TY - JOUR
T1 - Analysis of traffic state during a heavy rain disaster using probe data
AU - Umeda, Shogo
AU - Kawasaki, Yosuke
AU - Kuwahara, Masao
N1 - Funding Information:
This research was supported by “Establishing the most advanced disaster-reduction management system by fusion of real-time disaster simulation and big data assimilation,” Japan Science and Technology Agency (JST, CREST). We thank FUJITSU TRAFFIC & ROAD DATA SERVICE LIMITED Co., Ltd. for providing the probe vehicle data used in this work.
Publisher Copyright:
© 2019, Fuji Technology Press. All rights reserved.
PY - 2019/3
Y1 - 2019/3
N2 - 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 ac-tion) 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.
AB - 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 ac-tion) 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.
KW - Heavy rain
KW - Natural disasters
KW - Probe data
KW - Traffic analysis
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U2 - 10.20965/jdr.2019.p0466
DO - 10.20965/jdr.2019.p0466
M3 - Article
AN - SCOPUS:85068770722
VL - 14
SP - 466
EP - 477
JO - Journal of Disaster Research
JF - Journal of Disaster Research
SN - 1881-2473
IS - 3
ER -