Transportation Research Part D: Transport and Environment, Volume 92, March 2021,
Vehicle driving patterns greatly impact the sustainability of the transportation system. Based on V2X communication, the ecological cooperative adaptive cruise control (Eco-CACC) is proposed combing the advantages of eco-driving and car-following to minimize the energy consumption of the connected automated vehicles platoon. Herein, the vehicle platoon behavior in the scenario of driving through a signalized intersection exhibits great benefits for sustainability which is even improved along corridors with more traffic lights. In the velocity trajectory planning process, a modified dynamic programming algorithm is formulated with the switching logic gate of two types of optimal control problems to increase the computational speed. By testing in the real-world scenario, the results of the proposed Eco-CACC demonstrate excellent energy performance which improves 8.02% compared to manual driving with the constant acceleration policy. Moreover, energy can be further improved by 2.02% and 1.55% when the car-following strategy is selected with MPC and IDM algorithm.
Adaptive Cruise Control; Algorithm; Computation Theory; Computational Speed; Constant Acceleration; Cooperative Adaptive Cruise Control; Cooperative Communication; Dynamic Programming; Dynamic Programming Algorithm; Eco-driving; Ecosystem Service; Energy; Energy Use; Energy Utilization; Intelligent Transportation System; Optimal Control Problem; Optimal Control Systems; Planning Process; Signal Processing; Signalized Intersection; Speed Control; Strategic Approach; Street Traffic Control; Sustainability; Sustainable Development; Traffic Signals; Traffic Signs; Transportation Policy; Transportation System; Travel Behavior; Vehicle Platoon; Vehicles; Velocity Trajectories; Global