Comprehensive Truck Size and Weight Limits Study - Modal Shift Comparative Analysis Technical Report

Appendix E: Traffic Operations Impact Analysis Approach

This documentation is intended to describe the methodology and procedures of the traffic operations impact analysis. Much of the analysis was based on analyses conducted for the USDOT's Comprehensive Truck Size and Weight Study, 2000 (2000 CTSW Study). Principles and methods in the spreadsheet model developed for the 2000 CTSW Study were judged to still be applicable to the estimate of delay and congestion costs for this study. Some improvements and updates were made to the 2000 CTSW Study model and underlying data to make it more consistent with HCM 2010 and other more recent analytical tools.  

E.1 Methodology

The spreadsheet model used in traffic operations impact analysis was originally developed by Pennsylvania State University, and is now updated with 2011 network variables and new speed-flow rate curves from the 2010 Highway Capacity Manual. For the traffic operations impacts outside the spreadsheet model, context was provided in the document to evaluate their impacts in qualitative terms.

In principle, traffic congestion is a function of the difference between the capacity of a given highway and the amount of traffic on it. In this study, the impact of trucks on traffic operations is assessed in terms of passenger car equivalents (PCE). The value of PCEs depends on the operating speed and grade of the highway section, the vehicle's length, and its weight-to-horsepower ratio, which measures how a vehicle can accelerate. After PCE values are determined, they are applied to VMT (vehicle miles traveled) from previous mode split tasks to derive the "PCMT" (passenger car miles traveled) on various highway functional classes. The PCMT is used to calculate a flow rate (passenger cars per hour), which can then be compared to the speed-flow rate curve included in the HCM 2010 to determine the link speed. As a result of this study, the VHT (vehicle hours traveled) is calculated based on the values of VMT and speed, and economic cost is reported by applying the economic value of travel time.

Network

For this update, functional class and length of the 2011 highway network (FHWA Highway Statistics Series) were used. In addition, sample data from 2008 HPMS network was used to derive the geometric and congestion split.

Table E1. Network Length, Geometric and Congestion Splits

F_SYSTEM	FC	Lane-Mile	Pr(g<3)	Pr(g>=3)	Pr(v/sf<0.8)	Pr(v/sf>=0.8)
1	RI	139,526	0.872	0.128	0.045	0.955
2	ROPA	282,569	0.879	0.121	0.020	0.980
3	RMA	240,023	0.857	0.143	0.021	0.979
4	RMjC	843,318	0.829	0.171	0.005	0.995
5	RMnC	526,107	0.829	0.171	0.005	0.995
6	RLoc	4,075,567	0.829	0.171	0.005	0.995
7	UI	92,714	0.892	0.108	0.352	0.648
8	UOFE	53,852	0.895	0.105	0.315	0.685
9	UOPA	277,348	0.907	0.093	0.110	0.890
10	UMA	230,272	0.819	0.181	0.090	0.910
11	UCol	252,041	0.911	0.089	0.061	0.939
12	ULoc	1,554,283	0.911	0.089	0.061	0.939

Table E1 illustrates the network length, geometric types, and degree of congestion for different highway functional classes. The network was modeled with the geometrics and congestion splits as shown in Table E2. Note that the definitions of geometric types and traffic congestion are kept the same as in the 2000 CTSW Study; however, the splits have been updated based on the 2011 network data.

Table E2. Functional Classes and Segment Geometries

	Geometric Type		Geometric Type Split		% of Lane-Miles Congested
FC	Segment 1	Segment 2	Segment 1	Segment 2	Congested	Non-Congested
RI	ri0_12	ri3_34	0.85	0.15	0.05	0.95
ROPA	r20_12	r24_34	0.90	0.10	0.02	0.98
RMA	r20_12	r24_34	0.85	0.15	0.02	0.98
RMjC	r20_12	r24_34	0.85	0.15	0.00	1.00
RMnC	r20_12	r24_34	0.85	0.15	0.00	1.00
RLoc	r20_12	r24_34	0.85	0.15	0.00	1.00
UI	ri0_12	ri3_34	0.90	0.10	0.35	0.65
UOFE	ri0_12	ri3_34	0.90	0.10	0.32	0.68
UOPA	ua_11	ua_2l	0.90	0.10	0.10	0.90
UMA	ua_11	ua_2l	0.80	0.20	0.10	0.90
UCol	ua_11	ua_2l	0.90	0.10	0.05	0.95
ULoc	ua_11	ua_2l	0.90	0.10	0.05	0.95

Vehicle.

Trucks are larger and, more importantly, slower to accelerate to their desired speeds than passenger cars, and thus have a greater effect on traffic flow. In hilly or mountainous terrain and in congested traffic, their effect on traffic flow often is much greater, and they may be equivalent to 15 or more passenger cars. The value of PCEs depends on the operating speed and grade of the highway section, the vehicle's length, and its weight-to-horsepower ratio, which measures how a vehicle can accelerate.

In the 2000 CTSW Study, traffic operations impacts were assessed using three traffic simulation models-one for Interstate highways, one for rural two-lane highways, and one for urban arterials. As these models are sensitive to vehicle length, gross weight, and engine power, the analysis for this Study is sensitive to these factors. To obtain PCEs by truck length and gross weight-to- horsepower ratio, the models were run many times for two sets of representative roadway geometric conditions (relatively level versus mountainous) for each of the three highway types.

The effects of differences in truck length and weight-to-horsepower ratio are shown in the tables below.

Table E3. PCE for Different Truck Dimensions at Different Segment Geometries

ri0_12						ri3_34
LENGTH	WTHP	PCE	PCEnc	PCEnnc	PCEno	LENGTH	WTHP	PCE	PCEnc	PCEnnc	PCEno
40	150	2.22	2.0	2.5	2.0	40	150	9.01	1.5	2.0	9.0
40	200	2.54	2.5	3.0	2.5	40	200	11.29	2.0	2.5	11.5
40	250	3.13	3.0	3.0	3.0	40	250	13.19	2.0	3.0	13.0
40	300	3.72	3.0	3.5	3.5	40	300	15.09	2.0	3.5	15.0
80	150	2.59	2.5	2.5	2.5	80	150	9.55	2.5	2.0	9.5
80	200	3.34	3.0	3.5	3.5	80	200	11.77	2.5	2.5	12.0
80	250	3.36	3.0	3.5	3.5	80	250	14.05	3.0	3.0	14.0
80	300	3.38	3.0	4.0	3.5	80	300	16.33	3.0	3.5	16.5
120	150	3.01	2.5	3.0	3.0	120	150	10.46	2.5	2.0	10.5
120	200	3.60	3.0	3.5	3.5	120	200	12.40	2.5	2.5	12.5
120	250	4.03	3.0	4.0	4.0	120	250	14.73	3.0	3.0	14.5
120	300	4.46	3.0	4.0	4.5	120	300	17.06	3.0	3.5	17.0
r20_12						r24_34
LENGTH	WTHP	PCE	PCEnc	PCEnnc	PCEno	LENGTH	WTHP	PCE	PCEnc	PCEnnc	PCEno
40	150	1.53	1.5	1.5	1.5	40	150	4.98	5.0	5.0	5.0
40	200	1.66	1.5	1.5	1.5	40	200	8.22	8.0	8.0	8.0
40	250	2.43	2.5	2.5	2.5	40	250	13.78	14.0	14.0	14.0
40	300	3.20	3.0	3.0	3.0	40	300	19.34	19.5	19.5	19.5
80	150	1.70	1.5	1.5	1.5	80	150	5.36	5.5	5.5	5.5
80	200	1.83	2.0	2.0	2.0	80	200	8.90	9.0	9.0	9.0
80	250	2.67	2.5	2.5	2.5	80	250	15.07	15.0	15.0	15.0
80	300	3.51	3.5	3.5	3.5	80	300	21.24	21.0	21.0	21.0
120	150	1.87*	1.5*	1.5*	1.5*	120	150	5.74*	6.0*	6.0*	6.0*
120	200	2.0*	2.5*	2.5*	2.5*	120	200	9.58*	10.0*	10.0*	10.0*
120	250	2.91*	2.5*	2.5*	2.5*	120	250	16.36*	16.0*	16.0*	16.0*
120	300	3.82*	4.0*	4.0*	4.0*	120	300	23.14*	22.5*	22.5*	22.5*
ua_11						ua_21
LENGTH	WTHP	PCE	PCEnc	PCEnnc	PCEno	LENGTH	WTHP	PCE	PCEnc	PCEnnc	PCEno
40	150	1.25	1.5	1.5	1.5	40	150	1.87	2.0	3.0	2.0
40	200	1.57	1.5	1.5	1.5	40	200	2.00	2.0	3.5	2.0
40	250	1.84	2.0	2.0	2.0	40	250	2.37	3.0	3.5	2.5
40	300	2.11	2.0	2.0	2.0	40	300	2.74	3.0	3.0	2.5
80	150	1.78	2.0	2.0	2.0	80	150	2.20	2.0	3.0	2.0
80	200	1.75	2.0	2.0	2.0	80	200	2.22	2.0	3.5	2.0
80	250	2.25	2.5	2.5	2.5	80	250	2.69	3.0	4.0	2.5
80	300	2.75	3.0	3.0	3.0	80	300	3.16	3.0	4.0	3.0
120	150	2.43	2.5	2.5	2.5	120	150	2.38	2.5	3.5	2.5
120	200	2.62	2.5	2.5	2.5	120	200	2.56	3.0	3.5	2.5
120	250	3.01	3.0	3.0	3.0	120	250	3.15	4.0	4.0	3.0

In addition to general PCE values, three alternative PCE values are included to model effects under different traffic conditions:

• PCEnc denoting PCE values under new congested situations,
• PCEnnc denoting PCE values under new-non-congested conditions, and
• PCEno denoting all other conditions.

In addition to simulation results, at some situations where PCE values were not simulated (shown in red in the table), the PCEs were calculated using extrapolation for later computation conveniences. The tables are not intended to show extreme situations either in terms of roadway or vehicle characteristics; under some different settings the PCEs could be higher than shown in those tables.

It is important to note that using 2000 simulation results should not cause inconsistencies with the HCM 2010. The 2010 HCM provides average PCE values representing a fleet mix of trucks instead of unique PCEs for trucks with different weight-to-horsepower ratios.  The values presented in the HCM reference the same research as the 2000 CTSW study. While the state-of-the-art in simulation modeling has improved since the 2000 study was conducted, there is no research suggesting these improvements would significantly affect the relative PCEs for the scenario and base case vehicles being analyzed in the current study. 

Capacity.

Network capacity is evaluated using the most recent speed-flow rate curve data from the HCM 2010. The updated speed-flow rate tables for different roadway segments are shown below.

Table E4. Speed Flow Rates

ri0_12			ri3_34			r20_12
Lower Flow	Upper Flow	Speed	Lower Flow	Upper Flow	Speed	Lower Flow	Upper Flow	Speed
0	500	70.00	0	499	67.53	0	300	55.25
500	750	70.00	499	749	67.53	300	452	55.25
750	999	70.00	749	999	66.59	452	607	53.78
999	1250	70.00	999	1250	65.23	607	762	52.98
1250	1500	69.97	1250	1500	62.76	762	918	52.63
1500	1750	68.96	1500	1751	58.16	918	1062	51.81
1750	2000	66.49	1751	1907	50.05	1062	1199	50.80
2000	2247	62.58	1907	1907	31.73	1199	1199	51.31
2247	2313	57.28
2313	2313	55.63
r24_34			ua_1l			ua_2l
Lower Flow	Upper Flow	Speed	Lower Flow	Upper Flow	Speed	Lower Flow	Upper Flow	Speed
0	300	50.58	0	199	38.08	0	178	39.11
300	452	50.58	199	299	38.08	178	267	39.11
452	606	48.32	299	400	37.06	267	357	37.87
606	762	46.78	400	500	36.51	357	446	37.19
762	917	45.63	500	599	35.93	446	535	36.91
917	1060	44.30	599	700	35.55	535	625	36.36
1060	1197	42.61	700	800	34.65	625	713	35.10
1197	1197	41.71	800	901	34.43	713	803	34.74
			901	1001	36.52	803	891	36.37
			1001	1102	34.41	891	891	33.95
			1102	1199	32.78
			1199	1199	29.13

In general, the speeds tend to be higher than these included in the 2000 CTSW Study. This is consistent with the higher roadway capacity presented in HCM 2010 and other recent studies.

Limitations

The 2014 CTSW Study model employs a very general approach in computing roadway capacity and travel speed. As a result, variations in time and location were not factored into the model. In addition, the model focuses on the corridor and network levels, but does not take into consideration extra delay caused at hot spots such as at interchange ramps and at grade intersections. Instead, these issues were discussed qualitatively in other sections.

The 2014 CTSW Study has assessed, but not quantified in detail, the impact of longer and heavier trucks on traffic operations in the areas of vehicle off-tracking, passing, acceleration (including merging, speed maintenance, and hill climbing), lane changing (including weaving), sight distance requirements, clearance times, pedestrian areas, and work zones. As with congestion, the speed (a function of weight, engine power, and roadway grade) and length of a vehicle are the major factors of concern, although vehicle speed is more important than length in assessing congestion effects.

Among the subject areas, vehicle off-tracking, passing, acceleration, lane changing, sight distance, and clearance time requirements were discussed in the 2000 CTSW Study. Truck impacts in these areas remain the same over time. Therefore, the contexts in these areas were included in a very similar fashion in this study. In addition, the 2014 CTSW Study included two new areas, namely pedestrian areas and work zones. The significance of truck impacts on traffic operations and safety impacts was identified. However, as with some other factors, research on truck impacts in these two areas is limited, and any original data collection or new simulation modeling to produce quantitative impact estimates in these areas was beyond the scope of this study.

A user guide including a step-by-step procedure for the application of spreadsheet model follows.

2014 CTSW Traffic Operations Impact Analysis Model User Guide

The Traffic Operations Impact Analysis Model is developed as part of the 2014 CTSW Study. The model uses Excel Spreadsheet (Microsoft Excel 2010) to calculate travel time and delay on the national truck network, based on mode split for certain truck dimension changes (scenarios). The model approach was based on the approach adopted in the 2000 CTSW Study, but was updated with the 2011 truck network data and most recent capacity analysis guidance.

Step-by-Step Procedure

1. Compute VMT: The first step is to summarize the VMT by functional class and weight  for the entire Nation. For each scenario, a "VMT and Weight" distribution table by State is provided from preceding tasks. A functional class/weight ("fcw") index column needs to be inserted to the distribution table, and the SUMIF function needs to be used to summarize the tabular data matching the prescribed fc and weight criteria. Due to the large amount of calculations involved, it is recommended that users save the summary nationwide VMT table in a separate file and break the data links between files to avoid computation freeze.
2. Compute PCE and input network variables. The 2011 network geometry and congestion split have been saved in the "Network" worksheet, PCE values for different truck sizes on the roadway segments with different geometrics are computed in the "PCE" worksheet with the interpolation or extrapolation templates, and the base speed-flow rate tables for the roadway segments are saved in the "Capacity" worksheet. These values are considered essential basis for this model, and shouldn't be changed unless there is a new type of vehicle (new scenario) or new network information (new update).
3. Compute PCEMT. For each roadway function class, there is a worksheet computing PCEMT under each scenario. The names of tabs follow the convention of FCScenario. For example, RI01 denotes Rural Interstate Scenario 01. For any new scenario, users can simply copy an existing tab under the same function class and rename it with a new scenario. Move the national VMT table generated in step 1) to the workbook, name it MSScenario Number, for example, MS06 (denoting Mode Split Scenario 06). Select the range of cells D5 to AE24, replace the worksheet names contained in the equations to the worksheet names denoting the new scenario VMT. The PCEMT is automatically computed after the data is linked to the right worksheet. After computing PCEMT, other variables, including travel speed and VHT, are also automatically computed.
4. Summarize results. Each "Scenario XX" worksheet summarizes the model results for a specific scenario. The easiest way to analyze a new scenario is to copy an existing scenario summary tab and rename it for the new scenario. After the summary sheet is created, change the value of cell A1 to match the new scenario name. The spreadsheet model will take the last two letters of the new scenario name and look for VMT and VHT values across different function classes. For example, if the value of "Scenario 05" is coded in cell A1, the model will automatically look up VMT and VHT Values across worksheets RI05, ROPA05, RMA05, and so on. The annual cost is calculated with a travel time unit cost of $17.24, which represents the 2011 cost and is derived from a growth factor of the 2000 model value. The unit cost is saved in Cell I47 in the Scenarios worksheet if the user needs to update this value.

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