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Safety Implications of Managed Lane Cross Sectional Elements


Managed lanes (ML) can provide safety and operational performance benefits over general-purpose (GP) facilities, but the managed lane strategy must be appropriate for the intended user group. Specific benefits in crash reduction seen at one facility do not necessarily translate to another facility, so the selected strategy must account for the conditions unique to a particular facility. This section presents a summary of recent freeway and managed lane safety research.

Managed Lanes

Crashes within the Managed Lane Facility

Crashes on managed lanes are assumed to most likely be related to access and sight distance issues. For some situations, a failure to appreciate driver expectancy that differs for managed lanes as compared to general-purpose lanes may contribute to crashes, for example, when drivers need to exit the managed lane several miles prior to their destination. Adequate attention to placement of traffic control devices can help.

In addition to crashes near access points, crashes can also occur within a managed lane facility. Common types of crashes within a facility can include:

  • Rear-end crashes due to congestion.
  • Sideswipe crashes due to passing.
  • Crashes caused by drivers making unexpected maneuvers in violation of access restrictions, to avoid debris, or circumvent disabled vehicles that may block the travelway.

Crashes at Access Points

Freeway access points are common sites for crashes, just as crashes can commonly be found at intersections on surface streets. Crashes near access points can involve vehicles entering or leaving the managed lanes (e.g., sideswipe, striking separation device, etc.), and crashes can involve vehicles that are not changing facilities (e.g., rear-end crashes caused by drivers braking to avoid a vehicle entering the facility in front of them). Traffic volumes, the type of access and separation provided, and proximity of managed lanes access to general-purpose entrance and exit ramps may all have an effect on crashes, and these effects may vary from one facility to another.

A California study described comparisons of traffic safety during the morning and afternoon peak hours in extended stretches of eight high occupancy vehicle (HOV) lanes with two different types of access – four corridors with continuous access and the others with limited access. (1, 2) Traffic crash patterns for the two different types of HOV lanes were investigated by evaluating (a) the differences in crash distribution, severity, types of crashes, and per lane traffic utilization; (b) spatial distribution of crash concentrations by using Continuous Risk Profile approach; and (c) crash rates in the vicinity of access points in HOV lanes with limited access. In their study, the researchers conducted detailed analysis on crash data during peak hours in relation to geometry and traffic features. Based on the findings from the assessment on eight routes, the limited-access HOV lanes appeared to offer no safety advantages over the continuous-access HOV lanes. Although the overall safety seemed comparable, the observed differences between these types of facilities were attributed to more frequent and concentrated distribution of crashes at limited-access HOV lanes.

A recent study examined two facilities in Minnesota: (3)

  • I-394 freeway, the first dynamically priced high-occupancy toll (HOT) lane, was designed with limited access.
  • I-35W, the second HOT corridor, was designed with an open access philosophy where lane changes between the HOT and the general-purpose lanes are allowed everywhere except for a few specific locations.

The authors used shockwave length as a surrogate of safety based on the assumption that the more vehicles involved in a slow-and-go maneuver, the higher the possibility a driver will fail to react in a timely manner. They commented that the source of traffic demands has a notable impact on performance with respect to safety and access. I-394 is operating well with the limited access because the majority of the demand is originating from three specific interchanges. In contrast, I-35W has a higher interchange density so the open-access philosophy is working well on that facility. The authors developed a software tool capable of defining the Optimal Lane Changing Regions (OLCRs) that can be used with planned HOT facilities that adopt a closed access philosophy. The proposed methodology defines OLCRs with respect to the positions of entrance or exit ramps. The second methodology was designed to support decisions for access restrictions on existing HOT facilities. The core is a developed model capable of emulating shockwave propagation on the HOT lane given target densities and speed differential between the HOT and the adjacent general-purpose lane.

Safety of Buffer-Separated High Occupancy Vehicle Lanes

A 2013 paper reported on an evaluation of the relationship between cross-section design (i.e., lane width, shoulder width, and buffer width) to safety performance for HOV lanes. (4) The authors used three years (2005 to 2007) of crash data for 13 southern California segments totaling 153 miles. The segments had the HOV lanes buffer-separated from the general-purpose lanes. Crashes included those that occurred on the median shoulder, in the HOV lane, or in the adjacent general-purpose left lane. Independent variables included geometric attributes and annual average daily traffic (AADT). The authors made the following observations regarding geometric cross section and crashes:

  • HOV lane width: a wider HOV lane tends to be associated with lower crash frequencies except for the case with a width of 13 ft, which did not have enough segments to draw a conclusion.
  • AADT: higher AADTs in HOV and left lanes, except injury crashes in the left lane, are positively related to crash frequency, which means that freeway segments with more traffic tend to have higher crash frequencies. However, injury crashes in the left lane show an opposite, negatively correlated pattern, albeit by a very small number. This implies that more traffic leads to fewer crashes in the left lane but the variation is not substantial. The causal effect was not investigated in the study, but the authors offered a potential interpretation that crashes are likely to be more severe when traffic is light due to the likely higher speeds inherent in lower traffic density.
  • Shoulder width: the estimates indicated that wider shoulder width helps reduce crashes in HOV lanes.
  • Buffer width: coefficients for buffer widths were not found to be statistically significant at the 10 percent level in the model.
  • Left lane width: left lane widths were excluded in the estimated model due to their statistical insignificance (i.e., large standard errors); no inference could be drawn.

The authors stated that their findings could be used to determine the optimal cross-section and provided a case study discussion to illustrate the results. For one example, they recommended that a 12 ft lane and 10 ft left shoulder be converted to a 3.6 ft buffer, 12 ft lane, and 6.4 ft left shoulder. Two other examples were also provided in their paper, both of which suggested keeping the 12-ft lanes and shifting some of the left shoulder width into the buffer.

Cothron et al. and Cooner and Ranft reported on Texas research conducted to gain a better understanding of the safety issues and impacts associated with buffer-separated concurrent-flow HOV lanes. (5, 6) They reviewed hard-copy crash reports for multiple years from two urban freeways in Dallas, Texas. The objective was to determine trends and from those trends to make recommendations for absolute minimum and desirable buffer-separated concurrent flow HOV lane cross-section widths. In summary, researchers stipulate that the following factors all contribute to the increased injury crash rates experienced on the two Dallas corridors:

  • High daily traffic volumes and extensive congestion in the general-purpose lanes.
  • Ramp-pair combinations at or near the minimum ramp terminal spacing as recommended by the American Association of State Highway and Transportation Officials (AASHTO) in A Policy on Geometric Design of Highways and Streets (commonly known as the Green Book). (7)
  • Reduced HOV cross section.
  • Speed differential between the HOV and adjacent general-purpose lane traffic.

Figure 1 shows recommendations for desirable and absolute minimum cross sections for future buffer-separated HOV lanes in the Dallas area. The desirable cross-section guidance provides a typical section and a section with enforcement shoulders. Both desirable cross sections provide full inside shoulders and 4-ft buffers with a standard 12-ft lane for HOV traffic.

Figure 1. Graphic.
Source: adapted from Cooner, S., and S. Ranft. Safety Evaluation of Buffer-Separated High-Occupancy Vehicle Lanes in Texas. In Transportation Research Record: Journal of the Transportation Research Board, No. 1959, parts of the text, and Figure 8, p. 176. Copyright, National Academy of Sciences, Washington, D.C., 2006. Reproduced with permission of the Transportation Research Board. (6)

Note: abbreviations used in figure: GP = general purpose, HOV = high occupancy vehicle.

Figure 1. Graphic. Buffer-separated high occupancy vehicle lanes: (a) desirable cross section with enforcement shoulders, (b) desirable cross section, and (c) absolute minimum cross section that should be used only on short-distance interim projects or short sections, e.g., across narrow bridge.

Cooner and Ranft provided the following summary of previous studies:(6)

"Golob et al. compared the frequency and characteristics of crashes before and after an HOV lane was added to Riverside Freeway, CA-91, in the Los Angeles, California, area. (8) The HOV lane was created from the inside shoulder of the roadway. The study concluded that the HOV-lane project did not have an adverse effect on the safety of the corridor, and the changes in crash characteristics were attributed to the change in location and timing of traffic congestion.

Sullivan and Devadoss led a California Polytechnic State University study that reported the effects HOV lanes have on the safety of selected California freeways. (9) The study suggested that the observed crash pattern resulted from differences in traffic flow and congestion rather than geometric and operational characteristics of the HOV facilities. The crash hot spots during the peak periods of freeways with and without HOV lanes were a result of localized congestion.

A 1979 FHWA study indicated that the lack of physical separation between the HOV lane and the general-purpose lanes can create several operational and safety problems. (10) The speed differential and the merging into and out of the HOV lane were thought to contribute to increased crash potential. Slow vehicles merging into a high-speed HOV lane of faster vehicles or the HOV-lane vehicles having to decelerate rapidly to merge into the general-purpose lanes can result in either sideswipe or rear-end crashes.

The purpose of a 1995 study conducted by the Hampton Roads Planning District Commission in Virginia was to determine the safety effects of implementing a buffer-separated HOV lane. (11) Data from HOV lane facilities around the country were reviewed to determine the impact of varying buffer widths separating the HOV lane and the general-purpose lanes. The following HOV lane designs were reviewed: 3- to 8-ft buffer, 8-ft buffer raised 6 inches off the pavement, 13-ft buffer, and 0- to 2-ft buffer. The results indicated that the impact of the first three designs was inconclusive. However, the use of a buffer of 0 to 2 ft in width appeared to contribute to an increase in crash rates when compared to the pre-HOV crash rates for the freeways of interest. The speed differential between the HOV lane and the general-purpose lanes was identified as the possible cause of the crash rate increase.

In 2002, the Texas A&M Transportation Institute completed a multiyear research study. (12) In this study, injury crash rates were compared from before and after buffer-separated HOV lanes were implemented in two corridors. There was an increase in injury crash rates for the after condition; however, only one year of after data was available during this study. Several factors that may have contributed to an increase in crash rates were identified. These factors included the loss of the inside shoulder and a reduction in general-purpose lane width from 12 to 11 ft for implementation of the buffer-separated HOV lane.

Other recent research conducted by the Midwest Research Institute (MRI) studied crash data from California on freeways where the inside shoulder was converted to a travel lane and the other lanes were reduced in width. (13) All the freeways examined statistically used the converted inside lane as a concurrent-flow HOV lane. The analysis indicated that crash frequencies increased an average of 11 percent after the freeways were changed in this manner. However, the MRI research team did not attempt to explain the increase in the number of crashes. MRI’s primary data source was the Highway Safety Information System database." (Source page 168-169 in reference 6)

Differences in Crashes between Given Conditions

An Empirical-Bayes statistical estimation procedure was conducted to evaluate the effects of tolling on the I-394 MnPass Lanes in Minnesota, which opened for operation in 2005. (14) AADT data were used from 1998 to 2008. A four-year observation period was used before the start of tolling as well as a two-year post deployment observation period. Crash data of interstate highways in the Minneapolis-St. Paul (Twin Cities) seven-county metropolitan area from the Minnesota Department of Transportation (DOT) were used. The study found the overall number of crashes to be reduced by 5.3 percent, with an economic benefit of $5 million from 2006 to 2008. The authors of the paper stated that they were not confident that their results could be transferred to other HOT lane projects because of the limited research on this issue, and the newness of many HOT lanes that have recently opened.

A 2012 paper presented results of a safety analysis of a time-of-day managed-lane strategy that concurrently allows use of the inner left lanes by high-occupancy vehicles and use of right shoulders as general-purpose lanes during peak hours. (15) The crash data (3 years), corresponding annual average daily traffic volumes, and lane-type-specific AADT volumes were identified for various lane types, including the inner left lanes for HOV-only use during peak hours, general-purpose lanes, right shoulder lanes, and all lanes as a whole. Negative binomial regression models were used to estimate the effect of this traffic operations system and other factors relevant to crash frequency. The negative binomial regression model analyses presented no evidence that the interest factors, including the managed-lane strategy during peak hours, AADT volumes, merging and diverging influence areas, weather, light conditions, and existence of pull-off areas affected the crash frequency when aggregated across all lanes. The variable AADT volumes in the specific analysis of general-purpose lanes appear to be significant and show about a 2 percent increase in weekday crashes for each increase of 1,000 vehicles per day in the AADT range of 50,000 to 83,000 vehicles per day. Right shoulder-specific analysis shows that motorist behaviors at the merge and diverge areas during adverse light conditions are significant and shows an increase of about 38 percent in crashes in these areas. The managed-lane strategy does not appear to be significant to the crash frequency in the inner left lanes for HOV, general-purpose lanes, or right shoulders.


The Highway Safety Manual (HSM) now includes crash predictive methods for freeways. (16) The developed chapters were based on research conducted as part of National Cooperative Highway Research Program (NCHRP) 17-45. (17) The researchers found that reductions in lane widths and inside (left) shoulder widths are associated with increased crashes. The proposed crash modification factor for the HSM along with the findings from other recent work is shown in Figure 2 for lane width and Figure 3 for inside (left) shoulder width. The range of shoulder widths included in the NCHRP 17-45 study was 2 to 12 ft. An inside shoulder width of 6 ft was assumed as the base condition. Some agencies avoid inside shoulder widths greater than 4 ft and less than 8 ft because of concerns that drivers may attempt to seek refuge in a space that does not have sufficient width to accommodate a typical vehicle (6 ft) plus clearance (desirably 1 ft to 2 ft as discussed in the Green Book, see Section 4.4.2, page 4-10). (7)

Freeway General-purpose Lane Cross Section

A recent Texas DOT project that examined the tradeoffs of reducing lane and shoulder widths to permit an additional freeway lane also identified increased crashes when the widths of lanes or shoulders are reduced. (18) The identified safety improvements included the following:

  • Table 1 provides the safety benefit of 12-ft lanes compared to 11-ft lanes, based on the number of travel lanes per direction, when there are not changes in the other variables included in the model.
  • The safety improvement associated with increased left shoulder width is a reduction of crashes by 5 percent per additional foot of left shoulder, when there are no changes to the other model variables.
  • The safety improvement associated with increased right shoulder width is a reduction of crashes by 9 percent per additional foot of right shoulder, when there are no changes to the other model variables.
  • There is a safety improvement associated with each additional lane (see Table 2).
Figure 2. Chart.
Source: Figure 49 on page 142 of Bonneson, J., A. S. Geedipally, M. P. Pratt, and D. Lord (2012). Safety Prediction Methodology and Analysis Tool for Freeways and Interchanges (NCHRP Project 17-45, online final report).
Reproduced with permission of the Transportation Research Board. (17)

Figure 2. Chart. Proposed crash modification factor for lane width. (17)

Figure 3. Chart.
Source: Figure 51 on page 144 of Bonneson, J., A. S. Geedipally, M. P. Pratt, and D. Lord (2012). Safety Prediction Methodology and Analysis Tool for Freeways and Interchanges (NCHRP Project 17-45, online final report).
Reproduced with permission of the Transportation Research Board.(17)

Figure 3. Chart. Proposed crash modification factor for inside shoulder width. (17)

Table 1. Safety of lane width (fatal and serious injury crashes). (18)
Number of Lanes Multiplicative Effect in Model Fatal and Serious Injury Crash Reduction of a 12-ft Lane Compared to 11-ft
2 0.95 5%
3 0.93 7%
4 0.90 10%
5 0.88 12%

Source: Table 45 on page 76 from Dixon, K., K. Fitzpatrick, R. Avelar, M. Perez, S. Ranft, R. Stevens, S. Venglar, and T. Voigt (2015) Reducing Lane and Shoulder Width to Permit an Additional Lane on a Freeway: Technical Report. FHWA/TX-15/0-6811-1.

Table 2. Safety change per additional lane (fatal and serious injury crashes). (18)
Average Lane Width (ft) Multiplicative Effect Reduction of Fatal and Serious Injury Crashes per Additional Lane
11.0 0.76 24%
11.5 0.75 25%
12.0 0.74 26%

Source: Table 46 on page 77 from Dixon, K., K. Fitzpatrick, R. Avelar, M. Perez, S. Ranft, R. Stevens, S. Venglar, and T. Voigt (2015) Reducing Lane and Shoulder Width to Permit an Additional Lane on a Freeway: Technical Report. FHWA/TX-15/0-6811-1.

While the research also identified that an additional lane can result in reductions in crashes, whether the benefits of the additional lane completely offset the consequences of the reduced lane and shoulder widths would depend upon the conditions present at the site. The authors of the Texas study developed an equation and a spreadsheet that could be used to evaluate the tradeoffs. Note that the Texas work focused on freeways with general-purpose lanes rather than freeways that include a managed lane.

Freeways With High Occupancy Vehicle Or High Occupancy Toll Lanes

A Florida study developed crash prediction equations for freeways facilities with HOV and HOT lanes. (19) The authors developed unique models by number of freeway lanes. Models were developed for 6-, 8-, 10-, and 12-lane freeways (number of lanes reflect both directions and include the managed lanes). For all the models, segment length and AADT were significant and included. For most of the models, left shoulder width was the only other significant variable. An increase in left shoulder width was associated with decreases in crashes. The effect of buffer type on crashes was found to be statistically significant only in the model for 10-lane freeways with an inclusion of a 2- to 3-ft buffer being associated with fewer fatal and injury crashes. Figure 4 illustrates the findings for fatal+injury crashes and Figure 5 for all crashes.

Figure 4. Chart.
Source: Figure 4.5 on page 40 from Srinivasan, S., P. Haas, P. Alluri, A. Gan, and J. Bonneson (2015) Crash Prediction Method for Freeway Facilities with High Occupancy Vehicle (HOV) and High Occupancy Toll (HOT) Lanes. FDOT Contract BDV32-977-04.

Note: abbreviations used in figure: FI = fatal and serious injury, AADT = annual average daily traffic.

Figure 4. Chart. Variation of fatal and serious injury crashes with annual average daily traffic for 10-lane freeways with high occupancy vehicle lanes from Florida study. (19)

Figure 5. Chart.
Source: Figure 4.6 on page 40 from Srinivasan, S., P. Haas, P. Alluri, A. Gan, and J. Bonneson (2015) Crash Prediction Method for Freeway Facilities with High Occupancy Vehicle (HOV) and High Occupancy Toll (HOT) Lanes. FDOT Contract BDV32-977-04.

Note: abbreviation used in figure: AADT = annual average daily traffic.

Figure 5. Chart. Variation of all crashes with annual average daily traffic for 10-lane freeways with high occupancy vehicle lanes from Florida study. (19)

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