Chiba Taxi Association uses AI to understand and ease congestion at JR Maihama Station

Every day, tens of thousands of visitors use JR Maihama Station to reach Tokyo Disneyland and nearby attractions, creating what is commonly described as an overtourism situation. Around 8 p.m., when the fireworks before park closing finish, demand for taxis peaks.

During these times, passengers often had to wait at the taxi stand, and as wait times grew longer, queues formed and disputes between customers could arise. Over time, congestion at the taxi stand became a persistent issue, and the association sought a sustainable way to address it without compromising safety or service quality.

As part of the Japan Tourism Agency's initiatives to prevent and mitigate overtourism, the team noted measures focused on collecting and analyzing people-flow data. Since their existing systems already made use of cameras, they began considering how AI-powered video analytics could help them better understand actual passenger flows.

The agency found that Synology's Surveillance Station platform, which offers people and vehicle counting capabilities, would provide the necessary analysis accuracy for the JR Maihama Station area without having to replace their existing cameras. Its functionality and cost-effectiveness ultimately led them to choose Synology for this project.

Around JR Maihama Station, a total of 20 cameras — a combination of third-party cameras and new Synology network cameras — are used at key locations such as bus and taxi stands and the second-floor concourse. Video from these cameras is fed back to a Synology DVA system installed in the office, where traffic from specific cameras are counted and analyzed.

By leveraging AI video analytics, the association has a clearer picture on the passenger traffic flow and demand for taxis. This has enabled them to dispatch vehicles more appropriately, reducing passenger waiting times at the taxi stand to about half of what they were before.

In addition to local monitoring, the video feeds are also distributed to taxi and bus companies, police stations, and the Urayasu City crisis management division to support coordination and safety measures around the station area.

Going forward, they plan to continue tracking fluctuations in people flow by season and time of day, using the data to better understand overtourism patterns and to study potential improvements. They also intend to deploy network cameras at other major terminal stations within the Keiyo branch area, using Synology's video analytics to help:

• Maintain order within station roundabouts
• Shorten passenger waiting times at taxi stands
• Provide video footage to law enforcement in the event of incidents, accidents, or fraud cases
• Check the status of stranded passengers and damage during disasters