The traditional path planning and selection system is based on a single target object to select the access road,which is often prone to problems such as path overlap,many nodes,and great safety hazards,and causes risks such as road path overlap.In order to obtain the optimal travel path of vehicles on congested roads in the IoT environment,this study designs and proposes a "distributed" multi-objective optimization algorithm for optimal vehicle travel paths under complex congested road conditions.By calculating the pheromone of vehicle driving conditions in the IoT environment,an algorithm model is constructed to deduce the development trend of the pheromone of the optimal passage of vehicles on the congested road,and the optimal information of the repeated route of the congested road is calibrated.Therefore,the feasible path for vehicles on the congested road based on the local optimum and the overall optimum is selected.After the optimal road expansion operation and the optimization analysis of the pass path refinement,in the simulated operating environment,the test verifies the rationality,safety and economy of the algorithm optimization scheme and the optimal pass path under the decision support.