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21st Century Operations Using 21st Century Technologies

Use of Narrow Lanes and Narrow Shoulders on Freeways: A Primer on Experiences, Current Practice, and Implementation Considerations

Chapter 4. Analyzing the Effects of Narrow Lane and Shoulder Width

As previously discussed, Performance-Based Practical Design (PBPD) and Performance-Based Planning and Programming (PBPP), plus the "objectives-driven, performance-based approach" to planning for operations, are all very compatible and consistent with one another. They also contain the term "performance-based;" and one of the key activities in all three approaches is to analyze and evaluate the resulting performance of various alternatives and strategies and how well they will meet the purpose and need of the project. From the perspective of narrowing lanes and/or shoulder widths to provide additional capacity within the existing footprint of an urban freeway, the operational and safety effects are perhaps the most critical aspect of this evaluation. This chapter provides an overview of some of the tools and analysis methods that can be used to estimate these effects.

Operational Effects

By definition, adding a travel lane — whether permanently or part time (as is often the case with shoulder use) — will increase overall roadway capacity, thereby reducing recurring congestion and improving operations. However, with narrower lanes, vehicles are traveling in closer proximity to each other, increasing the likelihood of lower speeds. Evaluations of narrow lane operations from the literature — as summarized in Table A-1 in the Appendix and as described in the case studies from the previous chapter — bear this out. The Level of Service (LOS) is generally improved, but with a slight reduction in average speed.

Analyzing Operational Impacts

Adding a lane by narrowing the existing lanes and shoulders generally improves operations and level of service, but with a decrease in average speeds.

The PBPD approach includes the evaluation of alternative solutions and making tradeoffs and decisions based on an objective analysis of performance data. The most recent version of the Highway Capacity Manual (HCM – Reference 18) includes information that can be used to estimate the operational impacts of additional, but narrow, lanes. For example, Table 7 shows the relationship between freeway lane widths, lateral clearances, and the resulting capacity and Free Flow Speed (FFS). As shown in this Table, a reduction in lane widths to less than 12′ will result in a reduction in free-flow speed. This reduction in free-flow speed does reduce throughput of an individual lane; but the additional lane more than offsets this loss in "per lane" throughput and capacity.

Adjustments should also be made to estimated FFS and lane capacity for lateral clearances if the width of the right side shoulder is reduced to accommodate an additional general purpose lane, or if the shoulder itself is used as a travel lane during parts of the day. Lateral clearance is measured from the right edge of the travel lane to the edge of the paved shoulder. As shown in Table 8, if the right-side lateral clearance is greater than or equal to 6 ft., no reduction in freeflow speed is made. The amount of free-flow speed reduction increases as the right-side lateral clearance decreases. The HCM assumes that left-side lateral clearance is greater than or equal to 2 ft. for all cases.

Table 7. Highway Capacity Manual Adjustment to Free-Flow Speed for Lane Width. (2010 Highway Capacity manual; Exhibit 11-8) (Free-Flow Speed values are based on freeway speeds ranging from 55 mph to 75 mph)
Average Lane Width (ft.) Reduction in FFS, fLW (mi/h)
≥12 0.0
≥11–12 1.9
≥10–11 6.6

Table 8. Highway Capacity Manual Reductions in Free-Flow Speed for Right-Side Lateral Clearance on Freeways. (2010 Highway Capacity Manual Exhibit 11-9)
Right-Side Lateral Clearance (ft) Lanes in One Direction
2 3 4 ≥5
≥6 0.0 0.0 0.0 0.0
5 0.6 0.4 0.2 0.1
4 1.2 0.8 0.4 0.2
3 1.8 1.2 0.6 0.3
2 2.4 1.6 0.8 0.4
1 3.0 2.0 1.0 0.5
0 3.6 2.4 1.2 0.6

Adding a lane within an existing roadway footprint will typically involve both the narrowing of the travel lanes and a reduction in shoulder width (and the associated right side lateral clearance). For example, consider a scenario where a directional roadway is converted from three 12 ft. lanes and a 10 ft. right shoulder to four 10.5 ft. lanes with a 4′ shoulder as shown in Figure 13.

Figure 13 is a diagram of an example conversion from three lanes to four lanes. The before cross section starting left to right is a 10′ left shoulder, three 12′ travel lanes and a 10′ right shoulder. The after cross section from left to right is a 10′ left shoulder, four 10.5′ travel lanes and a 4′ shoulder.
Figure 13. Diagram. Example Conversion from three Lanes to four Lanes.

Per the information in Tables 7 and 8, this example narrow lane conversion will reduce the free flow speed by an estimated 7.0 mph (6.6 mph from Table 7 plus 0.4 mph from Table 8). Using the maximum service flow rates from HCM Exhibit 11-17 (recreated in Table 9 below), and assuming a 10 mph reduction in FFS from 65 to 55 MPH (somewhat larger than the 7.4 mph value from Tables 7 and 8) and a target LOS D, the per-lane capacity will be reduced 6.4 percent from 2030 pc/hr to 1900 pc/hr (as highlighted in blue). However, converting this directional roadway from three lanes to four narrower lanes increases the total estimated directional throughput from 6090 pc/hr (2,030 X three lanes) to 7600 pc/hr (1,900 X four lanes) — nearly a 25 percent increase.

Table 9. Highway Capacity Manual Exhibit 11-17 (Maximum Service Flow Rates for Basic Freeway Segments).
FFS (mph) Target Level of Service
75 820 1310 1750 2110 2400
70 770 1250 1690 2080 2400
65 710 1170 1630 2030 2350
60 660 1808 1560 2010 2300
55 600 990 1430 1900 2250
Note: All values rounded to nearest 10 pc/hr/ln

It is critical to remember that when using tools such as the HCM, the baseline values and the adjustment factors — such as those shown in Tables 8 and 9 — are statistical estimates or expected values. Moreover, it is important to remember that while the HCM can give close approximations to changes in FFS, the speedflow curves have not been calibrated with real data for different (i.e., narrower) lane widths, and their true impact on driver behavior and the resulting capacity cannot be known for sure. As such, the HCM and other analytical tools should not be viewed as 100 percent accurate prognosticators of future conditions. The actual impact of narrow lanes may be expected to vary around the estimated values, dependent on a variety of factors. Decisions supported by the results of these analytical tools involve some degree of uncertainty, and engineering judgment is required as part of the overall PBPD process.

Impact of Trucks on Narrow Lanes Operations

One such area of uncertainty involves the operational impacts of trucks on narrow lanes operations. As discussed in NCFRP Report 31 – Incorporating Truck Analysis into the Highway Capacity Manual (Reference 22), most HCM chapters — including freeway — convert heavy vehicles5 to equivalent Passenger Car Equivalent (PCE) units6 (passenger cars per hour per lane) and add them to the passenger car volumes to obtain the total equivalent passenger car volume that is used in the HCM methodologies.

The HCM analysis then estimates the capacity, density, speed, delay, and LOS for the equivalent passenger car stream. Truck speeds and delays are not isolated from the values predicted using the equivalent passenger car stream performance.

The NCFRP Report evaluates the 2010 HCM from two perspectives: its ability to predict the specific performance of trucks, and its ability to model the effects of trucks on the traffic stream. Regarding the ability of the HCM to model the effects of trucks on the traffic stream NCFRP report states the following:

  • The HCM truck classification scheme is extremely simplistic, not reflecting the spectrum of truck performance capabilities in the U.S. fleet.
  • The HCM PCEs are too simplistic since they do not reflect the variation in the truck fleet or the influence of truck proportion or grades on urban street PCEs.
  • The HCM PCE look-up tables stop at 25 percent trucks (as a percentage of total traffic flow) even though there are many facilities in the United States where trucks routinely exceed 25 percent and can exceed 50 percent of the average daily traffic flow.
  • The HCM approach is independent of significant variables like the truck type and weight-to-horsepower ratio.

Thus, while narrow lanes are addressed in the HCM, their impact on truck operations is not addressed other than incorporating an increase in PCE's, which in turn may result in a further decrease in LOS and speeds that may not be reflected in the narrow lanes analyses.


The consideration of safety is arguably the primary issue involved in a PBPD-based analysis and subsequent decision to include narrow lanes and/or shoulders in a roadway design (and to subsequently approve a design exception). Evaluations of the safety of narrow lanes from the literature — as summarized in Table A-2 in the Appendix and as described in the case studies from the previous chapter — show mixed results; although there appears to be a general tendency for the frequency (or number) of crashes to increase with a narrowing of lanes and shoulders (although not always); while the crash rate (e.g., number of crashes per million vehicle-miles) often decreases (again, with exceptions). It may be that even with an increase in the number of crashes, the additional throughput provided by the extra lane results in an even greater increase in the denominator of vehicle-miles of travel, resulting in a decreased crash rate7 . There are undoubtedly several other factors that can impact crash frequency and rates associated with narrow lanes — such as volumes, speeds, the resulting decrease in congestion and improved traffic flow, the length of the narrow lane segment, horizontal and vertical curves, percentage of heavy vehicles in the traffic stream — which may explain the variations in results between different studies of the safety impacts of narrow lanes. Additionally, comparing studies and findings in terms of their statistical significance is difficult due to the different approaches used for statistical analysis.

As was the case with the operational analyses, the designer should address the entire network and system as part of the PBPD process, making sure that implementing narrow lanes to improve throughput in one segment doesn't increase congestion in a downstream segment potentially resulting in an increased number of crashes in that segment.

Analyzing Safety Impacts

When reviewing and comparing safety studies of narrow lanes, it is important to note which specific measures were used in the study:
  • Crash frequency (i.e., the number of crashes during a specific period of time).
  • Crash rate (i.e., number of crashes per some amount of vehicle-miles of travel.)

In performing a safety analysis of alternative lane and shoulder configurations and widths (as part of the PBPD process), it is important to understand the relationship of safety to design criteria and standards, along with the concepts of nominal and substantive safety as shown in Figure 14 and discussed below.

Nominal Safety

The concept of nominal safety is a consideration of whether a roadway, design alternative, or design element meets minimum design criteria. According to this concept, a highway or proposed design is considered to have nominal safety if its design features (such as lane width, shoulder width, lateral clearance, etc.) meet the minimum values or ranges. The measure of nominal safety is simply a comparison of design element dimensions to the adopted design criteria; an "either – or" scenario where a design feature either meets minimum criteria or it does not. Thus, narrowing one or more lanes of an urban freeway to less than the standard 12 ft. width (per the Green Book) would not meet the concept of nominal safety.

Nominal and Substantive Safety.
Figure 14. Graph. Nominal and Substantive Safety.

Substantive Safety

Substantive safety is defined as the expected, or estimated long-term average, safety performance of a roadway. The concept of substantive safety encompasses methods for estimating the following expected quantitative measures:

  • Crash frequency (number of crashes per mile or location over a specified time period).
  • Crash type (run-off-road, intersection, pedestrian, etc.).
  • Crash severity (fatality, injury, property damage).

Understanding a location's substantive safety and making judgments about whether it meets expectations may involve formal comparisons of its crash profile with aggregate data for facilities with similar characteristics (e.g., traffic volumes, number of current and proposed lanes and widths, location (urban, rural, suburban), inclusion of TSMO strategies, and terrain); predictive methods such as those presented in the AASHTO Highway Safety Manual (HSM); or some combination.

In evaluating project alternatives from a substantive safety perspective, the practitioner is interested in the future safety performance of a facility and comparing that future performance for alternative geometrics, lane and shoulder widths, operational strategies, etc. Crash history is used to identify and diagnose safety concerns on an existing facility; but it may not be the most accurate approach for estimating long-term average safety performance. The HSM argues for the value of using predictive methods in addition to crash history, to improve accuracy and precision of estimates.

Highway Safety Manual

The HSM (Reference 20) complements design guidelines, such as the AASHTO Green Book, by allowing a more scientifically rigorous methodology to quantify the "safety effects" of various design choices as part of the PBPD process. The 2014 Supplement to the HSM, 1st Edition, provides a structured methodology and specialized procedures to estimate the expected average crash frequency for various freeway facilities.

The HSM freeway chapters provide Safety Performance Functions (SPF) for 4- to 10-lane freeway facilities that account for several variables that need to be considered when looking at cross-section alternatives, including the following:

  • Average Annual Daily Traffic (AADT),
  • Proportion of AADT during high-volume hours,
  • Number of through lanes,
  • Distance to median barrier
  • Lane width, and
  • Shoulder width (left and right).

The HSM also provides Crash Modification Factors (CMS's) for various roadway treatments. These are used to estimate the expected number of crashes after implementing a given treatment. A CMF less than 1.0 — the value that corresponds to a 12-ft. lane width for freeways, a 6-ft. width for inside shoulders, and a 10-ft. width of outside shoulders — indicates that a treatment has the potential to reduce the number of crashes. Figures 15–17 show the CMF's for lane widths, inside shoulder widths, and outside shoulder widths, respectively. Looking at the CMF alone, narrowing a freeway lane to under 12 ft. and/or narrowing the outside shoulder to less than 10 ft. will result in an increase in the number of crashes (i.e., the associated CMF values are greater than 1.0.)

Figure 15 is a graph of crash modification factors for lane widths. The Y axis is a crash modification factor and the x axis is lane width in feet. The fatal injury vehicle crashes is a linear line starting from coordinates (10.5, 1.06) sloping downward to coordinates (13, 0.98) and then flattening parallel to the x axis.
Figure 15. Graph. Crash Modification Factors for Lane Widths.

Figure 16 is a graph of crash modification factors for inside shoulder widths. The y axis of the graph is crash modification factor and the x axis is shoulder width in feet. The fatal injury single vehicle crashes is a linear line starting from coordinates (2,1.05) sloping downward to (10,0.9)
Figure 16. Graph. Crash Modification Factors for Inside Shoulder Widths.

Figure 17 is a graph of crash modification factors for crash modification factors for outside shoulder widths. The y axis represents crash modification factor and the x axis represents shoulder width in feet. The fatal injury single vehicle crashes are a slightly upward facing curve starting from coordinates (4,1.55) down to (14,0.75)
Figure 17. Graph. Crash Modification Factors for Outside Shoulder Widths.

HSM Evaluation of Narrower Lanes and Narrower Shoulders

The HSM freeway crash prediction model can be used to assess the change in crash frequency and severity associated with increasing the number of freeway lanes by reducing lane and shoulder widths. The before and after alternatives listed in Table 10 were analyzed for before conditions of a 4-lane freeway, 6-lane freeway, and 8-lane freeway (bi-directional in each case) with an increase in the number of lanes (one per direction) by narrowing the current lane widths from 12 ft. to 11 ft. and narrowing the shoulders so as to add the lane within the existing roadway footprint (i.e., no widening). Figures 18, 19, and 20 illustrate the predicted frequency of Fatal and Injury (FI) Crashes and Property Damage Only Crashes (PDO) for each freeway alternative shown in the Table.

Table 10. Inputs for Narrow Lane / Shoulder Alternative.
Variable Narrow Lane / Shoulder Alternatives
4-Lane Freeway 6-Lane Freeway 8-Lane Freeway
Before After Before After Before After
Number of Lanes (bi-directional) 4 6 6 8 8 10
Lane Width 12 11 12 11 12 11
Right Shoulder Width 10 4* 10 4* 10 4*
Left Shoulder Width 6 3* 6 4* 6 5*
*These are the narrowest shoulder widths for which the HSM has modification factors

igure 18 is a graph of predicted crash frequency with and without narrow lanes and narrow shoulders in conversion of a 4-lane freeway to a 6-lane freeway.
Figure 18. Graph. Predicted Crash Frequency With and Without Narrow Lanes and Narrow Shoulders (Conversion from 4-lane Freeway to 6-lane Freeway).

Figure 19 is a graph of predicted crash frequency with and without narrow lanes and narrow shoulders in conversion of a 6-lane freeway to a 8-lane freeway.
Figure 19. Graph. Predicted Crash Frequency With and Without Narrow Lanes and Narrow Shoulders (Conversion from 6-lane Freeway to 8-lane Freeway).

Figure 20 is a graph of predicted crash frequency with and without narrow lanes and narrow shoulders in conversion of a 8-lane freeway to a 10-lane freeway.
Figure 20. Graph. Predicted Crash Frequency With and Without Narrow Lanes and Narrow Shoulders (Conversion from 8-lane Freeway to 10-lane Freeway).

The HSM freeway crash prediction models estimate that narrowing lanes and shoulder widths to create an additional lane in each direction might have the following influence on crash frequency and severity:

  • Reduce the frequency of PDO crashes
  • Increase the frequency of FI crashes when converting existing 4- or 6-lane freeways (i.e., two lanes and three lanes in each direction)
  • Have little to no effect on the frequency of FI crashes when converting existing 8-lane freeways (i.e., four lanes in each direction)

While Figures 15 and 17 indicate an increase in the number of crashes with a narrowing of travel lanes to less than 12 ft. or a narrowing of the outside shoulder to less than 10 ft., and Figures 18–20 show a slight decrease in PDO crashes (but an increase in injury crashes); there are other considerations in any safety analysis of narrow lanes — specifically, that the increase in the number of lanes (and available capacity) may also reduce congestion, which in turn may improve overall safety.

Figure 21 summarizes the scenarios shown in previous Table 12 and shows the safety effects of adding a lane by narrowing the general purpose lanes to 11 feet and reducing shoulder widths. The point at which each line crosses the 0 percent mark on the y-axis indicates the AADT above which the implementation of narrow lanes and shoulders — with an increase in the number of lanes — would be expected to decrease crash frequency8 . In general, the greater the average daily traffic — and presumably the greater level of congestion during the "before" condition — the more likely that the safety benefits from reduced congestion (resulting from an additional lane) will outweigh the potential safety issues associated with narrower lanes and shoulders.

Figure 21 is a graph of predicted percent change in crash frequency when adding a lane by using the right shoulder and narrowing lanes
Figure 21. Graph. Predicted Percent Change in Crash Frequency when Adding a Lane by Using the Right Shoulder and Narrowing Lanes.

For the example identified in previous Figure 13, adding a fourth lane to a the 3-lane directional roadway (as shown in the line with "diamonds" in Figure 21 – "6 to 8 Lane Freeway Conversion"), would be predicted to result in a net reduction in the crash frequency if the two-way average annual daily traffic was greater than approximately 95,000 vehicles per day.

Other considerations in performing a safety analysis of narrow lanes include:

  • As addressed in an August 2011 article in the Journal of Economic Literature (Reference 23), even if narrower lanes and shoulders increase accident rates by 10 percent, applying standard parameters for costs of accidents, these extra costs may not reverse the advantage of a "narrow" design (in terms of travel time savings and the additional costs associated with widening to maintain 12-foot lanes).
  • The predictive methods in the HSM do not include the effect of traffic volume variations throughout the day (other than a factor for the proportion of AADT during peak periods) or the percentages of different vehicle types. Per the HSM, these variables were not necessarily excluded because they have no effect in crash frequency; it may merely mean that the effect is not fully known or has not been quantified at this time.

Impact of Trucks on Narrow Lanes Safety

Trucks are wider than cars. Federal size regulations for commercial motor vehicles stipulate a maximum width of 2.6 meters (102.36 inches, or 8.53 feet), excluding mirrors and other safety devices. Thus, with a 12 foot lane, a truck driving in the center will have approximately 21 inches on either side between the truck and the adjacent lanes (not counting mirrors). If the lanes are narrowed to 11 feet, this clear distance to the adjacent lanes is reduced to 15 inches (and even less between mirrors of trucks in adjacent lanes). Thus, narrower lanes may make it more difficult for the drivers of heavy vehicles (including buses) to position their vehicle completely within their lane. A truck encroaching into an adjacent lane can cause a sideswipe crash. Moreover this is probably a greater concern on tight horizontal curves.

The literature on the subject of narrow lanes, trucks, and safety is somewhat sparse (e.g., as noted above, the HSM does not address the proportion of trucks.) Some highlights from the available literature are noted below:

  • The 1995 NCHRP Report 369 ("Use of Shoulders and Narrow Lanes to Increase Freeway Capacity" – Reference 3) studied several altered and unaltered9 corridor segments, concluding that “truck accident rates are almost always higher on altered sections compared with unaltered”. At the same time, looking at the results available in the report, there does not seem to be any correlation between the change in truck accident rate and the percentage of trucks (up to 10 percent trucks, the greatest percentage of truck traffic for the study sites with crash data for trucks).
  • As reported Ng and Small (Reference 23), on the New Jersey Turnpike, which has two parallel roadways (both with standard lane widths) of which one is for cars only, accident rates are higher in the lanes that allow trucks.
  • A Florida study of the influence of arterial lane width on bus safety (Reference 24) suggests a strong relationship between lane width and bus vehicle safety, noting that the narrower the lane width, the higher the likelihood of having bus sideswipe and mirror crashes. The results indicate that narrow lane widths, especially lane widths of 10 feet and narrower, are overrepresented in the occurrences of bus sideswipe crashes.

Based on this admittedly limited documentation, coupled with the notion discussed above that narrow lanes reduce the margin of error for a heavy vehicle operator in terms of keeping the truck in the lane, an analysis of roadway design alternatives involving narrow lanes should consider the safety impacts of trucks, particularly when the percent of trucks in the traffic flow is greater than five to ten percent.

Considerations in this regard include the length of the segment and the horizontal and vertical alignments throughout the segments. Potential mitigation measures include the use of dynamic speed limits wherein the speed limits are lowered depending on the percentage of truck traffic in the flow, the horizontal and vertical curvature, and weather and visibility conditions. Consideration should also be given to keeping one or two of the lanes — including possibly a shoulder lane, assuming that the shoulder was constructed at full depth and can accommodate trucks — at 12-feet or greater, and restricting trucks to those lanes.

Transportation Systems Management and Operations and Safety

Implementing TSMO strategies (refer to previous Table 5) may provide additional safety benefits beyond the changes in crash frequency predicted by the HSM tools, and should be considered as part of the PBPD activities and the associated trade-off analyses. Table 11 shows the safety benefits resulting from several TSMO applications.

Table 11. Examples: Safety Benefits of Transportation System Management and Operations Strategies.
TSMO Strategy Location Safety Benefits
Traffic Incident Management (TIM) (Reference 21) General
  • Incident duration reduced 30–50 percent (For example, average total incident duration in New Jersey has declined 48 percent, from 2.75 hours (1995) to 1.44 hours (2008)
  • Effective TIM reduces the occurrence of secondary crashes. The likelihood of a secondary crash increases by 2.8 percent for each minute the primary incident continues to be a hazard.
  • Faster detection of and response to highway incidents saves lives.
Ramp Metering (Reference 7) Portland, Oregon
  • 43 percent reduction in peak period crashes
Seattle, Washington
  • 39 percent reduction in crash rate
Minneapolis, Minnesota
  • 24 percent reduction in peak period crashes
Dynamic Speed Limits and Dynamic Lane Assignment (Reference 7) Seattle, Washington (Seven mile segment of I-5)
This corridor was already actively managed via ramp metering and a robust incident management program.
  • A before-and-after study showed total crashes decreased 4.1 percent along the ATM segment. (During the same period, the southbound segment of I-5 — without ATM — experienced a 4.4 percent increase in the number of crashes.)
London, England (M-25 Orbital)
  • Injury crashes decreased by 10 percent.
  • Damage-only crashes decreased by 30 percent.
Dynamic Shoulder Lanes with Dynamic Speed Limits and Dynamic Lane Assignment (Reference 7) Minneapolis, Minnesota I-35W (with speed advisories (not legal limits) and shoulder used as part time HOT) Crash reductions in the 6-month postdeployment period were as follows:
  • 9 percent for fatal plus injury crashes
  • Greater than 20 percent for property damage only, and for total crashes (when the change in vehicle miles traveled was accounted for)
General – Results of 2006 FHWA Scanning Tour of Europe
  • A decrease in primary incidents of 3 to 30 percent.
  • A decrease in secondary incidents of 40 to 50 percent.


Travel Time Index
The ratio of the travel time during the peak period to the time required to make the same trip at free-flow speeds

The concept of travel time reliability has been receiving significant attention of late, particularly as part of the Strategic Highway Research Program (SHRP 2). The overall goal of the SHRP 2 Reliability program is to reduce congestion through incident reduction, management, response, and mitigation, thereby significantly improving travel time reliability for many types of person and freight trips on the nation's highways. Per SHRP documentation: "travel time reliability refers to how travel time varies over time and the impacts of this variance on highway users. In other words, for repeated travel or vehicles making similar trips, there is an underlying distribution of travel time for a particular type of trip within a specific time period between two points. Individual travelers respond differently to the factors and uncertainties associated with the travel time.

Considering the example in previous Figure 13 (three lanes to four narrower lanes), and assuming that this conversion covers a five-mile segment with a peak hour volume of 5500 pce (compared to the aforementioned before capacity of 6090 pce/hr at LOS D), and an average travel speed of 40 mph during the peak hour; using equations identified in Reference 2210 , the Travel Time Index (TTI) for this before condition is estimated as 1.4 (indicating that the average peak hour travel time is 6.4 minutes, nearly two minutes greater than the free flow travel time of 4.6 minutes).

Following the conversion to four lanes, it is assumed that the peak hour volume increases to 6200 pce (i.e., the result of some induced demand brought about by the additional capacity — now at 7600 pce/ hr. — provided by the fourth lane), with the directional roadway now operating at a reduced FFS of 55 MPH (due to the narrower lanes) during the peak period, resulting in a travel time of 5.45 minutes over the 5-mile segment. The new average annual mean travel time for the after condition is calculated as 5.8 minutes (with a TTIm of 1.067), an improvement over the before condition.

These equations and the associated reliability measures do not take into consideration the possibility of an increase in crashes, thereby causing nonrecurring congestion and increased travel times (and less reliability. Moreover, a large reduction in shoulder width— such as occurs in the example (i.e., where the shoulder is reduced from 8 ft. to 2. ft.) — may negatively impact reliability. For example, there may no longer be a safe refuge for emergency stops and broken-down vehicles outside the traveled way, nor space for drivers of errant vehicles to make steering corrections before leaving the roadway. Moreover, without a wide shoulder, response times for emergency service vehicles — which often use the shoulder to bypass slow traffic when responding to a crash scene — may increase, thereby increasing incident-related congestion and reducing reliability. Accordingly, enhanced incident management strategies (e.g., frequent service patrols), dynamic lane assignment allowing the closure of a lane upstream of a crash site, and/or emergency refuge areas should be considered when analyzing the possibility of adding a lane via narrow lane and shoulder widths.

5A heavy vehicle is defined in the HCM as "A vehicle with more than four wheels touching the pavement during normal operation." Three heavy vehicle types are defined: transit buses, recreational vehicles (RVs), and trucks. These three types are grouped in the HCM under the broader category of heavy vehicles.

6These adjustment factors vary with the percent of grade, length of grade, and the proportion of heavy vehicles in the traffic stream — from the lowest value are 1.5 PCE per heavy vehicle for grades less than 2 percent for all listed percentages of trucks and buses (1 to 25 percent), to the highest value of 7.0 PCE per heavy vehicle for an upgrade greater than 6 percent stretching for over a mile in length and 2 percent trucks. As the number of trucks increases for this steep grade, the PCE value decreases to a value of 4.0 for 25 percent trucks (The equivalents decrease as the number of heavy vehicles increases, because these vehicles tend to form platoons and have operating characteristics that are more uniform as a group than those of passenger cars).

7The additional throughput may be the result of freeing up a bottleneck or other constraint to flow, induced demand, or some combination.

8In one respect, Figure 21 does not appear intuitive; that the AADT threshold between an increase to a decreases in crash frequency is greater for the conversion from six to eight lanes (three to four lanes in each direction) than for the eight to ten lane conversion. The HSM is all field-data based, and sometimes the data yields slightly unpredictable results. Another way of looking at this is it reflects the model prediction that an eight- to ten-lane conversion is expected to have a greater reduction in crashes than a six- to eight-lane conversion.

9Unaltered refers to standard 12-foot lane; altered refers to narrowed lanes and shoulders.

10 The average annual mean travel time index (TTIm) =
   1 + FFS * (RDR + IDR), where:
   FFS = free flow speed (mi. / hr.)
   RDR = recurring delay rate (hr. / min.)
   IDR = incident delay rate (hr. / min.)
   RDR is calculated using: RDR = 1/S - 1/FFS
IDR is calculated using: IDR = [0.020 - (N - 2) * 0.003] * X12
S = peak hour average speed
N = number of lanes (between 2 and 4)
X = peak hour volume to capacity ratio

Free flow travel time (in minutes) is calculated as [Length of Segment (mi.) / FFS] * 60 minutes / hr.

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