TD3 Tuned PID Controller for Autonomous Vehicle
Platooning 2023-01-7108
The main objective of platoon control is coordinated motion of autonomous vehicle
platooning with small intervehicle spacing while maintaining the same speed and
acceleration as the leading vehicle, which can save energy consumption and
improve traffic throughput. The conventional platoon control methods are
confronted with the problem of manual parameter tuning. In order to addres this
isue, a novel bifold platoon control approach leveraging a deep reinforcement
learning-based model is proposed, which enables the platoon adapt to the complex
traffic environment, and guarantees the safety of platoon. The upper layer
controller based on the TD3 tuned PID algorithm outputs the desired
acceleration. This integration mitigates the inconvenience of frequent manual
parameter tuning asociated with the conventional PID algorithm. The lower layer
controller tracks the desired acceleration based on the inverse vehicle dynamics
model and feedback control. Through this dynamic inverse model, the desired
acceleration of the platoon vehicle is transformed into a feedforward control
input. This input is then supplemented by feedback from a PID controller. A
comprehensive validation of the proposed approach is conducted through a
collaborative simulation experiment using Carmaker/Simulink. The results show
the trajectory of the desired acceleration is smooth, indicating a ride comfort
of vehicle. Moreover, the platoon vehicle is able to make a quick response to
the speed change of the predecesor. The maximum error in the distance between
vehicles in the platoon is 2.5m. In summary, the proposed control method of
connected and automated vehicle platoon based on TD3 tuned PID effectively
realizes cooperative control of platoon vehicles.
Affiliated:
China Merchants Testing Vehicle Technology Research Institut, Wuhan University of Technology, Wuhan University of Technology, Intelligent Transportation S, Wuhan University of Technology, School of Mechanical and Ele, University of Waterloo Faculty of Engineering
Pages: 8
Event:
SAE 2023 Intelligent Urban Air Mobility Symposium
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Autonomous vehicles
Vehicle ride
Vehicle dynamics
Platooning
Automated vehicles
Energy consumption
Vehicle acceleration
Comfort
Control systems
Mathematical models
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