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Human Factors Progress IDS Project. Nicholas Ward Jason Laberge Mick Rakauskas HumanFIRST Program. Unsignalized Intersections: Previous work on DII’s. Collision Countermeasure System Prince William Co., Virginia Intersection Collision Avoidance Warning System Norridgewock, Maine - PowerPoint PPT Presentation
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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.
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