Study On Urban Logistics Vehicle Path Planning Based On Cloud Computing

With the acceleration of the urbanization process,the city presents regional distribution,and our daily travel tools are naturally inseparable from the car,although it is convenient for citizens to travel,but also make the city’s traffic is facing great pressure.At the same time,with the rapid development of Internet technology in the information age,new shopping methods appear,mainly in the form of online shopping,which makes the logistics enterprises to pay more attention to the control of their distribution process.High-speed road,lane,rail transit and other transport infrastructure construction to a certain extent,ease the traffic pressure of the city,improve the enterprise’s distribution limitation,but the way the complexity of the urban construction,the sharp increase in the number of vehicles and the relatively fixed daily travel and holiday rush,let we have to consider more reasonable path planning strategy.Based on the modern intelligent traffic network,this paper analyzes the characteristics of traffic information in the intelligent traffic network,the time-varying of the road and the intricate complexity of the traffic network.Call Baidu intelligent cloud API interface to obtain real-time road traffic information,including traffic congestion status and vehicle travel time,etc.,which to some extent makes up for the defect of not considering the real road condition in the study of vehicle path planning.It also avoids the inaccuracy of using the road impedance function to qualitatively describe the state of road passage.In this paper,the route planning of logistics vehicles is modeled and solved by the improved adaptive genetic algorithm.The first is the iterative process of the standard genetic algorithm analysis shows that the algorithm in the process of evolution,this paper analyses the operator to set the irrationality of operation,according to the iterative process early,middle and end of the performance of the population,the adaptive crossover probability and mutation probability to choose,to jump out of local optimal solutions as possible to find the global optimal solution.This paper designs and establishes the urban logistics vehicle path planning system based on cloud computing.Firstly,according to the characteristics of cloud computing technology,the optimization algorithm model is changed to the parallel genetic algorithm which is adapted to the characteristics of cloud computing.Then,the regional road network information of Jinan city is established,the order demand information is established according to the actual demand of logistics enterprises,the process of enterprise logistics distribution is simulated,a certain number of vehicles are set up to participate in the distribution,and all the information is stored in the database.Finally,based on Visual Studio platform,with the goal of minimizing the cost of distribution,the trajectory of logistics distribution vehicles is visualized.The system provides a good reference and analysis platform for the formulation of vehicle scheduling strategy of logistics distribution enterprises.