Research On Cooperative Green Driving Strategy For Stop-and-Go Traffic Based On Inter-vehicle Communication

Stop-and-go traffic is a phenomenon of traffic flow periodic fluctuations which occurs when road transport network is affected by some factors such as road bottleneck,car accidents,weather changing,special events,government regulations and driving habits.When a vehicle is traveling in stop-and-go traffic,it goes through some processes of frequent accelerations and decelerations which causes air emissions and fuel consumption increasing.By studying and utilizing green driving strategy which offers appropriate advisory speed to the driver,vehicle could run at relatively stable speed in stop-and-go traffic,thereby decreasing the air emissions and fuel consumption of the vehicle.On the basis of car-following models and emission models,this thesis made a study of green driving strategy for smoothing vehicle speed fluctuations in stop-and-go traffic.The main research contents are as follows:Classified and analyzed commonly used car-following models and emission models.For solving problems in this thesis,collision a voidance models and microscopic emission models were chosen to describe car-following behavior and calculate air emissions and fuel consumption.An advisory speed algorithm based on inter-vehicle communication for cooperatively smoothing traffic fluctuatio ns was proposed.First,by analyzing Newell’s car-following model,a description method for describing characteristics of vehicle’s behavior in stop-and-go traffic was established,and derived the formula of safe speed limit and the judgment formula of car ’s following condition.Then,pick up the oscillation period of the leading vehicle’s speed by using fast Fourier transform to calculate the average speed in one oscillation cycle of the leading vehicle.Finally,through the steps of dynamic following,exp onential smoothing,vehicles cooperation etc.,an appropriate advisory speed is provided to driver as a guidance to make the vehicle travels more smoothly.The results of simulation based on real-world traffic data show that this algorithm can effectively smooth the influences on vehicle’s speed which caused by traffic fluctuations,and significantly reduce vehicle’s air emissions and fuel consumption.By analyzing vehicle’s braking process under car-following circumstance,braking deceleration was introduced as a key parameter into the improvement of the algorithm to address the potential safety issue that the algorithm may provide illogical braking suggestion to driver on occasion.This improved algorithm has better safety performance and lower requirement for braking deceleration with better smoothing effect.