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This study examines the effects of an aftermarket crash avoidance system on warning rates and driver acceptance in urban and rural environments. The study analyzes the impact of various crash avoidance technologies, such as lane departure warning, forward collision warning, and adaptive cruise control. The findings indicate that these technologies significantly reduce the risk of relevant police-reported crashes and improve driver acceptance. The study also explores the usefulness and self-reported experiences of drivers with the aftermarket crash avoidance system.
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Effects of an Aftermarket Crash Avoidance System on Warning Rates and Driver Acceptance in Urban and Rural Environments ADTSEA 2019 Burlington VT July 22, 2019 Ian J. Reagan, Ph.D. Senior Research Scientist
Vehicle Automation and Crash Avoidance Features Lane Maintenance • Lane Departure Warning (LDW) • Lane Keep Assist Front Crash Prevention • Forward Collision Warning (FCW) • Automatic Emergency Braking (AEB) Adaptive Cruise Control (ACC) Blind Spot Monitoring / Park Assist • Rear cross traffic alert • Rear crash prevention Fatigue Alert Electronic Stability Control
Crash avoidance technologies are working Effects on relevant police-reported crash types statistically significant injury all severities
New vehicle series with forward collision warning By model year
Registered vehicles with forward collision warning By calendar year
Estimated registered vehicles by feature Calendar years 2016 and 2021
Aftermarket crash avoidance systems Mobileye-630 crash avoidance technologies Telematics • record of warnings issued, speed, posted limit, GPS, hard accelerations forward collision warning (FCW) and urban forward collision warning (UFCW) lane departure warning (LDW) headway monitoring (HWM) pedestrian collision warning (PCW) speed limit information (SLI)
Study Methods 22 participants w/ Mobileye • 15 also with telematics Independent variables • Primary roadway type: • urban (Arlington, VA) and rural (Ruckersville, VA) • Study period: • Mobileye data (baseline, treatment); • self-report data (week 2 and week 8 surveys)
Study timeline and procedure 8 week treatment, alerts active 4 week baseline, alerts silent 1 week washout 1 week washout alerts activated installations, May 2017 week 2 post-activation survey week 8 post-activation survey
Forward collision warning Mean warning rate per 100 miles driven study period: F(1,13)=6.01, p=0.03 location: F(1,13)=5.06, p=0.04 interaction: F(1,13)=0.34, p=0.57
Forward collision warning Mean warning rate per 100 miles driven study period: F(1,13)=6.01, p=0.03 location: F(1,13)=5.06, p=0.04 interaction: F(1,13)=0.34, p=0.57
Headway monitoring warnings (HMW) Mean warning rate per 100 miles driven study period: F(1,13)=7.30, p=0.02 location: F(1,13)=7.55, p=0.02 interaction: F(1,13)=1.96, p=0.18
Lane departure warning (LDW) Mean warning rate per 100 miles driven study period: F(1,13)=4.67, p=0.05 location: F(1,13)=3.80, p=0.07 interaction: F(1,13)=2.04, p=0.18
Mobileye safety score Rural Urban study period: F(1,13)=7.35, p=0.02 location: F(1,13)=6.10, p=0.03 interaction: F(1,13)=2.53, p=0.14
Criticality, urgency, and annoyance for FCW, LDW, and HMW Mean Rating
Self-report experience (agree/disagree) Would like to turn off (FCW or LDW) Increased following distance because of HMW Reduced time spent driving over the posted limit because of SLI Mobileye helped improve safety while driving
Self-report experience (agree/disagree) Would like to turn off (FCW or LDW) • FCW: 84 percent disagreed, LDW: 81 percent disagreed Increased following distance because of HMW • 48 percent disagreed, 48 percent agreed Reduced time spent driving over the posted limit because of SLI • 67 percent disagreed, 15 percent agreed Mobileye helped improve safety while driving • 19 percent disagreed, 67 percent agreed
Conclusion Warning-triggering behaviors less frequent when warnings present • The warnings work! Roadway conditions modify driving risk, change possible with feature Research need: Effects of age?
Ian J. Reagan, Ph.D. Senior research scientist ireagan@iihs.org