Human Factors ProgressIDS Project

Nicholas Ward

Jason Laberge

Mick Rakauskas

HumanFIRST Program

Unsignalized Intersections:Previous work on DII’s

Collision Countermeasure SystemPrince William Co., Virginia

Intersection Collision Avoidance Warning System

Norridgewock, Maine

Limited Sight Distance Warning Signs

Gwinnett County, Georgia

Collision Countermeasure SystemPrince William Co., Virginia

Thru-STOP at two 2-lane roads

Focus on warning major approach

Data Collected:Speed (intersection arrival, reduction)

Projected time to collision (PTC)

Human machine interface evaluated forCollision Countermeasure System (CCS)Prince William County, Virginia Aden road (major) & Fleetwood Drive (minor) intersection located on plateau with restricted sight distances. Drivers on minor leg often had difficulty sensing safe gap

On minor leg On major leg

Collision Countermeasure System

(minor approach)

(major approach)

Intersection Collision Avoidance Warning SystemNorridgewock, Maine

Thru-STOP at two 2-lane roads

Focus on warning minor approach

Data:Observational techniques

Surveys

Limited Sight Distance Warning SignsGwinnett County, Georgia

18 Thru-STOPs at two 2-lane roadsChosen based on minimum sight distance guidelines & reported problems

Warnings for major &/or minor approaches

Signs considered interim solution

STOP

Human Factors TasksAnalyze problem

Task analysis“What are drivers doing wrong?”“Who is at most risk?”

Driver model (Information Process)“Why are they doing it wrong?”“What information could support correct behavior?”

Previous solutions“What has not worked before?”

Simulate case sitePropose interfaces and simulate candidateEvaluate candidate interface

Task AnalysisDetect intersection

Decelerate and enter correct lane

Signal if intending to turn

Detect and interpret traffic control device

Detect traffic and pedestrians

Detect, perceive, and monitor gaps

Accept gap and complete maneuver

Continue to monitor intersection

Human factors issuesIn Minnesota, most drivers stop before proceeding (Preston & Storm, 2003)

57% stopped in 2296 rural thru-STOP accidents87% of right angle crashes at US 52 and CSAH 9 occurred after the driver stopped

NOT a violation problemInstead, a gap acceptance problem

Detecting vehicles and presence of gaps in trafficPerceiving gap sizeJudging safe gaps

Information NeedsA. Vehicle Detection

B. Convey speed/distance/arrival time of lead vehicle

C. Convey lead gap size

D. Judge “safe gap” (and display location in traffic)

Information NeedsMost prior systems limited to emphasizing:1. Presence of intersection and traffic control device.2. Presence of approaching cars.3. Approach speed of cars.

Given that awareness of intersection and compliance with TCD’s is not the problem in our case, method 1 above will not benefit safety.To the extent that drivers are at risk because of problems with more complex information needs (C and D), simply presenting information about vehicle detection will not benefit safety.

Information NeedsA. Vehicle Detection

B. Convey speed/distance/arrival time of lead vehicle

C. Convey lead gap size

D. Judge “safe gap” (and display location in traffic)

Since the research does not give evidence of the relative importance of these factors toward crash risk, it is necessary to design options for ALL of the above.

Note also, that the highest level (D) also satisfies the lowest level (A), but NOT conversely.

Target PopulationOlder drivers (> 65 years) have a high crash risk at intersections

Drivers > 75 years had greatest accident involvement ratio (Stamatiadis et al., 1991)Drivers > 65 years - 3 to 7 times more likely to be in a fatal intersection crash (Preusser et al., 1998)Drivers > 65 years - over-represented in crashes at many rural intersections in Minnesota (Preston et al., 2003)

Intersection Selection: Based on State-wide Crash Analysis

Analysis of present conditions and intersections …. Howard Preston, leadIdentification of Experimental Site: Minnesota Crash Data Analysis

3,784 Thru-STOP Isxns in MN Hwy Systemwere evaluated Total > CR (% of total)

2-Lane - 3,388 | 104 (~ 3%)Expressway - 396 | 23 (~ 6%)

Age of At-Fault Drivers Involved in Crossing Path Crashes

33%

58%

8%13%

53%

33%

18%

82%

5%

16%

72%

7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Young (< 20) Middle (20 - 64) Old (> 64) Unknown

Age of At-Fault Driver

Per

cen

tag

eUS 10 & CR 43 (12)

US 52 & CSAH 9 (15)

MN 65 & 177th Ave (11)

Expected

Candidate Intersections: At-Fault Driver Age

Source: Mn/DOT 2000 – 2002 Crash Data

Crash Type Distribution for the Candidate Intersections

6% 6%

10%

5%

15%

65%

24%

14%

10% 10%

5%

21%

5%2% 1%

11%

61%

11%

6% 5%

38%

0.4%

14%

4%

17%

36%

0%

10%

20%

30%

40%

50%

60%

70%

Other Rear End SideswipePassing

Left Turn Run OffRoad

Right Angle Head On Sideswipe -Opposing

Right Turn

Crash Type

Per

cent

age

US 10 & CR 43 (18)

US 52 & CSAH 9 (22)

MN 65 & 177th Ave (21)

Expected (396)

Candidate Intersections:Crash Type Distribution

Source: Mn/DOT 2000 – 2002 Crash Data

Selected Intersection

Sight distance restricted on the W approach at

CSAH 9

Note differences inN and S vertical alignments

Elevation

Intersection Simulation Task

Intersection Simulation Task

Interface TaskHuman factors analysis of crash problem

Task AnalysisDriver ModelAbstraction Hierarchy

Expert panel review of conceptsEveryone had own perspectiveNo consensus

Candidate set proposed based on information needs:

Detect vehiclePresent speed and timePresent gap sizeSpecify safe gap

Sign formats consistent with MUTCD (shape, color)

Four PrototypesStatic Warning•New warning sign•Sign conforms to human factors criteria for warning labels•Low cost solution(baseline)

Split-Hybrid•Arrival time countdown forlead vehicle•Prohibitivesymbol relative tomaneuvers based on near and far-sidetraffic conditions.

Hazard Beacon•Flashing red beaconactivates whenintersection is unsafe•System tracksspeeding or arrival time of lead vehicle

Speedometer•Speed monitorfor lead vehicle•Flashes red when near or far-sidevehicle is speeding

Expert Review19 evaluations sent out (37 % response rate)

2 Minnesota IDS team

5 Expert panel

No consensus

Static Warning Sign

STOP

STOP

CAUFAS

<-------->

DIVIDED

HIGHWAY

CAUTION

FAST CROSSING TRAFFIC

BE CAREFUL

STOP

Hazard Beacon

STOP

The light above the sign is solid white at all other times to indicate the system is functional

A light above the STOP sign flashes red if any “lead” vehicle is speeding and/or if an unsafe gap is detected in either direction

STOP

Dangerous Crossing Flashing

Red

CAUFAS

<-------->

STOPDIVIDED

HIGHWAY

DANGEROUSCROSSING

WHENFLASHING RED

Split-Hybrid

STOP

STOP

VEHICLE WILL ARRIVEFROM THE RIGHT IN

SECONDS

VEHIC WILL ARRIFROM LEFT IN

SECONDS

VEHIC WILL ARRFROM LEFT IN

SECONDS

VEHICLE WILL ARRIVEFROM THE LEFT IN

SECONDS

This display must be angled to be seen by the stopped driver

14

Split-Hybrid

STOP

STOP

VEHICLE WILL ARRIVEFROM THE RIGHT IN

SECONDS

3

VEHIC WILL ARRIFROM LEFT IN

SECONDS

VEHIC WILL ARRFROM LEFT IN

SECONDS

VEHICLE WILL ARRIVEFROM THE LEFT IN

SECONDS

14 This display must be angled to be seen by the stopped driver

When a vehicle is withinthe arrival time that definesthe safe gap limit, the backgroundchanges to red and the arrival timeflashes

Both the left and right displays will show thesame symbols.

Split-Hybrid

STOP

STOP

VEHICLE WILL ARRIVEFROM THE RIGHT IN

SECONDS

3

VEHIC WILL ARRIFROM LEFT IN

SECONDS

VEHIC WILL ARRFROM LEFT IN

SECONDS

VEHICLE WILL ARRIVEFROM THE LEFT IN

SECONDS

This display must be angled to be seen by the stopped driver

6

Speedometer

STOP

STOP

FASTVEHICLES

APPROACHING

FROM LEFT

MPH

55

Speed changes white and flashes; background changes red when major road vehicle approaches at greater (> 10mph) than posted speed

FROM RIGHT

MPH

85

Speedometer

Classification of conceptsHow each concept automates or supports the information processing stages of drivers at thru-STOP intersections (from Parasuraman, Sheridan, and Wickens; 2000).

Information acquisition: Extent to which each concept helps with sensing and detecting info (i.e., vehicles, hazards)

Low = applying limited or no sensors to scan and observe different parts of the road High = filtering and highlighting specific information content from sensors

Information analysis: Extent to which information is processed and inferences made

Low = predict changes in information over timeHigh = integrate information and potentially extract a single value

Decision making: Process by which decision alternatives are evaluated and selected

Low = present a driver with the full set of alternativesHigh = make the decision for the driver and act autonomously

Action execution: Process by which a specific action is completedLow = automating a simple task such as turning on the vehicle headlightsHigh = taking full control of a car

Overview

EvaluationSimulation required

Interfaces do not exist in real world

Need flexibility to modify interfaces

Need control over traffic (and environment) conditions

Need repeated exposure to same conditions to produce reliable data

Simulation limitsCalibration with real world data from on site instrumentation

Limitations to “size” of experiment

Time intensive to implement and validate

Practical limits to size of experiment

Keep subjects 2 to 3 hours; < 2 hrs of driving in 30 min sessions.Issues:

• 5 interface conditions (baseline, static warning, hazard beacon, hybrid, and speedometer). All subjects will see all condition worlds.

• In each world, mainline traffic conditions will be scripted to represent specific gap sequences – need to determine wait time and the presence of different (safe) gap sizes in the traffic stream.

• Will test long and short wait times.• To collect reliable data (e.g., gap size accepted, clearance time, safety

margin with respect to remaining gap during merge), each condition world must be experienced at least twice…Implies that each condition world must have at least 2 variants in terms of traffic conditions.

• Each replicated world will need different traffic conditions to limit effects of learning and expectancy on driver decisions.

• If allow 10 minutes for each drive, then we have approx 1 and 2/3 hrs of driving per subject. May be too much for individual drivers (notably older drivers). Piloting will be used to evaluate study design.

ConclusionTask S03 O N D J04 F M A M J J A S O N D J05 F Intersection

Select Intersection

X

Simulator Intersection

X X X X

Demo intersection

X

Interface Simulate Interface

X X X

Demo Interface

X

Revise Interface

X X

Evaluation Develop

Simulation X X X

Develop Protocol

X

Recruit & Pilot

X

Conduct Study

X X

Analyze Data

X X

Report Draft Report X X X X X X

Task Completed:Intersection selected

and simulated with high Geospecific accuracy.

Task On schedule:•Interface concepts generated based on human factors analysis and preliminary review by experts.•Interface candidates simulated in driving simulator environment.•Demo scheduled for project panel.