Estimating Potential Safety Benefits for Advanced Vehicle Technologies

Transcription

1 Estimating Potential Safety Benefits for Advanced Vehicle Technologies Mikio Yanagisawa June 8, 2016 The National Transportation Systems Center Advancing transportation innovation for the public good U.S. Department of Transportation Office of the Secretary of Transportation John A. Volpe National Transportation Systems Center

2 Presentation Outline Background How do we project potential safety benefits? What is the crash problem? Examine key steps within the process Projecting safety benefits 2

3 Advanced Vehicle Technology Research Division within the Volpe Center Research Crash Avoidance: Identify effective intervention opportunities for vehicle or cooperative based warning and automated systems and estimate potential safety benefits. National crash data query and typology Test procedures and instrumentation Data mining and analysis of naturalistic driving data Safety benefits estimation and simulation tools Also: Safety of Automotive Electronics Also: Vehicle Cybersecurity Safety Benefits Estimation System Evaluation Crash Problem Definition Objective Tests Countermeasure Functions 3

4 Technologies Researched Level Driver Vehicle-Based Cooperative Technology Automatic Controls Vehicle Feature Drowsy Driver Detection Pre-Crash Sensing - Advanced Restraints Intelligent Cruise Control & Forward Collision Warning Lane Change Warning & Lane Drift Warning Lateral Drift Warning & Curve Speed Warning Pedestrian Warning Intersection Movement Assist Left Turn Assist Blind Spot Warning Electronic Emergency Brake Lighting Do Not Pass Warning Vehicle-to-Infrastructure Vehicle-to-Pedestrian Crash Imminent Braking Lane Keeping Technology Cooperative Cruise Control 4

5 Projecting Potential Safety Benefits CCCCCCCCCCCCC AAAAAAAAAAAAAA = # TTTTTTTTTTTT CCCCCCCCCCCCC SSSS CCCCCCCCC Identify and define a safety system SSSS CCCCCCCCC = 1 EEEEEEEEEEEEEEEE RRRRRRRRRR CCCCCCCCCC PPPPPPPPPPPPPPPPPPPP RRRRRRRRRR Exposure Ratio Probability of encountering a driving conflict Crash Prevention Ratio Probability of a crash given an encounter with a driving conflict Ratios are estimated from driver/vehicle/system performance data with and without automated vehicle functions Approach is used in vehicle-based, vehicle-to-vehicle, and pedestrian safety system research Potential to estimate injury mitigation 5

6 Safety Benefits Estimation Data Flow Crash Data Pre-Crash Scenarios Field Data Driving Conflicts Safety Benefits Modeling Crash Probability 6

7 National Crash Trends 7,000 Injury Crashes Fatal Crashes Property Damage Only Crashes 6,000 Number of Crashes (Thousands) 5,000 4,000 3,000 2,000 1, Calendar Year In 2014: 3,026B Miles 275M Registered 214M Licensed Since 2001: VMT 8% Vehicles 24% Drivers 12% Source: NHTSA Traffic Safety Facts 2014, DOT HS

8 Crash Fatalities Trends Number of Fatalities 50,000 45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 Total Fatalities % Pedestrians % Cyclists % Motorcyclist 16% 14% 12% 8% 6% 4% 2% 0% FARS Crash Year Total fatalities have decreased by 9,521 ( 23%) Since 2001: Pedestrians 3% Cyclists 1% Motorcyclists 7% 10% % of All Fatalities Source: NHTSA Traffic Safety Facts 2014, DOT HS

9 Defining 37 Pre-Crash Scenarios Crash Type Pre-Crash Scenario Crash Type Pre-Crash Scenario Animal Animal/maneuver No Driver No driver present Animal/no maneuver Non-Collision Non-collision - No Impact Backing Backing into vehicle Object/maneuver Object Control loss/vehicle action Object/no maneuver Control Loss Control loss/no vehicle action Opposite direction/maneuver Crossing Paths Cyclist Evasive Turn signal Straight crossing non signal non signal Other Other Opposite direction/no maneuver Other - Opposite Direction Other - Turn Across Path Parking Parking/same direction Other - Turn Into Path Other - Straight Paths Running red light Running stop sign Cyclist/maneuver Cyclist/no maneuver Evasive maneuver/maneuver Evasive maneuver/no maneuver Pedestrian/maneuver Pedestrian/no maneuver Rear-end/striking maneuver Rear-end/lead vehicle accelerating Rear-end/lead vehicle constant speed Rear-end/lead vehicle decelerating Rear-end/lead vehicle stopped Other - Rear-End Hit and Run Hit and run Road edge departure/maneuver Lane Change Left Turn Across Path/ Opposite Direction (LTAP/OD) Turning/same direction Changing lanes/same direction Opposite Direction Pedestrian Rear-End Road Departure Drifting/same direction Rollover Rollover Road edge departure/no maneuver Road edge departure/backing signal Sideswipe Other - Sideswipe non signal Vehicle Failure Vehicle failure Source: Pre-Crash Scenario Typology for Crash Avoidance Research, 2007 NHTSA, DOT HS

10 Example Pre-Crash Scenarios Rear-End Lead Vehicle Stopped Left Turn Across Path / Opposite Direction Lane Change Straight Crossing Paths 10

11 Crash Probability Estimation Field Operational Tests Exposure Ratio Objective Tests Historical Research Safety Impact Methodology Tool Crash Prevention Ratio Analysis and Results National Crash Databases INPUTS Pre-Crash Data System Data Driver Data SIMULATION Treatment Crash Counts Impact Speeds ΔV Values ANALYSIS Crash Avoidance System Effectiveness Safety Benefits 11

12 Potential Crash Avoidance Effectiveness 70% 60% 50% 40% 30% 20% 10% 0% Forward Collision Warning Intersection Movement Assist Left Turn Assist Potential System Effectiveness Road Departure Crash Warning Adaptive Cruise Control Electronic Stability Pedestrian Crash Avoidance/Mitigation Ignition Interlock Vehicle Feature Source: Various publications including: New Car Assessment Program, Notice For Proposed Rulemaking, Insurance Institute for Highway Safety research, and Enhanced Safety of Vehicle research 12

13 Example of Potential Safety Benefits Annual Number of Crashes (Thousands) Crashes Reduced - 48% Remaining Crashes 49% Intersection Left Turn Assist Movement Assist Communication-Based Warning System Source: NHTSA V2V Readiness Document, 2014, DOT HS Other Factors Deployment, penetration rates Driver interaction Acceptance, usage, misuse, negligence, and abuse False activation Unintended consequences Operational boundaries Speed, environment Crash statistics over time Improvement of technology 13

14 Questions and Contact Mikio Yanagisawa Advanced Vehicle Technology (617) Volpe Center 55 Broadway Cambridge, MA