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Abstract
The goal of this study was to develop a new method for identifying the actual risky spots by using the geographic information system (GIS). For this purpose, in this study, three different methods for detecting hotspots are developed, i.e., (1) the annual average daily traffic (AADT) normalization method, (2) AK crashes (A is the incapacitating crash, and K is the fatal crash) percentage method, and (3) distribution difference method. To evaluate the performances of these three hotspot detection methods along with a baseline method that only considered the frequency of crashes, we applied these three methods to identify the top 20 hotspots for truck crashes in two representative areas in Texas. The results indicated that (1) all three proposed methods produced more reasonable results than the baseline method, and (2) the “distribution difference” method outperformed the other methods.
Highlights
Due to the size and weight of large trucks, their crashes often result in fatal injuries, property damage, and significant economic losses
One of the problems in the existing hotspot analysis method is that many of the detected hotspots are near a truck distribution center (TDC). ese spots usually are not very risky, and the high crash rates more likely were due to the high volume of truck traffic. erefore, if most of the identified hotspots are close to a TDC, it indicates that the detection result is biased and not reliable
The distribution difference method has the lowest number of observations close to TDC. ese results potentially indicate that the distribution difference method can detect the crash hotspots by considering the impacts of traffic exposures
Summary
Due to the size and weight of large trucks, their crashes often result in fatal injuries, property damage, and significant economic losses. Most of the methods that are currently used to analyze crash hotspots have no effective way of considering the impacts of roadway traffic conditions and exposure factors, and very few of them have taken account of the severities of the crashes. Qi et al [2] analyzed hotspots for truck crashes in Texas; but because they did not consider the volumes of traffic on different segments of the roadway, 7 of the top 10 hotspots they identified were in congested urban areas. Because the severities of the crashes that occurred were not considered, most of the top 10 hotspots that were identified for truck crashes were located near locations that generate or attract truck traffic, such as the distribution centers, rest areas, or stopping places for trucks
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