirements System-State Version, Technical Report, Federal Highway Administration, Washington, DC, 2005.) HERS-ST recommends an AVO of 1.025 for a single-unit truck (i.e., 1.05 for single-unit, six-tire trucks and 1.0 for heavier single-unit trucks) and 1.12 for combination trucks. The weighted average of AVOs of different truck types can be used.

Step 2. Determine the average wages and benefits for truck drivers. Per the BLS National Occupational Employment and Wage Estimates published in May 2009, the median hourly wages for truck drivers are presented as follows (Occupational Employment Statistics, Published by Bureau of Labor Statistics, US Department of Labor.):

Truck Drivers, Heavy and Tractor-Trailer = $18.87/hr (May 2009)
Truck Drivers, Light or Delivery Services (capacity of under 26,000 lb gross vehicle weight [GVW])
= $14.90/hr (May 2009)
Truck Drivers (both light and heavy) = $16.89/hr (May 2009)

Per the BLS ECEC data, the average benefit for employees in transportation and material moving jobs is $7.60/hr (for June 2009). Note that the wage rates and benefits can be adjusted to the current year using the current release of the BLS ECI or the Occupational Employment Statistics. State or local estimates of wages and benefits can be substituted for national estimates.

The following computation shows how to adjust the existing hourly compensation data to the current year data:

Wages & benefits of truck drives (both light and heavy) = $16.89/hr (May 2009)
Employment Cost Index (June 2009) (Historical ECI data can be obtained from ECT databases on the BLS website. Total compensation, all civilian, index numbers and all workers were used in determining the ECI value.) = 110.3
Employment Cost Index (Dec 2010) = 113.3
Wages & benefits adjusted for Dec 2010 = $16.89 * 113.3/110.3 = $ 17.35 /hr

Step 3. Estimate per hour monetary value of truck travel time. Determine the hourly dollar value of truck travel time by multiplying the hourly compensation (sum of wages and benefits) of truck drivers with the AVO factor.

Single-unit trucks = 1.025 * ($14.90 + $7.60) = $23.06/hr (May 2009)
Combination-unit trucks = 1.12 * ($18.87 + $7.60) = $29.65/hr (May 2009)

Step 4. Compute delay costs for truck travel. To determine the delay cost component of truck travel, multiply the hourly dollar value with travel delay time of trucks, either by truck type (single-unit or combination trucks) or the total number of trucks.

2.2.2.4 Cost of Time-Related Vehicle Depreciation

Vehicles depreciate as a function of aging and usage over time. Total vehicle depreciation costs are estimated from the average annual ownership costs of vehicles, while mileage-related vehicle depreciation costs are estimated using the VOC procedure discussed in section 2.3. Time-related vehicle depreciation costs typically are estimated by subtracting mileage-related depreciation from total depreciation. Time-related vehicle depreciation costs incurred by vehicle owners due to work zone delay are estimated herein using the methodology outlined in the HERS-ST Technical Report. The steps involved in computing the time-related vehicle depreciation costs are as follows:

Step 1. Determine the HERS-ST estimates of hourly cost of time-related vehicle depreciation for each vehicle type in 1995 dollars. Table 5 presents the HERS-ST estimates of hourly cost of total, mileage-related, and time-related vehicle depreciation (in 1995 dollars) for various vehicle types.

Step 2. Adjust the depreciation costs from 1995 dollars to current year dollars. To adjust 1995 dollars to current year dollars, the use of the Producer Price Index (PPI)—Commodity data for transportation equipment (Item 14) is recommended. (Producer Price Indexes, Published by Bureau of Labor Statistics, US Department of Labor (the use of multi-screen search tool is suggested.) As the time-related depreciation largely depends on the initial price of the vehicles, the use of the PPI for cost adjustment is deemed appropriate. However, this adjustment may not consider the change in vehicle registration, licensing and permit taxes, insurance premiums, and financing costs over time. Table 6 presents the hourly costs of time-related vehicle depreciation adjusted to 2010 values.

Table 5. Hourly costs of time-related vehicle depreciation in 1995 dollars.

Vehicle Type	Total Depreciation ($/hr)	Mileage-Related Depreciation		Time-Related Depreciation ($/hr)
		$/mile	$/hr
Small autos	1.72	0.109	0.63	1.09
Medium-sized to large autos	2.02	0.098	0.57	1.45
Four-tire single-unit trucks	2.18	0.045	0.28	1.90
Six-tire trucks	3.08	0.079	0.43	2.65
3+ axles combination trucks	8.80	0.175	1.64	7.16
3 or 4 axles	7.42	0.057	1.01	6.41
5+ axles	7.98	0.060	1.82	6.16

Source: HERS-ST Technical Manual (2005) (FHWA, Highway Economic Requirements System-State Version, Technical Report, Federal Highway Administration, Washington, DC, 2005.)

In addition to the depreciation values provided by the HERS-ST, practitioners also can use the following resources:

• American Automobile Association (AAA) (American Automobile Association, Your Driving Costs.)
• American Transportation Research Institute (ATRI) (Trego, T., and D. Murray (2010))

Table 6. Hourly costs of time-related vehicle depreciation in 2010 dollars.

Vehicle Type	Time-Related Depreciation ($/hr) in 1995 $	PPI		Adjustment Factor= PPI2010/PPI1995	Time-Related Depreciation ($/hr) in 2010 $
		1995	2010 P
Small autos	1.09	134.1	129.0 (PPPI for passenger cars (Item # 141101))	0.962	1.05
Medium-sized to large autos	1.45	159.0	153.3 (PPPI for trucks with GVW less than 14,000 lb (Item # 141105))	0.964	1.40
Four-tire single-unit trucks	1.9	144.1	195.7 (PPI for trucks with GVW over 14,000 lb (Item # 141106))	1.358	2.58
Six-tire trucks	2.65	144.1	195.7 (PPI for trucks with GVW over 14,000 lb (Item # 141106))	1.358	3.60
3+ axles combination trucks	7.16	124.5	175.9 (PPI for truck trailers (Item # 141406))	1.413	10.12
3 or 4 axles	6.41	124.5	175.9P (PPI for truck trailers (Item # 141406))	1.413	9.06
5+ axles	6.16	124.5	175.9P (PPI for truck trailers (Item # 141406))	1.413	8.70

Step 3. Compute the hourly costs of time-related vehicle depreciation. Total depreciation cost is computed for each vehicle type by multiplying the hourly depreciation costs with the vehicle delay time.

2.2.2.5 Cost of Freight Inventory Delay

Hourly dollar value of freight inventory delay is estimated using the procedure described in the HERS-ST Technical Report. The inventory cost is computed by multiplying the average payload of the truck with the average value of commodities shipped by truck. HERS-ST recommends the calculation of inventory delay costs only for combination trucks; however, this report provides the calculation steps for both single-unit and combination trucks:

Step 1. Determine the number of loaded (partially or fully) freight trucks by FHWA vehicle class or vehicle type and their average pay loads. This information can be obtained from weigh-in-motion (WIM) data representative of the project. In the absence of such data, follow the discussion presented in Steps 2 and 3. Otherwise, skip to Step 4.

Step 2. Estimate the number of empty and loaded trucks. The number of loaded freight trucks can be obtained from subtracting the empty trucks from the total trucks. Note that the truck composition may also consist of empty trucks (otherwise called backhaul trucks) returning from the original destination point to the point of origin. The number of loaded trucks can be estimated from the national averages of percent empty trucks presented in Table 7.

Table 7. Percent of empty trucks.

Truck Type	Percent of Empty Trucks
Single-unit truck	29
Combination truck with semitrailer	27
Combination truck with trailer	24
Combination truck with double trailer	24
Combination truck with triple trailer	19

Source: Alam, M., E. Fekpe, and M. Majed, FAF2 Freight Traffic Analysis, Submitted to FHWA Office of Freight Management and Operations, 2007. (Refer to Table 4)

Step 3. Estimate the average payload of trucks. Use the national averages presented in Table 8 to estimate average truck payload. These averages were obtained from an FAFP2P study that utilized the U.S. Census Bureau’s Vehicle Inventory and Use Survey (VIUS) database in the freight analysis. Practitioners may also use the State-specific payload data presented in Table 9 or local data.

Step 4. Determine the hourly discount rate. Hourly discount rate is the annual discount rate divided by the number of hours in a year (8,760 hours). The annual discount rate is the average prime bank lending rate plus 1 percent. The average prime bank lending rate for 2010 is 3.25 percent. (Prime bank lending rates for current can be obtained from the Statistics & Historical Data releases of the Federal Reserve.)

Hourly discount rate for 2010 = (3.25% +1%)/8760 = 0.000485%

Table 8. Average payload (lb) by distance traveled and truck type – national statistics.

Distance Traveled	Single-Unit			Truck/Tractor Trailers			Combination Trucks
	2-axle	3-axle	4-axle or more	4-axle or less	5-axle	6-axle or more	5-axle or less	6-axle	7-axle or more
Off-the-road	9,235	24,210	37,058	22,034	46,144	39,989	N.A.	N.A.	68,099
Less than 50 miles	7,223	25,293	35,198	13,392	42,135	44,964	37,611	47,330	77,886
51 to 100 miles	6,851	23,736	36,198	18,590	43,911	48,072	48,328	46,877	73,810
101 to 200 miles	7,509	23,463	35,732	21,207	42,061	53,637	40,054	43,074	71,319
201 to 500 miles	7,085	21,407	32,938	18,909	41,588	35,180	33,250	35,455	61,586
501 miles or more	6,231	21,334	39,368	21,271	40,184	47,807	38,505	39,928	67,979

Source: Alam, M., and G. Rajamanickam, Development of Truck Payload Equivalent Factor, Submitted to FHWA Office of Freight Management and Operations, 2007. (Refer to Table 3)

Table 9. Average payload (lb) by distance traveled and truck type by State.

State	Single-Unit			Truck/Tractor Trailers			Combination Trucks
	2-axle	3-axle	4-axle or more	4-axle or less	5-axle	6-axle or more	5-axle or less	6-axle	7-axle or more
Alabama	6,534	26,277	47,116	16,272	43,141	42,072	28,000	27,000	-
Alaska	5,859	22,573	31,430	15,695	39,528	51,935	-	31,800	70,325
Arizona	6,281	22,278	38,708	13,974	39,146	17,793	44,300	43,225	-
Arkansas	7,184	22,697	32,204	15,025	44,629	32,551	-	33,960	54,500
California	5,639	20,023	33,732	16,746	40,403	42,462	49,511	47,073	41,530
Colorado	7,594	25,252	37,090	14,105	42,974	46,373	51,000	-	-
Connecticut	7,265	25,769	37,803	13,729	40,415	46,281	37,000	59,000	-
Delaware	7,250	30,254	41,258	17,303	42,457	28,605	-	-	-
District of Columbia	5,346	20,388	11,978	3,500	-	-	-	-	-
Florida	6,637	30,529	38,986	14,857	42,885	34,338	30,667	23,000	-
Georgia	6,801	24,925	31,954	12,172	37,304	42,892	-	-	-
Hawaii	5,651	21,442	35,388	15,699	36,369	41,519	-	-	-
Idaho	9,127	26,349	34,967	15,157	44,307	52,455	59,900	-	67,000
Illinois	7,444	23,364	27,380	21,667	44,606	41,816	38,993	39,675	53,983
Indiana	8,700	30,144	32,671	14,165	41,512	44,022	35,000	60,218	58,000
Iowa	8,680	23,560	30,398	16,602	44,449	42,275	-	-	37,500
Kansas	10,101	24,547	30,116	20,853	45,064	38,650	44,737	42,500	36,170
Kentucky	8,889	25,942	38,711	15,125	40,730	42,766	-	-	37,280
Louisiana	7,144	25,256	34,072	14,327	47,028	47,319	-	-	59,224
Maine	9,127	27,086	36,926	17,650	40,267	55,838	-	-	-
Maryland	6,205	29,582	38,000	11,114	32,038	38,109	-	-	-
Massachusetts	5,247	26,974	38,085	11,834	45,852	39,958	-	-	-
Michigan	6,771	20,065	30,697	15,412	37,088	61,272	38,000	40,000	100,145
Minnesota	7,581	23,509	31,129	14,178	41,868	39,443	36,000	31,500	-
Mississippi	6,223	28,608	29,248	15,779	44,716	44,753	-	-	-
Missouri	9,105	26,110	31,533	13,636	42,471	39,272	-	-	-
Montana	10,912	25,410	29,729	17,813	43,243	49,817	-	-	70,824
Nebraska	11,054	24,528	32,747	15,087	41,550	50,195	-	36,500	53,013
Nevada	7,550	22,711	40,499	17,123	42,319	51,454	48,553	45,265	68,513
New Hampshire	7,313	25,825	34,054	13,667	40,755	53,346	-	-	-
New Jersey	7,154	29,850	44,487	15,388	41,927	30,040	38,190	-	-
New Mexico	6,655	23,854	33,538	16,277	42,173	32,867	51,000	53,525	87,000
New York	6,883	25,703	38,705	9,568	42,558	54,837	51,000	-	90,755
North Carolina	7,522	24,688	32,827	19,043	41,852	35,086	31,529	34,000	34,000
North Dakota	13,344	25,525	29,259	17,158	46,730	50,459	-	-	69,500
Ohio	7,021	22,493	33,568	12,799	41,318	41,881	-	45,000	30,000
Oklahoma	8,030	23,057	33,847	18,560	40,674	42,141	24,817	30,333	-
Oregon	5,244	22,832	27,449	16,998	44,978	47,662	48,166	40,492	62,234
Pennsylvania	6,540	25,872	39,530	8,976	40,187	32,124	-	-	26,000
Rhode Island	5,576	31,550	42,570	11,907	44,264	52,904	-	-	-
South Carolina	7,280	24,417	35,520	14,789	42,222	43,311	-	-	-
South Dakota	11,210	24,178	29,315	17,687	45,679	46,840	-	-	77,997
Tennessee	6,561	26,774	41,064	14,827	41,013	36,271	45,000	-	32,000
Texas	7,275	26,224	36,280	17,665	42,948	42,209	23,514	21,583	110,000
Utah	5,917	16,510	32,118	15,307	41,196	53,222	27,606	32,503	77,802
Vermont	8,439	27,309	34,971	12,803	45,788	45,911	-	61,400	-
Virginia	7,352	27,859	34,654	16,424	42,527	47,412	37,159	40,282	45,500
Washington	6,638	22,209	35,971	14,366	39,919	56,690	37,728	51,149	64,585
West Virginia	7,120	27,446	36,591	13,947	41,495	49,097	-	-	-
Wisconsin	6,865	22,474	37,909	16,624	42,399	44,392	13,000	-	-
Wyoming	8,067	24,995	34,214	14,983	43,061	54,541	51,000	-	70,772

Source: Alam, M., and G. Rajamanickam, Development of Truck Payload Equivalent Factor, Submitted to FHWA Office of Freight Management and Operations, 2007. (Refer to Table 3)

Step 5. Determine the average value of commodities shipped by truck. The HERS-ST Technical Report cites that the average value of commodities shipped by truck (on a ton-mile weighted basis) was $1.35 per pound in 1993. ( The practitioners are recommended to periodically check with the FHWA Office of Freight Management and Operations for updated dollar value of commodities shipped by trucks.) Adjust this value to the current year using the Implicit Price Deflators for Gross Domestic Product-Goods. (Implicit Price Deflators for GDP can be obtained from Table 1.1.9 of the National Income and Product Account (NIPA) published by the Bureau of Economic Analysis.)

Average value of commodities shipped by truck = $1.35/lb (in year 1993)
Implicit Price Deflator for GDP-Goods = 93.786 (for year 1993)
Implicit Price Deflator for GDP-Goods = 105.405 (for year 2010)
Adjusted value of commodities shipped by truck in 2010 = $1.35 * (105.405/93.786) = $1.52/lb

Step 6. Determine the hourly value of freight shipped by truck. Multiply the current year value of commodities by the hourly discount rate.

Hourly value of freight inventory for 2010 = $1.52/lb * 0.000485%
Hourly value of freight inventory for 2010 = $7.37E-06/lb/hr

Step 7. Determine the hourly inventory cost for each truck. Multiply the hourly value of commodities ($/lb/hr) by the average payload of each truck type. The hourly inventory costs for the suggested payload values of single-unit trucks (25,000 lb) and combination trucks (42,000 lb) are $0.18 and $0.31 in 2010 dollars, respectively. Table 10 presents the hourly inventory costs for the average payload values presented in Table 8.

Table 10. Hourly cost ($/hr) of freight inventory by distance traveled and truck type – national averages in 2010 dollars.

Distance Traveled	Single Unit			Truck/Tractor Trailers			Combination Trucks
	2-axle	3-axle	4-axle or more	4-axle or less	5-axle	6-axle or more	5-axle or less	6-axle	7-axle or more
Off-the-road	0.07	0.18	0.27	0.16	0.34	0.29	N.A.	N.A.	0.50
< 50 miles	0.05	0.19	0.26	0.10	0.31	0.33	0.28	0.35	0.57
51- 100 miles	0.05	0.17	0.27	0.14	0.32	0.35	0.36	0.35	0.54
101 - 200 miles	0.06	0.17	0.26	0.16	0.31	0.40	0.30	0.32	0.53
201 - 500 miles	0.05	0.16	0.24	0.14	0.31	0.26	0.25	0.26	0.45
> 500 miles	0.05	0.16	0.29	0.16	0.30	0.35	0.28	0.29	0.50

Step 8. Compute freight inventory delay costs. Multiply the number of loaded freight trucks (by truck type) by their hourly cost of freight inventory values.

2.3 Vehicle Operating Costs

VOC are the expenses incurred by road users as a result of vehicle use. VOC are the running costs that vary with the degree of vehicle use, and are thus mileage dependent, and do not include fixed costs such as insurance, time-dependent depreciation, financing, and storage.

In WZ RUC analysis, VOC is an aggregation of the following components:

• Speed change VOC is the additional cost under unrestricted conditions associated with decelerating from the upstream approach speed to the work zone speed and then accelerating back to the approach speed after leaving the work zone.
• Stopping VOC is the additional cost under restricted conditions associated with stopping from the upstream approach speed and accelerating back up to the approach speed after traversing the work zone.
• Queue idling VOC is the additional cost associated with stop-and-go driving in the queue. The idling cost rate multiplied by the additional time spent in the queue is an approximation of actual VOC associated with stop-and-go conditions. When a queue exists, stopping delay and VOC replace the free-flow speed change delay and VOC.
• Detour VOC is the additional cost associated with the excess distance to be traveled by selecting a detour route under unrestricted or restricted conditions.

2.3.1 Estimating VOC

VOC includes the consumption costs of the following resources:

• Fuel consumption.
• Engine oil consumption.
• Tire-wear.
• Repair and maintenance.
• Mileage-related depreciation.

VOC is measured by quantifying the consumption of these resources while driving a vehicle between two points and multiplying those quantities with the corresponding unit cost of resources. Figure 3 presents the computation of VOC schematically.

Figure 3. Schematic illustrating the components of VOC.

The resource consumption is a function of prevailing roadway and traffic characteristics and can vary significantly with factors such as roadway geometry, traffic volume and composition, travel delay, and speed. Table 11 presents a matrix showing how each resource is influenced by various roadway factors.

Table 11. Roadway factors affecting vehicle operating costs.

Roadway Factor	Fuel	Oil	Tire Wear	Maintenance and Repair	Depreciation (mileage-related)
Vehicle Class	X	X	X	X	X
Vehicle Speed	X	X	X	X	X
Road Grade	X	X	X	X
Surface Type	X	X	X	X	X
Surface Condition	X	X	X	X	X
Road Curvature	X		X	X

Source: Lewis, D. L. Road User and Mitigation Costs in Highway Pavement Projects, NCHRP Synthesis 269, National Cooperative Highway Research Program, Transportation Research Board, Washington DC, 1996.

For WZ RUC analysis, the VOC is estimated for the traffic flowing through the work zone as well as those diverted through detour routes (if applicable). Traffic flowing through the work zone undergoes acceleration/deceleration cycles, stopping and idling depending on the flow condition (i.e. unrestricted or restricted). VOC models can be used to account for the effect of change in flow condition changes on resource consumption.

Traffic diverted through the detour routes may or may not experience change in flow conditions depending on the detour route capacity and diverted traffic volume. If there is forced flow condition, a detailed traffic analysis using VOC models is required for detour routes at the network or route level (depending on the impact and site-specific factors). Otherwise, a simple per-mile estimate can be used in VOC estimation for free flow conditions. VOC models provide per-mile estimates for constant-operating conditions with due consideration to travel speed, grade, and pavement conditions. Alternate cost sources such as AAA or ATRI can also be used for simpler, flat-rate per-mile estimates.

2.3.2 VOC Models

VOC models provide a detailed methodology for quantifying the additional resources consumed due to change in traffic flow conditions. Three methods are used commonly in the U.S. for determining VOC:

• National Cooperative Highway Research Program (NCHRP) Report 133 method. (Curry, D.A. and D.G. Anderson, Procedures for Estimating Highway User Costs, Air Pollution, and Noise Effects, National Cooperative Highway Research Program Report 133, Transportation Research Board, Washington, DC, 1972.)
• Texas Research and Development Foundation method. (Zaniewski, J. P., B. C. Butler, G. Cunningham, G. E. Elkins, M. S. Paggi, and R. Machemehl. Vehicle Operating Costs, Fuel Consumption and Pavement type and Condition Factors, Final
  Report # DOT-FH-11-9678, Prepared by Texas Research and Development Foundation, Federal Highway Administration, Washington, DC, 1982.)
• HERS-ST method.20
• U.S. Environmental Protection Agency (EPA)’s Motor Vehicle Emission Simulator (MOVES)—Only fuel consumption costs can be estimated using this tool (see section 2.5.1.2 for more discussion)

This document presents a detailed discussion of VOC models commonly used in the U.S. Some of the International sources of VOC models include:

• The World Bank’s Highway Design and Maintenance Standards (HDM-IV) model.
• The British Cost Benefit Analysis Program (COBA).
• The Australian Road Research Board’s Road Fuel Consumption model.
• The National Association of Australian State Road Authorities’ Improved Model for Project Assessment and Costing (NIMPAC).
• The Swedish National Road and Transport Research Institute (VTI) Vejstandard og transportomkostninger (VETO) model.

2.3.2.1 Report 133 Method

NCHRP Report 133 provides relationships to calculate VOC consumption for work zone conditions. These relationships were based largely on earlier work by Winfrey and Claffey. (Winfrey, R., Economic Analysis of Highways, International Textbook Company, Scranton, Pennsylvania, 1969. Claffey, P. J., Running Costs of Motor Vehicles as affected by Road Design and Traffic, National Cooperative Highway Research Program Report 111, Transportation Research Board, Washington, DC, 1971.) Since these earlier studies were published, there have been improvements in fuel efficiency standards, vehicle technologies, and tire technologies; therefore, the accuracy of these relationships is questionable for current vehicle standards.

The NCHRP Report 133 relationships were utilized in RealCost for computing work zone VOC. (Walls III, J. and M. R. Smith, Life-Cycle Cost Analysis in Pavement Design — Interim Technical Bulletin, Report No. FHWA-SA-98-079, Federal Highway Administration, Washington, DC, 1998.) Table 12 presents the additional time and operating costs in 2010 dollars resulting from vehicle stopping, idling, and speed changes in work zones. Both time and cost factors are presented as a function of vehicle traveling speed. Reproduced from the RealCost technical bulletin, the cost table was adjusted from 1996 to 2010 rates using the Consumer Price Index (CPI) (transportation component).

Table 12. Added time and vehicle running cost/1,000 stops and idling cost in 2010 dollars.

Initial Speed (mph)	Added Time (Hr/1000 Stops)			Added Cost ($/1000 Stops)
	Passenger Cars	Single-Unit Truck	Combination Truck	Passenger Cars	Single-Unit Truck	Combination Truck
0	0.00	0.00	0.00	$0.00	$0.00	$0.00
5	1.02	0.73	1.10	$3.66	$12.53	$45.53
10	1.51	1.47	2.27	$11.96	$28.06	$104.95
15	2.00	2.20	3.48	$20.53	$45.90	$176.02
20	2.49	2.93	4.76	$29.44	$65.55	$257.40
25	2.98	3.67	6.10	$38.83	$86.64	$347.44
30	3.46	4.40	7.56	$48.89	$108.66	$444.50
35	3.94	5.13	9.19	$59.67	$131.21	$546.93
40	4.42	5.87	11.09	$71.37	$154.35	$653.06
45	4.90	6.60	13.39	$84.06	$176.17	$761.31
50	5.37	7.33	16.37	$97.93	$197.68	$870.02
55	5.84	8.07	20.72	$113.04	$217.90	$977.50
60	6.31	8.80	27.94	$129.61	$242.40	$1,082.08
65	6.78	9.53	31.61	$147.65	$265.23	$1,150.68
70	7.25	10.27	39.48	$167.41	$283.13	$1,247.36
75	7.71	11.00	47.90	$188.97	$304.54	$1,344.05
80	8.17	11.73	57.68	$212.42	$325.96	$1,440.75
Idling Cost ($/veh-hr.)				$0.94	$1.04	$1.12

Source: FHWA’s RealCost and NCHRP Report 133.
Original CPI: 142.8 (year 1996)
Current year CPI: 193.396 (year 2010)

Speed change VOC is calculated by subtracting the cost factors at the work zone speed from those at the upstream speed. This difference is then multiplied by the number of vehicles traversing the work zone under the unrestricted flow scenario. Similarly, for calculating the stopping VOC of vehicles, the difference in cost factors at the upstream speed and stopping is then multiplied by the number of vehicles traversing the work zone under the restricted flow scenario. The idling VOC is calculated by multiplying the idling cost factors by the number of delayed vehicles and their queuing/idling time. For additional miles resulting from detour, the RealCost software recommends the use of flat, mileage-based rates under normal vehicle operating conditions. Sources of mileage-based VOC are presented in section 2.3.3.

2.3.2.2 Texas Research and Development Foundation Method

In 1982, the Texas Research and Development Foundation (TRDF) developed relationships to incorporate the effects of highway design and pavement condition on VOC for FHWA. This study provided a VOC model as a function of vehicle speed, grade, and vehicle class. This model was developed based on highway, vehicle technology, operation, and economic conditions typical of the 1970s. Table 13 presents a sample relationship showing the TRDF estimates of VOC resource consumption for vehicle idling.

Table 13. TRDF estimates of VOC consumption during idling.

Vehicle	Fuel (gallon /l000 hrs)	Oil (quart/ 1000 hrs )	Tire (% of wear/1000 hrs)	Depreciation (% of new veh. price/l000 hrs )	Maint. & Repairs (% of avg. cost per 1000 miles/1000 hrs)
Small Passenger Car	271	5.8	0	0.81	57
Medium/Large Passenger Car	563	5.8	0	0.81	58
Pickup/Van	756	3.5	0	0.5	60
Buses	398	3.46	0	1.1	26
2-Axle Single Unit	198	3.2	0	1.1	23
3-Axle Single Unit	398	3.46	0	1.1	26
2-S2 Semis	470	3.46	0	0.38	24
3-S2 Semis	470	3.46	0	0.38	24

TRDF VOC data have been used in many highway planning and project evaluation models, including HERS-ST, MicroBENCOSTP (a benefit-cost analysis tool for highway applications), and the Canadian Highway User Benefit Assessment. However, this method, like the NCHRP Report 133 method, falls short of taking changing vehicle standards and technologies into account. (Bein, P., and D.C. Biggs, Critique of Texas Research and Development Foundation Vehicle Operating Cost Model, Transportation Research Record No.1395, Journal of the Transportation Research Board, Washington, DC, 1993.)

2.3.2.3 HERS-ST Method

FHWA’s HERS-ST model provides a comprehensive method to compute VOC resource components for various vehicle types, roadway conditions, and traffic characteristics. For every cost component, HERS-ST provides separate VOC models for calculating each resource component based on:

• Constant-speed operating conditions as a function of average effective speed, average grade, and pavement serviceability rating.
• Excess resource consumption due to speed-change cycles.
• Excess resource consumption due to roadway curvature. (Additional vehicle operating costs incurred due to the effects of roadway curvature is not required for WZ RUC analysis, as the differential costs between the normal operating and work zone conditions are only considered.)

The HERS-ST VOC estimation models are derived based on the TRDF VOC relationships, with some adjustments made based on the findings of Claffey and Daniels. (Zaniewski, J. P., B. C. Butler, G. Cunningham, G. E. Elkins, M. S. Paggi, and R. Machemehl. Vehicle Operating Costs, Fuel Consumption and Pavement type and Condition Factors, Final Report # DOT-FH-11-9678, Prepared by Texas Research and Development Foundation, Federal Highway Administration, Washington, DC, 1982. Claffey, P. J., Running Costs of Motor Vehicles as affected by Road Design and Traffic, National Cooperative Highway Research Program Report 111, Transportation Research Board, Washington, DC, 1971. Daniels, C. Vehicle Operating Costs in Transportation Studies, E.S.U. Technical Series, No. 1, Spencer House, London (1974).) In addition, HERS-ST facilitates adjustments for commodity cost fluctuations and improvements in vehicle fuel efficiency.

The HERS-ST model contains numerous equations for VOC estimation based on the combinations of VOC resource components, vehicle types, and influencing factors (e.g., average effective speed, speed change, horizontal curves, and vertical grade). The HERS-ST software package facilitates the analysis of VOC estimation using a set of equations. (Equations of HER-ST VOC models are presented in Appendix E of the HERS-ST Technical Report.) Tables 14 and 15 present sample HERS-ST estimates of VOC for each resource component estimated using constant speed and speed variability submodels, respectively. These tables were estimated for a given set of influencing factors.

The overall equation for estimating VOC is presented as follows:

CSOPCSTRvtR = CSFC*PCAFFC *COSTFRvtR/ FEAFRvtR+CSOC * PCAFOC *COSTORvtR /OCAFRvtR + 0.01 *CSTW *PCAFTW *COSTTRvtR /TWAFvt +0.01 *CSMR *PCAFMR *COSTMRRvtR/MRAFRvtR + 0.01 *CSVD* PCAFVD *COSTVRvtR /VDAFRvt
where,
CSOPCSTvt = constant speed operating cost for vehicle type
CSFC = constant speed fuel consumption rate (gallons/1000 miles)
CSOC =constant speed oil consumption rate (quarts/1000 miles)
CSTW = constant speed tire wear rate (% worn/1000miles)
CSMR = constant speed maintenance and repair rate (% of average cost/1000 miles)
CSVD = constant speed depreciation rate (% of new price/ 1000 miles)
PCAFFC = pavement condition adjustment factor for fuel consumption
PCAFOC = pavement condition adjustment factor for oil consumption
PCAFTW = pavement condition adjustment factor for tire wear
PCAFMR = pavement condition adjustment factor for maintenance and repair
PCAFVD = pavement condition adjustment factor for depreciation expenses
COSTFvt = unit cost of fuel for vehicle type
COSTOvt = unit cost of oil for vehicle type
COSTTvt = unit cost of tires for vehicle type
COSTMRvt = unit cost of maintenance and repair for vehicle type
COSTVvt = depreciable value for vehicle type
FEAFvt = fuel efficiency adjustment factor for vehicle type
OCAFvt = oil consumption adjustment factor for vehicle type
TWAFvt = tire wear adjustment factor for vehicle type
MRAFvt = maintenance and repair adjustment factor for vehicle type
VDAFvt = depreciation adjustment factor for vehicle type.

Table 14. Sample HERS-ST estimates of constant speed VOC in 2010 dollars.

Average Effective Speed (mph) (Note: These estimates were developed for an assumed roadway grade of 1 percent and a pavement serviceability rating of 2.5)	Small Autos	Medium/Large Auto	4-Tire Truck	6-Tire Truck	3+Axle Single Unit	3-4 Axle Combination	5+ Axle Combination
40	$0.36	$0.43	$0.45	$1.20	$1.38	$0.91	$1.09
45	$0.36	$0.43	$0.45	$1.20	$1.38	$0.90	$1.09
55	$0.37	$0.43	$0.45	$0.83	$1.37	$0.91	$1.08

Table 15. Sample HERS-ST estimates of speed variability VOC in 2010 dollars.

Maximum Speed in a Speed Change Cycle (mph)	Small Autos	Medium/Large Auto	4-Tire Truck	6-Tire Truck	3+Axle Single Unit	3-4 Axle Combination	5+ Axle Combination
5	$0.04	$0.04	$0.14	$0.26	$0.26	$0.12	$0.13
10	$0.08	$0.09	$0.17	$0.33	$0.50	$0.29	$0.32
15	$0.14	$0.15	$0.22	$0.44	$0.81	$0.52	$0.58
20	$0.21	$0.22	$0.30	$0.59	$1.17	$0.80	$0.90
25	$0.29	$0.31	$0.39	$0.79	$1.59	$1.15	$1.29
30	$0.38	$0.42	$0.50	$1.04	$2.08	$1.54	$1.75
40	$0.59	$0.66	$0.76	$1.66	$3.21	$2.50	$2.86
50	$0.83	$0.95	$1.09	$2.46	$4.55	$3.66	$4.26
60	$1.10	$1.27	$1.47	$3.45	$6.10	$5.02	$5.96
70	$1.39	$1.60	$1.91	$4.63	$7.85	$6.58	$7.98

2.3.3 Unit Cost Data Sources for VOC Estimation

Unit cost data are required to compute the costs of additional resources consumed due to work zone activity. Several unit cost data sources are available for VOC estimations, and commonly cited U.S. cost sources include:

Passenger cars only

• AAA - Your Driving Costs (published annually) – see Table 16.

Trucks only

• American Transportation Research Institute (ATRI)-see Table 17.

All vehicles

• Barnes and Langworthy (Barnes, G and P. Langworthy, The Per-Mile Costs of Operating Automobiles And Trucks, Report No. MN/RC 2003-19, Submitted to Minnesota Department of Transportation, St. Paul, 2004.) – see Table 18.
• Sinha and Labi (2005) – see Table 19.
• HERS-ST – see Table 20.

Table 16. AAA estimates of VOC for passenger cars in 2010 dollars (cents/vehicle mile).

Cost Component	Small Sedan	Medium Sedan	Large Sedan	4WD Sport Utility Vehicle	Minivan
Fuel	9.24	11.97	12.88	16.38	13.7
Maintenance and oil	4.21	4.42	5	4.95	4.86
Tires	0.65	0.91	0.94	0.98	0.75
Depreciation @ 15000 miles/year	15.89	23.01	32.19	33.35	26.63

Table 17. ATRI estimates of VOC for trucks in 2008 dollars (cents/vehicle mile).

Cost Component	Trucks
Diesel Fuel (@ $4.69/gallon) No surcharge	63.4
Diesel Fuel (@ $4.69/gallon) With surcharge	21.9
Fuel taxes	6.2
Maintenance	9.2
Tires	3.0
Depreciation	N.A.

Table 18. Barnes and Langworthy estimates of VOC in 2003 dollars (cents per vehicle mile).

Cost Component	Automobile		Pickup/SUV/Van		Trucks
	Highway	City	Highway	City	Highway	City
Fuel @ $1.50/gallon	5.0	7.0	7.8	10.1	21.4	28.0
Maintenance	2.1	2.5	2.4	2.8	10.5	12.1
Repair	1.1	1.3	1.3	1.5	10.5	12.1
Tires	0.9	0.9	1.0	1.0	3.5	3.5
Depreciation	6.2	7.4	7.0	8.1	8.0	9.2
Total	15.3	19.1	19.5	23.6	43.4	52.9

Table 19. Average VOC (cents/vehicle mile) in 2005 dollars.
(Note: This table is a compilation of cost data from several sources:
Non-trucks: fuel, maintenance and repair, and tires from AAA Your Driving Costs 2005); Trucks: fuel, maintenance and repair, and tires from Barnes and Langworthy (2003); and, Depreciation estimations and projections from the HERS-ST Technical Report (2002).)

Cost Component	Small Autos	Medium-sized Autos	Large Autos	SUVs	Vans	Trucks
Fuel and Oil	5.4	6.44	7.5	8.34	7.5	21.41
Maintenance and Repair	3.5	4.12	4.33	4.33	4.12	11.09
Tires	0.5	1.58	1.9	1.58	1.69	3.7
Depreciation	13.9	12.5	12.5	12	12	10.6
Total	20.59	20.59	22.17	22.7	21.75	44.64

Table 20. HERS-ST unit costs of VOC resource components in 2004 dollars.

Cost Component	Small Autos	Medium/ Large Auto	4-Tire Truck	6-Tire Truck	3+Axle Single Unit	3-4 Axle Combination	5+ Axle Combination
Fuel ($/gal)	$1.93	$1.93	$1.93	$1.93	$1.84	$1.84	$1.84
Oil ($/quart)	$4.48	$4.48	$4.48	$1.79	$1.79	$1.79	$1.79
Tires ($/tire)	$45.89	$72.55	$79.96	$193.00	$477.90	$477.90	$477.90
Maintenance & Repair ($/1000 miles)	$103.50	$125.60	$159.60	$298.70	$422.50	$437.60	$437.60
Depreciation ($/vehicle)	$19,717	$23,255	$25,061	$37,448	$82,386	$95,432	$103,767

2.3.3.1 Updating Cost Data Sources for VOC Estimation

Unit cost data shown in Tables 16 through 20 do not reflect the current year prices. To update the cost of individual resource components to current year prices, adjustments using standard price indices, such as CPI and PPI, are recommended. Table 21 presents the guidelines on using the price indices for price adjustment. The information presented in the parentheses indicates the appropriate items codes of CPI or PPI data for each combination of resource and vehicle type. To estimate current year prices, multiply the existing year prices by a ratio of CPI (current year) to CPI (existing year), or PPI values as appropriate.

Table 21. Price adjustments for VOC components.

Resource	Automobile	Pickup/SUV/Van	Single-unit Trucks	Combination Trucks
Consumer Price Index-All Urban Consumers
Fuel	Gasoline (SETB01)	Gasoline (SETB01)	Gasoline (SETB01) for 2-axle 6-tire truck. Other motor fuels for Diesel (SETB02) for 3-axle truck	Other motor fuels for Diesel (SETB02)
Consumer Price Index-All Urban Consumers
Oil	Motor oil, coolant, and fluids (SS47021)	Motor oil, coolant, and fluids (SS47021)	Motor oil, coolant, and fluids (SS47021)	Motor oil, coolant, and fluids (SS47021)
Consumer Price Index-All Urban Consumers
Maintenance and Repair	Motor vehicle maintenance and repair (SETD)	Motor vehicle maintenance and repair (SETD)	Motor vehicle maintenance and repair (SETD)	Motor vehicle maintenance and repair (SETD)
Consumer Price Index-All Urban Consumers
Tires	Tires (SETC01)	Tires (SETC01)	Tires (SETC01)	Tires (SETC01)
Producer Price Index - Commodity Data Transportation Equipment (14)
Depreciation	Passenger cars (1101)	Trucks with GVW under 14,000 lbs (1105)	Trucks with GVW over 14,000 lbs (1106)	Truck trailers (1406)

To illustrate, the HERS-ST estimates of unit costs presented in Table 20 reflect the prices in 2004. To convert the 2004 prices to 2010 prices, the ratio of 2010 CPI or PPI value to 2004 CPI or PPI value for each of the codes presented in Table 21 are first computed (see Table 22). The 2004 prices in Table 20 are then multiplied by the appropriate price adjustment factors presented in Table 22 to estimate the unit costs of various resource components in 2010 dollars (see Table 23).

Table 22. 2004 to 2010 price adjustment factors for VOC components.

Resource	Automobile	Pickup/SUV/Van	6-tire Single-unit Trucks	3-axle Single-unit Trucks	Combination Trucks
Fuel	1.497	1.497	1.497	1.539	1.539
Oil	1.847	1.847	1.847	1.847	1.847
Maintenance and Repair	1.214	1.214	1.214	1.214	1.214
Tires	1.239	1.239	1.239	1.239	1.239
Depreciation	0.979	1.013	1.257	1.257	1.226

Table 23. HERS-ST unit costs of VOC resource components in 2010 dollars.

Cost Component	Small Autos	Medium/Large Auto	4-Tire Truck	6-Tire Truck	3+Axle Single Unit	3-4 Axle Combination	5+ Axle Combination
Fuel	$2.89	$2.89	$2.89	$2.89	$2.84	$2.84	$2.84
Oil	$8.27	$8.27	$8.27	$3.31	$3.31	$3.31	$3.31
Tire (single)	$55.70	$88.07	$97.06	$234.28	$580.11	$580.11	$580.11
Maintenance and Repair	$128.21	$155.59	$197.71	$370.03	$523.39	$542.09	$542.09
Depreciation	$19,303	$23,569	$25,399	$47,069	$103,551	$116,979	$127,196

2.4 Crash Costs

Crash costs associated with work zones and work zone-related detours are a function of the expected change in the crash rates due to the presence of work zones. Required crash-related inputs for WZ RUC analysis include:

• Crash rate and /frequency at work zones.
• Crash severity rating.
• Unit cost of crashes.

2.4.1 Work Zone Crash Rate

Crash statistics often are reported in terms of crash rate and crash frequency. Crash rate is the number of crashes expected or observed along a roadway segment during a time period normalized to the roadway segment length and the traffic volume over the same period. Crash rate typically is expressed as “crashes per VMT” or “crashes per million VMT (MVMT)” for roadway sections and “crashes per million entering vehicles (MEV)” for intersection locations. The formula for calculating the crash rate for a roadway segment is presented as follows:

where,
CR = number of crashes per million vehicle miles of travel
A = average number of crashes along the roadway segment for the analysis period
T = duration of the analysis period (years)
L = length of roadway segment (miles)
AADT = annual average daily traffic (in both directions)

Crash frequency is the number of crashes normalized to the roadway segment length and time period. It typically is expressed as “crashes per mile per year.”

The presence of a work zone increases the likelihood of crashes in a given location. Therefore, the work zone crash rates typically are estimated by applying a multiplicative factor, called crash modification factor (CMF), to the pre-work zone crash rates at the project location. Crash records collected over a typical 3-year period are considered in determining pre-work zone crash rates.

Numerous studies indicate that the pre-work zone crash rates are likely to increase by 20 to 70 percent when there is a work zone in place. For active work with temporary lane closure on freeway and expressway facilities, Ullman et al (2008). found that the crash risk increased by about 66 percent during the day and by 61 percent at night for a motorist traveling through the work zone; however, the actual change in crash risk varied significantly when the crash data was examined on the basis of time of work (daytime or nighttime work) and work conditions (no work activity, active work with lane closures, or active work with no lane closures). (Ullman, G. L., M. D. Finley, J. E. Bryden, R. Srinivasan, and F.M. Council, Traffic Safety Evaluation of Nighttime and Daytime Work Zones, NCHRP Report 627, National Cooperative Highway Research Program, Transportation Research Board, Washington, DC, 2008.)

Work zone CMFs are available on the CMF Clearinghouse website, a repository established and maintained by the FHWA Office of Safety. (CMF Clearinghouse) This site contains the best available information on the crash modification factors for a variety of scenarios, including countermeasure strategies to address specific work zone safety issues. Table 24 presents typical work zone CMFs for temporary lane closure on freeways and expressways.

There are no statistically accepted values of CMFs, as they were found to vary from study to study. Furthermore, numerous factors pertaining to the operational and physical characteristics of the facility influence the likelihood of increase in crash rates at work zones:

• Roadway functional class (e.g., freeways vs. two-lane highways).
• Location (e.g., urban vs. rural).
• Work zone configuration (e.g., work zone length, number of open lanes).
• Traffic volume.
• Exposure period (e.g., number of days, night vs. daytime).
• MOT strategy (e.g., partial lane closure vs. crossover).
• Traffic management strategies (e.g., flagger vs. non-flagger).
• Weather conditions.

Therefore, agencies could consider establishing their own CMFs reflecting local trends using historical data. Other approaches such as historical averages, regression-based models involving key influencing variables, and crash reduction factors also can be employed. Table 25 presents an example showing the difference in work zone and pre-work zone crash rates observed in various work zone sites in Indiana. (Pal, R., and K. Sinha, An Evaluation of Lane Closure Strategies for Interstate Work Zones, Report No. FHWA/IN/JHRP-95/1, Joint Transportation Research Program, Purdue University, West Lafayette, IN, 1995.) This table also illustrates how the work zone conditions, such as lane closure strategies and number of available lanes, influence the likelihood of increase in crash rates at work zones. Table 26 presents an example of the CMFs calculated for Ohio’s work zones. (Presented by Mr. Holstein, State Traffic Engineer of Ohio DOT, 2008 Work Zone Rule Virtual Workshop.)

Table 24. Typical work zone crash modification factors for temporary lane closure on freeways.
(Note: Reported for work zones with active work and temporary lane closure.)

Crash Types	Crash Severity	CMF
All	All	1.77
All	Property damage only (PDO)	1.9
All	Serious injury, Minor injury	1.6
Nighttime	All	1.57
Nighttime	Property damage only (PDO)	1.63
Nighttime	Serious injury, Minor injury	1.34

Table 25. Average crash rates at Interstate work zones in Indiana.

Sites	Crash Rate (per 10 Million VMT)
	Without Work Zone	With Work Zone	CMF
Sites Using Cross-over (2 lanes in each direction)	6.0329	8.0431	1.33
Sites Using Partial Lane Closure (2 lanes in each direction)	5.5916	7.4528	1.33
Sites Using Cross-over (3 lanes in each direction)	5.8278	9.3544	1.61
Sites Using Partial Lane Closure (3 lanes in each direction)	7.5166	10.1006	1.34

Table 26. Work zone crash rates in Ohio.

Year	Crash Rate (per Million VMT)		CMF
	Before Work Zone	With Work Zone
2002	1.04	1.68	1.62
2003	1.19	2.02	1.69
2004	1.34	1.71	1.28
2005	1.29	1.23	0.95
2006	1.51	1.51	0.0

In addition to the elevated crash related risks due to work zone, the pre-work zone crash rates should be adjusted for:

• Influence Zone (or Analysis Area) — The influence zone is the area or roadway segments that are adversely impacted by the work zone hazards. The safety impacts of the work zone are evaluated not only in the immediate work zone area but also on the adjacent roadways, and are duly accounted in the crash cost computations.
• Traffic Volume and Length of the Influence Zone — The variable “VMT” is a measure of exposure expressed in terms of traffic volume and section length. When computing the expected or actual work zone crash rate, the traffic volume exposed during the work zone period as well as the length of the influence zone should be taken into account.
• Work Zone Safety Improvement— Appropriate crash reduction factors should be included in the crash rate computations to account for future safety improvement countermeasures to be implemented in the work zone. For instance, See et al. reported that the work zone crash rate in Arkansas highways fell by 46 percent when the conventional right-hand lane closure was replaced with the Iowa weave lane closure (i.e., lane closure with a left-hand merge and lane shift) strategy was implemented. (See, C. F., S. D. Schrock, and K. McClure, “Crash Analysis of Work-Zone Lane Closures with Left-Hand Merge and Downstream Lane Shift,” Paper #09-0979, DVD Compendium, Proceedings of 88th Annual Meeting, Transportation Research Board, Washington, DC, 2009.)

2.4.2 Crash Severity Rating

Roadway crashes are commonly identified in one of the following categories on the basis on their severity:

• Fatal crash is one where the crash results in at least one death.
• Injury crash results in non-fatal bodily injury.
• Property damage only (PDO) involves damage to property but does not result in bodily injury /fatality.

The National Highway Traffic Safety Administration (NHTSA) uses the following scale to report the extent of a roadway crash or the severity of an associated injury:

• KABCO injury scale: KABCO is a coding scheme designed for police officers assessing the crash scene. The scale requires no medical training for police officers at the crash scene to assess the severity level of the injury/trauma. This scale has been criticized for coding inconsistencies. See Table 27 for guidelines on KABCO coding.
• Abbreviated injury scale (AIS): AIS is an anatomically based severity scoring scheme that classifies each injury in every region of human body according to its relative severity on a six-point adjectival scale. AIS is often used with the KABCO scale in NHTSA reporting. See Table 28 for guidelines on AIS coding.

Table 27. KABCO injury scale.

Code	Severity	Description
K	Fatal	Any injury that results in death within 30 days of crash occurrence
A	Incapacitating	Any injury other than a fatal injury which prevents the injured person from walking, driving, or normally continuing the activities the person was capable of performing before the injury occurred (e.g., severe lacerations, broken limbs, damaged skull)
B	Injury evident	Any injury other than a fatal injury or an incapacitating injury that is evident to observers at the scene of the crash in which the injury occurred (e.g., abrasions, bruises, minor cuts)
C	Injury possible	Any injury reported that is not a fatal, incapacitating, or non-incapacitating evident injury (e.g., pain, nausea, hysteria)
O	Property damage only	Property damage to property that reduces the monetary value of that property

Table 28. Abbreviated injury scale.

Code	Severity	Description
AIS 6	Fatal	Loss of life due to decapitation, torso transaction, massively crushed chest, etc.
AIS 5	Critical	Spinal cord injury, excessive second- or third-degree burns, cerebral concussion (unconscious more than 24 hours)
AIS 4	Severe	Partial spinal cord severance, spleen rupture, leg crush, chest wall perforation, cerebral concussion (unconscious less than 24 hours)
AIS 3	Serious	Major nerve laceration; multiple rib fracture, abdominal organ contusion; hand, foot, or arm crush/amputation
AIS 2	Moderate	Major abrasion or laceration of skin, cerebral concussion finger or toe crush/amputation, close pelvic fracture
AIS 1	Minor	Superficial abrasion or laceration of skin, digit sprain, first-degree burn, head trauma with headache or dizziness
AIS 0	Uninjured	No injury

2.4.3 Monetary Value of Crashes

There are two approaches in assigning a monetary value for roadway crashes:

• Human capital costs: Include those “hard dollar” costs related directly to the crash such as property damage, medical care, compensations and legal costs. Primary sources include NHTSA and the National Safety Council (NSC) bulletins.
• Comprehensive costs: Include the intangible nonmonetary losses or consequences to individuals, families and the society, in addition to the human capital costs. Examples include the risk of loss of life, physical and mental suffering, diminished quality of life, and permanent cosmetic damage. Primary sources include USDOT estimates (USDOT, Treatment of the Value of Preventing Fatalities and Injuries in Preparing Economic Analyses-Revised Departmental Guidance, Memorandum, Office of the Secretary of Transportation, U.S. Department of Transportation, Washington, DC. 2009.) of “Treatment of Value of Life and Injuries in Preparing Economic Evaluations” based on the economic value of a statistical life and the FHWA Technical Advisory (FHWA, Motor Vehicle Accident Costs, Technical Advisory T 7570.1, Federal Highway Administration, Washington, DC, 1994.), “Motor Vehicle Accident Costs.”

The FHWA report, Crash Cost Estimates by Maximum Police-Reported Injury Severity Within Selected Crash Geometries, serves a comprehensive resource for obtaining both human capital and comprehensive costs. (Council, F., E. Zaloshnja, T. Miller and B. Persaud, Crash Cost Estimates by Maximum Police-Reported Injury Severity Within Selected Crash Geometries, Report No. FHWA-HRT-05-051, Submitted to the Office of Safety Research and Development, Federal Highway Administration, 2005.) This report provides cost estimates for 22 scenarios of crash geometries, 2 vehicle speeds (≤ 45 mph, ≥ 50 mph), and 6 levels of KABCO crash severity rating combinations. Table 29 presents a sample of FHWA crash cost estimates for a given crash geometry in 2001 dollars. 49 To convert the cost estimates from 2001 dollars to the current year, human capital costs are adjusted using the CPI (all items). The adjustment to comprehensive cost is a two-step process: (1) the human capital cost portion of the comprehensive cost is adjusted using the CPI (all items), and (2) the remaining portion of the comprehensive cost is adjusted using the ECI (not seasonally adjusted, total compensation, total private industry).

Table 29. Sample FHWA crash cost estimates in 2001 dollars.

Crash Geometry	Speed Limit (mph)	Max. Injury Severity in Crash	Max. Injury Severity Code	Human Capital Cost per Crash		Comprehensive Cost per Crash
				Mean	Std. Err	Mean	Std. Err
Single vehicle struck human, at intersection	<=45	No injury	0	$8,512	997	$10,249	1,408
	<=45	B or C	1.5	$33,369	4,561	$60,333	9,021
	<=45	A	3	$163,157	15,153	$316,380	33,532
	<=45	K	4	$975,643	30,468	$3,234,016	114,015
	<=45	Injured, severity unknown	5	$67,342	22,127	$129,418	42,249
	<=45	Unknown	9	$14,386	-	$22,841	-
	>=50	No injury	0	$3,672	-	$4,015	-
	>=50	B or C	1.5	$54,605	32,590	$101,712	61,756
	>=50	A	3	$116,545	26,407	$189,805	36,182
	>=50	K	4	$1,022,983	1,695	$3,404,944	2,819
	>=50	Injured, severity unknown	5	$61,573	-	$146,281	-
	<=50	Unknown	N.A.	N.A.	N.A.	N.A.	N.A.

2.5 Emission Costs

Work zone activities have adverse effects on the environment through additional vehicle emissions resulting from reduced speeds and queuing. Vehicle emissions generally are categorized as:

• Air Pollutant Emissions – Include those emitted directly into the atmosphere, such as carbon monoxide (CO), volatile organic compounds, particulate matter (PM10), oxides of nitrogen (NOX), oxides of sulfur (SOX), and those formed in the atmosphere from the directly emitted pollutants, such as ozone and acidic depositions.
• Greenhouse Gases – Include those direct emissions that are not yet recognized as an air pollutants but trap heat within the atmosphere and thus contributing undesirable climatic effects, such as carbon dioxide (CO2).

Table 30 presents the list of major factors affecting the level and type of vehicular emissions. (Thompson, M., A. Unnikrishnan, A.J. Conway and C.M. Walton, A Comprehensive Examination of Heavy Vehicle Emission Factors, Report No. SWUTC/10/476660-00067-1, Southwest Region University Transportation Center, College Station, TX, 2010. Nesamani, K. S., Estimating Vehicle Emissions in Transportation Planning Incorporating the Effect of Network Characteristics on Driving Patterns, Ph.D. Dissertation, University of California, Irvine, 2007.)

In WZ RUC analysis, the expected increase in emissions (ton/mile) by emissions type is estimated as a function of vehicle type, reduced work zone speed, and increased congestion due to queuing and detours. Once the emission rates for different types of vehicles are estimated, the emissions cost is calculated as a function of vehicles miles traveled (VMT) and unit costs ($/ton) by emissions type. The emissions cost component of WZ RUC is the differential between emissions cost resulting from work zone activities and the pre-construction emissions costs

Emissions Cost = ∑ (VMT x Emissions Rate x Cost/ton) by Emissions Type
WZ RUC Emissions Cost = Emission Cost (work zone) - Emission Cost (pre-construction)

Procedures for estimating emission rates and cost per ton values are presented in sections 2.5.1 and 2.5.2, respectively.

Table 30. Factors affecting vehicular emissions.

Roadway Characteristics	Traffic Characteristics	Driver Characteristics	Vehicle Characteristics	Weather Characteristics
Number of lanes Lane width Sight distance Horizontal curves Vertical curves Grades Roadway type Speed limits Pavement quality Signal coordination Other traffic control measures	Volume Capacity Volume/Capacity ratio Vehicle composition Vehicle Speed	Attitude Experience Gender Age Aggressiveness Driving modes	Age Mileage Weight Fuel type Engine size Engine type an cycle characteristic Air to fuel mass ratio Catalyst Maintenance Aerodynamics Emission control devices Acceleration and deceleration characteristics	Temperature Humidity Visibility

2.5.1 Estimating Emissions Rates

There are several models for estimating roadway emissions. Based on the input parameters and the methodology used, these models are broadly classified into:

• Static emission factor models.
• Dynamic instantaneous emission models.

2.5.1.1 Static Emission Factor Models

Static emission factor models use emission factors (i.e., amount of pollutants released to the atmosphere for a given activity) to calculate emissions based on average operation conditions. These models typically include separate emission factors for a given speed and the type of vehicle (passenger cars, buses, light-duty trucks, medium-duty trucks, etc). These models generally are suitable for estimating emissions in large-scale planning studies where the estimations based on average speed are highly accurate; however, these models are not sensitive enough to capture the actual driving conditions such as acceleration, deceleration, idling, and cruising cycles in a work zone. For instance, an emission factor model will estimate the same quantity of emission for a vehicle that traveled smoothly at 15 mph speed in a non-work zone free flow condition and a vehicle that traveled across the work zone at an average speed of 15 mph speed under queuing and forced flow conditions. This limitation is due to the fact that the models lack sophisticated algorithms and data to account for variations in speed and acceleration profiles.

Notable examples include:

• Mobile 6.2: This model, developed by the EPA, is used in most of the U.S. except California. It provides estimates of criteria pollutants, toxic pollutants, and particulate matter by vehicle class (covering 28 vehicle types), roadway type (freeways, arterial, ramp and locals), time of day, fuel options, vehicle operating parameters, and other characteristics. It accounts separately for start emissions and running emissions. Mobile 6.2 can be used as a standalone program, while an earlier version of Mobile (version 5.0) is implemented in QUEWZ-98.
• EMFAC model: This model, developed by the California Air Resource Board (CARB), is used in California to estimate the emission rates for HC, CO, NORxR, PM, SOR2R, lead, and COR2R, as well as fuel consumption. The model provides rates for each emission type as a function of vehicle speed. The latest version of the EMFAC model includes low emission vehicle standards and EPA Tier II standards. The California Life-Cycle Benefit/Cost Analysis Model (Cal-B/C) version 3.2, a spreadsheet, uses EMFAC emission factors to estimate highway emissions cost. Table 31 provides a sample of EMFAC emission factors used in the Cal-B/C program for automobiles and trucks.

Table 31. EMFAC emissions factors (g/mi) used in Cal-B/C program – model year 2003.

Speed	Auto					Trucks
	CO	NO R X	PM R 10	SO R X	VOC	CO	NO R X	PM R 10	SO R X	VOC
5	16.97	1.39	0.10	0.01	1.97	31.44	16.57	0.71	0.12	3.60
10	14.25	1.21	0.07	0.01	1.48	26.81	15.19	0.63	0.12	3.18
15	12.23	1.07	0.06	0.01	1.18	20.51	13.11	0.51	0.11	2.58
20	10.79	0.97	0.05	0.01	0.99	16.68	11.70	0.42	0.11	2.19
25	9.75	0.90	0.04	0.01	0.88	14.29	10.80	0.36	0.11	1.93
30	8.98	0.86	0.04	0.00	0.80	12.78	10.28	0.31	0.11	1.74
35	8.42	0.83	0.04	0.00	0.75	11.83	10.08	0.28	0.11	1.62
40	8.02	0.81	0.03	0.00	0.72	11.27	10.18	0.25	0.11	1.53
45	7.77	0.81	0.03	0.00	0.71	11.00	10.59	0.23	0.11	1.47
50	7.66	0.82	0.03	0.00	0.70	10.98	11.35	0.22	0.11	1.42
55	7.71	0.84	0.03	0.00	0.71	11.19	12.54	0.21	0.11	1.40
60	7.97	0.88	0.03	0.00	0.73	11.69	14.30	0.20	0.11	1.38
65	8.51	0.94	0.03	0.00	0.76	12.55	16.87	0.20	0.11	1.38

2.5.1.2 Dynamic Instantaneous Emission Models

Dynamic emission factor models, otherwise called modal emission models, incorporate the effects of instantaneous changes in vehicle operating conditions in emission estimations. These models typically require extensive data for different operating scenarios at second-by-second intervals (Nesamani, 2007). Unlike emission factor based models, the dynamic models can accommodate changes in speed and acceleration profiles, and thus are suitable for applications at a micro-scale level. Many of these models have been integrated with traffic simulation models for evaluating the emission impacts of various traffic management strategies (Thompson et al., 2010). Notable examples of dynamic instantaneous emission models include:

• Motor Vehicle Emission Simulator (MOVES): This model is the new generation, state-of-the-art modeling tool, developed by the EPA, for estimating emissions from highway vehicles at a detailed level. The current version of this model, MOVES 10a, replaces Mobile 6.2 as the approved tool for use in transportation conformity analyses outside of California (EPA, Technical Guidance on the Use of MOVES2010 for Emission Inventory Preparation in State Implementation Plans and Transportation Conformity, Report No. EPA-420-B-10-023, Office of Transportation and Air Quality, United States Environmental Protection Agency, April, 2010.). This model is capable of estimating emissions on both a macro-scale (e.g., county level) and a micro-scale (e.g., work zone level). The model also can calculate emissions for the time aggregation level chosen (year, month, day, or hour). For example, if the user selects the hour option, the model will estimate emissions for each hour of a day based on the specific inputs for that hour (temperature, speed distribution, etc.). The model accounts for running, start, extended idle, evaporative, crank case, tire wear, brake wear, and life cycle process.

The vehicle classification used in MOVES10a is consistent with the classification used in the Highway Performance Monitoring System (HPMS). This model uses five different road types: off-network (parking lots, rest areas), rural highways with restricted access (i.e., can only be accessed by an on-ramp), rural highways with unrestricted accesses (arterials, connectors and local streets), urban highways with restricted access, and urban highways with unrestricted access.

• Comprehensive Model Emission Model (CMEM): This model, developed under NCHRP Project 25-11, can estimate emissions of cars and small trucks produced as a function of the vehicle's operating mode with high precision (Barth, M., F. An, T. Younglove, G. Scora, C. Levine, M. Ross and T. Wenzel, Development of a Comprehensive Modal Emissions Model, Final Report, NCHRP Project 25-11, National Cooperative Highway Research Program, Transportation Research Board, Washington DC, 2000.) This model is suitable for applications in project-level or corridor-specific transportation control measures (such as high-occupancy vehicle lanes), intelligent transportation systems (ITS) implementations (such as electronic toll collection), and traffic flow improvements (such as traffic signal coordination).
• Mobile Emission Assessment System for Urban and Regional Evaluation (MEASURES): This model, developed at Georgia Institute of Technology and North Carolina DOT, estimates emissions using an approach based on geographic information system (GIS) data.

2.5.2 Monetary Value of Emissions

Emission costs are social costs that are not borne directly by the road users but are estimated based on the impacts borne by the society in general. There is no consensus on how to assign a dollar value to quantify the impacts of each pollutant type. Unit costs of emissions typically used in practice are derived based on the economic analysis of health impacts caused by air pollutants and greenhouse gases.

Furthermore, the unit costs of emissions vary widely with source-related factors such as population density and land cover of the work zone location. Metropolitan areas with high population densities are affected more strongly by adverse health impacts of emissions than rural areas, and hence, higher unit costs are used. Therefore, practitioners should use emission costs that reflect region-specific values developed by the regional planning agency for each emission type. Examples of unit cost sources of emissions include:

• California Department of Transportation (Caltrans) estimates - See Table 32.
• HERS-ST Technical Report (2005) – See Table 33. In addition, Appendix F of the HERS-ST report provides dollar cost estimates per vehicle mile as a function of vehicle speed, vehicle type, and roadway functional class.

There is no consensus on guidelines on updating the existing year dollars to current year prices. The commonly used approach is to adjust the emission costs using Implicit Price Deflators for Gross Domestic Product-Goods. (California Life-Cycle Benefit/Cost Analysis Model (Cal-B/C) Technical Supplement to User’s Guide, Prepared by Booz Allen & Hamilton Inc., California Department of Transportation, Sacramento, 1999. Implicit Price Deflators for GDP can be obtained from Table 1.1.9 of the National Income and Product Account (NIPA) published by the Bureau of Economic Analysis. Using GDP deflators for adjustment treats emission costs as an economic product and will not capture the quality of life or well being.)

Table 32. Caltrans estimates ($/U.S. ton) of health cost of transportation emissions in 2010 dollars.

Pollutant	L.A./South Coast	CA Urban Area	CA Rural Area
Carbon Monoxide	$135	$70	$65
Nitrogen Oxide (NOx)	$55,700	$16,300	$12,100
Particular Matter (PM10)	$456,500	$131,800	$94,000
Sulfur Oxide (SOx)	$171,500	$65,800	$47,500
Volatile Organic Compounds	$3,465	$1,140	$895
Greenhouse Gases (C02) (Federal Register 74 FR 28759 (06-17-2009) suggests that the estimate of $33 per metric ton of carbon cited on page VIII-45 of National Highway Traffic Safety Administration (NHTSA)’s analysis may be used as a placeholder to measure the global benefits of reducing U.S. C02 (NHTSA Final Regulatory Impact Analysis, Corporate Average Fuel Economy for MY 2011 Passenger Cars and Light Trucks, published March 2009.)		$37

Table 33. HERS-ST estimates of air pollutant damage costs in 2000 dollars.

Pollutant	Damage Costs ($/ton)	Adjustment Factors
		Urban	Rural
Carbon Monoxide	$100	1	0.5
Volatile Organic Compounds	$2,750	1.5	1
Nitrogen Oxides	$3,625	1.5	1
Sulfur Dioxide	$8,400	1.5	1
Fine Particulate Matter (PM2.5)	$4,825	1	0.5
Road Dust	$4,825	1	0.5

2.6 Network/Corridor Level Impacts of Nearby Projects

Work zone can have more pronounced impacts at the corridor, network, and regional level than at the immediate work zone itself, particularly for significant projects. Hence, the analysis of work zone impacts and associated WZ RUC computation should extend beyond the immediate work zone area. Practitioners can use the guidance provided in the FHWA Traffic Analysis Toolbox Volume IX in selecting a work zone modeling program or approach to quantify impacts on a wider scale. (Hardy, M. and K. Wunderlich, Traffic Analysis Tools Volume IX: Work Zone Modeling and Simulation-A Guide for Analysts, Report No. FHWA-HOP-09-001, Office of Operations, Federal Highway Administration, Washington, DC, 2009.) The impact assessment and associated WZ RUC at the corridor, network, and regional level can help an agency to coordinate transportation management strategies within and outside the agency.

2.7 Non-Monetary Quantitative and Qualitative Factors

In addition to monetary components, other work zone effects that impact the community at-large are also taken into consideration. These factors are generally hard to monetize and therefore should be considered as non-monetary or qualitative factors in the decision-making process. The key non-monetary and qualitative factors include:

• Noise
• Business and societal impacts

2.7.1 Noise

Excessive noise resulting from work zone construction activities can have adverse effects on road users and other stakeholders. Noise can be a significant issue, especially with nighttime construction in residential and business areas, and may violate compliance of local ordinance requirements. Apart from general nuisance, excessive noise can pose health problems. Therefore, it is essential for highway agencies to estimate the work zone noise level and employ appropriate noise mitigation and work schedule strategies. Additional costs associated with noise mitigation strategies, such as the installation of noise barriers, should be considered in the MOT alternative analysis.

Practitioners can utilize the FHWA Roadway Construction Noise Model (RCNM) in predicting noise for highway construction projects of varying complexity. The RCNM is a Windows-based computer program that enables the prediction of construction noise levels for various construction operations while requiring no additional effort of collecting extensive project-specific input data. The RCNM is based on a compilation of empirical data and the application of acoustical propagation formulas. The RCNM provides the estimation of maximum, average, and percentile statistics of sound level at a work zone event over a given period of observation time for up to 10 receptor locations and 20 pieces of construction equipment.

Little information is available on monetizing the damage caused by construction noise. Delucchi and Hsu (1998) provide a theoretical basis and cost estimates for monetizing the external damage caused by noise emitted from motor vehicles under normal operating conditions. (Delucchi, M. and S. Hsu, The External Damage Cost of Noise Emitted from Motor Vehicles, Journal of Transportation and Statistics, Bureau of Transportation Statistics, 1998.) FHWA’s highway cost allocation study uses noise damage costs in estimating the share of highway costs that various highway users pay; however, these costs provide per mile rates (cents per mile) based on highway functional classification and vehicle type under normal operating conditions and do not account for work zone effects.

2.7.2 Business and Local Community Impacts

Work zones can affect accessibility to local business premises, thus adversely impacting local commerce. Many business owners are concerned about the potential negative impacts on their businesses, which may include: (Wildenthal, M. T. and J. L. Buffington, “Estimated Construction Period Impact of Widening State Highway 21, in Caldwell, Texas,” Transportation Research Record No. 1559, Journal of the Transportation Research Board, Washington, D.C, 1996.)

• Customer access and parking, and delivery access.
• Parking issues.
• Utility outages and disruptions.
• Congestion and traffic pattern changes.
• Temporary loss of customers.
• Decrease in gross sales revenue and net profits.
• Adverse impacts on full time and part time employment.
• Decrease in property and land values.

Highway agencies address the concerns of individual business owners by conducting business impact studies in the project development phase to identify critical needs and priorities of different types of businesses. Agencies then implement management strategies in the construction phase to mitigate these impacts.

Wolffing et al. (2004) conducted a survey to identify how State highway agencies gather information and manage business owners’ concerns. (Wolffing, C., J. Liesman, R. Young and K. Ksaibati, Highway Construction Related Business Impacts: Phase I Report, Report No. FHWA-WY-04/01F, Wyoming Department of Transportation, Cheyenne, WY, March 2004.) This study found that most State agencies involve the business owners and other stakeholders early in the project development process through public information meetings/hearings. In some cases, agencies may involve local government officials or hire facilitators/liaison officers in the process before scheduling public information meetings.

In addition to public meetings, agencies use strategies such as surveys with business managers and door-to-door visits with residents and business owners to gather information of local community and business impacts. The purpose of these meetings is to provide project information to business owners, answer questions about the project, and solicit inputs regarding potential concerns and impacts. The inputs gathered at these meetings often are incorporated as mitigation strategies in devising MOT alternatives.

Local communities have similar concerns, such as issues related to resident access, decrease in property and land values, noise, and air pollution. The strategies used for gathering information of societal impacts are similar to those for gathering information on business impacts. Some agencies, such as Florida DOT, have a community awareness program for every project to involve with adjacent communities early in the process and address local conditions during construction.

2.8 Data Requirements for WZ RUC Mobility Analysis

This section presents a discussion of the input data required for conducting work zone mobility impact analysis. The following inputs are required to estimate or assess work zone mobility impacts for WZ RUC computation:

• Hourly traffic demand.
• Traffic composition.
• Work zone capacity.
• Travel speed.
• Work zone configuration.
• MOT strategy.

2.8.1 Hourly Traffic Demand

Hourly traffic demand is the 24-hour hourly distribution of vehicles passing through the work zone in a single direction under normal operating conditions. The hourly variations can be obtained from actual traffic count measurements at the work zone site or estimated from the projected ADT using hourly distribution factors (percent of ADT during the specific hour). In determining hourly demand, distinctions should be made among weekday, weekend, and seasonal traffic patterns. The hourly demand also may vary between urban and rural roadways, by location, and among various functional classes.

Hourly distribution factors can be determined by analyzing traffic data obtained from data collection devices such as WIM systems, automatic vehicle recorders (ATR), and accumulative count recorders (ACR). In the absence of such site-specific data, regional estimates, typical, or default hourly patterns can be used. Table 34 presents an example of hourly distribution factors used in MicroBENCOST for urban and rural highways. Using default hourly traffic patterns may not be representative of the actual project conditions and can be appropriate for preliminary analyses.

Table 34. Sample hourly traffic distribution factors.

Hour of the Day	Urban			Rural
	Hourly Factors	Percent Inbound Direction	Percent Outbound Direction	Hourly Factors	Percent Inbound Direction	Percent Outbound Direction
0 - 1	1.20	47.0	53.0	1.80	48.0	52.0
1 - 2	0.80	43.0	57.0	1.50	48.0	52.0
2 - 3	0.70	46.0	54.0	1.30	45.0	55.0
3 - 4	0.50	48.0	52.0	1.30	53.0	47.0
4 - 5	0.70	57.0	43.0	1.50	53.0	47.0
5 - 6	1.70	58.0	42.0	1.80	53.0	47.0
6 - 7	5.10	63.0	37.0	2.50	57.0	43.0
7 - 8	7.80	60.0	40.0	3.50	56.0	44.0
8 - 9	6.30	59.0	41.0	4.20	56.0	44.0
9 - 10	5.20	55.0	45.0	5.00	54.0	46.0
10 - 11	4.70	46.0	54.0	5.40	51.0	49.0
11 - 12	5.30	49.0	51.0	5.60	51.0	49.0
12 - 13	5.60	50.0	50.0	5.70	50.0	50.0
13 - 14	5.70	50.0	50.0	6.40	52.0	48.0
14 - 15	5.90	49.0	51.0	6.80	51.0	49.0
15 - 16	6.50	46.0	54.0	7.30	53.0	47.0
16 - 17	7.90	45.0	55.0	9.30	49.0	51.0
17 - 18	8.50	40.0	60.0	7.00	43.0	57.0
18 - 19	5.90	46.0	54.0	5.50	47.0	53.0
19 - 20	3.90	48.0	52.0	4.70	47.0	53.0
20 - 21	3.30	47.0	53.0	3.80	46.0	54.0
21 - 22	2.80	47.0	53.0	3.20	48.0	52.0
22 - 23	2.30	48.0	52.0	2.60	48.0	52.0
23 - 24	1.70	45.0	55.0	2.30	47.0	53.0

2.8.2 Traffic composition

A traffic stream typically includes various vehicle types—passenger cars, buses, single-unit trucks, tractor-trailers, and multi-trailer trucks. These vehicle types are associated with different usage, operating characteristics, and performance, and thus, have different vehicle operating costs and monetary values of time. Furthermore, heavy vehicles occupy more roadway space than passenger cars, affecting roadway capacity. Inputs for traffic composition can be categorized broadly as:

• Number of passenger cars (vehicle classes 1 through 3 as defined in the FHWA TMG) (Traffic Monitoring Guide, Report No FHWA-PL-01-021, Office of Highway Policy Information, Federal Highway Administration, Washington, DC, 2001.)
  • Small automobiles (Highway Economic Requirement System (HERS) considers small automobiles as smaller cars as opposed to FHWA vehicle class 1 (i.e. motorcycles.)
  • Medium/large automobiles
  • Pickups & vans
• Number of single-unit trucks (FHWA TMG vehicle classes 4 through 7)
  • Six-tire trucks
  • Three or more axle single-unit trucks
• Number of combination trucks (FHWA TMG vehicle classes 8 through 13)
  • Three/four axle combination trucks
  • Five or more axle combination trucks

Typical sources of data include an agency’s traffic monitoring programs and HPMS data inventories; in the absence of location-specific data, typical values representative of project conditions can be substituted.

2.8.2.1 Passenger Car Units

As heavy vehicles in the traffic stream occupy more physical space than passenger cars, these vehicles affect the number of vehicles that can be served on a roadway segment. Therefore, to allow a consistent measure of traffic flow in demand-capacity analysis, each heavy vehicle is converted into an equivalent number of passenger cars using a heavy vehicle adjustment factor called passenger-car equivalents (ERT). This conversion depends on the proportion of heavy vehicles in the traffic stream as well as the geometric alignment of the roadway.

Chapters 11 and 14 of the HCM 2010 present ERT values for multilane highways and highways respectively, for various terrain types and grade geometries. (Highway Capacity Manual 2000, Transportation Research Board, Washington, DC, 2000. Highway Capacity Manual 2010, Transportation Research Board, Washington DC, 2010.)

2.8.3 Work Zone Configuration

Work zone configuration inputs required for WZ RUC analysis typically include:

• Number of lanes in each direction.
• Number of open lanes through the work zone in each direction.
• Length of the lane closure.
• Lane width.
• Lateral clearance restrictions.
• Turn restrictions.
• Layout of project sequencing.
• Availability and traffic characteristics of alternative routes.
• Hours of lane closure (begin and end time).
• Hours of work activity (begin and end time).
• Signalization
• Segment information – network information

2.8.4 Work Zone Capacity

Work zone capacity is defined as the maximum sustainable flow rate at which vehicles can pass a given point or uniform segment of a lane or roadway in a work zone during a specified period under prevailing roadway, traffic, and control conditions. Capacity usually is expressed as passenger cars per hour per lane (pcphpl) or vehicles per hour per lane (vphpl).

The vehicle capacity of a facility is a function of roadway and traffic characteristics; the capacity is at the maximum under base conditions and uninterrupted traffic flow. The base conditions of a facility represent best possible characteristics at which no further improvements would increase vehicle capacity. Base conditions include factors such as the criteria for minimum lane width and lateral clearance, level terrain (less than 2 percent), free-flow speed, flow of passenger cars only, no direct access points along the segment, and a good, rideable surface.

The capacity values (at base conditions) for various highway types are recommended in the HCM 2010. HCM 2010 also presents guidelines to determine reduction in capacity resulting from work zone activities. The suggested values are 1,600 pcphpl for short-term work zones and a range of 1,550 to 2,060 pcphpl for long-term work zones.

As the prevailing conditions of a facility deviate from the base conditions, appropriate adjustments to the capacity must be made. Factors that warrant adjustments to the work zone capacity estimates include:

• Work zone configuration.
  • Number of opened lanes.
  • Number of closed lanes.
  • Location of closed lanes (left or right).
  • Work zone grade.
  • Work zone length.
  • Lane width.
  • Area type (rural/urban).
  • Presence of ramps.
• Traffic characteristics.
  • Effect of heavy vehicles.
  • Driver population.
  • Entrance ramp volume.
  • Lateral distance to the open travel lanes.
  • Work zone speed.
  • Platoon factor (i.e., fluctuation in capacity utilization).
• Intensity of work activity.
• Work zone duration (short term or long term).
• Weather condition.
• Work time (day or night).

In addition to the HCM 2010 guidelines, there are numerous work zone capacity models available. Notable examples include (presented in chronological order):

• Weng and Meng (Weng, J. and Q. Meng, A Decision Tree-based Model for Work Zone Capacity Estimation, Paper No. 11-0865, DVD Compendium, Proceedings of 90th Annual Meeting, Transportation Research Board, Washington, DC, 2011.) – Presents a decision tree model based on 16 influencing factors and 182 data sets from 14 States and cities.
• Benekohal et al (Benekohal, R. F. A. Kaja-Mohideen, M. V. Chitturi, A Methodology for Estimating Operating Speed and Capacity in Work Zones, Transportation Research Record No. 1883, Journal of the Transportation Research Board, Washington, DC, 2004.) – Presents a methodology based on data from 11 work zone sites in Illinois.
• Sarasua et al. (Sarasua, W. A., W. J. Davis, D.B. Clarke, J. Kottapally, P. Mulukutla, Estimating Interstate Highway Capacity for Short-Term Work Zone Lane Closures: Development of Methodology, Transportation Research Record No. 1877, Journal of the Transportation Research Board, Washington, D.C., 2004.) – Presents a prediction model based on data from 22 short-term work zone sites along South Carolina’s Interstate system.
• Al-Kaisy & Hall (Al-Kaisy, A. and F. Hall, Guidelines for Estimating Freeway Capacity at Long-Term Reconstruction Zones, CDROM Compendium, Proceedings of 81th Annual Meeting, Transportation Research Board, Washington, DC, 2002.) – Presents a prediction model based on data from 7 long-term work zone sites in Toronto, Ontario.
• Kim’s model (Kim, T., D. J. Lovell, and J. Paracha, A New Methodology to Estimate Capacity for Freeway Work Zones, Paper No. 01-0566, CDROM Compendium, Proceedings of 80th Annual Meeting, Transportation Research Board, Washington, DC, 2001.) – Presents a prediction model based on data from 12 work zone sites in Maryland.
• Jiang, Y (Jiang, Y. Traffic capacity, Speed and Queue-discharge rate for Indiana’s Four-lane Freeway Work Zones. Transportation Research Record No. 1657, Journal of the Transportation Research Board, Washington, D.C.,1999) – Presents the findings of work zone capacity studies of 12 data sets from 4 work zone sites in Indiana.
• Dixon et al. (Dixon, K. K., Hummer, J. E. and Lorscheider, A. R. Capacity for North Carolina Freeway Work Zones. Transportation Research Record No. 1529, Journal of the Transportation Research Board, Washington, D.C., 1996.) – Presents the findings of capacity studies of 24 short-term freeway lane closures in North Carolina.
• Krammes & Lopez (Krammes, R. A. and G. O. Lopez, Updated Short-Term Freeway Work Zone Lane Closure Capacity Values, Report No. FHWA/TX-92/1108-5, Texas Department of Transportation, Austin, TX, 1992.) – Adopted in QUEWZ-98, Cited in HCM 2000 for short-term work zone capacity.
• Dudek & Richards (Dudek, C. L. and S. H. Richards. Traffic Capacity through Work Zones on Urban Freeways. Report FHWA/TX-81/228-6, Texas Department of Transportation, Austin, TX, 1981.) – Adopted in 1984 version of QUEWZ. Presents the findings of work zone capacity studies conducted in Houston and Dallas, Texas.

2.8.5 Travel Speed

Two key inputs required for delay-capacity analysis are the free-flow speed (adjusted to roadway conditions) and the work zone speed limit. Free-flow speed is the operating speed at which the traffic travels under normal operating conditions (when there is no work zone). Work zone speed limit is the posted speed limit in a work zone. At this speed, the vehicles are expected to travel the work zone with no queuing and reduction in posted speed limit. As the demand/capacity ratio approaches 1.0 (i.e., the demand reaches saturation levels), the travel speed decreases. When the demand exceeds available capacity, queuing can result.

2.8.6 Maintenance of Traffic Strategy

MOT is a set of coordinated strategies to meet the traffic mobility and safety needs within a work zone. MOT traditionally has included temporary traffic control strategies and devices for managing work zone traffic; however, with the implementation of the FHWA Final Rule on Work Zone Safety and Mobility, the scope of MOT has expanded to include strategies for addressing public information and transportation operations needs for all projects with significant work zone impacts including Federal-aid projects. (A significant project is one that, alone or in combination with other concurrent projects nearby is anticipated to cause sustained work zone impacts (or high level of disruption) that are greater than what is considered tolerable based on the respective agency’s policy and/or engineering judgment. The agency’s work zone policy provisions, the project’s characteristics, and the magnitude and extent of the anticipated work zone impacts should be considered when determining if a project is significant or not. Frequently Asked Questions for the Work Zone Safety and Mobility Rule.) These strategies are grouped taxonomically as follows:

• Temporary traffic control (TTC) strategies.
  • Traffic control strategies – include various traffic control approaches to accommodate road users within the work zone or the adjoining corridor in an efficient and safe manner, while providing adequate access to construction activities.
  • Traffic control devices – include various traffic control devices installed for maintaining work zone traffic as outlined in the MUTCD standards.
  • Project coordination, contracting, and innovative construction strategies – include coordination strategies with other projects and infrastructure elements (e.g., railroad, utilities).
• Transportation operations strategies
  • Demand management strategies - include various strategies intended to reduce the volume of traffic traveling through the work zone.
  • Corridor/network management strategies- include various traffic operations techniques and technologies to optimize traffic flow through the work zone and adjacent roadways.
  • Work zone safety management strategies – include various devices, features, and management procedures to address work zone safety concerns.
  • Traffic/incident management and enforcement strategies – include various strategies to monitor traffic conditions and make adjustments as required to traffic operations based on changing conditions.
• Public information strategies
  • Public awareness strategies - include various methods to educate and reach out to the public, businesses, and the community on the upcoming/ongoing project work zones and potential impacts.
  • Motorist information strategies – provide current and/or real-time information to road users regarding the project work zone.

Tables 35 through 37 presents specific strategies classified under each of these groups (Jeannotte, K., and A. Chandra, Developing and Implementing Transportation Management Plans for Work Zones, Report No. FHWA-HOP-05-066, Office of Transportation Operations, Federal Highway Administration, Washington, DC, 2005.

Table 35. Work zone management strategies by category – temporary traffic control.

Traffic Control	Traffic Control Devices	Project Coordination, Contracting, and Innovative Construction
Construction phasing/staging Full roadway closures Lane shifts or closures Reduced lane widths to maintain number of lanes (constriction) Lane closures to provide worker safety Reduced shoulder width to maintain number of lanes Shoulder closures to provide worker safety Lane shift to shoulder/median to maintain number of lanes One-lane, two-way operation Two-way traffic on one side of divided facility (crossover) Reversible lanes Ramp closures/relocation Freeway-to-freeway interchange closures Night work Weekend work Work hour restrictions for peak travel Pedestrian/bicycle access improvements Business access improvements Off-site detours/use of alternate routes	Temporary signs Warning Regulatory Guide/information Changeable message signs Arrow panels Channelizing devices Temporary pavement markings Flaggers and uniformed traffic control officers Temporary traffic signals Lighting devices	Project coordination Coordination with other projects Utilities coordination Right-of-way coordination Coordination with other transportation infrastructure Contracting strategies Design-build A+B bidding Incentive/disincentive clauses Lane rental Innovative construction techniques (pre-cast members, rapid cure materials)

Source: Jeannotte and Chandra (2005)77 (Jeannotte, K., and A. Chandra, Developing and Implementing Transportation Management Plans for Work Zones, Report No. FHWA-HOP-05-066, Office of Transportation Operations, Federal Highway Administration, Washington, DC, 2005.)

Table 36. Work zone management strategies by category – transportation operations.

Demand Management	Corridor/Network Management	Work Zone Safety Management	Traffic/Incident Management and Enforcement
Transit service improvements Transit incentives Shuttle services Ridesharing/carpooling incentives Park-and-ride promotion High-occupancy vehicle lanes Toll/congestion pricing Ramp metering Parking supply management Variable work hours Telecommuting	Signal timing/ coordination improvements Temporary traffic signals Street/ intersection improvements Bus turnouts Turn restrictions Parking restrictions Truck/heavy vehicle restrictions Separate truck lanes Reversible lanes Dynamic lane closure system Ramp metering Temporary suspension of ramp metering Ramp closures Railroad crossings controls Coordination with adjacent construction site(s)	Speed limit reduction/ variable speed limits Temporary traffic signals Temporary traffic barrier Movable traffic barrier systems Crash-cushions Temporary rumble strips Intrusion alarms Warning lights Automated flagger assistance devices Project task force/committee Construction safety supervisors/inspectors Road safety audits TMP monitor/inspection team Team meetings Project on-site safety training Safety awards/incentives Windshield surveys	ITS for traffic monitoring/ management Transportation management center Surveillance Helicopter for aerial surveillance Traffic Screens Call boxes Mile-post markers Tow/freeway service patrol Total station units Photogrammetry Coordination with media Local detour routes Contract support for incident management Incident/emergency management coordinator Incident/emergency response plan Dedicated (paid) police enforcement Cooperative police enforcement Automated enforcement Increased penalties for work zone violations

Source: Jeannotte and Chandra (2005)77 (Jeannotte, K., and A. Chandra, Developing and Implementing Transportation Management Plans for Work Zones, Report No. FHWA-HOP-05-066, Office of Transportation Operations, Federal Highway Administration, Washington, DC, 2005.)

Table 37. Work zone management strategies by category – public information.

Public Awareness

Motorist Information

Brochures and mailers Press releases/media alerts Paid advertisements Public information center Telephone hotline Planned lane closure web site Project web site Public meetings/hearings Community task forces Coordination with media/schools/businesses/emergency services Work zone education and safety campaigns Work zone safety highway signs Rideshare promotions Visual information (videos, slides, presentations) for meetings and web

Traffic radio Changeable message signs Temporary motorist information signs Dynamic speed message sign Highway advisory radio Extinguishable signs Highway information network (web-based) 511 traveler information systems (wireless, handhelds) Freight travel information Transportation management center

Source: Jeannotte and Chandra (2005)77 (Jeannotte, K., and A. Chandra, Developing and Implementing Transportation Management Plans for Work Zones, Report No. FHWA-HOP-05-066, Office of Transportation Operations, Federal Highway Administration, Washington, DC, 2005.)

2.9 Tools for WZ RUC Computation

Available WZ RUC computation tools can be categorized into two groups: work zone traffic analysis and economic analysis tools.

2.9.1 Work Zone Traffic Impact Analysis Tools

Traffic analysis tools help practitioners to understand and assess the mobility impacts of work zone strategies prior to deployment and monitor performance during construction. While the traffic analysis tools focus on quantifying the mobility impacts, a robust mobility analysis is often instrumental in the assessment of factors such as safety, economic, environmental and other work zone related impacts. (Hardy, M., and K. Wunderlich, Traffic Analysis Tools Volume VIII: Work Zone Analysis - A Guide for Decision-Makers, Report No. FHWA-HOP-08-029, Office of Operations, Federal Highway Administration, Washington, DC, 2008.) The mobility impacts form the core for aggregating user delay costs, VOC, impacts to local businesses, and costs to the local agency.

Various traffic analysis tools are available for analyzing work zone related mobility impacts at various stages of a project. The FHWA Traffic Analysis Toolbox (TAT) provides detailed guidance on using various traffic analysis methodologies and tools. (FHWA Traffic Analysis Toolbox.) FHWA TAT organizes currently available tools into six categories:

• Sketch-planning/HCM based methods.
• Travel demand models.
• Traffic signal optimization.
• Macroscopic simulation.
• Mesoscopic simulation.
• Microscopic simulation.

The following section limits the discussion to sketch-planning and HCM based tools.

2.9.1.1 Sketch-Planning and HCM Methodologies

These tools utilize hourly traffic demand data and capacity analyses to estimate and quantify work zone impacts. These estimates may be less precise, owing to the simplistic approach adopted by these tools, and thus often are considered more appropriate for use in the early stages of a project.

Some tools have advanced functionalities. For example, Quick Zone can handle delay impacts at the corridor level and facilitates tradeoff analyses between construction costs and delay costs, while CA4PRS is equipped to handle “what if” scenarios for highway rehabilitation to identify solutions that balance on-schedule construction production, traffic inconvenience, and agency costs. Commonly used sketch-planning and HCM based tools are listed in Appendix A, Volume I of the TAT. (Alexiadis,V., K.Jeannotteand A. Chandra, Traffic Analysis Toolbox Volume I: Traffic Analysis Tools Primer, Report No. FHWA-HRT-04-038, Office of Operations, Federal Highway Administration, Washington, DC, 2004.) Notable examples include:

• Spreadsheet-based tools.
• QUEWZ-98.
• Quick Zone.
• CA4PRS.

Spreadsheet-based Tools

Several State DOTs have developed spreadsheet-based tools to analyze the traffic impacts at work zones. Typical examples include those developed by Arizona, Florida, Idaho, Illinois, Maryland, Michigan, Missouri New Jersey, Ohio, Pennsylvania, and Virginia. While most spreadsheet-based tools use analytical equations and HCM procedures, some tools use only simple mathematical formulae.

In addition to these general capabilities, some spreadsheet-based tools possess unique functionalities tailored to a particular agency’s needs. Some of the salient features are summarized as follows:

• Maryland’s Loss of Public Benefit (LOPB) spreadsheet can estimate crash costs and has a separate module for temporary signal and flagging operations.
• Florida’s spreadsheet can perform demand-capacity analysis for two-lane, two-way operations, and urban streets. This tool includes formulae for calculating crash costs and a general impact factor to adjust the overall WZ RUC results.
• Illinois’s tool is equipped with an improved queuing analysis methodology calibrated using field data from 13 work zones. This approach includes separate speed-flow curves for work zones with speed limit of 45 mph and a flagger, work zones with speed limit of 45 mph and without a flagger, and work zones with speed limit of 55 mph.
• Highway User Benefit-Cost Analysis Program (HUB-CAP), a Virginia DOT benefit-cost analysis spreadsheet tool, includes a comprehensive crash cost estimation tool based on the KABCO crash severity scale. This tool also includes look-up tables of source information used for deriving unit costs.
• The Construction Congestion Cost (CO3) tool, developed for Michigan DOT, has an additional module for analyzing the impact of different construction methods on construction costs. This module includes individual components for calculating project costs associated with labor, equipment, materials, traffic control, and project-related agency costs. Notable among them is the labor cost component, which takes the fixed mobilization costs and productivity-based variable labor wage costs into account for standard and overtime conditions.
• Oregon DOT has replaced its spreadsheet-based package with a web-based tool, Work Zone Traffic Analysis Tool (WZTA), that allows users to access location-specific traffic data, free flow capacity, and vertical and horizontal geometric features of the work zone location and generate delay times and queue length for a user-specified lane closure period.
• Colorado DOT uses a standalone program, Work Zone-RUC that possesses typical capabilities of a spreadsheet-based tool. This tool contains productivity rates (number of estimated days to complete a specific unit of work) for typical highway construction related activities. It also allows adjustments to lane capacity based on the activity type, lateral distance to obstruction, and geometric features of the work zone location. It allows only two types of MOT strategies: crossovers and single lane closures.

Figures 4 through 7 present screenshots of some spreadsheet tools.

Figure 4. Sample screenshot from the New Jersey DOT spreadsheet tool.

Figure 5. Sample screenshot from the Colorado WZ RUC program with input screens (left) and the productivity rates for various highway construciton activities and the corresponding lane capacity adjustment values (right).

Figure 6. Sample screenshot from the Maryland LOPB tool, showing work zone flagger operation inputs.

Figure 7. Sample screenshot from the Michigan CO3 spreadsheet, showing the construction cost module.

Inputs and Outputs

The basic inputs required for spreadsheet-based tools are:

• Work zone configuration- total number of lanes, number of closed lanes, lane width, normal and work zone speed, period of lane closure, normal and work zone lane capacity, etc.
• Traffic – hourly traffic demand, percent trucks, etc.
• Unit costs - hourly cost of travel delay, VOC for various vehicle types, etc.

The typical outputs reported by spreadsheet-based tools are travel delay time, number of queued vehicles, queue lengths, and in some cases, crash costs and emission estimates.

QUEWZ-98

Developed for the Texas DOT, QUEWZ-98 is a DOS-based analysis tool for evaluating freeway work zone lane closures. This tool simulates traffic conditions on a freeway segment with and without a lane closure in place and provides estimates of the queue lengths and additional road user costs resulting from work zone lane closures. The computed WZ RUC include travel time costs, VOC, and excess emissions. QUEWZ-98 can be used to identify time schedules for lane closures that will not produce excessive queue lengths and delays.

QUEWZ-98 has two output options:

• RUC option - this option analyzes a user-specified lane closure configuration and schedule of work activities. The outputs include estimates of traffic volumes, capacities, speeds, queue lengths, emissions, and additional road user costs for each hour affected by the lane closure.
• Lane closure schedule option - this option summarizes the hours of the day for a given number of closed lanes without causing user-defined excessive queuing.

QuickZone

Developed by FHWA, QuickZone is a sketch-planning tool for analyzing work zone mobility impacts such as traffic delays, queuing, and associated delay costs. The tool uses a link-node system for network layout and configuration and a deterministic delay estimation algorithm to estimate traffic delays and queuing.

This tool can be used in quantifying delay at the corridor level resulting from work zone related mobility constraints, identifying the mobility impacts of alternative project phasing plans, evaluating the impacts of various construction staging strategies, and supporting tradeoff analyses between construction costs and delay costs.

Capabilities

QuickZone can estimate travel delay time, queuing, and delay costs per vehicle hour for not only the roadway segment under work zone but also all available alternative segments of the roadway network defined in the program. This tool can be used in estimating traffic delays, potential backups, and associated delay costs for both an average day of work and for the whole life cycle of construction.

Inputs and Outputs

QuickZone requires the following data for evaluating mobility impacts in work zones:

• Network (Nodes and Links) - a network of nodes and links, segment (link) capacity, segment length, free-flow speed, and jam density.
• Traffic volume - hourly demand for each link and each day of a week.
• Project Information - project description, start date, project duration, yearly demand increase, yearly capacity decrease.
• Construction Phase Data - phase description, duration, infrastructure cost.
• Work Zone Plan - work zone start and end times, links and nodes affected by work zone, mitigation strategies, travel behavior (mode change, trip cancellation).

QuickZone reports the following outputs:

• Delay Graph - delay graphs comparing up to six phases of the project for the whole or any day of the week or delay graph for just a single phase.
• Travel Behavior Summary - a summary of the number of vehicles that choose one of the four travel behaviors determined for each phase: cancel trip, mode shift, hour time shift, and takes detours.
• Life Cycle Costing Graph - a summary of both delay and infrastructure costs for the project by year.
• Summary Table - provides estimates of queue length, delay, travel behavior, and costs. The table provides average, total, or maximum values for each phase as well as for the individual work zone plans within each phase.

Advantages and Disadvantages

Unlike similar spreadsheet based tools, QuickZone is capable of modeling the entire network for work zone mobility impact analysis. In addition, the tool evaluates traveler behavior to prevailing traffic conditions such as route changes, peak-spreading, mode shifts, and trip losses. While the interface is simple and easier to use, it may require more time and effort than similar spreadsheet-based tools. (Edara, P., Estimation of Traffic Impacts at Work Zones: State of the Practice, Report No. VTRC 06-R25, Virginia Department of Transportation, Richmond, VA, 2006.)

CA4PRS

CA4PRS is a construction schedule, staging, and traffic analysis tool that helps to identify optimal rehabilitation strategies by balancing project duration, lane closure strategies, and road user impacts. The traffic analysis module quantifies the impact of various work zone lane closure strategies on the traveling public in terms of WZ RUC and travel delay time, while the scheduling module estimates the required number of lane closures for project completion by taking into account the alternative strategies for pavement designs, lane closure tactics, and contractor logistics. The tool employs “what if scenarios” to determine which rehabilitation strategies maximize production without creating unacceptable traffic delays. (Lee, E. B., and C. W. Ibbs, Computer Simulation Model: Construction Analysis for Pavement Rehabilitation Strategies, ASCE Journal of Construction Engineering and Management, Vol. 131, No. 4, 2005.)

Capabilities

The CA4PRS tool can be used in establishing schedules, developing staging construction plans, estimating cost (A) + schedule (B) contracts, and calculating incentive and disincentive specifications for contracts. CA4PRS uses an HCM-based demand-capacity algorithm for quantifying mobility impacts; this tool also can be integrated with macro and microscopic traffic simulation tools to estimate road user delay costs arising from construction.

121BInputs and Outputs

CA4PRS uses the following input variables in evaluating “what-if” scenarios:

• Work zone constraints - number of lanes before and during construction, number of partial or full lane closures, roadway capacity, traffic composition, hourly demand, unit costs for delay time and VOC, lane width, lateral clearance.
• Construction window - nighttime closures, weekend closure, continuous closure, or combinations of the above.
• Pavement strategy – portland cement concrete (PCC) reconstruction, asphalt overlay of crack and seat PCC, or full-depth asphalt concrete replacement.
• Material constraints - concrete mix design and curing time or asphalt cooling time for asphalt
• Pavement cross section - thickness of new concrete or asphalt concrete, concrete pavement base types.
• Contractor’s logistical resource constraints - location, capacity, and numbers of rehabilitation equipment available (paver, batch plant, delivery and hauling trucks).
• Scheduling interfaces - mobilization/demobilization time, traffic control time, and activity lead-lag time relationships (e.g., lag time from demolition to PCC pavement installation), and buffer sizes.

The outputs reported by CA4PRS include:

• Mobility impacts - maximum delay time and queue length before and during construction.
• Road user costs - daily, per closure and total road user costs.
• Project costs - pavement, non-pavement and indirect costs.
• Traffic handling and management costs - daily traffic handling, extra TMP and incident management costs.

Figure 8 presents a sample screenshot showing lane closure analysis of I-80 pavement rehabilitation project using CA4PRS. (Pyeon, J. H., and E. B. Lee, "CA4PRS Application for Determination of Incentive/Disincentive Dollar Amount," CA4PRS Peer Exchange Workshop, St. Louis, MO, 2010.)

Advantages and Disadvantages

The primary advantage of CA4PRS is its capability to perform comprehensive analysis for WZ RUC computations by integrating traffic mobility analysis with construction scheduling, constructability and logistics, and pavement rehabilitation alternatives. It supports decision making by identifying the resource bottleneck limiting the project acceleration and allows users to specify the type of operations, concurrent or sequential. Another advantage is its ability to verify contractor submitted schedules. This tool can be used in conjunction with macroscopic or microscopic simulation tools for wider coverage of work zone influence and more in-depth impact analysis.

The current version of CA4PRS (version 2.5) is limited to pavement rehabilitation activities. Future versions of this tool plan to extend its scope to roadway widening, bridge and interchange replacement and include life-cycle cost analysis. WZ RUC computation using this tool is limited to travel delay costs and VOC; it does not compute emission or crash costs.

Figure 8. Sample screenshot showing lane closure analysis using CA4PRS.

2.9.1.2 Work Zone Traffic Analysis Tools used by State DOTs

State DOTs typically use more than one tool for evaluating work zone impacts. These agencies typically use sketch-planning and HCM –based tools for projects where:

• The work zone mobility, safety, and economical impacts are expected to be low to moderate.
• The proposed work zone has limited impacts on the network.
• The agency resources are limited.
• The project completion time is not a major factor.
• Rough estimation of performance measures is sufficient.

State agencies also use sophisticated traffic analysis tools, such as microscopic and mesoscopic simulation tools, for projects where:

• The work zone mobility, safety, and economical impacts are expected be high.
• The work zone impacts are expected over a large geographic area.
• The project completion time is a critical factor.
• Accurate estimation of performance measures is a requirement.

Table 38. Traffic analysis tools used by State DOTs.

State	RUC-specific	Non-RUC Specific (traffic analysis only)
California	CA4PRS (CA4PRS has been used in several other States, such as Minnesota, Oklahoma, Utah, Virginia, and Washington State.)	HCM, SYNCHRO
Colorado	WorkZone RUC	N.A.
Delaware	N.A.	HCS, spreadsheet, Quick Zone, SYNCHRO
District of Columbia	QuickZone, QUEWZ-98,	SYNCHRO/SimTraffic, CORSIM
Florida	FDOT RUC	N.A.
Hawaii	N.A.	HCM
Illinois	DOT-specific spreadsheet, Quickzone	N.A.
Iowa	QuickZone	N.A.
Kansas	N.A.	HCM, Travel Demand Models, Simulations
Maryland	LOPB, LCAP	HCS, SYNCHRO, CORSIM
Massachusetts	N.A.	HCS, SYNCHRO, SIDRA, Transyt-7F, TSIS-CORSIM, GDOT Roundabout Analysis Tool, VISSIM
Michigan	CO3	HCM, SYNCHRO
Missouri	QuickZone	MoDOT Work Zone Impact Analysis Spreadsheet, VISSIM, CORSIM, SYNCHRO
New Hampshire	QuickZone	HCM, SYNCHRO
New Mexico	N.A.	HCM and Simulation
New Jersey	DOT-specific spreadsheet	N.A.
New York State	QuickZone, AASHTO User Benefit Analysis	CORSIM
North Carolina	QUEWZ-98	in-house detour and flagging programs
Ohio	DOT-specific spreadsheet
Oklahoma	N.A.	HCM-based spreadsheet
Oregon	N.A.	Work Zone Traffic Analysis Tool
Pennsylvania	DOT-specific spreadsheet
Rhode Island	N.A.	HCM, QuickZone
Texas	RUC Tables	PASSER V
Utah	N.A.	HCM, SYNCHRO, VISSIM
Virginia	HUB-CAP	N.A.
Washington	QUEWZ-98	SYNCHRO
Wisconsin	N.A.	HCM w/spreadsheet, Quadro, SYNCHRO
Tennessee	N.A.	HCM, Web-based Queue/Delay Prediction Model
Wyoming	N.A.	HCM, SYNCHRO

2.9.2 Economic Analysis Tools

Economic analysis tools help decision makers to identify and quantify the value of economic costs and benefits of highway projects/programs over a multi-year period. These tools allow highway agencies to utilize the available resources to their best for maximizing benefits to the public. (Economic Analysis Primer, Office of Asset Management, Federal Highway Administration, U.S. Department of Transportation, August 2003.) Notable examples of economic analysis tools are discussed below.

RealCost

RealCost is a tool for conducting life cycle cost analysis in pavement design. Developed by the FHWA, this tool can be used for selecting a cost-effective pavement alternative among competing alternatives that offer essentially identical benefits. RealCost has a built-in tool for capacity flow analysis and for calculating road user costs associated with establishing a work zone. The capacity flow analysis is based on the traffic flow concepts presented in the 1994 edition of the HCM.

RealCost version 2.5 allows users to compute travel delay costs and VOC. Though illustrated in the interim technical bulletin, the computation of crash costs is not yet implemented in the software. RealCost has adopted the approach presented in NCHRPReport 133 for computing travel delay costs and VOC. Figure 9a presents a RealCost screenshot illustrating the hourly traffic demand and capacity analysis, lane closure timings, and resulting queue conditions for a typical work zone project. Figure 9b presents an example of various WZ RUC components computed for that project.

HERS-ST

HERS-ST is a benefit-cost analysis tool for selecting an economically efficient highway investment alternative among competing alternatives based on their potential impacts on highway condition, performance, and users. The benefits include reductions in user costs, agency maintenance costs, and externalities over the life of the improvement, while the costs include initial capital costs of the improvement. HERS-ST is designed to select only those projects where benefits will exceed initial costs. Developed by FHWA, HERS-ST has a suite of comprehensive submodels for computing various cost components of WZ RUC, including crash and emission costs.

MicroBENCOST

MicroBENCOST, developed under NCHRP Project 7-12, is an economic analysis tool for calculating road user benefit and costs of highway investments on a wide range of projects from individual intersection improvements to major road upgradings and construction of new roads. MicroBENCOST allows computation of travel delay costs, VOC, safety costs, and emission costs (considers the estimation of carbon monoxide only) for various work zone lane closure scenarios. Figure 10 presents a screenshot of work zone impact analysis functionalities of MicroBENCOST for use in WZ RUC computation.

BCA.Net

BCA.Net is the FHWA’s web-based benefit-cost analysis tool to support the highway project decision making process. The tool evaluates the economic merits of investment alternatives by comparing their relative costs and benefits. BCA.Net takes the capital costs, physical and performance characteristics, and forecast travel demand for the evaluation of a highway project.

The user specifies strategies for improvements and maintenance for a base case and an alternate case. The tool performs traffic impact analysis and calculates the agency and user costs and benefits for each case. The expected benefits and costs are compared on a time scale (i.e., discounted using the time value of money concept) to calculate the net benefits. The results of the simulation include various measures of economic worth such as the net present value, benefit-cost ratio, and internal rate of return for both base and alternate cases. For user costs, the BCA.Net tool is capable of calculating the following components: delay costs, VOC, crash and emission costs. Figure 11 presents a screenshot of RUC analysis functionalities of BCA.Net.

Figure 9.a Screenshot showing the WZ RUC analysis in RealCost version 2.5 – An example of work zone traffic analysis illustrating lane closure timings and queuing conditions.

Figure 9.b Screenshot showing the WZ RUC analysis in RealCost version 2.5 – An example showing computed RUC components for a typical work zone project.

Figure 10. Screenshot showing the work zone analysis functionalities of MicroBENCOST.

Figure 11. Screenshot showing the RUC analysis functionalities of BCA.Net.

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