Simulation And Optimization Of Vehicle Energy Consumption And Emission At Urban Road Signalized Intersection

Signal intersection,the basic component of urban traffic network,is the main node of congestion and delay in the road network.Vehicles will repeatedly divert,merge,and park for a long time when driving in the urban traffic system because of numerous signalized intersections.Complex traffic conditions can substantially increase the energy consumption and exhaust emissions of vehicles when passing through intersections.With the rapid growth of motor vehicle ownership and increasing average mileage of vehicles,the problem of traffic energy consumption and exhaust pollution becomes increasingly serious.Therefore,micro-quantitative research on energy consumption and exhaust emissions of vehicles passing through signalized intersections will be necessary to alleviate traffic energy consumption and exhaust pollution.Considering the complexity of drivers'driving behavior at signalized intersections,this study takes undersaturated signalized intersections as the research object,analyzes the trajectory of vehicles passing through intersections by the car-following model,and combines the instantaneous energy consumption and emission models of fuel vehicles and electric vehicles.The energy consumption and emission of vehicles passing through signalized intersections are simulated,and the energy consumption and emission of vehicles at signalized intersections are analyzed in terms of signal cycle,green signal ratio,and vehicle arrival rate.The incremental energy consumption and emission model of vehicles at signalized intersection approach are presented from the perspective of inductive reasoning and regression statistics.Furthermore,the timing optimization of signalized intersection and line control system is conducted under different traffic conditions that consider different road section speeds and mixed proportion of electric vehicles to minimize vehicle CO₂ emission.With the development of intelligent transportation systems and autopilot technology,this study further analyzes the effect of multi-preceding vehicle information feedback on vehicle energy consumption and emissions at the intersection under the connected cruise control environment.In this study,the specific works conducted were as follows:?1?The trajectory of vehicles passing through intersections is analyzed by the full velocity difference?FVD?car-following model.The simulation results show that several vehicles cannot passing through the intersection smoothly and must stop completely or incompletely under the influence of the signal light.The combination of FVD car-following model and the vehicle specific power fuel consumption and emission model was used to estimate vehicle fuel consumption and CO₂,CO,HC,and NO_X emissions at signalized intersections.The change of vehicle trajectory causes increased vehicle fuel consumption and CO₂,CO,HC,and NO_X emissions.Considering that the vehicle trajectory at signalized intersections varies along with the signal cycle,green signal ratio,and vehicle arrival rate,the influence of these factors on vehicle fuel consumption and CO₂,CO,HC,and NO_X emissions in the single approach and the entire intersection is further analyzed.?2?Considering the difference of energy consumption and emission characteristics between electric vehicles and fuel vehicles,the energy consumption and CO₂,CH₄,NO₂,and SO₂ emission characteristics of electric vehicles at intersections are simulated and analyzed by the combination of the FVD car-following model;energy consumption model of electric vehicles;and the CO₂,CH₄,NO₂,and SO₂ emission factors of power grid.Compared with fuel vehicles,electric vehicles can achieve energy recovery in braking phase and do not need to maintain engine operation in idling phase.Thus,the energy consumption rate only depends on the power of vehicle auxiliary components.These two factors make the energy consumption and emission characteristics of electric vehicles at intersections different from those of fuel vehicles.The influence of signal cycle,green signal ratio,and vehicle arrival rate on electric vehicles'energy consumption in the single approach and the entire intersection is analyzed.?3?Based on the foregoing simulation analysis,from the angle of stop rate and stopped delay at the intersection approach,the estimation model of incremental energy consumption and emission of vehicles in single approach is concluded.The numerical simulation method is used to validate the estimation model and illustrate its accuracy.The results show that the calculated values of the estimation model agree with the simulation results under different traffic conditions.The changes of incremental energy consumption and emission of vehicles are correlated with stop rate and stopped delay.The regression analysis of different polynomial combinations of stop rate and control delay is conducted by SPSS statistical software,and the regression statistical model of incremental energy consumption and emission of vehicles in the single approach is established.?4?On the basis of the previous research results and vehicle incremental energy consumption and emission statistical model,the optimization models of signal timing of intersection and the phase difference of line control system are established to minimize vehicle CO₂ emissions.On the premise of considering the road section speed and the mixed proportion of electric vehicles,analysis on the example shows that it is necessary to optimize the timing parameters of signalized intersection and line control system from the angle of minimizing vehicle CO₂ emission.In essence,it is a comprehensive consideration of vehicle control delay and stop rate.Furthermore,the multi-objective timing optimization of signalized intersection and line control system is analyzed with the combined objectives of vehicle CO₂incremental emission and control delay,vehicle CO₂ incremental emission and stop rate,and control delay and stop rate.The spatial range of Pareto solution obtained by different combined objectives under different traffic conditions is taken as evaluation criterion,the analysis results shows that it is reasonable to select vehicle CO₂ incremental emission as the optimization objective.?5?The influence of multi-preceding vehicle information feedback on vehicle trajectory at intersections in the internet of vehicles environment is analyzed using a car-following model of cruise control vehicle based on multi-preceding vehicle information feedback.The car-following model of multi-preceding vehicle information feedback is combined with the vehicle instantaneous energy consumption and emission model,the vehicle energy consumption and emission of the cruise control vehicle based on multi-preceding vehicle information feedback at signalized intersection are simulated and analyzed.The trajectory,energy consumption,and emission of the cruise control vehicle are compared with those of the traditional manual driving vehicle.The comparison results show that the cruise control based on multi-preceding vehicle information feedback in internet of vehicles environment can reduce the change range of vehicle speed that needs to incomplete stop and the number of vehicles that needs to change the trajectory at the intersection approach,which is beneficial for the reduction of energy consumption and emission of vehicles at the signalized intersection.Under different traffic conditions of signal cycle,green signal ratio,and vehicle arrival rate,the influence of cruise control vehicle based on multi-preceding vehicle information feedback on vehicle energy consumption and emission in the single approach and entire intersection is analyzed.In this study,the energy consumption and emissions of fuel vehicles and electric vehicles at signalized intersections are analyzed in depth.The car-following model is used to reconstruct the trajectory of vehicles passing through signalized intersections and is combined with the vehicle instantaneous energy consumption and emission model to estimate the energy consumption and emissions when vehicles passing through signalized intersections.The effects of signal cycle,green signal ratio,and vehicle arrival rate on vehicle energy consumption and emission are analyzed on the basis of the proposed simulation method,and the incremental energy consumption and emission models of vehicles at signalized intersections are established from the perspective of inductive reasoning and regression statistics.The timing optimization model of different signal control systems is given from the point of view of reduce vehicle CO₂ emission.Through in-depth analysis of different car-following models,the widely used FVD car-following model is selected to simulate the vehicle trajectory passing through intersections,which lays the foundation for subsequent numerical analysis and model verification.The model is combined with the instantaneous energy consumption and emission models of fuel vehicles and electric vehicles,the energy consumption and emissions of vehicles in the single approach and the entire intersection are simulated,and the influencing factors on vehicle energy consumption and emissions are analyzed from different angles.The incremental energy consumption and emission models of vehicles at signalized intersections are analyzed and established,and the optimization model of timing parameters considering vehicle CO₂ emission is studied for signalized intersections and line control systems.Analysis of the example shows that it is necessary and reasonable to optimization the timing parameters of signalized control systems from the perspective of vehicle CO₂ emission.The influencing factors and optimal control are analyzed from different perspectives through in-depth study on vehicle energy consumption and emission at signalized intersections.The conclusion can help alleviate the problems of traffic energy consumption and environmental pollution and provide some theoretical reference for the scientific management of signalized intersections.