A Human Centered Systems Research Perspective for Road Safety

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A Human Centered SystemsResearch Perspective
forRoad Safety
Dr. Thomas M. Granda United States Department of
Transportation Federal Highway Administration Offi
ce of Safety Research and Development Human
Centered Systems

• Low-Cost Safety Improvement Technical Advisory
  Committee Meeting
• June 19, 2007

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Overview
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• Introduction
• Description of Human Centered Systems laboratory
  facilities
• Description of nature and scope of research
• Selected areas/studies of behavioral research

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Human Error Crash Causation
K. Rumar, 1985
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Turner-Fairbank Highway Research Center HCS
Research Capabilities
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Sign Simulator Field Research Vehicle Field- Tes
ts, Validation
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• Desktop
• Simulator
• Highway
• Driving
• Simulator
• (HDS)
• Photometric
• Visibility
• Laboratory

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Sign Simulator

• Determine meaning of signage
• Obtain initial estimates of recognition distance

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Low Fidelity Simulation
Field Data Collection
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Field Research Vehicle

• 1999 Saturn SL-1
• Data collection system
• 4 cameras
• Video quad unit
• 3 axis digital accelerometer
• GPS receiver
• Inverter for 120v AC power
• Laptop computer for data storage
• Analog and digital video recording

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Highway Driving Simulator

• Saturn Car cab with 3 df motion base
• 270 degree field of view
• Rear and side view mirrors
• cluster-based PC workstation environment
• GeForce NVidea 7900 GTX Pro graphics cards
• In-house programming using open source code in a
  Linux Environment

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Proper Fit of Research Tools Activities
Research tools proceeds from simple on the left
to complex on the right SQ Survey/Questionnaire
, TA Task Analysis, CM Computer Model, PT
Part Task Simulator, LF Low Fidelity
Simulator, HF High Fidelity Simulator, FT
Field Test
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HCS Program Areas

• Intersections
• Warning to potential crash victims
• Diverging Diamond Interchange
• Pedestrians Bicycles
• Speed Management
• Visibility
• Operations
• Transportation Management Pooled Fund Study
• Traffic Control Device Pooled Fund Study

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Intersections Infrastructure Based Red-Light
Violator Warning

• Test 3 warnings in HDS
• Assess driver response to unexpected warning
• 64 of drivers responded in a way that would
  prevent collision with a red-light violator

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Intersections Field Validation ofRed-Light
Violator Warning

• Assessed unexpected warning on Smart Road
• 90 of drivers stop given 2.7 sec. advance
  warning
• Need to assess driver response when subject
  vehicle is part of a platoon

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IntersectionsRed-Light Violator Warning to
Drivers in Platoons

• Four platoon scenarios
• Lead vehicle brakes
• Lead vehicle does not react to warning
• Vehicle following participant
• No other vehicles present
• Three warning distances (assuming 45 mph)
• 180 ft (2.7 s,)
• 142.5 ft (2.2 s)
• 105 ft (1.6 s)

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Pedestrian Exposure to Risk

• Problem
• Crash statistics must be adjusted
• for exposure
• Risk Crashes / Exposure
• Procedure
• Conducted literature review of 100 papers
• Analyzed previously suggested exposure metrics
• Recommended new metric hundred million
  pedestrian feet of roadway traveled
• Tested feasibility of collecting data with new
  metric at 7 sites in Washington, DC

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Pedestrian Exposure to Risk Sampling Sites

• Calm stop-controlled intersection
• Metro stop mid-block crossing
• Dead-end street with car repairs, etc.
• Busy entertainment area intersection
• Busy Metro stop intersection
• Shopping mall parking lot
• Residential street with many driveways

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Pedestrian Exposure to Risk Findings

• It is feasible to collect data using proposed
  metric
• 8 hour samples at 7 sites in one city yielded
  total of 1.13 million pedestrian feet of roadway
  traveled
• Developed special measurement techniques for
  driveways and parking lots
• Proposed metric has promise to serve as
  denominator of pedestrian risk equation

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Pedestrian Exposure to RiskNext Research Steps

• Collect more samples in a single city
• Test collecting samples in a rural area
• Generalize to entire city or area
• Employ combination of empirical sampling and
  statistical modeling
• Generalize to exposure for entire nation
• Develop validation and update procedures

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Pavement Markings for Speed Reduction Research
Goals
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• Determine a low-cost pavement marking treatment
  with a high probability of success
• Determine the effectiveness of the marking
  through a field evaluation at three different
  locations

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Pavement Markings for Speed Reduction Results

• Peripheral Transverse Lines as a Pavement Marking
  Pattern have the ability to significantly reduce
  vehicle speeds (4 mph reduction in average speeds
  in New York and 5 mph reduction in Mississippi)
• Appear to be most effective with unfamiliar
  drivers and in situations where roadway geometry
  requires a reduction in speed

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Colors for Transponder-Controlled Tollbooth
Lanes Research Goal

• Purpose of study
• Develop a set of sign color recommendations for
  Transponder-Controlled Tollbooth Lanes
• Background Color
• Font Color
• Overlay Color with Pictographs

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Colors for Transponder-Controlled Tollbooth
Lanes Results
Consistent with current practice, signs with a
green background and white font was easiest to
see at larger distances by research participants.
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Human Centered Systems Perspective
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Questions

• View our Website at www.tfhrc.gov
• Contact Tom Granda
• 202-493-3365
• thomas.granda_at_dot.gov