Advanced Crash Avoidance Technologies (ACAT) Program - Final Report of the Volvo-Ford-UMTRI Project: Safety Impact Methodology for Lane Departure Warning - Method Development and Estimation of Benefits
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2010-10-01
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TRIS Online Accession Number:01358017
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Edition:Final Report
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Abstract:The Volvo-Ford-UMTRI project: Safety Impact Methodology (SIM) for Lane Departure Warning is part of the U.S. Department of Transportation's Advanced Crash Avoidance Technologies (ACAT) program. The project developed a basic analytical framework for estimating safety benefits in the form of computed reductions in US crash numbers assuming the vehicle fleet was fully equipped with Volvo Lane Departure Warning (LDW) systems. Attention was limited to crashes initiated by the lane departure of a light passenger vehicle. The SIM uses computer models, Monte-Carlo methods and extensive batch simulations to fuse together diverse data sources into a Virtual Crash Population. The simulation model incorporates sub-models for the driver, vehicle, environment and technology (DVET model). The simulated population of virtual crashes makes use of historical crash data (NASS GES and Michigan Crash File), naturalistic driving data, objective test data from test track and driving simulator experiments, as well as highway data to populate the environmental sub-model. The vehicle model was based on a representative mid-sized sedan, and test data was used to estimate initial conditions, parameters and parameter ranges in the various sub-models. The driver component of the DVET model includes sensing, information processing and control action modules, and represents the stochastic effects of distraction and delayed driver reaction to a lane departure event. Batch simulations were run in cases where the LDW technology model is active or suppressed. Taken together with estimates of system availability and driver responsiveness, an estimate for the range of safety benefits was developed. The SIM provides detailed indications of how the DVET components are expected to interact in the field, and hence the results provide safety-related information that goes beyond the numerical benefit estimates, considered preliminary in this first analysis. This project was led by the Ford Motor Company.
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