Study On Recommendation Algorithm With Multi-shorter-path For Vehicle Navigation

With the fast development of Chinese economy, how to reduce the negative impact brought by traffic congestion are China's present urgent problems. The paper proposes a hybrid algorithm based on genetic algorithm after analyzing algorithms of urban traffic route guidance system from a practical viewpoint. Some improvements are also made to meet the actual traffic needs. The proposed algorithm provides the driver with multi-shorter navigation paths; therefore, it can increase the subjectivity of driver to choose the path and help drivers to try to reach the destination within the expected time. The main contributions of the paper are the following aspects:Firstly, do some researches and analyze the Multi-Route problem in a mathematical model to determine the multi-path problems using mathematical models. Meanwhile, after analyzing the strengths and weaknesses of the current main algorithms in traffic route guidance system, including Dijkstra algorithm, Floyd algorithm, K shortest path algorithm, A* algorithm and the genetic algorithm.Secondly, for the transport route guidance system in MQSRP problem, the hybrid algorithm is proposed in this paper. This algorithm combines the advantages of Floyd algorithm, A * algorithm and genetic algorithm, and solves the bottleneck of the genetic algorithm when it is used to solve the shortest path problem.Thirdly, in order to apply the proposed hybrid algorithm to the real traffic network, TDRNM model is introduced. To make the algorithm more practical, a matrix variable S is added and can make hybrid algorithm more effectively.Fourthly, propose CRHA to solve the problem of rationality of the multi-quasi-shortest paths. There are many algorithms which can solve the number of navigation routes, but they do not consider rationality of the multiple paths. Therefore, CRHA is proposed to solve this problem in this paper.Finally, on the static and TDRNM model, some simulation of the proposed hybrid algorithm on the effectiveness and efficiency are tested respectively, and results show their good performance. The effectiveness of CRHA is also tested, and results are fully satisfied.