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Safety Impact Methodology

Explore the Safety Impact Methodology (SIM) tool for assessing connected vehicle safety benefits and evaluating crash prevention scenarios using data sources and simulations. Learn about SIM's ability to estimate effectiveness based on system deployment and scenario evaluation, focusing on rear-end, lane change, and intersection pre-crash simulations. Analyze results for crash ratio, severity, and speed reduction to understand the tool's overall effectiveness in enhancing safety for target populations.

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Safety Impact Methodology

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  1. Safety Impact Methodology Mikio Yanagisawa RITA / Volpe ITS Connected Vehicle Public Meeting Arlington, VA September 24-26, 2013

  2. Safety Benefits – Basic Equations • Data Sources • # Target Crashes: Crash databases (GES, FARS,…) • Exposure Ratio: Field operational tests and controlled experiments • Crash Prevention Ratio:Field tests, objective tests, controlled experiments, and computer simulation Safety Impact Methodology (SIM) tool

  3. SIM Tool Overview Safety Impact Methodology (SIM) Crashes without V2V Probability of crash V distributions Harm from crashes without V2V SIM Tool Crashes prevented Conflict exposure with/ withoutV2V Harm reduced • SIM estimates effectiveness of individual scenarios • SIM estimates are based on 100% system deployment • SIM tool is developed for evaluation, not design

  4. Rear-End Pre-Crash Simulation VEHICLE Host Vehicle State Remote Vehicle State • Number of Crashes • Number of Non-Crashes • Impact Speed Distribution • ΔV Distribution • Host and Remote Effectiveness Rear-End SIM Simulation DRIVER Reaction Time Braking Level Control vs. Treatment SYSTEM Time-to-Collision of Warning Automatic System Activation

  5. Rear-End Pre-Crash Walkthrough (LVS) Control Treatment

  6. Probability of Crash Estimation Example: Lead Vehicle Stopped – Brake Response Initial Conditions vH = Host velocity TTCwarn= Time-to-collision of warning Driver Response tR = Reaction time from warning aH = Host average deceleration • {IFdstop ≤ dinitialTHEN crash is prevented, ELSE crash occurs} • Run Monte Carlo simulations by drawing random numbers from tR & aH distributions and account for crashes occurred and prevented: • tR & aH from drivers without system assistance • tR & aH from drivers withsystem assistance

  7. Lane Change Pre-Crash Simulation VEHICLE Host Vehicle State Remote Vehicle State • Number of Crashes • Number of Non-Crashes • Impact Speed Distribution • ΔV Distribution • Host and Remote Effectiveness Lane Change SIM Simulation DRIVER Driver Reaction Time Driver Counter Steer Control vs. Treatment SYSTEM Initial Lateral Distance

  8. Lane Change Pre-Crash Walkthrough Control Treatment

  9. Intersection Pre-Crash Simulation VEHICLE Host Vehicle State • Remote Vehicle State • Host Distance and Acceleration (Encroaching) • Number of Crashes • Number of Non-Crashes • Impact Speed Distribution • ΔV Distribution • Host and Remote Effectiveness Intersection SIM Simulation DRIVER Driver Reaction Time Driver Braking Level Control vs. Treatment SYSTEM Time-to-Intersection

  10. Straight Crossing Paths – Both Vehicles Moving Control Treatment

  11. Straight Crossing Paths – Stopped and Starting Control Treatment

  12. Input Parameters *Example Mock Data Driver Reaction (Treatment) • Data • Field • Track • Experiment • Literature • Relationships • Dependencies • Flexible • Variable inputs Link? Link? Link? Brake Force (Treatment) Brake Force (Control) Link? Driver Reaction (Control)

  13. SIM Results and Analysis SIM pCrash Crash Ratio Crash Severity Speed Reduction Analysis Pre-crash mode Crash Count Impact Mode Treatment Type Crash Severity • Results from SIM analyzed for effectiveness • Applied to appropriate target population • Pre-crash scenarios combined • Effectiveness estimates lead to overall benefits

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