Abstract
Red light running at signalised intersections is a growing road safety issue worldwide, leading to the rapid development of advanced intelligent transportation technologies and countermeasures. However, existing studies have yet to summarise and present the effect of these technology-based innovations in improving safety. This paper represents a comprehensive review of red-light running behaviour prediction methodologies and technology-based countermeasures. Specifically, the major focus of this study is to provide a comprehensive review on two streams of literature targeting red-light running and stop-and-go behaviour at signalised intersection - (1) studies focusing on modelling and predicting the red-light running and stop-and-go related driver behaviour and (2) studies focusing on the effectiveness of different technology-based countermeasures which combat such unsafe behaviour. The study provides a systematic guide to assist researchers and stakeholders in understanding how to best identify red-light running and stop-and-go associated driving behaviour and subsequently implement countermeasures to combat such risky behaviour and improve the associated safety.
| Original language | English |
|---|---|
| Pages (from-to) | 25309-25326 |
| Number of pages | 18 |
| Journal | IEEE Access |
| Volume | 10 |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2013 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
Keywords
- Red-light running
- behavior prediction
- countermeasures
- dilemma Zone
- intersection
- statistical and machine learning models
- stop-go at yellow onset
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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