Energy Consumption Optimization Of Heavy Duty Vehicles Based On Traffic Cyber Physical System

Transportation costs and greenhouse gas emissions are important indicators of intelligent transportation systems.Effective transport scheduling can reduce transportation cost and environmental damage.We investigate a coordination scheduling and merging strategy for large-scale vehicles based on transportation cyber physical systems(TCPS)to minimize transportation costs and carbon emissions.Firstly,aiming at the optimization problem of a single heavy-duty vehicle energy consumption,we proposed a vehicle routing scheme based on green path.Using the highway speed-flow practical relationship model and traffic flow forecast to obtain vehicle energy consumption.Analyzed the energy consumption of vehicles passing through congested sections.According to the shockwave of the vehicle reaching the congested road section,we propose a congestion avoidance strategy.According to the energy consumption difference between the congestion avoidance strategy and initial transportation scheme,we can get the optimal path and speed of the vehicle.The vehicle scheduling is completed.N-shortest green paths are find to provide alternative routes for large-scale vehicle merging scheduling.Simulation results show that this scheme can effectively reduce energy consumption.Secondly,with the question of how to coordinate different trucks scattered on road to form a platoon,we propose an optimal merging strategy of heavy-duty vehicles based on velocity and fuel consumption.Based on the research of two heavy-duty vehicles,we can obtain the merging condition,the optimal acceleration,the optimal merging speed and the location of the merging point.Then the results are generalized and forming the general decision-making algorithm and the merging system controller design method.Numerical simulation and experiments have shown that the method presented can greatly reduce the overall fuel consumption of vehicle fleets in fact.Finally,combined with the advantages of small spacing platooning and the feasibility of vehicle scheduling,we proposes a vehicle coordinated scheduling and merging strategy for large-scale vehicles.A local scheduling strategy is used in combination with the leader vehicle selection algorithm and cluster analysis to construct the vehicle merging set.Through the nonlinear programming method,the improvement and optimization of vehicle path and speed in each platooning set are realized.The expandability of the scheduling strategy is proved by the simple processing of emergency situations.Numerical simulation has shown that the method presented in this paper to schedule vehicle can greatly reduce the overall fuel consumption of vehicle fleets in fact compared to the fixed path merging strategy.