Crash prediction with behavioral and physiological features for advanced vehicle collision avoidance system

Crash prediction with behavioral and physiological features for advanced vehicle collision avoidance system

作者:Ba, YT(Ba, Yutao)^[1];Zhang, W(Zhang, Wei)^[2];Wang, QH(Wang, Qinhua)^[1];Zhou, RG(Zhou, Ronggang)^[3];Ren, CR(Ren, Changrui)^[1]

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

DOI: 10.1016/j.trc.2016.11.009

出版年: JAN 2017

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Real-time crash prediction is the key component of the Vehicle Collision Avoidance System (VCAS) and other driver assistance systems. The further improvements of predictability requires the systemic estimation of crash risks in the driver-vehicle-environment loop. Therefore, this study designed and validated a prediction method based on the supervised learning model with added behavioral and physiological features. The data samples were extracted from 130 drivers' simulator driving, and included various features generated from synchronized recording of vehicle dynamics, distance metrics, driving behaviors, fixations and physiological measures. In order to identify the optimal configuration of proposed method, the Discriminant Analysis (DA) with different features and models (i.e. linear or quadratic) was tested to classify the crash samples and non-crash samples. The results demonstrated the significant improvements of accuracy and specificity with added visual and physiological features. The different models also showed significant effects on the characteristics of sensitivity and specificity. These results supported the effectiveness of crash prediction by quantifying drivers' risky states as inputs. More importantly, such an approach also provides opportunities to integrate the driver state monitoring into other vehicle-mounted systems at the software level. (C) 2016 Elsevier Ltd. All rights reserved.

作者关键词:Crash prediction;Driving behavior;Fixation;Physiological measures;Discriminant analysis

KeyWords Plus:DRIVING SIMULATOR VALIDATION;HAZARD PERCEPTION;MENTAL WORKLOAD;WARNING SYSTEMS;DRIVERS;PERFORMANCE;ALGORITHM;RESPONSES;ROAD;INTERSECTIONS

通讯作者地址:Ba, YT (通讯作者)

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电子邮件地址:bytbabyt@cn.ibm.com

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