Study On Driving Path Guidance Method Based On Real-time Traffic Information

Dynamic Route Guidance System(DRGS)is an important branch of intelligent transportation System.By collecting real-time traffic information,DRGS understands the real-time road status and makes reasonable path planning for travelers according to their starting and ending points.In this paper,a path induction method is proposed through ranking,filtering and efficiency evaluation of the induced path,and algorithm optimization is carried out for the proposed method to improve the operation efficiency of the path induction system.Firstly,the dynamic path induction method is studied in this paper.The route guidance strategy is based on the dual objectives of improving driver’s driving experience and managing road traffic.In this strategy,real-time guidance of driver’s driving path is implemented in the process of travel,and drivers’ behaviors and preferences are taken into account.In order to meet the real-time safety and satisfaction needs of drivers in the process of travel,a driving trip path guidance method is proposed in this paper.Firstly,the parameters of driving behavior,real-time traffic information and road conditions are collected and provided to the subdivision filtering and scoring section for operation.Then through the filtering part,the section is filtered according to the driver behavior and preference,and the scoring part is scored according to the traffic conditions,road integrity and driver preference satisfaction in the driving process.According to the scores calculated by Dijkstra algorithm,the filtered and graded sections are fed back to the final section for path calculation.Secondly,this paper proposes a real-time path guidance optimization algorithm in real-time traffic environment.The algorithm uses the generalized adaptive A*algorithm and genetic algorithm as the main body to filter the induced path,and combines with the pruning algorithm to improve the efficiency of the optimization algorithm.In order to adapt to the real-time performance of the proposed path guidance method,the fuzzy time window algorithm is introduced,and A* hybrid optimization algorithm based on real-time traffic information is proposed.The pruning algorithm takes the current local optimal solution as the threshold value,and can adjust the threshold value according to the local optimal solution in real-time state.The fuzzy time window constraint algorithm is introduced to optimize the time,so that the proposed optimization algorithm has real-time performance.In order to verify the algorithm,the actual road network data of San Francisco Bay Area was used as the experimental data,and the optimization algorithm proposed in this paper was compared with A* algorithm in the simulation experiment environment.The experimental results show that the algorithm proposed in this paper can effectively improve the operation rate of the path guidance system,and it is proved that the algorithm proposed in this paper can be applied to the path guidance system in real-time traffic environment.Based on the consideration of real-time traffic information,this paper proposes its own path guidance method,which takes into account the driver’s driving behavior and driving preferences,and in order to improve the reaction time of the path guidance system,a hybrid algorithm combining A* algorithm and genetic algorithm is proposed,and the pruning strategy and fuzzy time window are introduced to improve the operation rate of the system.