1. Traffic Generation for Studies of Gap Acceptance
Joseph Kearney
Timofey Grechkin
James Cremer
Department of Computer Science
Jodie Plumert
Department of Psychology
University of Iowa

2. Bicycling Injuries
Bicycle crashes are a common cause of severe injury in childhood
ERs treat 500,000 bicycle-related injuries a year
Highest injury rate is among children 5-15
Motor Vehicles involved in 90% of bicycling fatalities
Prevention
Need to understand why car-bicycle collisions occur
How do immature cognitive and perceptual skills put children at risk for car-bicycle collisions?

3. Gap Acceptance in the Hank Bicycle Simulator

4. Bicycle Simulator Video

5. Research Questions Are there age differences gaps selection?
How are gap choices related to crossing behavior?
Do gap choices change in dense traffic?
How is temperament related to risk in road crossing?

6. Prior Work on Gap Acceptance
Critical Gap Estimation
Important component of flow computations
Focus on gap selection
Crossing behavior not examined
Gap Affordance
How is gap selection related time to cross?
Converging evidence that people do not account for diminished skill
Child pedestrians
Alcohol impaired pedestrians
Elderly with attentional deficits
Child bicyclists

7. Virtual Environment Three 10X8 ft screens (rear projection)
Projection Design Projectors -1280x1024 pixels/screen
Square (Cave-like) configuration
Seven networked PCs
Dynamic pedal torque

8. Road Crossing Experiment (Plumert, Kearney, Cremer, Child Development 7(4), 2004)
Subjects: Sixty 10- and 12 year olds and adults
Procedure
Warmup: 3 blocks with no traffic
Gap crossing
6 intersections with steady traffic at 25 or 35 MPH
Random gaps (1.5, 2.0, 2.5, 3.0, 3.5, 4.0 seconds)
Subjects instructed to stop at each intersection and safely cross
Measures
Gap choice
Time to spare
Wait time
Stopping

9. Coding: The “Data Visualizer”

10. Summary of Road Crossing Results
Children and adults chose the same size gaps
Average size of seconds
Children had less time to spare
when cleared path of car, on average
10-year olds had 1.13 sec to spare
12-year olds had 1.49 sec to spare
Adults had 1.98 sec to spare
Why did children have less time to spare?
Started later
Took more time to get going

11. Long Wait Experiment Subjects: 120 10- and 12 year olds and adults
Procedure
Warmup
Gap crossing
4 intersections with random gaps
4 long wait intersections
Long Wait Traffic
8-10 uncrossable gaps (1.5 and 2 s)
Stair-step increase in gap size
Alternating: (two crossable gaps; four uncrossable gaps)
1.5, 2.0, 1.5, 1.5, 2.0, 1.5, 1.5, 2.0, 3.0, 3.0, 1.5, 2.0, 2.0, 1.5, 3.5, 3.5, 1.5, 1.5, 2.0, 1.5, 4.0, 4.0,…

12. Long Wait Gap Choice 1.0 0.9 Middle four intersections
Last four intersections
0.8
0.7
Gaps Taken
0.6
Gaps Seen
0.5
0.4
first four intersections
0.3
0.2
0.1
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Gap Size

13. Summary of Long Wait Results
Children and adults chose the same size gaps
Children had less time to spare when they cleared path of oncoming car
Both children and adults accept much smaller gaps at intersections with dense traffic
This risky behavior carries over to intersections with “normal” traffic density

14. Analysis of Gap Acceptance Data
Average gap selected is biased
Over-estimates critical gap
Cautious drivers are over-represented
(Gattis and Low, 1999)
Logistic Regression
Estimates critical gap
Cautious drivers still over-represented
Stair-step presentation
Long waits may influence response criteria
Savvy drivers may wait

15. How Do Children and Adults Cross Mutli-Lane Traffic?
Requires passage through two overlapping gaps
More difficult perceptual task spatially and temporally
Greater payoff for anticipation
Greater overall distance to be crossed
Staged crossing through rolling gaps
Improving Pedestrian Safety at Unsignalized Crossings
TCRP Report 112, 2006

16. Gap Acceptance with One-Lane Traffic
Tail
Lead
current time
time

17. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
current time
time

18. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
time
current time

19. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near gap
Near lane
time
current time

20. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far gap
Far lane
Near lane
time
current time

21. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Overlap
Near lane
time
current time

22. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
crossing interval
time
current time

23. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
crossing interval
time
current time

24. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
crossing interval
time
current time

25. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
crossing interval
time
current time

26. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
crossing interval
time
current time

27. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
crossing interval
time
current time

28. Gap Acceptance with Two-way Traffic
Lead far lane
Tail far lane
Tail near lane
Lead near lane
Far lane
Near lane
crossing interval
time
current time

29. Generation of Two-way Traffic
Specify Between Lane Gaps
Randomly generate gaps
(time between successive arrivals irrespective of lane)
Randomly assign lane
Produces natural clusters and breaks
May reduce problem to one-lane crossing
Specify Within Lane Gaps
Independent (randomized) streams on two lanes
Produces steady stream of two-way traffic
Requires synchronization of gaps
Increased gap size

30. Future Work: Young Drivers
How are young drivers’ gap choices related to their crossing behavior?
Little is known about road-crossing behavior in young drivers
Studies of road-crossing require a wide FOV
Scenarios apply to driving

31. Summary Gap Crossing Critical events vs. prosaic driving tasks
Essential skill for safe driving
Complex perceptual task
Detect temporal relations in spatially disparite dynamic streams
Complex motor task
Synchronize movement to multiple temporal intervals
Anticipate arrival times
Probe for investigating skill of driving populations
Critical events vs. prosaic driving tasks
Understand perceptual and motor skills needed for safe driving
Investigate differences in driving populations
Identify risky behaviors
Improve Training

32. Acknowledgments Contributing students, staff, faculty
NSF Support: INT , EIA , and IIS ; National Center for Injury Prevention and Control: R49/CCR721682;
National Institutes of Health: 1 R01 HD
Contributing students, staff, faculty
Hongling Wang Geb Thomas
David Schwebel Pete Willemsen
Penney Nichols-Whitehead Scott Davis
Jennifer Lee Steffan Munteanu
Sarah Rains Joan Severson
Sara Koschmeder Tom Drewes
Ben Fraga Forrest Meggers
Kim Schroeder Paul Debbins
Stephanie Dawes Bohong Zhang
Lloyd Frei Zhi-hong Wang
Keith Miller Xiao-Qian Jiang
Timofey Grechkin Christine Ziemer