Analyzing the time to death of pedestrian fatalities: A copula approach

The study aims to investigate the instant fatality likelihood and time to death (lag time) of pedestrian fatalities using a copula-based joint modeling framework. The upper level model investigates whether or not the pedestrian died instantly, while the lower level model investigates time to death for pedestrians who did not die instantly.

The joint model was run on a dataset of 33,615 observations obtained from the Fatality Accident Reporting System for the 2015-2019 period. The effect of roadway and traffic characteristics were investigated on time to death using six copula structures along with their parameterized versions.

Gaussian parameterized copula was found to have the best fit. Weather, Driver age groups, Drunk/ distracted/ drowsy drivers, Hit and Run, Involvement of Large Truck, VRU age group, VRU Gender, Presence of Sidewalk, Presence of Intersection, Light Condition, and Speeding were significant common factors for both sub-models. The factors found to be significant exclusively to one of the sub-models include: Area type for the Binary Logit model, and Presence of Crosswalk and Fire station nearby for the Ordered Logit model.

Instant fatality likelihood increased and lag time for non-instant fatalities decreased for 16-24 year old drivers, drunk drivers, during hit and run situations, when large trucks were involved, for the elderly pedestrians, for female pedestrians, during dark conditions, and when vehicles were speeding. On the other hand, instant fatality likelihood decreased and lag time for non-instant fatalities increased in adverse weather conditions, for elderly drivers, on sidewalks, at intersections, and during daylight hours.

Results can be useful to transportation policymakers and practitioners in implementing countermeasures to improve road safety. These include placing sidewalks, various types of crosswalks, traffic calming measures, and adequate artificial lighting in areas frequented by pedestrians. Alcohol and drug testing need to be enforced.