Research On Dynamic Travel Path Guidance Under The Background Of Internet Of Things

Dynamic path planning for vehicles and rational distribution of traffic flow can effectively solve the problem of road traffic congestion and improve travel efficiency.This is also one of the hot research directions of scholars in the field of intelligent transportation.The research in the direction mainly focuses on how to fully obtain realtime traffic data on the road network,extract effective traffic information,and quickly plan a reasonable path for drivers to meet their travel requirements and shortest travel time based on this.Based on the application of Internet of Things technology to fully obtain real-time traffic data on the road network,the thesis studies how to provide dynamic travel guidance for vehicles in the face of real-time changes in road network traffic status.The main research work of this thesis is as follows:In the thesis,a dynamic raster road map is constructed to simulate the traffic conditions of the road network that change in real time in the process of real-time vehicle driving.With regard to the calculation of vehicle’s estimated travel time,the thesis introduces the idea of fuzzy mathematics,which takes into account the actual distance of each road section and the equivalent distance cost of each road section of vehicle intersection delay,and the estimated speed of the vehicle on the road section is obtained.The thesis analyzes the traditional A* pathfinding algorithm in path planning for vehicles exist deficiencies,in the face of map grid on the basis of dynamic assignment,based on A* algorithm is proposed considering the dynamic weight of hops search(DJPS)algorithm,this algorithm through improving access to grid rules,and redundancy in the process of pathfinding reduced grid access,in order to improve the path finding efficiency of the algorithm.Finally,the algorithm is applied to a small example road network for simulation,and the simulation results are analyzed.It is found that the algorithm is due to the traditional A* algorithm in terms of route finding results and algorithm time.On the basis of the proposed DJPS algorithm,this thesis defines the aggregation effect coefficient and builds a dynamic path selection model in view of the adverse effects that dynamic path induction may bring to travelers,such as aggregation effect.Will gather effect coefficient into calculation of solving the traveler for compliance with dynamic route guidance,online questionnaire to fill in investigation method to investigate the driver,Analytic Hierarchy Process(AHP)was used to comprehensive analysis,the result of the investigation have gathered effect coefficient is 0.713,which will have determined the traveler at the end of according to the proportion into the existing road vehicles,By participating in the calculation of road impedance,the problem of aggregation effect caused by dynamic path induction on travelers can be avoided,and different and hierarchical route recommendations can be provided for travelers at the same starting and ending points at the same time.Finally,based on real road network traffic scenarios,experiments are designed to simulate the proposed pathfinding algorithm and the dynamic path selection model based on the algorithm considering aggregation effect,and the simulation results are analyzed to verify that the model has certain practical value in intelligent traffic scenarios.