Research on the mechanism of the impact of traffic environment on near-collision behavior of hazardous goods vehicle drivers based on EEG

Liu Xuanyi

doi:10.1117/12.3051611

20 January 2025 Research on the mechanism of the impact of traffic environment on near-collision behavior of hazardous goods vehicle drivers based on EEG

Liu Xuanyi

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 134221R (2025) https://doi.org/10.1117/12.3051611
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

To study the influence of the traffic environment on the near-collision behaviors of drivers of dangerous goods road transportation vehicles (dangerous goods vehicles) at the mechanism level, based on electroencephalogram (EEG) and simulated driving data, this paper investigated how the traffic environment affects the near-collision behaviors of drivers of dangerous goods vehicles using a deep learning model. We found that specific EEG features, especially in the parietal and central brain regions, have a significant impact on the prediction of near-collision events. The model achieved a prediction accuracy of 77.2% in predicting near-collisions and can better accurately determine the driving state by capturing the dynamic information of the driver's EEG and the traffic environment. The research results can provide a theoretical basis for warning of near-collisions in the road transportation of dangerous goods vehicles.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Liu Xuanyi "Research on the mechanism of the impact of traffic environment on near-collision behavior of hazardous goods vehicle drivers based on EEG", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 134221R (20 January 2025); https://doi.org/10.1117/12.3051611

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