Development of a Prediction Method for Driver's Propensity

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• 作者：Jinglei Zhang ; Xiaoyuan Wang ; ^{wangxiaoyuan@sdut.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Cuicui Yu ; Zhenxue Liu ; Haibo Wang
• 关键词：Driver's propensity ; Physiological and psychological factors ; Affective computing ; Traffic safety ; Driver-assistance system
• 刊名：Procedia Engineering
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：137
• 期：Complete
• 页码：161-170
• 全文大小：348 K

文摘

Driver's propensity describes the physiological and psychological states of a vehicle driver and can be used as a dynamic measurement of driver characteristics and an important index for determining factors that may affect driver characteristics such as emotional state and decision preference. Drivers with different propensities behave differently under the same traffic situations; therefore, it is an important concept for studying traffic flow theory and developing new vehicle warning systems. In this study we focused on the prediction of driver's propensity, and an overall consideration of the physiological and psychological indexes which influence the prediction were investigated. Psychological measurements, simulated driving, and vehicle tests were conducted and a prediction model for driver's propensity was established. Validation results showed that the method in this paper was a better predictor of driver's propensity than previous methods, and the new model provides a basis for further study of dynamic characteristics and recognition of driver's propensity.