Center for Injury Research and Prevention

Efficacy of Automatic Emergency Braking Among Risky Drivers Using Counterfactual Simulations from the SHRP2 Naturalistic Driving Study

TitleEfficacy of Automatic Emergency Braking Among Risky Drivers Using Counterfactual Simulations from the SHRP2 Naturalistic Driving Study
Publication TypeJournal Article
Year of Publication2020
AuthorsSeacrist T, Sahani R, Chingas G, Douglas EC, Graci V, Loeb H
JournalSafety Science
Date Published08/2020
Abstract

Motor vehicle crashes remain a significant problem in the US and worldwide. Automatic emergency braking (AEB) is designed to mitigate the most common crash mode: rear-end striking crashes. However, assessing the efficacy of AEB in real-world crash scenarios is challenging given that avoided crashes are rarely documented except during naturalistic driving studies. In the absence of such data, AEB can be evaluated in real-world crash scenarios by retrospectively adding AEB to naturalistic crashes using counterfactual simulations. AEB was retrospectively applied to rear-end striking crashes (n = 40) from the SHRP 2 database among teen (16–19 yrs), young adult (20–24 yrs), adult (35–54 yrs), and older (70+ yrs) drivers. Real-world AEB deceleration profiles from IIHS AEB tests were paired with SHRP 2 vehicles based on vehicle make and class. AEB onset for SHRP 2 crashes was based on a brake threat number (BTN) algorithm. AEB curves were adjusted to match the speed of the vehicle at AEB onset. AEB deceleration curves were scaled based on road surface conditions. Driver reaction was accounted for by beginning the deceleration curve at the current driver-initiated braking level. Overall, AEB was found to be very effective, preventing 83% (n = 33) of rear-end striking crashes. However, AEB was less effective for crashes that occurred at higher speeds and during inclement weather conditions. These data provide a counterfactual evaluation of AEB that can be used by OEMs to prioritize AEB optimization for higher speed crashes and sub-optimal road conditions.

URLhttps://doi.org/10.1016/j.ssci.2020.104746
DOI10.1016/j.ssci.2020.104746