title: Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve.
abstract: 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.
authors.affiliation: The Key Laboratory of Road and Traffic Engineering, Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China. 1510704@tongji.edu.cn.
authors.forename: Yi
authors.initials: Y
authors.lastname: Li
authors.affiliation: The Key Laboratory of Road and Traffic Engineering, Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China. chenyr@tongji.edu.cn.
authors.forename: Yuren
authors.initials: Y
authors.lastname: Chen
mesh_terms: D000328:Adult; D001334:Automobile Driving; D006801:Humans; D008962:Models, Theoretical; D010465:Perception; D011930:Reaction Time; D012449:Safety; D014785:Vision, Ocular
keywords: driver vision; mountain highway curve; perception-response time