Dynamic vehicle route guidance model under internet of vehicles

In order to improve the route planning efficiency of vehicle route chain in Internet of vehicles and avoid traffic congestion by optimizing dynamic vehicle route planning, a dynamic vehicle route guidance model under Internet of vehicles based on global adaptive optimization scheduling is proposed. The regional grid segmentation method is adopted to design and plan nodes of dynamic vehicles under Internet of vehicles, and dynamic vehicle route planning is performed by constructing a network system through road segments and intersections and the travel time on roads as control constraint parameter; the particle swarm optimization algorithm is adopted to adaptively optimize dynamic vehicle routes, and a dynamic vehicle route guidance model under Internet of vehicles is constructed by taking the individual particle pheromone as guidance parameter to optimize the guidance route planning capability of vehicle routes. Simulation results show that the method proposed in this paper can increase traffic volume by 42.8% and shorten the travel time by more than 50% in dynamic vehicle route guidance under Internet of vehicles.