Research on vehicle lane change prediction considering driver’s behavior

Lijiale Su; Jiangtian Li

doi:10.1117/12.3011481

1 December 2023 Research on vehicle lane change prediction considering driver’s behavior

Lijiale Su, Jiangtian Li

Proceedings Volume 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023); 129400O (2023) https://doi.org/10.1117/12.3011481
Event: Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 2023, Sipsongpanna, China

Abstract

Accurate prediction of vehicle lane-change behaviour is beneficial for traffic efficiency and safety. This paper incorporates driver behavioural information indicators into the prediction of lane change behaviour. A driving simulator was used to collect driver behavioural characteristics and vehicle operating parameters during lane keeping and lane changing, and through theoretical analysis and data testing, seven indicators were obtained that could be used to predict lane changing behaviour: target area gaze time, head level turning angle, vehicle speed, lane drift angle, distance to the vehicle in front, and time to collision. Using the experimentally collected variable data, a logistic prediction model was developed and validated to have satisfactory prediction accuracy.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lijiale Su and Jiangtian Li "Research on vehicle lane change prediction considering driver’s behavior", Proc. SPIE 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 129400O (1 December 2023); https://doi.org/10.1117/12.3011481

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KEYWORDS

Data modeling

Head

Eye tracking

Roads

Education and training

Visualization

Eye

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