Effects of automated red-light running control on motorcycle riders in Thailand

Red-light running (RLR) by motorcycle riders is a prevalent traffic violation in developing Asian countries, posing significant safety risks. While automated RLR control has proven effective in reducing violations among drivers, its long-term impact on motorcycle riders remains underexplored. This s...

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Bibliographic Details
Main Authors: Thaned Satiennam, Piyanat Jantosut, Phongphan Tankasem, Rattanaporn Kaewkluengklom, Wichuda Satiennam
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Transportation Research Interdisciplinary Perspectives
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590198225000089
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Summary:Red-light running (RLR) by motorcycle riders is a prevalent traffic violation in developing Asian countries, posing significant safety risks. While automated RLR control has proven effective in reducing violations among drivers, its long-term impact on motorcycle riders remains underexplored. This study evaluates the effects of automated RLR control on motorcycle riders over a 1-year and 5-year period following implementation. The study, conducted at three intersections in Khon Kaen City, Thailand, examined the red-light-running (RLR) behavior of 13,997 motorcycle riders using logit models. These models examined the relationship between RLR occurrences—categorized by crossing behavior and temporal distribution during red times—and influencing factors, including RLR control periods. The results revealed that automated RLR control significantly reduced RLR violations among motorcycle riders. RLR behaviors decreased by 6.26% within one year and 2.09% after five years of control. In particular, opportunistic RLR behavior during the last five seconds of red lights decreased by 5.29% and 6.20% at the 1-year and 5-year marks, respectively. These findings highlight the effectiveness of automated RLR enforcement in influencing behavioral changes and provide valuable guidance for implementing similar measures in mixed-traffic environments in developing countries.
ISSN:2590-1982