Study On Guidance Strategy Of Energy Conservation And Emission Reduction At Intersection Under Electric Vehicle Mixed Traffic Flow

The signalized intersection is an important part of the urban road system.Vehicles passing through intersections often need to stop and wait because of the signal lights.Each stop and idle will not only increase travel time,but also greatly increase the vehicle’s emissions and energy consumption in the road network.Under the impetus of the new revolution of technology and the industrial transformation,Intelligent Network United Automobile has become an important strategic direction of the automobile industry.Using the real-time location information of motor vehicles and the signal phase information of intersections,the speed guidance strategy based on the cooperative vehicle-infrastructure system will provide drivers with reasonable speed suggestions,so that vehicles can pass through intersections more smoothly,thus improving the efficiency of intersections,which is also an effective way to reduce vehicles energy consumption and emissions.With the vigorous support of the state for new energy automobile,the electric vehicle(EV)is becoming more and more popular,and its market penetration is increasing.The mixed flow of EV and traditional internal combustion engine vehicle(ICEV)in the road network has become normal,which increases the complexity of traffic flow in the road network.However,in terms of energy system and powertrain system,there are great differences between EV and ICEV.The guidance strategy proposed only considering ICEV or EV can not achieve the desired results in practical applications.Considering the difference between two types of vehicles and the queuing dissipation at signalized intersections,this study further optimized the proposed guidance strategy,aiming at reducing emissions of ICEV and energy consumption of EV,we proposed an Eco-speed guidance strategy.The micro-traffic simulation software VISSIM and its secondary development we used to establish a simulation environment to realize real-time dynamic guidance of the vehicle.Different emission and energy estimation models were used to quantify the experimental results for these two types of vehicles.The results showed that the optimized model can achieve better emission reduction effect,although in the case of high volume situations.When the market share of EV is higher than 50%,this strategy can play a better role in reducing emissions.At the same time,it is reasonable to set the speed guidance time interval to 5seconds.As the receiver and implementer of the speed guiding strategy,the driver’s decision is limited by bounded rationality.In this paper,response time,acceptance threshold and execution degree were selected to quantify the influence of driver’s bounded rationality on the strategy execution.Box-Behnken test was used to verify the effects of these three factors on the emissions of ICEV and energy consumption of EV.The results were fitted by binomial equation,and the response surface equation was established to predict the optimal test conditions.The results showed that response time,execution degree and acceptance threshold have different effects on different emissions and energy consumption under different flow rates,but overall,excessive driver’s limited rationality would weaken the energy saving and emission reduction effect of speed guidance strategy.