With the concept of cloud control system (CCS) for intelligent and connected vehicles proposed and developed, the vehicles and traffic safety and economy have a comprehensive improvement. However, the current research mostly stays in vehicle-to-vehicle or vehicle-to-infrastructure, which requires an on-board calculator with large computational and storage capacity, and the planning range is short. To solve these problems, a predictive adaptive cruise control (PACC) algorithm based on CCS is proposed. Hierarchical control architecture of PACC between vehicle and cloud is constructed, coordinating free cruising mode with car-following mode. For the free cruising mode, an ergodic optimization method placed in the cloud is designed. A multi-objective optimization algorithm based on model predictive control is designed for the car-following mode, which can plan the vehicle speed in advance. Finally, the simulation results show that the PACC algorithm can achieve 8.16% fuel saving with consuming less time for free cruising, and for car-following, it can achieve 3.23% fuel saving. More importantly, the results also show that the CCS has significant potential and feasibility for intelligent and connected vehicles application.
Predictive Adaptive Cruise Control for Heavy-duty Vehicle based on Cloud Control System
08.10.2022
679388 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Adaptive Cruise Control for Heavy Duty Vehicles
British Library Conference Proceedings | 1995
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