A Review on Drivers Red Light Running Behavior Predictions and Technology Based Countermeasures

August 15, 2020 Β· The Cartographer Β· πŸ› IEEE Access

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Survey/review paper β€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Review on Drivers Red Light Running Behavior Predictions and Technology Based Countermeasures"

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Authors Md Mostafizur Rahman Komol, Jack Pinnow, Mohammed Elhenawy, Shamsunnahar Yasmin, Mahmoud Masoud, Sebastien Glaser, Andry Rakotonirainy arXiv ID 2008.06727 Category cs.AI: Artificial Intelligence Cross-listed cs.CY, cs.NE Citations 11 Venue IEEE Access Last Checked 3 days ago
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.
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