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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

Chalmers University of Technology, Sweden AVL List GmbH, Austria-Niklas Wikström
AVL List GmbH, Austria-Alejandro Ferreira Parrilla, Stephen John Jones
  • 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.