TY - JOUR
T1 - Model Predictive Longitudinal Control for Heavy-Duty Vehicle Platoon Using Lead Vehicle Pedal Information
AU - Wi, Hyoungjong
AU - Park, Honggi
AU - Hong, Daehie
N1 - Funding Information:
This research was supported by the Industrial Strategic technology development program (No. 10052965) funded by the Ministry of Trade, Industry and Energy (MOTIE), KOREA.
Publisher Copyright:
© 2020, KSAE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - The time delay in heavy-duty vehicle platoons due to actuators, sensors, and communication delays has significant effects on platoon performance; it is difficult to immediately ascertain the driver’s intention due to the time delay, so that there is a restriction on the intra-platoon spacing and the platoon’s performance is weakened. This study proposes a platooning control system that uses pedal information from the lead vehicle to overcome the time delay problem. Distributed Model Predictive Control (DMPC) is also used for the longitudinal control of the heavy-duty vehicle platoon to effectively address the time delay problem. The acceleration of the lead vehicle was estimated by its pedal information and a nonlinear vehicle dynamics model. The estimated acceleration was transmitted to the following vehicles and used as faster control input to the DMPC. The feasibility of the DMPC system for a heavy-duty vehicle platoon was verified by co-simulation on MATLAB-TruckSim using real pedal hardware. The performance of the control system was evaluated by comparing the results of using estimated acceleration with the TruckSim data. Furthermore, the improved platooning performance was confirmed by measuring the spacing error between successive vehicles, a tracking error index, and traffic flow.
AB - The time delay in heavy-duty vehicle platoons due to actuators, sensors, and communication delays has significant effects on platoon performance; it is difficult to immediately ascertain the driver’s intention due to the time delay, so that there is a restriction on the intra-platoon spacing and the platoon’s performance is weakened. This study proposes a platooning control system that uses pedal information from the lead vehicle to overcome the time delay problem. Distributed Model Predictive Control (DMPC) is also used for the longitudinal control of the heavy-duty vehicle platoon to effectively address the time delay problem. The acceleration of the lead vehicle was estimated by its pedal information and a nonlinear vehicle dynamics model. The estimated acceleration was transmitted to the following vehicles and used as faster control input to the DMPC. The feasibility of the DMPC system for a heavy-duty vehicle platoon was verified by co-simulation on MATLAB-TruckSim using real pedal hardware. The performance of the control system was evaluated by comparing the results of using estimated acceleration with the TruckSim data. Furthermore, the improved platooning performance was confirmed by measuring the spacing error between successive vehicles, a tracking error index, and traffic flow.
KW - Heavy-duty vehicle
KW - Intelligent vehicle and highway system (IVHS)
KW - Model predictive control (MPC)
KW - Pedal information
KW - Vehicle platoon
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U2 - 10.1007/s12239-020-0053-4
DO - 10.1007/s12239-020-0053-4
M3 - Article
AN - SCOPUS:85079755911
VL - 21
SP - 563
EP - 569
JO - International Journal of Automotive Technology
JF - International Journal of Automotive Technology
SN - 1229-9138
IS - 3
ER -