JDR Vol.14 No.3 pp. 466-477
doi: 10.20965/jdr.2019.p0466


Analysis of Traffic State During a Heavy Rain Disaster Using Probe Data

Shogo Umeda, Yosuke Kawasaki, and Masao Kuwahara

Graduate School of Information Sciences, Tohoku University
6-6-06 Aoba, Aramaki-aza, Aoba-ku, Sendai, Miyagi 980-8579, Japan

Corresponding author

October 31, 2018
February 22, 2019
March 28, 2019
probe data, heavy rain, natural disasters, traffic analysis

In this study, the traffic state of a commercial vehicle was analyzed from a macroscopic viewpoint by using the probe data of a commercial vehicle in the Shikoku region during a period of heavy rain that occurred in western Japan in July, 2018. A method is proposed to calculate indexes, such as the detour rate and reduction in the number of trips, through an analysis of a trip at each origin-destination (OD) and extracting the route of a detouring vehicle during a disaster by using the results of the calculation. Finally, a method for the early detection of abnormalities, which involves paying attention to U-turn action during traffic disturbances is proposed. The influence of heavy rain on a commercial vehicle was evaluated quantitatively by analyzing the probe data of the vehicle during a disaster period caused by heavy rain. Specifically, analysis was performed on the number of passing commercial vehicles before and after the occurrence of a disaster, changes in running speed, route changes at each OD, and the vehicle trajectory around a regulated area. From the results of the analysis, it was possible to grasp the macroscopic traffic state, OD influenced by the traffic restriction, route in use for the OD during a normal time period, and an alternate route (detour action) during the disaster time period. With the method for the early detection of abnormalities at the time of a traffic disturbance, which pays close attention to U-turn action, a U-turn after the traffic regulation can be detected; however, it was confirmed that there is a problem in detecting timing and the application range.

Cite this article as:
S. Umeda, Y. Kawasaki, and M. Kuwahara, “Analysis of Traffic State During a Heavy Rain Disaster Using Probe Data,” J. Disaster Res., Vol.14 No.3, pp. 466-477, 2019.
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