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Volume 7 Issue 4
Jun.  2020

IEEE/CAA Journal of Automatica Sinica

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Jing Huang, Yimin Chen, Xiaoyan Peng, Lin Hu and Dongpu Cao, "Study on the Driving Style Adaptive Vehicle Longitudinal Control Strategy," IEEE/CAA J. Autom. Sinica, vol. 7, no. 4, pp. 1107-1115, July 2020. doi: 10.1109/JAS.2020.1003261
Citation: Jing Huang, Yimin Chen, Xiaoyan Peng, Lin Hu and Dongpu Cao, "Study on the Driving Style Adaptive Vehicle Longitudinal Control Strategy," IEEE/CAA J. Autom. Sinica, vol. 7, no. 4, pp. 1107-1115, July 2020. doi: 10.1109/JAS.2020.1003261

Study on the Driving Style Adaptive Vehicle Longitudinal Control Strategy

doi: 10.1109/JAS.2020.1003261
Funds:  This work was supported by the National Natural Science Foundation of China (51775178, 51875049), and Hunan Province Natural Science Outstanding Youth Fund (2019JJ20017)
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  • This paper presents a fusion control strategy of adaptive cruise control (ACC) and collision avoidance (CA), which takes into account a driver’s behavioral style. First, a questionnaire survey was performed to identify driver type, and the corresponding driving behavioral data were collected via driving simulator experiments, which served as the template data for the online identification of driver type. Then, the driver-adaptive ACC/CA fusion control strategy was designed, and its effect was verified by virtual experiments. The results indicate that the proposed control strategy could achieve the fusion control of ACC and CA successfully and improve driver adaptability and comfort.

     

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    Highlights

    • A driver-adaptive fusion control strategy of Adaptive Cruise Control and Collision Avoidance was proposed.
    • Different styles of divers’ driving behavioural data were collected via driving simulator experiments, corresponding driving behaviour characteristics were extracted and used in the driver-adaptive control.
    • Real-time recognition of driving style was achieved based on fuzzy reasoning rule.
    • The effect of the fusion control strategy was validated by virtual experiments.

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