Estimation of Safety Benefits for Heavy-Vehicle Crash Warning Applications Based on Vehicle-to-Vehicle Communications

Guglielmi, John; Yanagisawa, Mikio; Swanson, Elizabeth; Stevens, Scott; Najm, Wassim · 2017 · ROSA P / United States. Department of Transportation. National Highway Traffic Safety Administration

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Summary

This report, produced by Volpe National Transportation Systems Center for the National Highway Traffic Safety Administration, establishes a methodology to estimate the crash avoidance effectiveness and potential safety benefits of vehicle-to-vehicle (V2V) communications for heavy vehicles. The study addresses the challenge of assessing safety benefits for emerging technologies that lack widespread real-world crash data. It focuses on three specific crash warning applications: Intersection Movement Assist (IMA), Forward Crash Warning (FCW), and Blind Spot/Lane Change Warning (BSW/LCW). The analysis assumes full deployment, where all heavy vehicles are equipped with these applications and all other motor vehicles transmit basic safety information to them. The methodology integrates data from multiple sources to simulate driving conflicts and driver responses. Baseline crash populations were derived from the 2011–2013 General Estimates System (GES) database, targeting multi-vehicle crashes involving at least one heavy vehicle without driver impairment or control loss. Driver and vehicle performance data were obtained from the National Advanced Driving Simulator (NADS) study and the Integrated Vehicle-Based Safety System (IVBSS) field operational test. These inputs were processed using the Safety Impact Methodology (SIM) tool, which employs Monte Carlo simulations of basic kinematics to estimate crash probabilities in baseline conditions versus treatment conditions with V2V assistance. The study identified an annual target population of 92,875 police-reported crashes, associated with a comprehensive cost of approximately $14.275 billion and 1,561 equivalent lives lost. The results indicate that the three V2V applications achieve a crash avoidance effectiveness of 45–49%. Specifically, IMA is projected to avoid 22,744 crashes annually, saving $5.528 billion and 604 equivalent lives. FCW is estimated to prevent 13,541 crashes, saving $1.921 billion and 209 equivalent lives. BSW/LCW is projected to avoid between 5,353 and 9,490 crashes, saving $225–$399 million and 25–44 equivalent lives. Collectively, these applications could reduce annual crashes by 41,638 to 45,775, saving between $7.674 billion and $7.848 billion and preserving 838 to 857 equivalent lives. The significance of this work lies in providing a validated framework for quantifying the safety benefits of V2V technology in the absence of extensive field crash data. By demonstrating substantial potential reductions in crash frequency, costs, and fatalities, the report supports government efforts to promote the development and deployment of cooperative vehicle safety systems. The findings offer policymakers and industry stakeholders concrete evidence of the economic and human safety value of equipping heavy vehicles with V2V crash warning applications.

Key finding

The three selected V2V crash warning applications have an estimated 45-49 percent crash avoidance effectiveness, resulting in an annual reduction of between 41,638 and 45,775 police-reported crashes and saving between $7,674 million and $7,848 million in comprehensive costs.

Methodology

modeling

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• adas effectiveness
• naturalistic crash near crash
• induced exposure
• incidence prevalence
• v2x connected vehicle
• telematics crash prediction

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Applied Guidance: countermeasure evaluation
• Empirical Findings: crash risk outcomes
• Methodological Resource: dataset resource