ITS America – April 2004 The Naturalistic Driving Study: Why are Crashes Occurring? Suzie Lee Research Scientist, Center for Crash Causation and Human Factors

ITS America – April 2004 Introduction There are over 40,000 fatalities and over 3,000,000 injuries each year. “Driver Error” is a contributing factor in over 90% of vehicular crashes. We need to collect data that provide detailed and valid representation of the driving environment to understand –Why crashes are occurring –Crash risk

ITS America – April 2004 The Options to Study Crashes Epidemiological Empirical “Naturalistic”

ITS America – April 2004 Precise knowledge about crash risk Information about important circumstances and scenarios that lead to crashes Reactive Very limited pre-crash information Epidemiological Data Collection Databases lack sufficient detail to be helpful for many applications –The development of crash countermeasures –Assessing the interaction of causal and contributing factors that lead to crashes Empirical Data Collection Proactive Provides important ordinal crash risk info Imprecise, relies on unproven safety surrogate Experimental situations modify driver behavior Often cannot capture the complexities of the driving environment Provides a limited vision of crash likelihood or the reduction potential of a crash countermeasure Large-Scale Pseudo Naturalistic Data Collection “Natural” driver behavior Detailed pre-crash/crash info Distraction Fatigue Aggressive driving Driver errors Vehicle dynamics Potential validation of surrogate measures

ITS America – April 2004 The Naturalistic “100 Car” Study Goal –To create a data collection environment of sufficient external validity, information detail, and scale to begin to understand the relationship between human and other factors that contribute to crashes Real time, continuous data collection for a period of one year for 100 drivers –78 privately-owned vehicles –22 leased vehicles

ITS America – April 2004 “Pseudo-Naturalistic” Approach Highly capable instrumentation (well beyond EDRs) –Five channels of digital, compressed video –Four radar sensors –Machine vision-based lane tracker –Many other sensors: GPS, glare, RF, acceleration, yaw rate, controls, etc. –Tied into vehicle network –Ruggedized, crash tested, all solid state –Crash detection, Fault detection

ITS America – April 2004 This project is:  Collecting naturalistic data to meet IVI Priorities:  rear-end crashes,  driver distraction,  other types of critical events and crashes  Providing infrastructure-based information for VDOT  Serving as a pilot project for a future large-scale instrumented vehicle study  Establish data set requirements  Identify parameters and measures  Evaluate hardware/software candidates Overall Objectives

ITS America – April 2004 Drivers & Data Sources  Drivers have been recruited based upon: –Age, gender, vehicle type driven, miles traveled, location of travel Data Sources  Driving performance data  Video data  General information/identification data  Subject classification data (questionnaires)  Police accident reports

ITS America – April Crashes Thus Far Type of Collision –Run-off-Road 14 –Rear-end Striking 6 –Rear-end Struck 11 –Rear-end, Struck & Striking 2 –Backing 5 –Left turn across path 1 –Lane change 1 12 of 40 Crashes were Police Reported

ITS America – April 2004 Why are Crashes Occurring? Distraction –Inattention to Forward Roadway –Secondary Tasks –Fatigue Speed/Loss of Vehicle Control/Traction Possibly Alcohol or Drugs