Traffic light assistant system for optimized energy consumption in an electric vehicle
Paper in proceedings, 2014

Increasingly intelligent vehicle driving systems are rapidly being developed, and will in the future become a necessity for sustainable, convenient and safe mobility in our ever more urbanized world. This paper presents an innovative approach for the control of a fully electric vehicle approaching a road segment with Multiple Traffic Lights (TL). By utilizing Vehicle to Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, the energy consumption for the maneuver completion can be reduced. The problem is approached from a Model Predictive Control (MPC) framework. The performance of the system is evaluated using a complex simulation toolchain representing the vehicle, powertrain, driver, and road including the traffic conditions. The results have shown an overall energy consumption reduction of 29 % for an idealized case and 17 % for a real road simulated scenario as compared to ‘normal’ human driver behavior.

Model Predictive Control (MPC)

Advanced Driver Assistance Systems (ADAS)

Simulation

Energy Consumption

Electric Vehicle

Vehicle-to-Infrastructure (V2I)

Traffic Lights

Author

Emre Kural

AVL

Stephen Jones

AVL

Alejandro Ferreira Parrilla

Chalmers, Signals and Systems

Anders Grauers

Chalmers, Signals and Systems, Systems and control, Automation

2014 International Conference on Connected Vehicles and Expo (ICCVE)

604-611

Areas of Advance

Transport

Energy

Subject Categories

Control Engineering

DOI

10.1109/ICCVE.2014.7297619

ISBN

978-1-4799-6729-2

More information

Latest update

3/6/2018 1