Citation

Wang K, Zhao S, Ivan JN, Ahmed I, Jackson E. J. Transp. Saf. Secur. 2020; 12(4): 463-481.

Copyright

(Copyright © 2020, Southeastern Transportation Center, and Beijing Jiaotong University, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/19439962.2018.1504262

PMID

unavailable

Abstract

Estimating crash prediction models and applying the Empirical Bayesian approach in identifying hotspots for roads under municipal jurisdiction is often challenging due to the lack of traffic count data. This study presents five hotspot identification (HSID) methods in which annual average daily traffic (AADT) information is not required (i.e., crash frequency [CF], equivalent property damage only, relative severity index, excess predicted average crash frequency using method of moments [MOM], and cross sectional analysis [CSA]), to identify hotspots for road segments under municipal jurisdiction in Connecticut. The segments were categorized into 11 homogenous groups based on the roadway geometric characteristics. The five HSID methods were applied to all segments in each roadway group separately and across the entire State for a systemic analysis. Four quantitative tests (i.e., site consistency test, method consistency test, total rank difference test, and total score test) were used to compare the performance of the five HSID methods. The results indicate that the MOM outperforms others in identifying hotspots for urban one-way arterials, urban one-way local roads, urban two-lane two-way local roads, urban multilane two-way arterials, and urban multilane two-way collectors; the CF outperforms others for rural arterials and collectors, rural local roads, urban one-way collectors, urban two-lane two-way arterials, urban two-lane two-way collectors and urban multilane two-way local roads, and the CSA performs best in all of the five HSID methods in identifying and ranking the roadway hotspots for all roadway groups together.

Language: en

Keywords

hotspot identification; hotspot identification comparison; municipal roads; roads without AADT