ANALYSIS OF TRAFFIC FLOW RECOVERY TIME DUE TO LANDSLIDES (CASE STUDY : ROUTE 31, HIROSHIMA, JAPAN)

• Main Author: Hakim Sjafruddin, Azis
• Format: Theses
• Language: Indonesia
• Subjects: Teknik sipil
• Online Access: https://digilib.itb.ac.id/gdl/view/56200
• Institution: Institut Teknologi Bandung

The existence of a good transportation system can support the movement of people, goods, and information in daily activities. However, the transportation system can be disrupted by various things, one of which is due to natural disasters. One type of disaster that often occurs is a disaster caused by heavy rains such as landslides. The movement of travelers can be disrupted due to natural disasters. This has an impact on the flow of traffic on a road network. This research will examine the recovery time of the R31 National Road in Hiroshima Prefecture, Japan due to the landslide disaster in 2018. As a result of the disaster, there were several damaged roads that disrupted traffic flow conditions. The performance indicator to identify the recovery stage is traffic flow. The data used in this study is traffic flow data obtained from loop detector data at 32 points spread along National Road R31, Hiroshima, Japan. The analytical method used in this study is a survival analysis method using the cox proportional hazard model. This method is able to display the temporal distribution of the factors that affect the recovery time. The tool used in this research is the R programming language. Based on the results of the analysis, each loop detector has a different recovery time. There are three factors that have a significant influence on recovery time, namely the location of the road segment, the presence of landslides, and the dominant type of land use in each R31 road segment. The location of the road segment that is further away from the landslide location makes the recovery time faster when compared to the location of the road segment that is closer to the landslide.