Improvement of Short-distance Subsidy Policy for Airport Taxi Based on Cluster Analysis

Abstract

The income of airport taxis is related to the mileage. Due to the difference in passenger destinations, the mileage is long and short, and the taxi driver cannot pick or refuse to load. Therefore, the difference between short-haul passengers and long-haul passengers is significant. Based on such realistic problems, a relatively reasonable priority policy has been proposed to balance the income of taxi drivers. Under the existing policy based on the short-distance ticket of Shanghai Pudong Airport, combined with the large number of drop-off point data of taxis, the data is pre-processed and then visually analyzed on Bigemap, and then cluster analysis is carried out in matlab environment. The mileage distribution makes a more reasonable division of short-distance long-distance definition and proposes new ideas for solving the problem.