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Driving Behavior Analysis for Pedestrian Collision Avoidance Under Emergency Scenarios

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Man-Machine-Environment System Engineering: Proceedings of the 21st International Conference on MMESE (MMESE 2021)

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Abstract

Based on the intent and operation of drivers, pedestrian collision can be divided into accidental and intentional vehicle ramming collisions. Compared to accidental cases in which the drivers are not able to avoid the collision successfully, intentional collisions are more dangerous for pedestrians. However, there is a lack of researches on judging intentional pedestrian collisions based on the statistical characteristics of the driver’s collision avoidance behavior. Therefore, in order to analyze and define the deliberate collisions behavior of drivers, a special driving simulation scenario was designed for driving simulation experiments of pedestrian collision avoidance in emergency situations. To provide a criterion for judging deliberate ramming behavior, the driver’s normal operations for collision avoidance, including reaction time and specific crash avoidance behavior characteristics, under the sudden intrusion of pedestrian conditions was analyzed. This study provides a reference for the verdict of intentional pedestrian collision.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 52072214), National Key R&D Program of China (No. 2017YFC0803802) and Student Research Training Program of Tsinghua University (No. 2021T0148). Thanks Peilin Guo, Xiaoyang Ma, Xingtian Wang for their contribution to the experiment.

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Correspondence to Quan Yuan .

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The study was approved by the Logistics Department for Civilian Ethics Committee of Tsinghua University.

All subjects who participated in the experiment were provided with and signed an informed consent form.

All relevant ethical safeguards have been met with regard to subject protection.

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Yuan, Q., Li, Q., Wang, W. (2022). Driving Behavior Analysis for Pedestrian Collision Avoidance Under Emergency Scenarios. In: Long, S., Dhillon, B.S. (eds) Man-Machine-Environment System Engineering: Proceedings of the 21st International Conference on MMESE. MMESE 2021. Lecture Notes in Electrical Engineering, vol 800. Springer, Singapore. https://doi.org/10.1007/978-981-16-5963-8_87

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  • DOI: https://doi.org/10.1007/978-981-16-5963-8_87

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5962-1

  • Online ISBN: 978-981-16-5963-8

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