The Optimization Research For Automation Heavy-duty Vehicle Platoon’s Fuel Consumption

Due to the rapid increase of motor vehicles,environmental pollution and energy crisis are becoming more and more serious.It is of great theoretical and applied value to study how to effectively reduce vehicle fuel consumption.Nowadays,the rapid development of Intelligent Transportation System(ITS)provides a theoretical basis for vehicle-road coordination and vehicle-vehicle coordination.The system can provide the required traffic information for vehicles,including the location,speed and acceleration of vehicles in the road.Based on the ITS,the looking-ahead optimization of optimal vehicle speed on sloping road,the optimal merging strategy of autonomous heavy-duty vehicle platoon and the optimization of vehicle on-ramp merging process are studied in this thesis.Firstly,the optimization of vehicle fuel consumption under gradient road conditions is studied.The fuel consumption can be effectively reduced by adjusting the vehicle’s motion state reasonably.Based on the ITS that vehicles can obtain the external road gradient information,the pigeon-inspired optimization arithmetic is incorporated into the receding horizon optimal control framework to achieve real-time optimization of vehicle speed.Through rolling optimization of vehicle reference speed,the optimal vehicle speed curve for a period of time in the future can be obtained.This method takes into account the anti-disturbance characteristics of receding horizon optimal control framework and the fast solving ability of intelligent optimization algorithm.The simulation results show that the proposed algorithm can effectively reduce the fuel consumption of vehicles on sloping roads.Secondly,the optimal decision-making problem in the process of autonomous vehicle platoon’s merging is studied.This paper presents a multi-vehicle merging algorithm based on three-vehicle merging,which first cluster and then merges layer by layer.Compared with platoon merging method based on the two-vehicle merging,the number of multi-vehicle merging strategies based on three-vehicle merging is larger and closer to the global optimum.Through simulation analysis,it is found that the proposed algorithm has greater oil-saving potential.Finally,the optimization of vehicles merging from ramp to main road is studied.Aiming at the problem that the on-ramp acceleration lane is easy to become a bottleneck area to restrict the capacity of the main road.Different guidance methods are given for different cases.In view of the situation that vehicles converge into the main road traffic flow,we first determine whether there is an ideal merging space.When there is an ideal space,the integrated optimization of fuel consumption and main road capacity can be guaranteed by optimizing its merging process.When the density of traffic flow is large and there is no ideal space,the optimal merging strategy is found by optimizing the moving state of the vehicles front and rear the target space.In view of the situation that ramp vehicles need to be imported into the main road platoons,it is necessary to traverse all mergineg space in platoon and optimize the movement state of vehicles front and rear the target space to find the optimal merging strategy.The results of numerical examples show that the guidance method proposed in this paper can effectively reduce fuel consumption in the process of ramp merging.Although it may cause some delays on the main road and ramp,the delay time is still within the acceptable range.