A Taxi Zoning Analysis Using Large-Scale Probe Data: A Case Study for Metropolitan Bangkok
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Taxis are considered one of the most convenient means of transportation, especially when people have to travel off-route, where public transportation is not a feasible option, and also when they need to reach a destination according to what is most convenient for them. However, many issues exist about taxi services, such as the problems of passengers who are unable to get taxi service at the location of their choice, or problems concerning when they need the taxi service to arrive. These problems may be due to the unavailability of the taxi at that particular location or due to the taxi driver not wanting to provide service. A taxi driver may not want to provide service to a potential passenger, because they may have preferences on the direction and areas they want to go or because of the different types of service zoning. Understanding the behaviors of taxi drivers and the characteristics of the trip/travel might be helpful to solving such issues. In this study, we conducted an analysis from a questionnaire survey and large-scale taxi probe data to understand taxi service behavior, travel characteristics, and to discover taxi service zoning characteristics. As a result, four types of taxi service zones including isolated zones, interactive zones, special service zones, and target zones were encountered. Travel characteristics were calculated and analyzed at different criteria, such as weekdays, weekends, and various time windows in a single day. The result of these characteristics was explained according to their similarities and dissimilarities in each type of zone. The discovery of the different zones and their respective definitions might be a good initiative for further development of a policy for taxi drivers to provide better service for passengers.
KeywordsTaxi service Taxi travel characteristics Taxi probe data
This research with taxi probe data was partially supported by Toyota Tsusho Nexty Electronics (Thailand) Co., Ltd. and the Asian Institute of Technology, Thailand, under the Remote Sensing and Geographic Information System Department. We would also like to acknowledge the Center for Spatial Information Science at the University of Tokyo, Tokyo, Japan, for research support.
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