Accident; analysis and prevention
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This research explores the injury severity of pedestrians in motor-vehicle crashes. It is hypothesized that the variance of unobserved pedestrian characteristics increases with age. In response, a heteroskedastic generalized extreme value model is used. ⋯ The heteroskedastic model provides a better fit than the multinomial logit model. Notable factors increasing the probability of fatal pedestrian injury: increasing pedestrian age, male driver, intoxicated driver (2.7 times greater probability of fatality), traffic sign, commercial area, darkness with or without streetlights (2-4 times greater probability of fatality), sport-utility vehicle, truck, freeway, two-way divided roadway, speeding-involved, off roadway, motorist turning or backing, both driver and pedestrian at fault, and pedestrian only at fault. Conversely, the probability of a fatal injury decreased: with increasing driver age, during the PM traffic peak, with traffic signal control, in inclement weather, on a curved roadway, at a crosswalk, and when walking along roadway.
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Although alcohol and distraction are often cited as significant risk factors for traffic crashes, most research has considered them in isolation. It is therefore necessary to consider the interactions between alcohol and distraction impairment sources, especially when examining the relationship between behavior and crash risk. In a driving simulator, the primary goal was to maintain a safe headway to a lead vehicle and the secondary goal was to maintain stable lane position. ⋯ Alcohol impairment was evident only in relation to lateral driving performance, however there was an amplification of impairment when alcohol and distraction conditions were combined. Distraction resulted in a general level of impairment across all driving goals, whereas participants with alcohol appeared to shed secondary driving goals to "protect" primary driving goals. Drivers' strategies to cope with alcohol (and distraction) may not be sufficient to offset the increased crash risk.
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This study examines the impact of passengers on the driver's crash potential on freeways. To estimate the impact, a set of bivariate probit models were developed using the 5-year (1999-2003) crash records on a 36.3-mile stretch of Interstate-4 freeway (I-4) in Orlando, Florida. Bivariate probit models identify the correlation between potentially inter-related choices of three passenger characteristics and three crash characteristics. ⋯ It was also found that younger driver's crash potential increases with the presence of a younger passenger only. In addition, the analysis of crash type using traffic flow parameters at the time of crashes showed that young drivers with only younger passengers are more likely to be involved in single-vehicle crashes in high-speed and low-volume conditions. The findings in this study provide insight into how the presence of passengers has an impact on driver behavior and traffic safety in various conditions.