We carried out a retrospective study on the presence of both alcohol and drugs in 179 forensic autopsy cases from traffic accidents in Kumamoto prefecture from 1999 to 2008. Blood-alcohol testing was performed in 149 cases, and alcohol was detected in 47 of these cases（32%）．A high alcohol positive rate was observed in bicycle（55 %）and pedestrian（44%）cases and in traffic accidents caused by driver/rider negligence in all types of accidents, which strongly suggests alcohol influences traffic accidents. TriageDOA® drug screening was performed in 90 cases from 2003 to 2008, with 8 cases（9%）presenting as positive. Tests were positive for benzodiazepines in six cases, barbiturates in three cases and opiates in one case. GC-MS drug screening of the 8 positive cases identified phenothiazine and several antiepileptic drugs that could not be detected by TriageDOA®. The possible effect of the detected drugs on the cause of accident was discussed in the 8 TriageDOA® positive cases. Drug analysis in the victims of traffic accidents was found to provide essential information to reconstruct the cases. However, further case information, including quantitative analysis of drugs, was necessary to evaluate the effect of drugs on the cause of traffic accidents.

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Impressions regarding risks related to traffic scenes were investigated. Adult participants（N=97）were shown five pictures consisting of traffic scenes drawn from the driver’s perspective. Using the hypothetical situation method, participants were requested to point to parts of the drawings that gave an impression of a risk. They identified 54 such parts. These parts, with the exception those identified by only a few participants were categorized as feeling risky or not risky. Then they were analyzed using Hayashi's quantification theory （III） and hierarchical cluster analysis. Results indicated five clusters: （1） Feeling of risk evoked by stimulus features, （2） Feeling of risk caused by distance from others, （3） Judgments on riskiness of a situation, （4） Expectations of risks caused by own behavior, and （5） Expectation that something will collides with own vehicle. These results suggest that both intuitive and analytic processing underlie the risk perception.

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Purpose: The aim of this study was to investigate the diagnostic ability of postmortem computed tomography（CT）in cases with traffic accident-related injuries. Methods: We examined postmortem CT in 51 subjects （male 33, female 18; mean age 57.4 years） who were brought to our institution after traffic accidents and died in our emergency department. These included 20 pedestrians, 12 cyclists or motorcyclists, and 19 automobile drivers or passengers. The examinations were performed with 16-row （n=29） or 64-row （n=22） detector CT scanners. All injuries detected by postmortem CT were coded using the Abbreviated Injury Scale （AIS）． Injury Severity Score （ISS） was calculated according to the AIS. Traditional autopsies were not performed. Results: Bone fractures, massive hemorrhage; e.g. hemothorax, hemoperitoneum, and retroperitonum hemorrhage, and gas density; e.g. pneumothorax and pneumocephalus were obviously recognized on postmortem CT. A total of 237 injuries （AIS 1: 5, AIS 2: 52, AIS 3: 78, AIS 4: 37, AIS 5: 43, and AIS 6: 22） were identified. All cases had AIS 3 or higher injuries （most severe injury, AIS 3: 3 cases, AIS 4: 7 cases, AIS 5: 21 cases, and AIS 6: 20 cases）． Calculated ISS ranged from 13 to 75 in pedestrians, from 13 to 75 in cyclists or motorcyclists, and from 25 to 75 in drivers and passengers. Postmortem CT revealed 68 injuries including 64 AIS 3 or higher injuries in head and neck, and 80 injuries including 65 AIS 3 or higher injuries in thorax, respectively. Injuries in the multiple regions were presented in 44 cases. Forty cases had AIS 3 or higher injuries in more than one region. Conslusions: Postmortem CT can detect fatal injuries, such as gross damages within viscera, bone fractures, massive hemorrhage, or pneumothorax. Postmortem CT is useful to evaluate the injuries in traffic accident victims.

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Rear-end collision is one of considerable accident types in Japan because many occupants are injured in this type of crash; however, most of their injuries are slightly injured. It is difficult to analyze regression models of rear-end collision using Japanese Micro Data with sampling limitations and few serious injuries. This study clarifies influential factors and injury prediction model in rear-end collisions using Japanese Macro Data, which is the police reported database for all traffic accidents that occur throughout Japan. The injury prediction method and influential factors are proposed using ordinal logistic regression model. The significant factors are delta-V, vehicle damage grade, seat belt use, occupant age, and vehicle category. The prediction model using these factors can correspond to the rate of fatalities and serious injuries in Macro Data; furthermore, it can show the good correlation to Micro Data. This model indicates the serious injury risk for belted occupants with delta-V of 60km/h or less, which is the majority of conditions in rear-end collisions, is 20% or less. The conditions with the risk of 50% or more are quite limited. This result shows the judgment of serious injuries using the injury prediction model needs many overtriage cases. Therefore, the balance between sensitivity and overtriage for the injury prediction model is important issue in rear-end collisions.

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This research seeks to improve the accuracy of calculating the collision speed of a vehicle in a car-pedestrian accident using computer simulation because most fatal accidents are pedestrian accidents. We therefore studied how to calculate the collision speed of vehicles involved in pedestrian accidents using the pedestrian simulation model （MADYMO） developed by JARI. In the computer simulation, we used two different brake conditions （braking level and braking time） to investigate the relation between the distance a pedestrian is thrown and the vehicle speed upon collision. Based on our research, we speculate that the distance a pedestrian is thrown increases when the braking level is low and that the distance thrown becomes maximum when braking is delayed and the collision speed exceeds 40km/h.

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