A Personalized Driver-passenger Two-sided Matching Decision Method for Online Taxi Platforms Considering Passengers'No-show Behavior
A personalized two-sided driver-passenger matching decision analysis method was proposed,which had taken passengers'no-show behavior,frequently existing in online taxi services.Firstly,on the basis of the process of calling a reserved vehicle on the online taxi platform,a passenger selection model was developed to measure the probability of passengers'no-show behavior.Secondly,an attribute correlation matrix based on linguistic scales was established to calculate the weight of drivers'every attribute in the process of online taxi matching.Furthermore,considering passengers'psychological expectations and perceptions,the comprehensive prospect value of passengers'satisfaction with the driver was calculated on account of the prospect theory.On this basis,a multi-objective optimization model driver-passenger matching was constructed,and the matching results were obtained by solving the model.Finally,the effectiveness and feasibility of the proposed method were further verified through the matching example of an online taxi platform.
万方数据
维普
