A Study of Intercity Transportation Demand in Fukui Prefecture Under 2018 Heavy Snowfall: Based on Mobile GPS Data

Abstract

Understanding intercity transportation demand and trends during snowstorms is crucial for mitigating traffic accidents and congestion. This study analyzed the characteristics of intercity transportation demand using Agoop mobile GPS data, focusing on the 2018 Fukui Heavy Snow Event. The K-dimensional Tree (KDTree) algorithm for neighbor matching was employed to examine the spatiotemporal characteristics of intercity transportation demand, providing insights into the overall trends under the influence of the snow disaster. Additionally, Singular Value Decomposition (SVD) was utilized to decompose and reduce the dimensions of the spatiotemporal OD matrix, facilitating the identification of the composition of intercity transportation flow. The study identified three phases of the event: the stable phase (January 27 to February 2), the snow disaster phase (February 3 to February 11), and the recovery phase (February 12 to February 16). During the snow disaster, intercity transportation demand dropped by 67.86% compared to the stable phase. Intercity transportation demand during the snow disaster included daily demand (M1) and special demand (M2). M1 traffic primarily originated from Fukui City, Sabae City, Awara City, and Sakai City, with Fukui City and Sakai City being key points of departure and arrival. In the M2 model, traffic from southern to northern Fukui Prefecture nearly ceased, shifting from a longitudinal pattern along National Route 8 and the Hokuriku Shinkansen to a horizontal distribution towards Ono and Katsuyama. Departure flows from Sakai City decreased significantly, while Tsuruga City saw a significant increase in traffic. This indicates that the snow disaster mainly affected northern Fukui Prefecture, especially Fukui City and Sakai City.