Research On Multi-attribute Decision Making And Shortest Path Algorithm For Parking Lot Application

With the improvement of people's living standards,transportation problems have become increasingly prominent,and “difficult parking” has become an important issue affecting smart transportation.The traditional parking guidance system uses large screens and signs to display the number of free parking spaces and the direction of the parking spaces in the parking lot,which is difficult to meet the user's requirements for personalized parking spaces and parking efficiency.This article analyzes the user's parking preference,parking route guidance,etc.,focusing on the parking preference parking recommendation and its weighting method and the shortest path algorithm operation efficiency.The content is as follows:Aiming at the problem of subjective arbitrariness and ignoring objective facts in preferential parking space recommendation,the thesis designs an analytic hierarchy—entropy method combined weighting model based on the multi-attribute decision-making algorithm.The model analyzes the user parking space influencing factors and parking space attribute types,and constructs a normalized multi-attribute decision-making matrix;then by minimizing the deviation between subjective weights and objective weights,the attributes are combined with weight assignments;finally,the decision matrix and attributes are assigned.The weights are multiplied to obtain the comprehensive attribute value and maximize it,and the order of the preferred parking space plan is obtained.Through example verification,it is found that the model can reduce the error range between the combined weight and the reasonable weight,which proves the accuracy of the AHP-entropy method combined weighting model.Aiming at the time-consuming problem of the classic Dijkstra shortest path algorithm,this thesis proposes an improved Dijkstra algorithm.The algorithm establishes an abstract data model of the parking lot based on the parking line information in the parking lot,and proposes an improved strategy for adding key nodes and dividing areas in the parking road network.The key parking nodes are assembled to facilitate the confirmation of the shortest path.Finally,according to the vertex.The information divides the parking space into areas,further narrowing the search scope of the algorithm.Through experimental analysis,it is concluded that the time of calculating the shortest path of the improved Dijkstra algorithm is shorter than that of the classic Dijkstra algorithm,which verifies that the improved strategy proposed in this thesis can effectively reduce the calculation time of the algorithm and improve the efficiency of the algorithm.The two algorithms studied in this article are both researched and optimized for their application in parking lots.The combined weighting model of AHP-entropy method can accurately reflect user preferences and objective facts,and the path improvement strategy can be greatly improved.The improved algorithm operation efficiency has certain reference value for the construction of parking guidance system.