In this paper, eight factors affecting taxi drivers' decision-making are divided into two categories by cluster analysis: first, factors affecting drivers' waiting time; The second factor is the one that affects the driver’s income. Secondly, this paper uses AHP to establish a hierarchical structure model for analyzing the influencing factors. A large amount of data from Shanghai Pudong Airport and its urban taxis is used to modify the model. In this paper, four factors that are suitable for evaluating taxi drivers' decision-making are finally obtained, including the number of cars queuing, the number of people queuing, the weather, the time slot and the dependent factors that affect drivers' decision-making.
Analysis on influencing factors of taxi driver's decision based on cluster analysis and analytic hierarchy process
Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024) ; 2024 ; Beijing, China
Proc. SPIE ; 13181
19.07.2024
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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