Research On Collaborative Optimization Model Of Heavy Truck Speed And Signal Timing Based On Fuel Consumption

With the increasing demand for logistics,trucks,as the main body of road transportation,are developing towards large-scale and heavy-duty.While promoting economic development and international trade,heavy trucks have gradually become the main vehicle for energy consumption and pollution emissions.In the intersection area of national and provincial highways,due to the influence of traffic lights,heavy trucks are prone to rapid deceleration or red light running,resulting in road ruts and traffic accidents.At the same time,compared with cars,heavy trucks are heavier,have more gears and slow acceleration.When they stop and restart,they often cause more fuel consumption and pollution emissions,and seriously affect the traffic efficiency of intersections.Aiming at the problem of high fuel consumption caused by frequent stops and starts of heavy trucks affected by signal lights,this study takes heavy trucks and traffic lights as control objects based on vehicle-road coordination technology,and establishes a coordinated optimization model of heavy truck speed and signal timing.The main contents of this paper are as follows:(1)The fuel consumption model and truck shift strategy were studied.Based on the analysis of the vehicle infrastructure cooperative system,the control system framework was established based on the functional requirements of the heavy truck cooperative optimization model.The vehicle fuel consumption model was sorted out,and the appropriate model was selected as the evaluation index for the speed trajectory optimization of heavy trucks.The shift strategy of heavy truck was selected,and the determination method of relevant shift parameters was given.(2)The speed guidance control model of one-way heavy truck was established.The guidance zone was divided into acceleration zone,uniform speed zone and deceleration zone.Considering the shift operation of truck,the speed guidance method of heavy truck was proposed.Based on the VT-CPFM model,the travel fuel consumption objective function was constructed,and the traffic wave theory was used to predict the real-time queuing dissipation process at the downstream intersection.By analyzing the trajectory of the truck,the speed guidance control model of the heavy truck was established.The results show that the model can not only reduce the average travel fuel consumption of trucks by 8.2 %,but also reduce the parking times and parking time of heavy trucks at downstream intersections.(3)A collaborative optimization model of one-way heavy truck speed and signal timing was established.Based on the speed guidance method of heavy trucks,a coordinated guidance method for heavy trucks was proposed by adjusting the signal timing through the green light extension and the red light early break strategy.The queuing dissipation time and truck parking time after signal timing adjustment were predicted,and the space-time trajectory of heavy trucks under the collaborative guidance method was constrained.A collaborative optimization model of heavy truck speed and signal timing with the goal of minimum fuel consumption was established.The test results show that compared with the speed guidance model,the collaborative optimization model can further reduce the travel fuel consumption,parking times and parking time of heavy trucks.(4)A collaborative optimization model of vehicle speed and signal timing for bidirectional heavy trucks was established.Based on the cooperative guidance method of heavy trucks,a bidirectional cooperative guidance method for heavy trucks was proposed based on the double-loop phase.This method comprehensively considers the straight trucks in the relative direction,and can better adapt to the randomly arriving heavy trucks by changing the phase order and duration.Based on the collaborative guidance method of two-way heavy trucks,a 0-1 nonlinear programming model was established and verified by setting different truck arrival parameters,straight traffic flow and intersection spacing.The results show that the bi-directional heavy truck collaborative optimization model reduces the travel fuel consumption of trucks at upstream and downstream intersections by 10.3 % and 14.0 %.By optimizing the speed of heavy trucks and the signal timing of intersections,this study can effectively reduce the fuel consumption and parking times of trucks,which is conducive to achieving the goal of energy conservation and emission reduction,and provides a theoretical basis for energy-saving driving and auxiliary driving of heavy trucks.