Developments in Cooperative Intelligent VehicleHighway Systems

1
Developments in Cooperative Intelligent
Vehicle-Highway Systems Human Factors
Implications

• Richard Bishop
• Bishop Consulting
• www.IVsource.net

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Introduction

• Cooperative Intelligent Vehicle-Highway Systems
  (CIVHS) offer potential to enhance effectiveness
  of active safety systems
• Autonomous systems are limited
• autonomous vehicle systems limited by laws of
  physics and cant see everything
• autonomous infrastructure systems cant affect
  vehicle or driver decision-making process
• CIVHS
• cooperative vehicleltgtvehicle, vehicleltgtroad
• intelligent multi-variate algorithms employed

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Purpose of Study

• Collect information on various forms of CIVHS
  worldwide
• Assess RD, deployment issues, standards
  development, and government policies
• Gain a sense of future trends
• Based on interaction with governments, vehicle
  industry, and academia

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CIVHS Application Areas (1)

• Safety -- Crash Avoidance
• hazards undetectable by the vehicle (blind
  curves, vehicles in crossing path, signalized
  intersections with limited sight distance)
• failure to slow for traffic signal or stop sign
• environmental / roadway condition info
• roadway geometry info
• animal activity
• Safety -- Enhanced Driver Awareness
• warning of obstacles driver may not see (such as
  pedestrian when turning)

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CIVHS Application Areas (2)

• Safety -- Compliance
• provision of speed limit information
• Traffic Flow
• micro-dynamic speed control to smooth traffic
• traffic signal response assist (start-up on
  green)
• Navigation
• collect mapping data to refine digital map
  databases
• receive mapping updates

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Input and Perspectives

• Public sector perspectives gained from
  California, Canada, Japan, Germany, Netherlands,
  U.S., Sweden, United Kingdom
• Private sector perspectives collected from AHSRA,
  General Motors, Mercedes Benz, Fiat, BMW,
  Renault,Visteon, Delphi, Cofiroute
• Academia / labs represented by TUV Rhineland,
  PATH, Western Transportation Institute

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Deployment Issues

• Stand-out Application Areas
• Enhanced ACC providing info on external factors
  to adjust vehicle parameters
• Intelligent Speed Adaptation haptic feedback to
  driver dynamic speeds based on conditions
• Intersection Collision Avoidance autonomous or
  cooperative?
• How to Gather External Information
• Floating car data collection using DSRC, toll
  tags, electronic license plates
• Infrastructure-based sensing problematic for
  many, but not all (may just have to live with
  crashes at blind curves, etc.)
• Vehicles can be designed to receive external info
  regardless of the means of data collection

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Standards Issues

• Standards seen as key to deployment
• Must focus on the what not the how
• parameters and types of information flowing
  between vehicles and external world
• External Adaptation Factors for ACC now a Work
  Item within TC 204 Working Group 14
• Advanced version of ACC which responds to
  externally-provided information to adjust speed
  and other parameters for safe operation
• Information only vehicle/driver determines
  response
• Infrastructure agencies must become actively
  involved in CIVHS standards process

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Parameters to/from Vehicle in CIVHS

• Ten categories of parameters identified, with
  over 50 sub-parameters
• Each category assessed by respondents in terms of
  feasibility, deployment timeframe, and degree of
  usefulness
• Listed in final report

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Parameters to/from Vehicle in CIVHS Category 1

• Obstacle in Projected Path of Vehicle
• obstacle type vehicle
• moving/stopped
• trajectory, speed, relative location, vehicle
  type
• obstacle type animal
• in road / out of road
• obstacle type pedestrian

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Parameters to/from Vehicle in CIVHS Category 2, 3

• Speed Advice
• current speed limit
• advisory speed
• lane-by-lane speed designation
• Gap Advice
• allowable minimum gap size

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Parameters to/from Vehicle in CIVHS Category 4

• Environmental Condition
• Precipitation
• rain, snow, sleet, type, intensity
• Freezing
• surface freezing conditions detected
• Visibility
• fog, smoke, dust, measured visibility (distance)

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Parameters to/from Vehicle in CIVHS Category 5

• Road Condition
• measurements/characterization of road surface
• dry, wet, water-covered, ice, slush, snow,
  snow-packed
• density/depth
• calculated available coefficient of friction

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Parameters to/from Vehicle in CIVHS Category 6

• Road Geometry
• intersection
• road path / geometry
• grade
• superelevation
• lane width
• number of lanes
• bridge height
• distance to feature and/or relative location

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Parameters to/from Vehicle in CIVHS Category 7, 8

• Road Use Status
• road open/closed
• reversible lane status
• shoulder use status
• Automated Vehicle Operation
• adjacent vehicle parameters
• relative location, speed, braking, intention,
  faults, requests for speed change / lane change
• approval for automated operation

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Parameters to/from Vehicle in CIVHS Category 9

• Traffic Control Devices
• sign
• stop, yield, one-way, other
• signal
• green, red, transition, left turn only, right
  turn only, flashing

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Parameters to/from Vehicle in CIVHS Category 10

• Messages from Host Vehicle
• local broadcast
• my car disabled, vehicle location
• to roadside or electronic infrastructure
• probe information speed, obstacle location,
  measured traction, foglamp status, rain sensor
  status, hazard flasher status, stability control
  status, end of traffic queue
• to adjacent vehicles
• create gap, change lanes, location of addressed
  vehicle

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Human Factors Implications (1)Shared Control

• Drivers must adapt successfully to a shared
  control paradigm in vehicle operation
• shared control already exists
• ABS, Traction Control, Stability Control
• either drivers fully understand the system
  operation, or
• system operation is transparent
• ex cooperative merge function where gap just
  shows up

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Human Factors Implications (2)User
Participation Choices

• Voluntary participation approaches may be a
  necessary factor for successful deployment
• Envision a designated lane in which driver turns
  over control of speed to a central manager in
  order to optimize traffic flow
• Will driver be willing to give up control for
  perceived benefits?

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Human Factors Implications (3)User Expectations

• External Inputs Not Available Everywhere
• Inform driver of availability via dashboard icon?
• Best to under-promise / over-deliver

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Human Factors Implications (4)Higher Awareness
for Drivers

• Data exchange between vehicles and sensors
  creates
• greater awareness as to unusual/hazardous
  conditions ahead
• thus, fewer surprises
• Measure of Effectiveness
• Reduction in number of emergency maneuvers

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Human Factors Implications (5)Driver Advisories
In-Vehicle or Roadside?

• Which is more effective? To what degree?
• Drives design / deployment discussions for
  Intersection Collision Avoidance, etc.
• Too much clutter in external environment for
  roadside warning to be effective
• In-vehicle is probably more effective, but how
  much?
• Compelling enough to accelerate deployment?
• Roadside warnings reach everyone

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Summary Observations

• For CIVHS, wide variations in level of investment
  and sense of deployment timing
• Floating car data collection approaches very
  promising as a virtual sensing infrastructure
• dont need to solve infrastructure deployment
  issues before proceeding
• More infrastructure agencies must become
  champions for significant progress to occur
• Quantitative human factors input important to
  process of defining systems

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Cooperative Intelligent Vehicle-Highway Systems
for Driver Assistance Status of Activities
Worldwide, Stakeholder Perspectives, Major
TrendsFinal Report available at
www.IVsource.net(comments welcome at
richardbishop_at_mindpsring.com)