Modified Driving Safety Field Based on Trajectory Prediction Model for Pedestrian–Vehicle Collision

Renfei Wu, Xunjia Zheng, Yongneng Xu, Wei Wu, Guopeng Li, Qing Xu and Zhuming Nie
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Renfei Wu: Department of Transportation, Nanjing University of Science and Technology, Nanjing 210094, China
Xunjia Zheng: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Yongneng Xu: Department of Transportation, Nanjing University of Science and Technology, Nanjing 210094, China
Wei Wu: Department of Transportation, Nanjing University of Science and Technology, Nanjing 210094, China
Guopeng Li: College of Information and Communication, National University of Defense Technology, Xian 710106, China
Qing Xu: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Zhuming Nie: Department of Education Technology, School of Educational Science Anhui Normal University, Wuhu 241000, China

Sustainability, 2019, vol. 11, issue 22, 1-15

Abstract: Pedestrian–vehicle collision is an important component of traffic accidents. Over the past decades, it has become the focus of academic and industrial research and presents an important challenge. This study proposes a modified Driving Safety Field (DSF) model for pedestrian–vehicle risk assessment at an unsignalized road section, in which predicted positions are considered. A Dynamic Bayesian Network (DBN) model is employed for pedestrian intention inference, and a particle filtering model is conducted to simulate pedestrian motion. Driving data collection was conducted and pedestrian–vehicle scenarios were extracted. The effectiveness of the proposed model was evaluated by Monte Carlo simulations running 1000 times. Results show that the proposed risk assessment approach reduces braking times by 18.73%. Besides this, the average value of TTC −1 (the reciprocal of time-to-collision) and the maximum TTC −1 were decreased by 28.83% and 33.91%, respectively.

Keywords: driving safety field; risk assessment; pedestrian–vehicle collision; pedestrian trajectory prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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