Toyota Motor Corporation and JapanTaxi Co., Ltd. (JapanTaxi), along with KDDI Corporation and Accenture, have developed a taxi dispatch support system that predicts demand for taxi services, combining data from taxi service logs with predictions of demographics made by location-based big data from smartphones as well as event information. The companies have started to deploy the system in Metropolitan Tokyo on a trial basis.

The system uses artificial intelligence (AI) to predict the number of occupied taxis in Tokyo using 500-meter, mesh-based parameters every 30 minutes. The companies collect taxi service log data and demographic predictions as well as other factors that affect taxi demand such as weather, public transport service availability, and events at large facilities, and apply learning models through an AI-based system to predict the size of demand. In a test run in Tokyo, the system demonstrated a high accuracy rate of 94.1 percent.

Since February 2018 the companies have been piloting the system with select taxis of Nihon Kotsu Co., Ltd., affiliate company of JapanTaxi, using tablet computers equipped with the system. A map on the tablet shows not only the predicted number of occupied taxis but the latest number of unoccupied taxis around the area, which allows drivers to position their taxis based on the supply-demand balance.

As a result, more taxis can serve areas with higher demand and insufficient supply to reduce waiting time for passengers while taxi occupancy rate is increased with optimal vehicle-dispatch. In addition, drivers can receive supporting information on the tablet that shows the routes where they are likely to find passengers, based on insights of excellent drivers.

During the pilot, drivers who used the system recorded an average sales increase of 20.4 percent in February 2018 on a month-on-month basis, compared to an overall average increase of 9.4 percent. Dozens more taxis will trial the system with an aim to roll it out for widespread use later in the year.