Model Predictive Longitudinal Control for Heavy-Duty Vehicle Platoon Using Lead Vehicle Pedal Information

Hyoungjong Wi, Honggi Park, Daehie Hong

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)563-569
Number of pages7
JournalInternational Journal of Automotive Technology
Volume21
Issue number3
DOIs
Publication statusPublished - 2020 Jun 1

Keywords

  • Heavy-duty vehicle
  • Intelligent vehicle and highway system (IVHS)
  • Model predictive control (MPC)
  • Pedal information
  • Vehicle platoon

ASJC Scopus subject areas

  • Automotive Engineering

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