Vehicle Collision Avoidance Algorithm And Traffic Flow Following Model Research Based On Vehicle Netwirking

With the rapid development of social economy and the improvement of people's living standard,the number of motor vehicles is increasing year by year,but the following traffic problems are becoming more and more prominent,the incidence of traffic accidents is also perennial.In this context,intelligent transportation as an effective solution to traffic problems has been increasingly valued.As the two essential research directions of intelligent transportation,vehicle collision avoidance and traffic flow modeling are also popular research fields in traffic engineering.The Internet of vehicles can make information transmitting between vehicles and vehicles,vehicles and devices,therefore,under the environment of vehicle networking,studying vehicle collision avoidance and traffic flow modeling,has far-reaching significance for slowing down traffic jams and reducing property losses caused by traffic accidents.This paper mainly studies vehicle longitudinal cooperative collision avoidance algorithm and traffic flow following modeling under the environment of vehicle interconnection.First,this paper optimize the traditional longitudinal collision avoidance algorithm,using the theory of longitudinal collision avoidance,adding car communication factors to traditional collision avoidance algorithm,on the premise that vehicles can communicate with each other,research on vehicle longitudinal cooperative collision avoidance.The collision avoidance acceleration is allocated through the front and rear vehicles to reduce vehicle collision avoidance acceleration,and it improves vehicle collision avoidance safety.Secondly,this paper think few researchers can consider driver's visual angle factors,so adding this factors into FVD model.What's more,this paper uses vehicle shape parameter to quantify the driver's perspective,and study the influence of vehicle shape parameters on traffic flow stability.Finally,this paper studies the traffic flow following model based on cellular automata.Aiming at the shortcoming of the traditional NaSch model,this paper adds the factor of driver random deceleration probability into NaSch model,and it makes the model has the higher vehicle flow and a safer driving environment.After constructing the corresponding algorithm model,this paper use simulation software to confirm every model's stability,clear conditions for stability,and compared with traditional algorithms and models,In this paper,the stability of each model is simulated and verified by simulation software,verifying the superiority of the algorithm and models studied by this paper and considering where it can be improved.