Search Results

This study aimed to clarify the relationship between truck-pedestrian crash impact velocity and the risks of serious injury and fatality to pedestrians. We used micro and macro truck-pedestrian accident data from the Japanese Institute for Traffic Accident Research and Data Analysis (ITARDA) database. We classified vehicle type into five categories: heavy-duty trucks (gross vehicle weight [GVW] ≥11 × 103 kg [11 tons (t)], medium-duty trucks (5 × 103 kg [5 t] ≤ GVW < 11 × 103 kg [11 t]), light-duty trucks (GVW <5 × 103 kg [5 t]), box vans, and sedans. The fatality risk was ≤5% for light-duty trucks, box vans, and sedans at impact velocities ≤ 30 km/h and for medium-duty trucks at impact velocities ≤20 km/h. The fatality risk was ≤10% for heavy-duty trucks at impact velocities ≤10 km/h. Thus, fatality risk appears strongly associated with vehicle class.

This study aims to clarify the relation between axonal deformation and the onset of axonal injury. Firstly, to examine the influence of strain rate on the threshold for axonal injury, cultured neurons were subjected to 12 types of stretching (strains were 0.10, 0.15, and 0.20 and strain rates were 10, 30, 50, and 70 s-1). The formation of axonal swellings and bulbs increased significantly at strain rates of 50 and 30 s-1 with strains of 0.15 and 0.20, respectively, even though those formations did not depend on strain rates in cultures exposed to a strain of 0.10. Then, to examine the influence of the strain along an axon on axonal injury, swellings were measured at every axonal angle in the stretching direction. The axons that were parallel to stretching direction were injured the most. Finally, we proposed an experimental model that subjected an axon to more accurate strain.

The purpose of this study is to clarify the mechanism of traffic accidents involving cyclists. The focus is on the characteristics of cyclist accidents and scenarios, because the number of traffic accidents involving cyclists in Tokyo is the highest in Japan. First, dangerous situations in traffic incidents were investigated by collecting data from 304 cyclists in one city in Tokyo using a questionnaire survey. The survey indicated that cyclists used their bicycles generally while commuting to work or school in the morning. Second, the study investigated the characteristics of 250 accident situations involving cyclists that happened in the city using real-world bicycle accident data. The results revealed that the traffic accidents occurred at intersections of local streets, where cyclists collided most often with vehicles during commute time in the morning. Third, cyclists’ behavior was observed at a local street intersection in the morning in the city using video pictures.