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SAfety VEhicles using adaptive Interface Technology Phase 1 Research Program Quarterly Program Review. Task 9: Safety Warning Countermeasures Matthew Smith Aug 12, 2003. Task description. Team Members: Delphi: Matthew Smith (Lead), Harry Zhang Ford: Ksenia Kozac, Jeff Greenberg

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Task 9 safety warning countermeasures matthew smith aug 12 2003

SAfety VEhicles using adaptive Interface Technology Phase 1 Research ProgramQuarterly Program Review

Task 9: Safety Warning Countermeasures

Matthew Smith

Aug 12, 2003

Task description
Task description

  • Team Members:

    • Delphi: Matthew Smith (Lead), Harry Zhang

    • Ford: Ksenia Kozac, Jeff Greenberg

  • Objective:

    • Enhance safety warning countermeasures to adaptively respond to distraction, gaze, demand, and intent information, e.g.,

      • Deliver earlier warnings for distracted drivers

      • Minimize nuisance alerts when the driver is attending on intending a maneuver

  • Purpose:

    • Improve system effectiveness and driver acceptance of safety warning countermeasures and support the evaluation of adaptive enhancements

    • Reducing false alarms may increase the credibility of the warnings so that they are less likely to be ignored

    • Earlier warnings for distracted drivers may reduce the number of collisions

Deliverables and schedule
Deliverables and Schedule

  • Deliverables:

    • Task 9A: A report based on the literature review and updated task definition document

    • Task 9B: A report that specifies the adaptive enhancements to the countermeasures, describes the research conducted to reach the provided specification, and proposes preliminary guidelines and standards (to be reviewed in Task 12)

  • Schedule:

    • 9A: Literature Review

      • First draft of literature review is complete

      • First draft currently under internal Delphi review before external circulation

    • 9B: Identify Adaptive Countermeasures

      • Identified Countermeasure Systems

      • Identified Adaptive Enhancement Issues

      • Defined and Described Potential Adaptive Enhancements

      • Selected and coded FCW algorithm

      • Selected FCW DVI

      • Preliminary Design BRT Study complete

Literature review task 9a
Literature Review: Task 9a

  • Research Areas of Interest / Literature Review Sections









    • Ford may be adding a short Curve Speed Warning (CSW) section

  • Key Source Material

    • Collision Types (Najm, Sen, Smith, & Campbell, 2003)

    • Rear-end crashes and countermeasures (Burgett, Carter, Miller, Najm, & Smith, 1998; Knipling, Hendricks, Koziol, Allen, Tijerina, & Wilson, 1992; ACAS FOT reports, 2002-2003)

    • Lane change crashes and countermeasures (Chovan, Tijerina, Alexander, Hendricks, 1994; Tijerina, & Hetrick, 1997)

    • Intersections crashes and countermeasures (Pierowicz, Jocoy, Lloyd, Bittner, Pirson, 2000)

    • SVRD crashes and countermeasures (Pomerleau, Jochem, Thorpe, Batavia, Pape, Hadden, McMillan, Brown, and Everson, 1999)

Task 9a literature review major findings
Task 9a: Literature ReviewMajor Findings


Light Vehicle Crashes

(Najm, Sen, Smith, & Campbell, 2003)

Roadway Fatalities

(U.S. Department of Transportation, 1997)

Task 9a literature review major findings cont
Task 9a: Literature ReviewMajor Findings (cont.)

  • Rear-end Crashes

    • Most prevalent category of crashes

    • Knipling et al. (1992) estimated that over ¾ of rear-end collisions involve driver inattention (including inattentive and following too closely)

    • Forward Collision Warning (FCW) systems are designed to prevent RE collisions but from the ACAS FOT program appear to have high nuisance alert rates

      • Many participants complained that the warnings are too late if they are not attentive and unnecessary when they are attentive

  • Road departure Crashes

    • Largest cause of roadway fatalities (36%)

    • Mironer and Hendricks (1994) estimated 9% of SVRD involve driver inattention to lane keeping (25% to driver impairment)

    • Lane Drift Warning (LDW) designed to prevent unintentional lane departure

    • Curve Speed Warning (CSW) designed to prevent roadway departures caused by excessive speed on curved road segments

Task 9a literature review major findings cont1
Task 9a: Literature ReviewMajor Findings (cont.)

  • Intersection Crashes

    • Second most prevalent category of crashes

    • Different countermeasures for different types of accidents (Pierwowicz et al., 2000)

    • Most sub-categories of intersection crashes require infrastructure support

    • Stop-sign violation warning (SSVW) involves simple sensor requirements and can target 18% of all intersection accidents

  • Lane Change/ Merge Crashes

    • 9% of collisions and 1% of fatalities

    • Wang et al. (1996) estimated 5.6% attributed to driver distraction and 17.2% to Looked-but-did-not-see (LBDNS)

    • Many blind-spot warning systems have emerged on the market

    • Many researchers suggest activating higher-levels of warning using the turn signal or some other indication of driver intention

Task 9a literature review countermeasure systems
Task 9a: Literature Review Countermeasure Systems

  • Forward Collision Warning (FCW)

    • Strong relationship to driver distraction

    • Problematic nuisance alerts

    • Task 9 (SWC) will investigate FCW

  • Lane Drift Warning (LDW)

    • Problematic nuisance alerts (e.g., intentional lane changes)

    • Task 9 (SWC) task likely to investigate LDW

    • If not feasible for SAVE-IT on-road testing/prototype vehicle it may still be feasible in driving simulator analyses

  • Curve Speed Warning (CSW)

    • Can develop relatively simple system with GPS/Map matching

    • Ford is currently considering supporting this activity for SAVE-IT

  • Stop Sign Violation Warning (SSVW)

    • Simple system

    • Task 9 (SWC) likely to investigate SSVW

  • Blind Spot Warning (BSW)

    • Difficult to evaluate in single-channel driving simulator in Phase I

Task 9a literature review forward collision warning fcw
Task 9a: Literature Review Forward Collision Warning (FCW)

  • Algorithm Alternatives

    • Time-headway

    • Time-to-collision

    • Kinematic Constraints

      • Calculates minimum range to avoid collision by braking at specified rate after a specified reaction time

      • Most comprehensive algorithm

  • Driver Vehicle Interface

Task 9a literature review lane drift warning ldw
Task 9a: Literature Review Lane Drift Warning (LDW)

  • Algorithm Alternatives

    • Zero-order Time-to-Line crossing (TLC)

      • Simple but doesn’t consider rate of drift

    • First-order TLC

      • Assumes lateral acceleration will remain constant

    • Second-order TLC

      • Use of acceleration amplifies measurement error

    • Kinematic TLC

      • Takes into account upcoming road geometry

      • More complex measurement requirements

  • Driver Vehicle Interface

    • Steering-wheel counterforce

    • Tijerina et al. (1996) recommended not using both auditory and haptic

Task 9a literature review stop sign violation warning ssvw
Task 9a: Literature Review Stop Sign Violation Warning (SSVW)

  • Pierowicz et al. (2000) used required deceleration to prevent intersection entry as the criterion for the warning

    • If required deceleration (ap) exceeds 0.35 g warn the driver

  • System only requires GPS signal and a digital map to determine the distance to the intersection

  • Driver Vehicle Interface

    • Pierowicz et al. (2000) used a stop-sign symbol on a HUD

Task 9a literature review blind spot warning bsw
Task 9a: Literature Review Blind Spot Warning (BSW)

  • Tijerina and Hetrick (1997) suggested three stages of warning

    • Stage 1: object in blind spot

      • Suggested using visual-only stimulus

    • Stage 2: object in blind spot and turn signal is activated

      • Suggested using “augmented” visual-only stimulus (e.g., flashing visual)

    • Stage 3: object in blind spot and host vehicle moving toward blind spot

      • Suggested using multi-modality (e.g., visual plus haptic or auditory)

  • Driver Vehicle Interface

Task 9 safety warning countermeasures matthew smith aug 12 2003

Task 9a: Literature Review Adaptive Enhancement Issues

  • Provide appropriate level of adaptive enhancement

    • Not over-sensitive so that it changes too frequently or appears to be unstable

    • Not under-sensitive so that it is non-responsive, providing little added value

    • Avoid closed-loop oscillations or impressions of system inconsistency

      • e.g.,

  • Billings (1997) argued that the adaptation must be predictable so the user can from a clear mental model of the system’s behavior



Research task 9b
Research: Task 9b

  • Research Objectives/Strategy

    • Countermeasures usually involve imminent alert levels and must predict how quickly the driver must react to the alert

    • Determine how the results from the other experiments can be mapped onto adaptive enhancements to the countermeasures

      • Experiment 1: Imminent Alerted Brake Reaction Time (BRT)

    • Determine the effectiveness of different adaptive enhancements

      • Experiment 2: Comparison of Different Adaptive Enhancements

  • Experiment 1 Method

    • Measure BRT to the FCW alert as a function of different levels of distraction

    • Manipulate distraction level in the driving simulator using conditions from Tasks 5 (Cognitive Distraction) and Task 7 (Visual Distraction)

    • Lead vehicle brakes suddenly at an imminent level (e.g., 0.5 g)

  • Experiment 2 Method

    • Expose subjects to different implementations of enhanced countermeasure systems during differing levels of imposed driver distraction

    • Assess the driver acceptance issues surrounding adaptive enhancements (e.g., should alerts be delayed or suppressed completely when the driver is attentive?)

Research task 9b experiment 1 imminent alerted brt
Research: Task 9b Experiment 1: Imminent Alerted BRT

  • Variables

    • Independent Variable: Distraction Level

    • Dependent Variable Brake Reaction Time (BRT)

  • Facilities/Apparatus/Subjects

    • Delphi Driving Simulator

    • Between-subject study

      • Can only surprise subjects once

      • 10-12 subjects per condition (50-60 total)

      • Subjects in 35 – 55 age group

  • Distraction Level Conditions

    • No distraction with alert

    • Mid-level cognitive distraction (from Task 5) with alert

    • High-level cognitive distraction (from Task 5) with alert

    • Mid-level visual distraction (from Task 7) with alert

    • High-level visual distraction (from Task 7) with alert

Research task 9b experiment 2 adaptive enhancements
Research: Task 9b Experiment 2: Adaptive Enhancements

  • Variables

    • Independent Variables

      • Countermeasure System / Adaptive enhancement concept alternatives

      • Distraction Level

    • Dependent Variables

      • Subjective responses regarding the enhancement alternatives (driver acceptance)

      • Observe different adaptive enhancements with different drivers

  • Facilities/Apparatus/Subjects

    • Delphi Driving Simulator

    • Use subset (10 – 24) of participants recruited from the reaction time experiment

      • Likely use the high-level visual and/or cognitive distraction group because they are likely to be familiar with the concept of driver distraction in relation to collision warnings

  • Design

    • Instruct participants to drive in the simulator while engaging in the distraction tasks and experiencing the adaptive enhancements

    • Lead vehicle will frequently brake to assess adaptively-enhanced FCW

    • Compare different types of adaptive countermeasures and non-adaptive countermeasures

Research task 9b issues concerns
Research: Task 9b Issues/Concerns

  • IRB approval

    • IRB approval (August 29th) may be delayed to allow more accurate and detailed submission (changes less likely)

  • Iteratively test and refine countermeasure concepts

    • Deadline of August 29th not feasible because Delphi driving simulator will not be available for development until early September (Used in Task 7)

    • Estimated completion October 17th

  • Facility Preparation

    • Deadline of August 29th not feasible because Delphi driving simulator will not be available for preparation until early September

    • Estimated completion October 17th

  • Design Adaptive Concept test study

    • Initial deadline of July 31st not feasible because of driving simulator delay

    • Estimated completion September 30th

  • Data Collection

    • Deadline of November 3rd not feasible because of delay in facility preparation

    • Estimated completion November 28th

  • Data Analysis, Final Report, and Phase II plan

    • Respective deadlines of Jan 5th, Jan 30th, and Feb 27th should still be possible