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Int. J. Environ. Res. Public Health 2017, 14(1), 31;

Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve

The Key Laboratory of Road and Traffic Engineering, Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China
Author to whom correspondence should be addressed.
Academic Editors: Suren Chen and Feng Chen
Received: 30 August 2016 / Revised: 14 December 2016 / Accepted: 20 December 2016 / Published: 30 December 2016
(This article belongs to the Special Issue Traffic Safety and Injury Prevention)
Full-Text   |   PDF [3244 KB, uploaded 30 December 2016]   |  


To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers’ perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers’ vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers’ perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers’ perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers’ perception-response time. View Full-Text
Keywords: perception-response time; driver vision; mountain highway curve perception-response time; driver vision; mountain highway curve

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Li, Y.; Chen, Y. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve. Int. J. Environ. Res. Public Health 2017, 14, 31.

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