Open AccessAnalysis of Traffic State During a Heavy Rain Disaster Using Probe Data
Author(s) -
Shogo Umeda,
Yosuke Kawasaki,
Masao Kuwahara
Publication year - 2019
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.332
H-Index - 18
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2019.p0466
Subject(s) - trajectory , computer science , environmental science , grasp , heavy traffic , state (computer science) , meteorology , period (music) , trips architecture , disaster area , transport engineering , real time computing , geography , engineering , algorithm , physics , astronomy , programming language , acoustics
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.