A note on modeling pedestrian-injury severity in motor-vehicle crashes with the mixed logit model.
ABSTRACT Pedestrian-injury severity has been traditionally modeled with approaches that have assumed that the effect of each variable is fixed across injury observations. This assumption ignores possible unobserved heterogeneity which is likely to be particularly important in pedestrian injuries because unobserved physical health, strength, and behavior may significantly affect the pedestrians' ability to absorb collision forces. To address such unobserved heterogeneity, this research applies a mixed logit model to analyze pedestrian-injury severity in pedestrian-vehicle crashes. Using police-reported collision data from 1997 through 2000 from North Carolina, several factors were found to more than double the average probability of fatal injury for pedestrians in motor-vehicle crashes including: darkness without streetlights (400% increase in fatality probability), vehicle is a truck (370% increase), freeway (330% increase), speeding involved (360% increase), and collisions involving a motorist who had been drinking (250% increase). It was also found that the effect of pedestrian age was normally distributed across observations, and that as pedestrians became older the probability of fatal injury increased substantially. Heterogeneity in the mean of the random parameters for the freeway and pedestrian-solely-at-fault collision indicators was related to pedestrian gender, and heterogeneity in the mean of the random parameters for the traffic-sign and motorist-back-up indicators was related to pedestrian age.
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ABSTRACT: The research described in this paper explored the factors contributing to the injury severity resulting from pedestrian at-fault crashes in rural and urban locations in Alabama incorporating the effects of randomness across the observations. Given the occurrence of a crash, random parameter logit models of injury severity (with possible outcomes of major, minor, and possible or no injury) for rural and urban locations were estimated. The estimated models identified statistically significant factors influencing the pedestrian injury severities. The results clearly indicated that there are differences between the influences of a variety of variables on the injury severities resulting from urban versus rural pedestrian at-fault accidents. The results showed that some variables were significant only in one location (urban or rural) but not in the other location. Also, estimation findings showed that several parameters could be modeled as random parameters indicating their varying influences on the injury severity. Based on the results obtained, this paper discusses the effects of different variables on pedestrian injury severities and their possible explanations. From planning and policy perspective, the results of this study justify the need for location specific pedestrian safety research and location specific carefully tailored pedestrian safety campaigns.Accident Analysis & Prevention 08/2014; 72C:267-276. · 1.87 Impact Factor
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ABSTRACT: Purpose Bus safety is a concern not only in developing countries, but also in the U.S. and Europe. In Denmark, disentangling risk factors that are positively or negatively related to bus accident severity and injury occurrence to bus passengers can contribute to promote safety as an essential principle of sustainable transit and advance the vision “every accident is one too many”. Methods Bus accident data were retrieved from the national accident database for the period 2002–2011. A generalized ordered logit model allows analyzing bus accident severity and a logistic regression enables examining occurrence of injury to bus passengers. Results Bus accident severity is positively related to (i) the involvement of vulnerable road users, (ii) high speed limits, (iii) night hours, (iv) elderly drivers of the third party involved, and (v) bus drivers and other drivers crossing in yellow or red light. Occurrence of injury to bus passengers is positively related to (i) the involvement of heavy vehicles, (ii) crossing intersections in yellow or red light, (iii) open areas, (iv) high speed limits, and (v) slippery road surface. Conclusions The findings of the current study provide a comprehensive picture of the bus safety situation in Denmark and suggest the necessity of further research into bus drivers’ attitudes and perceptions of risks and road users’ perceptions of bus operations. Moreover, these findings suggest the need for further training into bus drivers’ hazard recognition skills and infrastructural solutions to forgive possible driving errors.European Transport Research Review 01/2014; 6(1):17-30.
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ABSTRACT: Crashes occurring on rural two-lane highways are more likely to result in severe driver incapacitating injuries and fatalities. In this study, mixed logit models are developed to analyze driver injury severities in single-vehicle (SV) and multi-vehicle (MV) crashes on rural two-lane highways in New Mexico from 2010 to 2011. A series of significant contributing factors in terms of driver behavior, weather conditions, environmental characteristics, roadway geometric features and traffic compositions, are identified and their impacts on injury severities are quantified for these two types of crashes, respectively. Elasticity analyses and transferability tests were conducted to better understand the models' specification and generality. The research findings indicate that there are significant differences in causal attributes determining driver injury severities between SV and MV crashes. For example, more severe driver injuries and fatalities can be observed in MV crashes when motorcycles or trucks are involved. Dark lighting conditions and dusty weather conditions are found to significantly increase MV crash injury severities. However, SV crashes demonstrate different characteristics influencing driver injury severities. For example, the probability of having severe injury outcomes is higher when vans are identified in SV crashes. Drivers' overtaking actions will significantly increase SV crash injury severities. Although some common attributes, such as alcohol impaired driving, are significant in both SV and MV crash severity models, their effects on different injury outcomes vary substantially. This study provides a better understanding of similarities and differences in significant contributing factors and their impacts on driver injury severities between SV and MV crashes on rural two-lane highways. It is also helpful to develop cost-effective solutions or appropriate injury prevention strategies for rural SV and MV crashes.07/2014; 72C:105-115.