# Real-time Ecological Velocity Planning for Plug-in Hybrid Vehicles with Partial Communication to Traffic Lights

## TL;DR

This paper introduces a real-time, long-sighted ecological velocity planning method for plug-in hybrid vehicles that leverages partial traffic light communication and historical data to optimize energy efficiency.

## Contribution

It proposes a two-level receding-horizon control framework combining deterministic and historical traffic data for improved eco-driving in PHEVs.

## Key findings

- Hardware-in-the-loop simulations show significant energy savings.
- The method effectively handles limited communication with traffic lights.
- Long-sighted control improves over short-sighted schemes.

## Abstract

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.