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One goal of transportation safety engineers is to identify and prioritize safety deficient locations along roadways. The identification of such locations allows examination of possible engineering, enforcement, and/or educational measures to improve safety. In general, each state in the U.S. selects its own methodology for identification and prioritization of high crash locations. The Iowa Department of Transportation (DOT) annually identifies and then ranks the top 100 high crash locations using a combination of crash frequency, crash rate, and value loss. In the present methodology adopted by Iowa DOT for ranking of high crash locations, the crash database is filtered before the potential high crash locations are ranked. But, the currently used filter seems to inherently favor locations with fatalities. Hence, two new filters with a potential to reduce the bias have been analyzed and the sensitivity analysis of the two filters is explained as part of this thesis. Also, in the current methodology, once the crash database is filtered for the potential high crash locations, three ranking factors, crash frequency, crash rate, and value loss are used for ranking the locations. In the current process, all the three ranking factors are considered equal contributors to the final ranking position of a high crash location. This equal weightage does not seem to be correct. Hence, the impact of different weighting is considered and a sensitivity analysis of twenty-seven new combinations of ranking factors is performed as part of this research.
This dissertation, "Advances in Spatial Analysis of Traffic Crashes: the Identification of Hazardous Road Locations" by Shenjun, Yao, 姚申君, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: The identification of hazardous road locations is important to the improvement of road safety. However, there is still no consensus on the best method of identifying hazardous road locations. While traditional methods, such as the hot spot methodology, focus on the physical distances separating road crashes only, the hot zone methodology takes network contiguity into consideration and treats contiguous road segments as hazardous road locations. Compared with the hot spot method, hot zone methodology is a relatively new direction and there still remain a number of methodological issues in applying the method to the identification of hazardous road locations. Hence, this study aims to provide a GIS-based study on the identification of crash hot zones as hazardous road locations with both link-attribute and event-based approaches. It first explores the general procedures of the two approaches in identifying traffic crash hot zones, and then investigates the characteristics of the two approaches by conducting a range of sensitivity analysis on defining threshold value and crash intensity with both simulated and empirical data. The results suggest that it is better to use a dissolved road network instead of a raw-link-node road network. The segmentation length and the interval of reference points have great impacts on the identification of hot zones, and they are better defined as 100 meters considering the stabilities of the performance. While employing a numerical definition to identify hot zones is a simple and effort-saving approach, using the Monte Carlo method can avoid selection bias in choosing an appropriate number as the threshold value. If the two approaches are compared, it is observed that the link-attribute approach is more likely to cause false negative problem and the event-based approach is prone to false positive problem around road junctions. No matter which method is used, the link-attribute approach requires less computer time in identifying crash hot zones. When a range of environmental variables have to be taken into consideration, the link-attribute approach is superior to the event-based approach in that it is easier for the link-attribute approach to incorporate environmental variables with statistical models. By investigating the hot zone methodology, this research is expected to enrich the theoretical knowledge of the identification of hazardous road locations and to practically provide policy-makers with more information on identifying road hazards. Further research efforts have to be dedicated to the ranking of hot zones and the investigation of false positive and false negative problems. DOI: 10.5353/th_b5043444 Subjects: Traffic accidents - Statistical methods
TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 295: Statistical Methods in Highway Safety Analysis focus on the type of safety analysis required to support traditional engineering functions, such as the identification of hazardous locations and the development and evaluation of countermeasures. Analyses related specifically to driver and vehicle safety are not covered, but some statistical methods used in these areas are of relevance and are summarized where appropriate.
TRB's National Cooperative Highway Research Program (NCHRP) Report 672: Roundabouts: An Informational Guide - Second Edition explores the planning, design, construction, maintenance, and operation of roundabouts. The report also addresses issues that may be useful in helping to explain the trade-offs associated with roundabouts. This report updates the U.S. Federal Highway Administration's Roundabouts: An Informational Guide, based on experience gained in the United States since that guide was published in 2000.
This book increases the level of knowledge on road safety contexts, issues and challenges; shares what can currently be done to address the variety of issues; and points to what needs to be done to make further gains in road safety.