Pedestrian fatality and impact speed squared: Cloglog modeling from French national data

ABSTRACT

Objective: The present study estimates pedestrians' risk of death according to impact speed when hit by a passenger car in a frontal collision.

Methods: Data were coded for all fatal crashes in France in 2011 and for a random sample of 1/20th of all road injuries for the same year and weighted to take into account police underreporting of mild injury. A cloglog model was used to optimize risk adjustment for high collision speeds. The fit of the model on the data was also improved by using the square of the impact speed, which best matches the energy dissipated in the collision.

Results: Modeling clearly demonstrated that the risk of death was very close to 1 when impact speeds exceeded 80 km/h. For speeds less than 40 km/h, because data representative of all crashes resulting in injury were used, the estimated risk of death was fairly low. However, although the curve seemed deceptively flat below 50 km/h, the risk of death in fact rose 2-fold between 30 and 40 km/h and 6-fold between 30 and 50 km/h. For any given speed, the risk of death was much higher for more elderly subjects, especially those over 75 years of age. These results concern frontal crashes involving a passenger car. Collisions involving trucks are far less frequent, but half result in the pedestrian being run over, incurring greater mortality.

Conclusions: For impact speeds below 60 km/h, the shape of the curve relating probability of death to impact speed was very similar to those reported in recent rigorous studies. For higher impact speeds, the present model allows the curve to rise ever more steeply, giving a much better fit to observed data. The present results confirm that, when a pedestrian is struck by a car, impact speed is a major risk factor, thus providing a supplementary argument for strict speed limits in areas where pedestrians are highly exposed.

KEYWORDS:

• Crash
• pedestrian
• impact speed
• fatality
• statistical modeling

Acknowledgments

This study was based on data collected as part of the Voiesur project. Particular thanks are due to the project leader, Cyril Chauvel (LAB), and the Methodology Officer in charge of determining speeds, Vuthy Phan (Ceesar). The extrapolation method developed by Emmanuelle Amoros (IFSTTAR) was previously made possible using the data of the Rhône Road Accident Registry, managed by Blandine Gadegbeku, Amina Ndiaye, and Bernard Laumon (IFSTTAR).

Funding

Funding was provided by the French National Research Agency.