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Journal Article

Citation

Zurlinden H, Baruah A, Gaffney J. J. Road Safety 2020; 31(1): 66-80.

Copyright

(Copyright © 2020, Australasian College of Road Safety)

DOI

unavailable

PMID

unavailable

Abstract

Key Findings

• On highly trafficked urban motorways, complexity caused by unstable or congested flow in dense traffic increases the likelihood of human error when performing manoeuvres (e.g. lane changes);

• Complexity characterized by high vehicle density can be avoided through appropriate planning and real-time traffic control;

• Modern infrastructure or vehicle-based technologies allow analysis of individual vehicle manoeuvres e.g. 'Brake', 'Speed alert' or 'Lane change' events in terms of number, spatial or temporal occurrence and risk profiles;

• Emerging technologies show promise in exploring what makes high density traffic complex;


The purpose of this article is to present insights into the relationship between complex traffic flow phenomena on urban motorways and crash risk. Unstable or congested flow can trigger low speed/high density clusters (e.g. nucleations or shockwaves) creating 'surprise elements', therefore sharply increasing the cognitive workload for motorists. When combined with reduced road space and freedom to perform needed manoeuvres (e.g. lane changes), conditions can exceed the physical or mental capability and hence increase the likelihood of human error. There is overwhelming evidence that high traffic density drastically increases the crash risk. Some density concentrations can be avoided through appropriate planning and real-time traffic control, resulting in a reduction in crashes. Modern measurement devices allow for the analysis of individual vehicle behaviours such as 'Brake', 'Speed alert' or 'Lane change' events and show promise in providing robust data to further exploring what makes dense traffic complex. This allows establishing relationships between "events as elementary units of exposure" and crash occurrence resulting in a new way of understanding crash rates. These relationships are important to predict crashes, identify high-risk locations, and establish suitable measures for crash reduction.


Keywords: Complexity, Crash risk, Events of Exposure, Lane changes, Traffic management, Urban motorways


Language: en

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