# Presentation: 231600

## 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
- 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:
- 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

- Research Areas of Interest /  Literature Review Sections
- 9.1 INTRODUCTION
- 9.2 CRASH CLASSIFICATION AND THE ASSOCIATED SAFETY WARNING COUNTERMEASURES
- 9.3 FORWARD COLLISION WARNING (FCW)
- 9.4 LANE DRIFT WARNING (LDW)
- 9.5 STOP SIGN VIOLATION WARNING (SSVW)
- 9.6 BLIND SPOT WARNING (BSW)
- 9.7 ADAPTIVE ENHANCEMENTS
- 9.8 CONCLUSIONS
*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

- Police-Reported
- Light Vehicle Crashes
- (Najm, Sen, Smith, & Campbell, 2003)

- Roadway Fatalities
- (U.S. Department of Transportation, 1997)

## Rear-end Crashes
Most prevalent category of crashes
Knipling et al. (1992) estimated that over 3⁄4 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

- Most prevalent category of crashes
- Knipling et al. (1992) estimated that over 3⁄4 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 ReviewMajor Findings (cont.)

## Task 9a: Literature ReviewMajor 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

- 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)

- 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)

- 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)

- Pierowicz et al. (2000) used *required deceleration to prevent intersection entry* as the criterion for the warning
- If required deceleration (*a**p*) 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)

- 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

## 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

- 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

- Inattentive

- Attentive

- Task 9a: Literature Review Adaptive Enhancement Issues

## 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

- 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

- 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

- 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