| Popis: |
This research outlines the development of evaluating safety measures for bicycle traffic using state-of-the-art technology, which was started since 2020 as a four-year project. The project is funded by the Commission on Advanced Road Technology in the Ministry of Land, Infrastructure, Transport and Tourism(MLIT). While Japan has a high bicycle modal share of 12% (2010), bicycle-related fatalities are relatively high among other countries in the IRTAD database (2019). Under these circumstances, since 2007, various measures for bicycle traffic measures have been implemented to improve the safe bicycle traffic environment, including the revision of the Road Traffic Act and the formulation of a national plan to promote bicycle use. However, serious accidents involving bicycles are remained in some specific cases. According to the government's traffic accident analysis results (2019), right-hook crash at signalized intersections are one of the most serious types of collision involving bicycles, along with accidents at unsignalized intersections involving vehicles turning left, rear-end collisions, and single vehicle accidents due to off-road deviation. In particular, proactive safety measures are required at signalized intersections along arterial roads, where electric personal mobility vehicles traveling at speeds of up to 20 km/h are expected to share with bicycles in the future. In order to evaluate safety measures for bicycle-vehicle crashes, this project set the following goals. 1) Identify factors influencing near-miss incidents and collisions through analysis of drive recorder data and accident statistical data. 2) Detailed analysis of traffic conditions from the cyclist's perspective using a probe bicycle equipped with a LiDAR sensor. 3) Development of an experimental environment using a connected simulator for evaluation of cooperative driving behavior. 4) Clarification of experimental conditions to evaluate different scenarios and conditions with and without intervention. 5) Proposal of effective interventions to improve crash cases based on experiments. |
