Quantification of vehicle collision risk in smart way traffic environment to decrease traffic accidents

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This study focused attention on the risk of seven traffic accidents targeted for the smart way concerned with Intelligent Transport Systems and proposed a methodology to quantify the accident risk after the introduction of the smart-way, and then clarified reduction effects of accidents numerically.Representative example of the accidents was selected to describe a model which is based on a supposition that people has maximum standard of the acceptable risk. Three recognition results about an unsafe relation with a collision vehicle, occurrence probability of the unsafe relation and an unsafe action probability are defined. By formulating their relation, a relation between the recognition, the judgment and the action by a driver is shown quantitatively. Then, supporting evidence for this model is given by showing that a ratio derived by this model theoretically between the recognition errors and judgment errors in accidents was equivalent to existing accident data.This methodology was applied to the other accidents. A safety device, which gives a warning of a dangerous vehicle, was assumed and a reduction effect of accidents was evaluated quantitatively. Considering a failure lacking a warning by a safety device, necessary level of lacking a warning to reduce accidents was derived. It turns out that the extremely highly precise device, near to realization inability for engineering, is demanded from the driver who depends heavily on a device and relaxed reliability device is demanded from the driver who is independent on a device. And also a result was shown that a safety device might be able to tell the driver who depends completely on a device about danger but should not guarantee security.