Benefit

Front crash detection, lane maintenance, and blind spot detection technologies have the potential to prevent 8,000 two-vehicle crashes with motorcycles per year.

This study examined crash avoidance technologies using passenger vehicle crash data in the United States.


August 2017
Nationwide; United States


Summary Information

This report looked at crash avoidance technologies in passenger vehicles, such as front crash prevention, lane maintenance, and blind spot detection, and the potential benefits of refining them to detect motorcycles. Data from the Fatality Analysis Reporting System and the National Automotive Sampling System-General Estimates System were analyzed for crashes involving motorcycles during 2011-2015.

Findings
  • This analysis shows that three passenger vehicle crash avoidance technologies – front crash prevention, lane maintenance, and blind spot detection – have the potential to prevent more than 8,000 two-vehicle crashes with motorcycles per year.
  • Front crash prevention had the largest potential in passenger vehicle-motorcycle crashes, potentially preventing 4 percent of fatal crashes, 10 percent of non-fatal injury crashes and 13 percent of police-reportable crashes of any severity
  • Crashes relevant to lane maintenance systems accounted for 4 percent of fatal crashes, 3 percent of nonfatal injury crashes, and 4 percent of all police-reportable crashes.
  • Same-direction sideswipe crashes in which the passenger vehicle deliberately changed lanes, or those relevant to blind spot detection, included 95 fatal crashes (1 percent), 8,479 nonfatal injury crashes (6 percent), and 10,953 police-reported crashes (6 percent).

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Source

Motorcycle crashes potentially preventable by passenger vehicle crash avoidance technology

Author: Teoh, Eric R.

Published By: Insurance Institute for Highway Safety

Source Date: August 2017

URL: http://www.iihs.org/frontend/iihs/documents/masterfiledocs.ashx?id=2144

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Goal Areas

Safety

Typical Deployment Locations

Metropolitan Areas, Statewide

Keywords

None defined

Benefit ID: 2018-01303