Cooperative ecological cruising using hierarchical control strategy with optimal sustainable performance for connected automated vehicles on varying road conditions

Abstract Facing the increasingly severe energy and environmental problems, platooning of multiple vehicles has great potential for sustainability of intelligent transportation systems. This study develops a novel hierarchical ECACC strategy with energy-saving achievements by conducting the ecological velocity trajectory planning of the leading vehicle based on dynamic programming and car-following driving of the rest of the vehicles in the platoon based on combined feedforward-feedback control. The main purpose is to reduce the energy consumption of multiple vehicles in intelligent transportation systems with consideration of trip time and car-following performance. The optimal velocity planning uses an innovative integrated longitudinal and lateral vehicle dynamics approach where both the lateral stability and energy efficiency in continuous curved roads are guaranteed at the same time. The results show that the proposed ECACC in energy-optimal mode can reduce energy consumption by up to 38.1% compared to conventional energy-optimal fixed speed cruising. Moreover, the connected automated vehicle platoon presents better car-following performance with string stability as opposed to the Cooperative Adaptive Cruise Control based on feedback control and model predictive control. The results indicate the great potential of the proposed ECACC strategy to further improve the sustainability of intelligent transportation systems.

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