IVBSS car prototype set-up for verification test. (Credit: Ryan Harrington, Volpe Center)

The Volpe Transportation Systems Center serves as the independent evaluator of the Integrated Vehicle-based Safety Systems (IVBSS) project, the first large-scale initiative for both light vehicle and heavy truck platforms focused on safety system integration. IVBSS technologies warn drivers in crash-imminent situations, helping to prevent rear-end, lane-change, and road-departure crashes.

IVBSS is a cooperative effort by an industry team led by the University of Michigan Transportation Research Institute and the Department of Transportation (DOT). The team includes the National Highway Traffic Safety Administration (NHTSA), the Federal Motor Carrier Safety Administration (FMCSA), and the Research and Innovative Technology Administration Intelligent Transportation Systems Joint Program Office (RITA JPO).

The IVBSS research initiative seeks to accelerate the introduction and commercialization of integrated vehicle-based crash warning systems for light vehicles and heavy trucks. The objective is to assess potential safety benefits and driver acceptance of the integrated safety systems. These integrated systems are expected to prevent conflicting warnings, reduce false alarms, enhance consumer and fleet operator acceptance, and boost product marketability.

The Volpe Center team worked closely with DOT and industry team members, and provided expert input to the IVBSS program, including:

• IVBSS system design and functionality
• Verification of test procedures for track and public road tests for cars and trucks
• Test-track and public road verification testing of prototype IVBSS on both cars and trucks
• Evaluation of verification test results
• Recommended system performance enhancements prior to the field trials.

Based on test results, the project will proceed with large field operational tests (FOTs) of IVBSS-equipped light vehicles and heavy trucks this year. The Volpe Center team prepared an independent evaluation plan for IVBSS based on data to be collected in the FOTs, developed data mining algorithms, and devised analytical techniques to forecast the safety benefits likely to accrue from widespread national IVBSS deployment.