Citation

Chajmowicz H, Saadé J, Cuny S. Traffic Injury Prev. 2019; 20(Suppl 2): S20-S25.

Affiliation

Department of Accident Science, CEESAR, Nanterre, France.

Copyright

(Copyright © 2019, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2019.1679797

PMID

31750740

Abstract

Objective: This study aimed to assess the effectiveness of autonomous emergency braking (AEB) systems in car-to-cyclist frontal collisions by simulating their effects, in terms of crash avoidance and injury mitigation, on a representative target population of real-world accidents. Identifying effectiveness-critical AEB-cyclist design parameters through a sensitivity analysis was also targeted.Methods: The analysis is based on a representative set of real-world car-to-cyclist frontal collisions gathered from French police reports. AEB-cyclist-relevant accident cases were first selected and used to build injury risk curves for fatal, severe, and slight cyclist injuries. The effect of AEB-cyclist on these cases was then simulated by means of a car kinematic model involving sensor detection strategies and actuator actions. Combining the resulting simulated impact speed distributions with the injury risk curves allowed to assess AEB-cyclist's effectiveness in terms of lives saved and mitigated injuries. Using design of experiments methods, the sensitivity of this effectiveness with regards to AEB-cyclist design parameters could be assessed.Results: Cyclist injury risks curves were built, along with their confidence intervals, for fatal, severe, and slight injuries using a polytomous complementary log-log regression model, with squared impact speed as an independent variable. A sensitivity analysis on an ideal bisensor AEB-cyclist setting highlighted influential design parameters such as maximal braking intensity or crucial decision algorithm parameters such as maximal time and distance to collision thresholds. AEB-cyclist effectiveness was nevertheless shown to range from 35% to 59% in fatalities, 14% to 54% in severe injuries, and 11% to 42% in slight injuries, depending on field of view parameters alone, once reference values of decision algorithm parameters had been set.Conclusions: This study illustrates the potential benefits and limits of AEB-cyclist systems. High-end systems show acceptable effectiveness rates, but road safety performance strongly depends on external factors such as road surface conditions or has to be tuned in order to avoid unnecessary activations and driver discomfort. Limits of the system's everyday use (lack of maintenance, driver reaction time to collision warnings, etc.) were not taken into account, thus resulting in optimistic evaluations of AEB-cyclist effectiveness.

Language: en

Keywords

AEB; active safety; cyclist; effectiveness; injury risk curve; sensitivity analysis