Volume 24 Issue 6
Dec.  2024
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2024  >  24(6): 243-258
YANG Wei, SUN Xue, SI Yu, HAN Yi, CAI Yao. Homogeneous platoon speed planning and following control in front vehicle cut-in and cut-out conditions[J]. Journal of Traffic and Transportation Engineering, 2024, 24(6): 243-258. doi: 10.19818/j.cnki.1671-1637.2024.06.017
Citation: YANG Wei, SUN Xue, SI Yu, HAN Yi, CAI Yao. Homogeneous platoon speed planning and following control in front vehicle cut-in and cut-out conditions[J]. Journal of Traffic and Transportation Engineering, 2024, 24(6): 243-258. doi: 10.19818/j.cnki.1671-1637.2024.06.017
shu

Homogeneous platoon speed planning and following control in front vehicle cut-in and cut-out conditions

doi: 10.19818/j.cnki.1671-1637.2024.06.017
  • 1.

    School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China

  • 2.

    Automotive Engineering Research Institute, Guangzhou Automobile Group Co., Ltd., Guangzhou 511434, Guangdong, China

  • 3.

    Uisee Technology (Beijing) Co., Ltd., Beijing 102400, China

Funds:

National Key Research and Development Program of China 2021YFE0203600

Natural Science Foundation of Shaanxi Province 2017JQ6045

More Information
  • Author Bio:

    YANG Wei(1985-), male, assistant professor, PhD, yw@chd.edu.cn

  • Received Date: 2024-05-30
  • Publish Date: 2024-12-25
    Abstract
  • To solve the problems that the front vehicle cut-in and cut-out may lead to a collision risk, as well as the low efficiency and poor stability of following control during constant speed cruise of the homogeneous platoon, a homogeneous platoon speed planning and following control model in front vehicle cut-in and cut-out conditions was proposed. Based on the convolutional neural network-gated recurrent unit (CNN-GRU) hybrid network, a trajectory prediction model was established to predict the lane change trajectory of front vehicle within a future time domain. By constructing the relationship between longitudinal displacement and time, the front vehicle cut-in or cut-out state was determined. The speed following model of following vehicles was built, and the overall speed planning of the platoon was carried out. A fuzzy linear upper controller was established to output the desired acceleration according to the speed difference meeting the driving scenario requirements. Combining the longitudinal inverse dynamics model and fuzzy proportional integral derivative (PID) control, a lower controller was established to convert the desired acceleration into the driving torque or braking pressure. Thus, the direct control of the vehicle was achieved. To further verify the effectiveness of the proposed control model, a PreScan/CarSIM/SIMULINK co-simulation platform was built, simulation conditions for the adjacent front vehicle cut-in and cut-out were designed, and the proposed control model was compared with the adaptive cruise control (ACC) scheme. Research results show that after applying the proposed control model, no rear-end coallision occurs in platoons for all information flow topologies, and the maximum spacing difference, global average speed tracking error and local average speed tracking error reduce at least 55.9%, 40.6% and 42.0%, respectively. Therefore, the proposed control model can not only avoid potential rear-end collisions in front vehicle cut-in and cut-out conditions, but also can effectively shorten the maximum gap between platoon vehicles, reduce the speed tracking error of the platoon, and help to improve the following efficiency and driving stability of the platoon.

     

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