| Project/Area Number |
26540166
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Web informatics, Service informatics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Horanont Teerayut 東京大学, 空間情報科学研究センター, 客員研究員 (00598287)
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| Co-Investigator(Kenkyū-buntansha) |
SEKIMOTO YOSHIHIDE 東京大学, 生産技術研究所, 准教授 (60356087)
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| Project Period (FY) |
2014-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | Road traffic accident / Traffic volume / Risk factors / Spatial correlation / Modelling / Interpolation / Road traffic acciden / Data Mining / Traffic accidents / land use / GLM / zero-inflated models / risk factors |
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| Outline of Final Research Achievements |
A road traffic crash results from a combination of factors related to the components of the system comprising roads, the environment, vehicles and road users, and the way they interact. Some factors contribute to the occurrence of a collision and are therefore part of crash causation. Other factors aggravate the effects of the collision and thus contribute to trauma severity. Some factors may not appear to be directly related to road traffic injuries. Some causes are immediate, but they may be underpinned by medium-term and long-term structural causes. Identifying the risk factors that contribute to road traffic accidents is important in identifying interventions that can reduce the risks associated with those factors. The main finding of this study is the nfluential factors in traffic accidents.
Those independent variables are found to be influential and thus the
results can help increases the safety of vehicle collision avoidance system.
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