title: A tree-structured crash surrogate measure for freeways.
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.
authors.affiliation: Griffith School of Engineering, Griffith University, Gold Coast, QLD 4222, Australia.
authors.forename: Yan
authors.initials: Y
authors.lastname: Kuang
authors.affiliation: Griffith School of Engineering, Griffith University, Gold Coast, QLD 4222, Australia. Electronic address: x.qu@griffith.edu.au.
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Qu
authors.affiliation: Strome College of Business, Old Dominion University, Norfolk, Virginia 23529, USA.
authors.forename: Shuaian
authors.initials: S
authors.lastname: Wang
mesh_terms: D000063:Accidents, Traffic; D001315:Australia; D001334:Automobile Driving; D004779:Environment Design; D006801:Humans; D008962:Models, Theoretical; D012306:Risk; D012449:Safety
keywords: Crash surrogate measure; Hypothetical disturbance; Proactive safety evaluation