Jermakian, Jessica S.
Accident Analysis and Prevention
The objective of this paper was to estimate the maximum potential large truck crash reductions in the United States associated with each of four crash avoidance technologies: side view assist, forward collision warning/mitigation, lane departure warning/prevention, and vehicle stability control. Estimates accounted for limitations of current systems.
Crash records were extracted from the 2004–08 files of the National Automotive Sampling System General Estimates System (NASS GES) and the Fatality Analysis Reporting System (FARS). Crash descriptors such as location of damage on the vehicle, road characteristics, time of day, and precrash maneuvers were reviewed to determine whether the information or action provided by each technology potentially could have prevented the crash.
Of the four technologies, side view assist had the greatest potential for preventing large truck crashes of any severity; the technology is potentially applicable to 39,000 crashes in the United States each year, including 2000 serious and moderate injury crashes and 79 fatal crashes. Vehicle stability control is another promising technology, with the potential to prevent or mitigate up to 31,000 crashes per year including more serious crashes — up to 7000 moderate-to-serious injury crashes and 439 fatal crashes per year. Vehicle stability control could prevent or mitigate up to 20 and 11 percent of moderate-to-serious injury and fatal large truck crashes, respectively. Forward collision warning has the potential to prevent as many as 31,000 crashes per year, including 3000 serious and moderate injury crashes and 115 fatal crashes. Finally, 10,000 large truck crashes annually were relevant to lane departure warning/prevention systems. Of these, 1000 involved serious and moderate injuries and 247 involved fatal injuries.
There is great potential effectiveness for truck-based crash avoidance systems. However, it is yet to be determined how drivers will interact with the systems. Actual effectiveness of crash avoidance systems will not be known until sufficient real-world experience has been gained.