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Intersection crashes are a frequent and dangerous crash mode in the U.S. Emerging Intersection Advanced Driver Assistance Systems (I-ADAS) aim to assist the driver to mitigate the consequences of vehicle-to-vehicle crashes at intersections. In support of the design and evaluation of such intersection assistance systems, characterization of the road, environment, and drivers associated with intersection crashes is necessary. The objective of this study was to characterize intersection crashes using nationally representative crash databases that contained all severity, serious injury, and fatal crashes. This study utilized four national crash databases: the National Automotive Sampling System, General Estimates System (NASS/GES); the NASS Crashworthiness Data System (CDS); and the Fatality Analysis Reporting System (EARS) and the National Motor Vehicle Crash Causation Survey (NMVCCS).

The availability of active safety systems, such as Lane Departure Warning (LDW), has recently been added as a rating factor in the U.S. New Car Assessment Program (NCAP). The objective of this study is to determine the relevance of the NCAP LDW confirmation test to real-world road departure crashes. This study is based on data collected as part of supplemental crash reconstructions performed on 890 road departure collisions from the National Automotive Sampling System, Crashworthiness Data System (NASS/CDS). Scene diagrams and photographs were examined to determine the lane departure and lane marking characteristics not available in the original data. The results suggest that the LDW confirmation test captures many of the conditions observed in real-world road departures. For example, 40% of all single vehicle collisions in the dataset involved a drift-out-of-lane type of departures represented by the test.

The goal of this paper is to estimate near-side injury risk in vehicles with the best side impact performance in the U.S. New Car Assessment Program (NCAP). The longer-term goal is to predict the incidence of crashes and injury outcomes in the U.S. in a future fleet of the 2025-time frame after current active and passive safety countermeasures are fully implemented. Our assumption was that, by 2025, all new vehicles will have side impact passive safety performance equivalent to current U.S. NCAP five star ratings. The analysis was based on real-world crashes extracted from case years 2010-2015 in the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS) in which front-row occupants of late-model vehicles (Model Year 2011+) were exposed to a near-side crash.

Road departures are one of the most deadly crash modes, accounting for nearly one third of all crash fatalities in the US. Lane departure warning (LDW) systems can warn the driver of the departure and lane departure prevention (LDP) systems can steer the vehicle back into the lane. One purpose of these systems is to reduce the quantity of road departure crashes. This paper presents a method to predict the maximum effectiveness of these systems. Thirty-nine (39) real world crashes from the National Automotive Sampling System (NASS) Crashworthiness Data System (CDS) database were reconstructed using pre-crash velocities downloaded for each case from the vehicle event data recorder (EDR). The pre-crash velocities were mapped onto the vehicle crash trajectory. The simulations assumed a warning was delivered when the lead tire crossed the lane line. Each case was simulated twice with driver reaction times of 0.38 s and 1.36 s after which time the driver began steering back toward the road.

Intersection collisions currently account for approximately one-fifth of all crashes and one-sixth of all fatal crashes in the United States. One promising method of mitigating these crashes and fatalities is to develop and install Intersection Advanced Driver Assistance Systems (I-ADAS) on vehicles. When an intersection crash is imminent, the I-ADAS system can either warn the driver or apply automated braking. The potential safety benefit of I-ADAS has been previously examined based on real-world cases drawn from the National Motor Vehicle Crash Causation Survey (NMVCCS). However, these studies made the idealized assumption of full installation in all vehicles of a future fleet. The objective of this work was to predict the reduction in Straight Crossing Path (SCP) crashes due to I-ADAS systems in the United States over time. The proportion of new vehicles with I-ADAS was modeled using Highway Loss Data Institute (HLDI) fleet penetration predictions.

Lane Departure Warning (LDW) is a production active safety system that can warn drivers of an unintended departure. Critical in the design of LDW and other departure countermeasures is understanding pre-crash driver behavior in crashes. The objective of this study was to gain insight into pre-crash driver behavior in departure crashes using Event Data Recorders (EDRs). EDRs are units equipped on many passenger vehicles that are able to store vehicle data, including pre-crash data in many cases. This study used 256 EDRs that were downloaded from GM vehicles involved in real-world lane departure collisions. The crashes were investigated as part of the NHTSA's NASS/CDS database years 2000 to 2011. Nearly half of drivers (47%) made little or no change to their vehicle speed prior to the collision and slightly fewer decreased their speed (43%). Drivers who did not change speed were older (median age 41) compared to those who decreased speed (median age 27).

Four crash modes are overrepresented in traffic fatalities: run-off-road crashes, non-tracking run-off-road crashes, head-on crashes, and pedestrian crashes. Two advanced driver assist systems developed to help prevent tracking run-off-road crashes and head-on crashes are lane departure warning (LDW) and lane keeping assist (LKA). LDW acts to warn the driver when they are encroaching the lane boundary, whereas LKA performs automatic steering to prevent the vehicle from departing the lane. The objective of this research was to use real-world crash data to estimate current LDW and LKA system effectiveness in reducing run-off-road crashes and cross-centerline head-on crashes. All passenger vehicles that experienced a lane departure from 2017 to 2019 in the Crash Investigation Sampling System (CISS) were analyzed.