Research And Implementation Of Intelligent Parking Guidance System Based On Android

In recent years,people's living standards have been greatly improved,and the number of cars has grown rapidly,bringing convenience to people's lives.However,with the increase of cars,people in the normal parking process,because the parking users can not get timely and accurate parking information,parking lot induction system is not intelligent enough,etc.,resulting in the user parking lot can not find a suitable parking space Parking problems such as “circle” in the parking lot often occur,and the problem of “ difficult parking ” has affected people's lives.According to the status quo of the above problems,this paper designs a smart parking guidance system based on Android from the actual application requirements to help people find suitable parking lots and guide the parking spaces in the parking lot.The system improves the parking efficiency to a certain extent.The main work of the thesis is as follows:1.The parking path model in the parking lot is designed.After comparing the advantages and disadvantages of the shortest path algorithm Dijkstra algorithm and A* path finding algorithm,it is more suitable for the A* search of the shortest path of “point to point” when the parking space is known.The road algorithm is used to solve the indoor parking path planning problem,and the road resistance factor is added to the valuation function of the A* algorithm to guide the parking space path planning in the case of parking lane congestion.2.For the outdoor parking navigation module,combined with the characteristics and advantages of bionic genetic algorithm and ant colony algorithm in path planning in complex road network,the optimal path planning algorithm involved in system parking navigation function is improved and designed.A hybrid genetic ant colony algorithm(GACHA)is used in the path planning of the system.Starting from the basic ant colony algorithm,combined with the respective advantages of genetic and ant colony algorithms,the optimization loops of the two algorithms are introduced multiple times.After each iteration of the ant colony algorithm,the optimal solution generated by the ant colony algorithm is added to the genetic algorithm to speed up the iterative speed of the genetic algorithm.At the same time,the solution calculated by the genetic algorithm is set as a better path to update the pheromone allocation in the ant colony algorithm to achieve parameter adjustment.Multiple mutual guidance effectively solves the low efficiency of the early ant colony algorithm and the redundant iterative problem of the genetic algorithm.The simulation results show that the improved algorithm has good efficiency and convergence,and can accuratelyfind the optimal path that meets the comprehensive requirements of the road network.3.Design and implementation of each module of Android-based intelligent parking guidance system: Firstly,the overall framework of the system is designed,then the functional logic diagram of each module of the system is designed and summarized,and the genetic-ant colony hybrid algorithm is integrated.It is used for the design of outdoor navigation routes to the path planning problem in the intelligent traffic system.The system is developed through the Android Studio platform editor,and completes the functions of querying the surrounding parking lot,parking lot navigation,parking space reservation,parking space navigation,reverse car search,etc.,realizing the intelligent parking guidance integrating indoor and outdoor.system.At the end of this paper,the functional modules of the designed Android intelligent parking guidance system are tested in detail,and the designed algorithm is verified by simulation,which verifies the effectiveness of the algorithm and the practicability of the system.