Safety Impacts of Differential Speed Limits for Trucks and Passenger Cars on Rural Interstate Highways: A Modified Empirical Bayes ApproachSource: Journal of Transportation Engineering, Part A: Systems:;2006:;Volume ( 132 ):;issue: 001DOI: 10.1061/(ASCE)0733-947X(2006)132:1(19)Publisher: American Society of Civil Engineers
Abstract: To compare the safety effects of a uniform speed limit (USL) for all vehicles as opposed to a differential speed limit (DSL) for cars and heavy trucks, detailed crash data for six states were obtained for rural interstate highways for the period 1991–2000. The states were categorized into four policy groups based on the speed limit type employed during that decade: maintenance of a uniform limit, maintenance of a differential limit, a change from a uniform to a differential limit, and a change from a differential to a uniform limit. A modified empirical Bayes framework was used to evaluate crash frequency changes without presuming a constant relationship between crashes and traffic volume. Aggregate results showed no consistent safety effects of DSL as opposed to USL. The reason for this finding is that within each state, the modified empirical Bayes methodology suggested that crash risk increased regardless of speed limit policy. The crash estimation models (CEMs) that were developed for each state varied substantially from one state to another such that use of a single state’s CEM for other states could lead to an erroneous conclusion regarding DSL versus USL safety impacts. However, by looking at results for multiple states, this study shows how that problem is avoided. Two considerations for future applications of the empirical Bayes methodology that proved helpful for this investigation are noted. First, it is feasible to use a site as its own control group in a before/after study if the geographical variation from state to state is greater than the temporal variation from the before to the after period. Such a situation arises not only in the case of statewide speed limit policies, but also for other transportation-related policies enacted on a statewide basis. Second, results were consistent between conventional approaches and the modified empirical Bayes approach. The latter technique showed the crash frequency increasing regardless of whether a state changed from DSL to USL, changed from USL to DSL, maintained USL, or maintained DSL, leading one to conclude that speed limit policy has no consistent impact on safety. This conclusion is similar to that reached when using conventional methods, which had shown that in each state, speed limit policy (DSL versus USL) usually had no significant impact on crash rate (crash frequency divided by vehicle miles traveled).
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contributor author | Nicholas J. Garber | |
contributor author | John S. Miller | |
contributor author | Xin Sun | |
contributor author | Bo Yuan | |
date accessioned | 2017-05-08T21:04:42Z | |
date available | 2017-05-08T21:04:42Z | |
date copyright | January 2006 | |
date issued | 2006 | |
identifier other | %28asce%290733-947x%282006%29132%3A1%2819%29.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/37803 | |
description abstract | To compare the safety effects of a uniform speed limit (USL) for all vehicles as opposed to a differential speed limit (DSL) for cars and heavy trucks, detailed crash data for six states were obtained for rural interstate highways for the period 1991–2000. The states were categorized into four policy groups based on the speed limit type employed during that decade: maintenance of a uniform limit, maintenance of a differential limit, a change from a uniform to a differential limit, and a change from a differential to a uniform limit. A modified empirical Bayes framework was used to evaluate crash frequency changes without presuming a constant relationship between crashes and traffic volume. Aggregate results showed no consistent safety effects of DSL as opposed to USL. The reason for this finding is that within each state, the modified empirical Bayes methodology suggested that crash risk increased regardless of speed limit policy. The crash estimation models (CEMs) that were developed for each state varied substantially from one state to another such that use of a single state’s CEM for other states could lead to an erroneous conclusion regarding DSL versus USL safety impacts. However, by looking at results for multiple states, this study shows how that problem is avoided. Two considerations for future applications of the empirical Bayes methodology that proved helpful for this investigation are noted. First, it is feasible to use a site as its own control group in a before/after study if the geographical variation from state to state is greater than the temporal variation from the before to the after period. Such a situation arises not only in the case of statewide speed limit policies, but also for other transportation-related policies enacted on a statewide basis. Second, results were consistent between conventional approaches and the modified empirical Bayes approach. The latter technique showed the crash frequency increasing regardless of whether a state changed from DSL to USL, changed from USL to DSL, maintained USL, or maintained DSL, leading one to conclude that speed limit policy has no consistent impact on safety. This conclusion is similar to that reached when using conventional methods, which had shown that in each state, speed limit policy (DSL versus USL) usually had no significant impact on crash rate (crash frequency divided by vehicle miles traveled). | |
publisher | American Society of Civil Engineers | |
title | Safety Impacts of Differential Speed Limits for Trucks and Passenger Cars on Rural Interstate Highways: A Modified Empirical Bayes Approach | |
type | Journal Paper | |
journal volume | 132 | |
journal issue | 1 | |
journal title | Journal of Transportation Engineering, Part A: Systems | |
identifier doi | 10.1061/(ASCE)0733-947X(2006)132:1(19) | |
tree | Journal of Transportation Engineering, Part A: Systems:;2006:;Volume ( 132 ):;issue: 001 | |
contenttype | Fulltext |