Research On Campus Unmanned Distribution Optimization And Development Of The System

Universities are an important gathering place for online shopping consumer groups.The average daily delivery volume of parcels on campus is large.However,there are still many problems to be solved in the operation of express delivery on campus.In order to better meet the daily needs of college teachers and students,improve the quality of campus express delivery service.It is urgent to use more intelligent ways to optimize the terminal distribution,so as to make the campus express delivery more reasonable,standardized and convenient.With the rapid development of 5G and other related technologies,driverless technology is becoming more and more mature,and the application scenarios of driverless vehicles are constantly expanding,which provides an important development opportunity and technical support for logistics terminal distribution.Campus express demand concentration,fixed location,good road condition,suitable for the use of unmanned vehicles for distribution,to provide customers with good noncontact service.Therefore,this thesis studies the route optimization of campus unmanned distribution,and develops a campus unmanned distribution system which integrates reservation,route planning,order management and unmanned vehicle management.This thesis first optimizes the driving path of the unmanned vehicle,establishes the model of the path planning of the unmanned vehicle,and uses the classical Ant Colony Optimization(ACO)to solve it.At the same time,Ant Colony Optimization is easy to fall into the local optimum,which leads to the poor quality of the solution and slow convergence speed.In order to improve the convergence and the quality of solution,Premium-Penalty Ant Colony Optimization(PPACO)and 2-opt are added.In order to verify the effectiveness of the Ant Colony Optimization and the improved strategy,the Random Searching,the basic Ant Colony Optimization,the Ant Colony Optimization with 2-opt and the Premium-Penalty Ant Colony Optimization with 2-opt are used to solve the same example.The effectiveness of the improved Ant colony algorithm is verified.After the algorithm is verified,the algorithm is applied to the path planning module of campus unmanned distribution system,and the results of unmanned vehicle distribution path are displayed through visual programming.Then,on the basis of demand analysis,overall structure,function module and database design,the development,debugging and application of campus unmanned distribution system are realized.In the process of platform development,Baidu map API and Ajax are mainly used in two Java Script based technologies.The former is used to realize the visualization of Web Front-end page map and geographic information processing,while the latter is mainly used for data exchange between Web Front-end pages and database server.Finally,combined with the path planning algorithm in front of this thesis,the unmanned vehicle distribution management and path optimization platform is realized.This thesis contains 60 figures,22 tables and 59 references.