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vii Executive Summary NCHRP Project 17-23 is a study of the safety and other impacts of speed limit changes on high- speed roads. The work was carried out by a team consisting of Prof. Kara Kockelman and her students, and CRA International, Inc. (formerly Charles River Associates). Prof. Kockelman is an Associate Professor at the University of Texas at Austin. To accomplish the project objectives, the project team carried out activities in a number of areas: ⢠A review of relevant literature, covering a broad range of topics relevant to this study. These included prior studies of the safety impacts of speed limit changes, discussions of statistical methodology applicable to the particular issues presented by traffic safety analyses, reviews of non-safety impacts of speed limit changes, and analyses of the effects of differential speed limits between light duty and heavy duty vehicles (e.g. cars and trucks). ⢠An Internet-based survey of State Departments of Transportation. The survey focused on each DOTâs decision-making processes about speed limit changes, but also obtained basic information about traffic volume and safety data availability, and a number of other issues. ⢠Telephone surveys of a number of State Highway Patrol or equivalent agencies. Here the intent was to obtain information regarding the responses of these agencies to the NMSL repeal, especially regarding changes in the deployment of traffic enforcement resources. ⢠Collection of data relating to the effects of speed limits on traffic safety, and the analysis of this data to identify and quantitatively model the various ways in which speed limits directly and indirectly affect safety. Analyses of speed choices (their central tendencies and variability) were undertaken for data from high-speed roadways in several regions (including Washington State, Southern California and Austin, Texas). Crash frequency was modeled as a function of roadway design and use characteristics, while relying on both discrete and continuous models of panel data from across Washington State. Crash severities were modeled using heteroscedastic ordered logit models, as applied to both Washington and U.S. datasets. These analyses were the major focus of the project effort, and were primarily carried out by Prof. Kockelman and her students. The principal analyses and conclusions of this work are summarized below. Safety Impacts of Speed Limit Changes The safety-related analyses were based on a comprehensive framework of the disaggregate relationships between speed limits, driver speed choices, crash occurrence and crash severity. The analyses drew on a variety of data types including loop detector measurements, stated preference surveys and revealed choices, and crash records containing information about crash counts and severities, vehicles and their occupants, and roadways and their environments. The project made extensive use of data obtained from Washington State because of its quality and state of preparation. However, data from a national driver safety survey, vehicle speed data from Southern California and Austin, Texas, and a national sample of crash records were also used. The analyses applied state-of-the-art statistical methods to address a number of data characteristics that complicate traffic safety analyses. The projectâs datasets and analyses are thoroughly described in Chapter 4 of this report.
viii It should be noted that, following the projectâs original scope of work, our data, analyses and conclusions pertain to speed limit increases on high-speed roads. Most (but not all) of our data concerned high-type roadways (Interstates and freeways) with full access control. Our conclusions cannot be extended to predict the safety impacts that might be associated with speed limit increases on lower speed roadways. Speed Choice Models Analyses of driver speed choices were intended to illuminate the relationships between speed limits and actual driver behavior, as this is reflected in average vehicle speeds and speed variability. A number of analyses were carried out; two in particular are highlighted here. A study of speed limit changes in Washington State (section 4.2.4) was based on a before-after comparison of four sites: two urban and two rural, as well as two that experienced speed limit changes and two that did not. The analysis showed that a 5 mi/h speed limit increase at two sites was associated with an increase in average speeds of 1.2-1.6 mi/h, and with a 5 mi2/h2 speed variance increase at the rural site. Over the same period, the sites that did not experience a speed limit change exhibited essentially no changes in their traffic speed characteristics, suggesting that the âspilloverâ effect (the impact that a speed limit change on one road may have on parallel facilities) in this case was small or negligible. The analysis of individual vehicle speed data obtained from a small cross-section dataset of radar gun speed measurements on roadways in Austin, Texas (section 4.2.3). This was the only source of individual vehicle speed data available to the project and speed limits were not changed during the study period. The analysis identified a number of engineering, environmental and traffic characteristics that influence average speed and speed variance. Comparing different roadway sections in the cross-sectional analysis, it was found that a 5 mi/h difference in speed limits was associated with a roughly 3.2 mi/h difference in average vehicle speeds. A particular highlight of this analysis was its demonstration that the impact of speed limits on vehicle speed variances is, at most, very small. It is noteworthy that the before-after analysis of vehicle speeds on roads that experience a speed limit change suggests a much more moderate response to the change than does the cross- sectional analysis of speeds on roadways with different limits (e.g., 3 mi/h change in actual speeds following a 10 mi/h change in speed limits, rather than the 6 mi/h change that a cross- sectional analysis would suggest â a factor of 2 difference). Existing literature, which is frequently based on before-after analyses, also tends to support the lower result. Most of the projectâs speed choice model analyses involved cross-sectional data, however, because the Washington sample of before-after data speed and crash data was felt to be too small for use in disaggregate model development. Consequently, the magnitude of the effects of speed limit changes on average speeds may be overestimated here. Moreover, since predictions of the overall effects of a speed limit change on safety depend in part on expected driving speed changes, an overestimate of the latter will propagate through the model system and may lead to an overestimate of the overall safety effects of a speed limit change. This caveat should be kept in mind when examining predictions of overall speed limit change effects. However, even allowing for a possible overestimate of these effects, the magnitudes of the speed limit change effects remain in most cases both statistically and practically significant.
ix Crash Occurrence Models The results of the project analyses of the statistical association between speed limits and total crash rates suggested only slight effects. This work is described in Section 4.3. The projectâs main work on crash occurrence models was based on datasets obtained by clustering Highway Safety Information System (HSIS) roadway segments over several years of data. Two separate analyses of this dataset found that, other things equal, the statistical relationship between speed limit and total crash rate is concave, with a maximum around 70 mi/h. (This was the highest observed speed limit in the dataset, and the model was not extrapolated beyond that value.) For a âtypicalâ high-speed roadway section, a 10 mi/h speed limit increase is associated with a 2.9% to 3.3% increase in the overall crash rate. Injury Severity Models Injury severity models apply when crashes have occurred, and are then used to estimate the associated distribution of injury severities. The project used HSIS data for Washington State as well as the National Automotive Sampling System (NASS) Crashworthiness Dataset (CDS) to estimate occupant-based injury severity models (sections 4.4.1 and 4.4.2). Both models are consistent in that they associate sizeable percentage increases in the rates of incapacitating and fatal injuries with a 10 mi/h or higher speed limit increase. However, the magnitudes of the increases calculated by the two models are quite different. For typical speed limit increases, the model developed from Washington State data on high speed roads predicts an increase in fatalities in the range of 7%-39% following a crash, while the model estimated from NASS CDS data on all roads predicts crash fatality rate increases in the range of 31%-110%, or roughly twice as high. Of the two sets of results, it is likely that the model developed from Washington State HSIS data is more applicable to the analysis of speed change impacts on high- speed roads because the estimation dataset contained only data on such roads. The NASS dataset offered a much wider range of roadway types and speed limits; thus, its speed-related results are more striking. (It is rare that vehicle occupants die on low-speed roadways.) For this reason, the lower range of fatality rate changes is likely to be more appropriate when crafting speed policies for high-speed roadways. Overall Effects Within the comprehensive framework described above, the overall safety effects associated with a speed limit change are determined by tracing its separate and inter-related effects on driver speed choice, crash rates, and the probabilities of different injury severity levels. For example, considering that the crash rate itself increases slightly with a speed limit increase, the overall change in the fatal crash rate following a speed limit increase will be slightly higher than just the increase in the probability of a fatality when a crash occurs. Broadly speaking, however, the association between speed limit and injury severity dominates the overall relationship between speed limit and overall injury or fatality counts. The following table illustrates this point.
x Safety Effects Associated with a 10 mi/h Speed Limit Increase on High Speed Roads Increase in Speed Limit (mi/h) Change in Average Driving Speed (mi/h) Change in Total Crash Count Change in Probability of Fatal Injury Total Change in Fatal Injury Count 55 to 65 +3 +3.3% +24% +28% 65 to 75 +3 +0.64% +12% +13% Note: Calculations assume average high-speed roadway geometry. It can be seen from the above that in both cases a 10 mi/h speed limit increase is estimated to result in a 3 mi/h increase in average driving speed. In the lower speed limit range (55 to 65 mi/h), data analyses suggest a 3.3% increase in the total number of crashes, and a 24% increase in the probability that a crash results in a fatal injury. Together, these increases combine to a 28% increase in the number of fatalities following the speed limit increase. In the higher speed limit range (65 to 75 mi/h), on the other hand, the increase in the total number of crashes is considerably smaller (0.64%). This is an illustration of the concave relationship between crash rate and speed limit described above. Although the statistical analysis does not provide an explanation for the form of this relationship, it may be that drivers are naturally more cautious at higher speeds, or that the roads deemed suitable for 75 mi/h speed limits are intrinsically safer, so that the crash rate effect of increasing speed limits to this level is attenuated. For this speed limit increase, the predicted increase in the probability of a fatality in a crash is 12%, again lower than for the 55 to 65 mi/h speed limit increase. Explanations similar to those suggested above may apply here as well. The overall effect of these increases is a 13% increase in total fatalities, which is slightly less than half the fatality increase predicted for a 55 to 65 mi/h speed limit increase. The explanations for this smaller overall increase follow directly from those for the individual effects that contribute to it. It should be noted that predictions of injury severity distribution changes following speed limit changes, such as those mentioned above, require the application of both speed choice models and injury severity models. The crash severity models were based on cross-sectional data and, as was discussed above, may overestimate the speed change impact by a factor of roughly 2 when compared to the results of actual before-after studies on individual roadways. This implies that the predictions of injury severity changes following a speed limit change may be based on travel speed differences that are themselves too high. This could, of course, result in an overestimate of the injury severity impact, perhaps by a factor of more than 2. Nonetheless, even after making allowances for such effects, the relationship between typical speed limit changes on high-speed roads and the injury severity distribution would in many cases remain statistically and practically significant. It is interesting to note that some (but by no means all) studies have found significant increases in fatality rates on high-speed roads following the 1987 NMSL relaxation from 55 to 65 mi/h on rural interstates. Fatality rate increases in the range of 30%-57% have been reported, using aggregate data. The corresponding prediction of the HSIS-based model is 24% for a âtypicalâ high-speed roadway. Strictly speaking, these values cannot validly be compared; nonetheless, it is striking that our result, although slightly lower, is in the same general range as the values found by these other studies. While this is not a validation of the HSIS-based model, it is fair to
xi say that its predictions are roughly consistent with the overall NMSL relaxation fatality impacts found by some researchers, using more aggregate datasets and statistical methods less able to account for their specific characteristics. Our results, however, provide considerably more insight into the various effects of speed limit changes on speed, crash probability, and the injury severity distribution following a crash. Secondary Effects It is sometimes argued that changes in the speed limit on one road or road class may affect the distribution of traffic across other roads and road classes, from driver reactions either to the speed limit change itself, or to the associated enforcement activities (if any). The data available to our study did not allow a systematic investigation of these potential secondary effects of speed limit changes. An analysis of these effects, at the disaggregate level pursued throughout our work, would require a detailed set of traffic volume, speed and crash data extending across all road types (including non-high speed roads) likely to be affected by driver reactions to a speed limit change, and such a dataset was not available to us. Nonetheless, two comments can be made regarding secondary effects. First, a before-after analysis conducted at four sites in Washington State suggested that the average speed effects of a speed limit change were confined to the roadways on which the changes occurred. Two of the sites were on roadways that experienced 5 mi/h speed limit changes; statistically significant changes in average speeds were observed at these sites, but not at nearby sites that did not experience speed limit changes. This suggests that, in this case at least, secondary effects on speeds (and perhaps volumes) were not significant. Second, interviews conducted with state DOT and police officials regarding enforcement policy changes following the NMSL repeal suggest that any such changes were at most limited in extent and geographic scope. Thus, it appears to be unlikely that driver route choice behavior was affected in a systematic and large-scale way by changes in traffic safety enforcement practices following the NMSL repeal, and so that these secondary effects may have been minor. Non-Safety Impacts of Speed Limit Changes The investigation of non-safety impacts of speed limit changes relied on published literature, unpublished reports by state DOTs, and results of surveys of state DOT and police officials. This investigation was a lower-priority project effort than the analysis of safety impacts discussed above. Economic Impacts In broad terms, non-safety impacts of speed limit changes may include effects on economic, environmental and/or commercial conditions. Unfortunately, generally applicable conclusions regarding such effects are mostly lacking. As noted above, speed limit increases translate into less-than-equivalent increases in average travel speed. The reduced travel times made possible by higher travel speeds have an economic
xii value. However, when considering the system-wide impacts of a speed limit change, it must be remembered that in general not all travel will be fully affected by the change; for example, travel for which average speeds are significantly constrained by congestion will likely not experience the full impacts of a speed limit change.. Changes in average travel speed also affect vehicle operating costs. Of the various cost components that contribute to overall operating costs, running costs (those that directly result from vehicle operation) are most significantly impacted by speed; and of running cost components, fuel consumption costs are the largest portion. Under typical operating conditions on high-speed roads, a 10 mi/h speed limit increase would lead to an operating cost increase of roughly half the value of the travel time savings, further reducing the net economic benefit from higher speeds. Other Impacts With respect to the noise and air quality impacts of speed limit changes, the little evidence available suggests that these are small to negligible. The project was unable to find any empirical or documentary evidence regarding possible commercial impacts of speed limit increases. The resulting (smaller) increases in average speeds of commercial vehicles should, in the medium to long term, result in opportunities for more efficient transportation and business operations. However, such speed changes are typically small, and the productivity of a commercial vehicle (and of the operations that it serves) depends only partly on its travel speed since it may spend significant time in loading/unloading operations or waiting for cargo. Thus, the impacts on business and commerce of speed limit changes are likely to be marginal. Enforcement Policy Responses to the NMSL and Its Repeal The project conducted surveys of State DOTs and Police Agencies to identify enforcement policy responses to the NMSL and its repeal. It is sometimes claimed that the NMSL imposition and related Federal mandates led to a systematic concentration of speed limit enforcement efforts on high-speed roads, to the detriment of potentially more beneficial traffic enforcement efforts of other kinds or on other facility types. Available data from DOTs and state police agencies did not allow a rigorous investigation of this assertion. Nonetheless, anecdotal evidence collected by the project through surveys of state DOT and police officials across the country does suggest that neither of these things happened systematically or on a large scale. Some respondents acknowledged that there was a concern in their agencies to demonstrate compliance with the NMSL in order to avoid Federal sanctions. However, respondents were adamant that no enforcement actions taken during the period of the NMSL were of a nature to compromise traffic safety. Similarly, respondents cited no examples of systematic changes in enforcement practices away from speed limit enforcement on high-speed roads following the NMSL repeal. Indeed, several respondents and DOT reports noted that speed limit enforcement activities actually became more intensive on high-speed roads in the period following the repeal.
xiii The evidence suggests that the response of most police agencies to the NMSL relaxation and repeal generally took more measured forms: for example, reduced tolerance for speeds higher than the new limits together with, in some cases, a new speeding fine structure and/or an aggressive information campaign to notify the public of the tougher post-repeal policy. Data Recommendations The methods used in this work were guided, and limited, by the extent and quality of existing datasets. Consequently, the project has a number of recommendations regarding future data collection efforts to support fundamental research into crash causality and characteristics. Research-oriented data collection efforts should, as much as possible, be complementary to and build on the crash, traffic, and highway inventory data collection efforts routinely carried out. Given these sources of currently available data, it is worthwhile to focus research-oriented data collection in a few specific ways. First, traffic safety research would benefit from the collection and assembly of additional types of information on the characteristics of roadways and their environments. This could include information on pavement and weather conditions; the presence and nature of embankments, barriers and culverts; driveway and cross-road frequencies; clear zone width; and sight distances. None of the datasets that the project analyzed contained such data. Second, as a practical matter it would be more efficient to concentrate near term research- oriented data collection efforts on the high-speed roadway subsystem. Over the longer term, it would be desirable to extend such data collection efforts to other components of the overall system. Data producing agencies should be encouraged to adopt consistent geo- or linear referencing systems to facilitate the assembly of integrated sets of disparate data types. Furthermore, agencies should be encouraged to preserve collected data in the most disaggregate form feasible, rather than aggregating it in order to reduce archiving costs. A dataset containing actual vehicle speeds, year-round traffic counts, design attributes, and crash information for a thousand homogeneous sites over several years would go a long way toward making these analyses more directly connected and their results more robust.
