A tree-structured crash surrogate measure for freeways

Yan Kuang; Xiaobo Qu; Shuaian Wang

doi:10.1016/j.aap.2015.02.007

A tree-structured crash surrogate measure for freeways

Accid Anal Prev. 2015 Apr:77:137-48. doi: 10.1016/j.aap.2015.02.007. Epub 2015 Feb 21.

Authors

Yan Kuang¹, Xiaobo Qu², Shuaian Wang³

Affiliations

¹ Griffith School of Engineering, Griffith University, Gold Coast, QLD 4222, Australia.
² Griffith School of Engineering, Griffith University, Gold Coast, QLD 4222, Australia. Electronic address: x.qu@griffith.edu.au.
³ Strome College of Business, Old Dominion University, Norfolk, Virginia 23529, USA.

PMID: 25710638
DOI: 10.1016/j.aap.2015.02.007

Abstract

In this paper, we propose a novel methodology to define and estimate a surrogate measure. By imposing a hypothetical disturbance to the leading vehicle, the following vehicle's action is represented as a probabilistic causal model. After that, a tree is built to describe the eight possible conflict types under the model. The surrogate measure, named Aggregated Crash Index (ACI), is thus proposed to measure the crash risk. This index reflects the accommodability of freeway traffic state to a traffic disturbance. We further apply this measure to evaluate the crash risks in a freeway section of Pacific Motorway, Australia. The results show that the proposed indicator outperforms the three traditional crash surrogate measures (i.e., Time to Collision, Proportion of Stopping Distance, and Crash Potential Index) in representing rear-end crash risks. The applications of this measure are also discussed.

Keywords: Crash surrogate measure; Hypothetical disturbance; Proactive safety evaluation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Accidents, Traffic*
Australia
Automobile Driving*
Environment Design
Humans
Models, Theoretical
Risk
Safety*