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Journal Article

Citation

Yu R, Quddus M, Wang X, Yang K. Accid. Anal. Prev. 2018; 120: 304-310.

Affiliation

School of Transportation Engineering, Tongji University, 4800 Cao'an Road, 201804, Shanghai, China; Key Laboratory of Road and Traffic Engineering of Ministry of Education, 4800 Cao'an Road, 201804, Shanghai, China.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.aap.2018.06.007

PMID

30195137

Abstract

The impact of operating speed on traffic crash occurrence has been a controversial topic in the traffic safety discipline as some studies reported a positive association whereas others indicated a negative relationship between speed and crashes. Two major issues thought to be accountable for such conflicting findings are the application of inappropriate statistical methods and the use of sample datasets with varying levels of aggregation. The main objective of this study is therefore to investigate the impacts of data aggregation schemes on the relationships between operating speed and traffic safety. A total of three aggregation approaches were examined: (1) a segment-based dataset in which crashes are grouped by roadway segment, (2) a scenario-based dataset where crashes are aggregated by traffic operating scenarios, and (3) a disaggregated crash-level dataset consisting of information from individual crashes. The first two aggregation approaches were used in examining the relationships between operating speed and crash frequency using Bayesian random-effects negative binomial models. The third disaggregated crash risk analysis was conducted utilizing Bayesian random-effects logistic regression models. From the modeling results, it has been concluded that the scenario-based approach shared similar findings with those of the disaggregated crash risk analysis approach in which a U-shaped relationship between operating speed and crash occurrence was identified. However, the commonly adopted segment-based aggregation approach revealed a monotonous negative relationship between speed and crash frequency. The implications of the different analyses results and the potential applications of the results on speed management systems have therefore been discussed.

Copyright © 2018 Elsevier Ltd. All rights reserved.


Language: en

Keywords

Bayesian random-effects model; Crash aggregation approach; Speed and crashes relationship; Urban expressway traffic safety

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