To explore the status of operation and travel demand characteristic, we extract the taxi operation and travel demand information based on data mining model. On this basis, the passenger flow volume in each period, travel time distribution, travel distance distribution are discussed. Simultaneously, the spatial distributive characteristic of travel demand is obtained by displaying the location information on Arcgis software. In addition, we verified the characteristic through data analysis. Some significant conclusions are drawn through the taxi operation in Chengdu: (1) the travel demand of taxi in Chengdu is stable, and the travel demand on weekends decreased slightly compared with the travel demand on weekdays. (2) The travel demand is concentrated on the district within the third ring road. (3) A significant difference between Chengdu taxi passenger flow and conventional bus flow is that taxi passenger flow does not show obvious peak characteristics in the morning and evening. The proposed approach can obtain taxi operation and travel demand situations, which can provide aid decision making for analysis and evaluation, operation dispatch, and assignment of vehicles.
Passenger Hotspot Mining Based on Taxi GPS Data—Taking Chengdu as an Example
Sixth International Conference on Transportation Engineering ; 2019 ; Chengdu, China
ICTE 2019 ; 883-892
2020-01-13
Conference paper
Electronic Resource
English
Passenger Flow Path Prediction Based on Urban Rail Transit AFC Data: An Example of Chengdu, China
DOAJ | 2023
|Predicting Taxi-Passenger Demand Using Streaming Data
Online Contents | 2013
|