Journal of the Eastern Asia Society for Transportation Studies
Online ISSN : 1881-1124
ISSN-L : 1341-8521
C: Travel Demand Analysis and Forecast
Creating User Profile of NEMT Travelers for Kanagawa Prefecture, Japan using K-Means Clustering Algorithm
Lucy Mariel LOPEZ QUIROGAShinji TANAKA
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JOURNAL FREE ACCESS

2025 Volume 16 Article ID: PP4070

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Abstract

In Japanese society, the elderly population is steadily increasing, which creates a growing demand for long-term medical care. Non-Emergency Medical Transportation (NEMT) plays a key role for individuals who face mobility barriers due to physical or mental conditions.

In 2022, NEMT service was launched in Kanagawa Prefecture, driven by demographic trends indicating market expansion potential. However, efforts should be made to ensure that this service is affordable and efficient. To that end, this study takes first step.

This study aims to profile NEMT travelers in Kanagawa to better understand their trip characteristics and needs using K-Means clustering. The results revealed two distinct clusters based on trip distance: short trips (average 5 km) and long trips (average 28 km). Both clusters primarily consist of travelers over 60 years old, with long trips often requiring special medical devices. Short trips typically involve hospital-to-hospital transfers, while long trips exhibit more varied origin-destination patterns.

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