@inproceedings{ec93bc2f327444d5b11bd4ddd1fe1dfc,
title = "Prediction accuracy improvement of avoidance driving behavior model based on game theory: Introducing jerk to refine acceleration",
abstract = "Understanding avoidance driving behaviors is important for both drivers and traffic managers owing to the high correlation between accidents and human driving behaviors. The most recent research in this area considers acceleration as the implement of decision result, which may cause inaccurate prediction results as acceleration changes continuously. To solve this problem, this study considers the acceleration as a continuously changing variable and utilizes jerk, the change rate of acceleration/deceleration to quantify the change of acceleration. We further applied the jerks in a game theory vehicle avoidance model. This method analyzes driving behaviors in a more detailed magnitude and finally improves the model results. Finally, a case study shows that this work improves the prediction accuracy of the driving behavior model compared to previous research.",
keywords = "Avoidance behavior, Decision model, Jerk, Traffic conflict",
author = "Jinghua Wang and Zhao Zhang and Guangquan Lu",
note = "Publisher Copyright: {\textcopyright} ASCE.; 19th COTA International Conference of Transportation Professionals: Transportation in China - Connecting the World, CICTP 2019 ; Conference date: 06-07-2019 Through 08-07-2019",
year = "2019",
doi = "10.1061/9780784482292.051",
language = "英语",
series = "CICTP 2019: Transportation in China - Connecting the World - Proceedings of the 19th COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "558--567",
editor = "Lei Zhang and Jianming Ma and Pan Liu and Guangjun Zhang",
booktitle = "CICTP 2019",
address = "美国",
}