Real-time Ecological Velocity Planning for Plug-in Hybrid Vehicles with Partial Communication to Traffic Lights
It addresses the practical limitation of limited communication range with traffic lights for energy-efficient driving in plug-in hybrid vehicles.
This paper proposes a two-level receding-horizon ecological adaptive cruise controller for plug-in hybrid vehicles that uses deterministic traffic light timing for the upcoming light and historical data for others, achieving energy savings validated by hardware-in-the-loop simulations.
This paper presents the design of an ecological adaptive cruise controller (ECO-ACC) for a plug-in hybrid vehicle (PHEV) which exploits automated driving and connectivity. Most existing papers for ECO-ACC focus on a short-sighted control scheme. A two-level control framework for long-sighted ECO-ACC was only recently introduced. However, that work is based on a deterministic traffic signal phase and timing (SPaT) over the entire route. In practice, connectivity with traffic lights may be limited by communication range, e.g. just one upcoming traffic light. We propose a two-level receding-horizon control framework for long-sighted ECO-ACC that exploits deterministic SPaT for the upcoming traffic light, and utilizes historical SPaT for other traffic lights within a receding control horizon. We also incorporate a powertrain control mechanism to enhance PHEV energy prediction accuracy. Hardware-in-the-loop simulation results validate the energy savings of the receding-horizon control framework in various traffic scenarios.