Trajectory Planning Based On Road Hazard Assessment In Vehicle Networking Environment

With the growing development of the transportation industry,while bringing convenience for people to travel,it also leads to a variety of road traffic safety and congestion problems.However,the emergence and development of intelligent transportation has effectively helped people alleviate these problems.Among them,the intelligent vehicle plays an important role in helping to solve the problems of road traffic safety and congestion,and has long been the focus of researchers in a wide range of fields.This paper studies the trajectory planning and control of vehicles in the road based on the network of vehicles,in order to achieve the purpose of assistant/automatic driving.However,it takes a lot of material and cost to conduct experimental research in real scenarios.Therefore,this paper considers building a complete vehicle network simulation framework under the computer simulation platform,and studies the planning and control of road trajectory from the perspective of the combination of communication and computer knowledge.In this paper,road information will be acquired by means of communication commonly used in vehicle networking,combined with the short-term prediction results of road regional hazard distribution trend,the improved trajectory planning algorithm will be applied to assist autonomous vehicles to pass through the road area efficiently and safely.The research results of this paper are closely related to the field of assistant/automatic driving technology,and also have good research significance and practical value.The specific research details are as follows:Firstly,the various kinds of driving motion models existing in the current traffic situation are briefly described,and a mesoscopic driving motion model based on the influence of workshop relationship is proposed by mining the characteristics of the driving behavior of the experimental simulation vehicles in this paper.Secondly,the hazard assessment method based on Ising model is introduced,and the road area is meshed to obtain the hazard distribution information of the road area.In addition,a simple short-term prediction of the hazard distribution trend is also carried out.Then,aiming at the shortcomings of the traditional Rapidly-exploring Random Trees(RRT)path planning algorithm,combined with the prediction results of the road grid hazard distribution trend,an improved RRT algorithm strategy is proposed.Thirdly,by choosing appropriate traffic simulation and network simulation tools,a complete vehicle network simulation framework is proposed and established,and the application of Mobile Edge Computing(MEC)is embedded in the vehicle network simulation platform,which makes the calculation of road grid hazard operate in roadside units to reduce the load of the vehicle itself.Finally,experiments are carried out on the established simulation platform,and the feasibility and effectiveness of the improved RRT algorithm are verified by comparing the experimental results.