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日本語

Compared to Western countries, Japan has a high rate of car accidents involving pedestrians and bicycles traveling in residential areas. Creating a safe community street space for pedestrians and cyclists is one societal issue we are currently facing in Japan. The importance of both lowering vehicle speeds in residential areas and limiting transit traffic that does not necessarily need to use such areas, or so-called “rat-run” traffic, is now recognized as an issue both domestically and overseas.

In order to implement effective rat-run traffic control measures, it is necessary to properly understand what kind of state the traffic is in. However, conventional surveying methods require a lot of time and manpower to qualitatively assess the state of rat-run traffic.

By using probe vehicle data, which is classified as one type of traffic big data, our urban & transportation systems laboratory has developed the technique for Grasping RAT-run traffic (GRATT), a method capable of grasping the state of rat-run traffic in residential areas in qualitative, wide-ranging, and efficient ways. Probe vehicle data is data that records the temporal position (longitude and latitude), travel state (speed, acceleration, direction), and other information of a vehicle as it travels. In the last few years, the amount of data being gathered on ordinary vehicles (limited to vehicles with drivers who agree to data collection) has increased due to the use of ETC 2.0, car navigation systems, smartphones, and other devices. With conventional field surveying methods, it is only possible to observe a part of each trip (movement from origin to destination).However, probe vehicle data can track and monitor the whole trip trajectory (Fig. 2). This particular feature of probe vehicle data is what inspired us to develop GRATT.

At present, we are conducting a traffic safety management project in collaboration with the road administrator of Toyohashi City (Road Maintenance section, Department of Construction) with the aim of implementing GRATT and improving traffic safety in the area. Introducing GRATT will help the road administrator more effectively and efficiently achieve the following PDCA cycle for traffic safety management (Fig. 3).

GRATT first extracts data on rat-run traffic in residential areas from probe vehicle data that has undergone primary data processing and map-matching processing. It then calculates an evaluation index (amount of rat-run traffic, rat-run usage rate, vehicle speed, etc.) for each segment of the road, and then visualizes this data using a geographic information system (GIS). The results are then discussed between our lab and the road administrator, after which we consider appropriate measures for areas in which priority measures are to be taken. At this step, we suppose 1. “Complementary use” for quantitatively assessing areas that the road administrator has already determined as candidate areas, 2. “Exploratory use” for extracting prioritized areas from the data, and 3. “Explanatory use” for communicating to local citizens the significance and effect of implementing the measures in question. The measures will then be actually implemented, and their effectiveness will be evaluated by GRATT through comparisons between the state of traffic before and after the measures were carried out.

Based on the fact that data analysis results cannot tell us everything, we place importance on sufficiently discussing GRATT results in terms of whether they match the experience and knowledge of the road administrator, as well as the intent of the measures. We believe that this way of analyzing results is very important, especially when applying engineering technology to the planning processes of governments and other institutions.

In addition to GRATT, our lab is also conducting research on various other traffic safety management methods, including traffic accident risk evaluation systems for small intersections with no traffic lights, and limiting vehicle speeds with Intelligent Speed Adaptation (ISA), with the aim of implementing these projects sometime in the future.

Our research on rat-run traffic issues on residential areas has been made possible thanks to MEXT’s Grant-in-Aid for Scientific Research #16K18168. Our project in collaboration with the road administrator of Toyohashi City was also made possible thanks to financial aid from Toyohashi City’s Innovation Support Project (local problem-solving field).