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U.S. Department of Transportation U.S. Department of Transportation Icon United States Department of Transportation United States Department of Transportation

Passenger Vehicle-Motorcycle Pre-Crash Trajectory Reconstruction Results Based on an Extended Application of the NHTSA-Honda-DRI ACAT Safety Impact Methodology

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Advanced Crash Avoidance Technologies (ACATs) such as Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) have been developed for Light Passenger Vehicles (LPVs) to avoid and mitigate collisions with other road users and objects. However, the number of crashes, injuries, and fatalities in the United States involving motorcycles (MCs) has remained relatively constant. As a result, the relative percentage of US traffic fatalities involving a motorcycle has increased from 11% in 2006 to 14% in 2015 (Source: NHTSA 2015 Traffic Safety Facts). Advanced driver assistance systems and future automated vehicle technologies also need to be effective in avoiding collisions with motorcycles. This paper describes the application of the NHTSA-Honda-DRI ACAT Safety Impact Methodology (SIM) to the evaluation of LPV ACAT system effectiveness in avoiding and mitigating collisions with motorcycles.

Towards this goal, the ACAT SIM Crash Scenario Database Development Tools have been extended to reconstruct real-world LPV-MC pre-crash/crash scenarios based on the recently completed Motorcycle Crash Causation Study (MCCS) data. Reconstructed pre-crash trajectory results using this extended tool indicate three main types of LPV-MC pre-crash conflicts. This information can potentially help define requirements for LPV-MC crash countermeasures and the development of performance confirmation tests (e.g., New Car Assessment Program (NCAP)). These pre-crash scenarios can also be integrated into the SIM Crash Sequence Simulation Module in order to estimate the safety benefits and effectiveness of the countermeasures. Overall, this paper illustrates how in-depth crash data can be used to reconstruct pre-crash vehicle control inputs and resulting motions.

Publishing Date:
January 2018
FHWA Program(s):
AMRP Program(s):
Safety Data and Analysis
FHWA Activities:
Highway Safety Information System
Subject Area:
Safety and Human Factors