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Energy-Efficient Cooperative Adaptive Cruise Control with Receding Horizon of Traffic, Route Topology, and Traffic Light Information

SAE International Journal of Connected and Automated Vehicles

AVL List GmbH, Austria-Alejandro Ferreira Parrilla, Stephen John Jones
Chalmers University of Technology, Sweden-Anders Grauers
  • Journal Article
  • 12-02-02-0006
Published 2019-05-16 by SAE International in United States
Advanced and cooperative vehicle (semi-) autonomous driving systems will become a necessity in the future for sustainable, convenient, and safe mobility. By utilizing Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, a vehicle’s energy consumption can be reduced while maintaining safety and driving comfort. A holistic control strategy is presented, which in a novel way incorporates traffic lights, road speed limits, gradients, and curvature, as well as surrounding traffic and detailed powertrain characteristics into a single Model Predictive Control formulation. The performance of the system is evaluated using a realistic co-simulation toolchain representing the vehicle, driver, and road, including complex traffic conditions. The approach is valid for a wide range of scenarios, ranging from urban city driving to highways. Simulation results for a D-class passenger car with a diesel engine and an automatic transmission in an urban route show energy savings between 5% and 30% with an unchanged travel time, compared to a simulated human driver.