1 / 25

ummer nternship

E. M. ye ovements. During Merging. S. I. ummer nternship. Jeannette Feliciano Cecilia. July 23,2009. A. genda. I ntroduction B ackground O bjectives/ P urpose M ethod S ubjects E quipment S pecial C onsiderations E xperimental P rocedure L ab W ork A nalysis

cyndi
Download Presentation

ummer nternship

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. E M ye ovements During Merging S I ummer nternship Jeannette Feliciano Cecilia July 23,2009

  2. A genda • Introduction • Background • Objectives/Purpose • Method • Subjects • Equipment • Special Considerations • Experimental Procedure • Lab Work • Analysis • Conclusion

  3. B ackground • The time course of lane change: Driver control and eye-movement behavior.* • Duration of a single lane change averaged 5.14 ± 0.86s. • “…drivers direct more their gaze to the mirror and less to the start lane.” • Control and monitoring during lane changes.** • “Gazes at the mirror [have] average duration of approximately 350ms.” • * Salvucci, D. D., Liu, A. (2002). The Time Course of a Lane Change: Driver Control and Eye Movement Behavior. Transportation Research, Part F, 5(2): 123-132. • **Salvucci, D. D., Liu, A., Boer, E. R. Control and Monitoring During Lane Changes. (Source: http://www.mit.edu/~amliu/Papers/VIV9-SalLiuBoer.pdf)

  4. L M ane change vs. ergeing • Previous work addresses lane change behavior. • This study looks at eye movements of drivers as they merge into incoming highway traffic.

  5. D escription Ramp Acceleration Lane Merging Area Traffic Flow Median • Figure 1 – Merging vs. Single lane change

  6. P W revious ork • TADDA- Traffic and Driver Data Analysis • This software developed at URI • It wirelessly integrates the sensors such as Automobile On Board Computers, accelerometers and GPSs. • When a test drive is completed the software allows easy export of all the data with synchronization for post drive analysis.

  7. O P bjectives / urpose • Identify most common eye movements during the merging maneuver in rural arterial road. • Determine the average number of total glances during such maneuver. • Determine gazes’ average duration for the most commons glances.

  8. S ubjects • 19 test drives performed • Only: • 14 could be used for determined the average glances • and 9 to calculated the eye fixations average duration • Reasons: • Bad eye data because excessive blinking • Faulty in calibration or synchronization

  9. C S onsiderations pecial • Eye makeup and glass can not be wear during the experiment. • Weather Conditions Sun light Must be cloudy interferes

  10. E quipment • Eye Scan Device (with 2 cameras) • Digital Video Recorder (DVR) • GPS reciever • Laptop computer • Camcorder • Figure 2 – Eye Scan Device • Figure 3 – Experiment’s equipment

  11. E P xperimental rocedure Adjust the eye tracker’s cameras to assure that the images are seen well. The subject must look at the test pattern for image calibration. Run TADDA software and pair the GPS receiver with the laptop. The subject is ask to close their eyes for 10 seconds for synchonization purpose. • Figure 5 – Procedure steps

  12. E P xperiment's hases GPS VS. Map

  13. L ocation URI Merging Experiment Area US 1 South • Figure 6 – Localization of experiment’s area [Source: Google Earth]

  14. L W ab ork Eye Tracker Eye Camera Eye Tracker View Camera Digital Video Recorder ISCAN Raw Eye Movement Data Acquisition Software Video with the overlaid cursor Figure 7 – ISCAN Raw Eye Movement Data Acquisition Software’s print screen

  15. L W ab ork Right Side Mirror Back (by Left) Left Side Rear Mirror Left Side Mirror Figure 8 – Point of interest ‘s print screen

  16. L W ab ork Vertical Position (Pixels) Graph 1 – Eye Fixations Horizontal Position (Pixels)

  17. L W ab ork Longitude At the ramp Latitud Graph 2 – Vehicle Path

  18. A nalysis

  19. Subjects by Glance’s Type Max Utilization by subject Min Graph 3 – Subjects by glances' type

  20. Glances by Subject Subjects 4, 7 & 12 did not look back and subject 5 none of both Number of Glances Graph 4 – Glances by subjects

  21. Glances’ Results Table 1 – Glances Results

  22. G D aze's uration Table 2 – Summery of gaze’s duration Max Duration (seconds) > 350ms Table 5 – Gaze’s mean duration by type Single Lane Change: “Gazes at the mirror [have] average duration of approximately 350 ms.” *

  23. Split Data Table 3 – Gaze mean duration when the merging maneuver was preformed with or without incoming cars Graph 6 – Comparison of left side mirror gaze mean duration . Table 4 – Comparison of left side mirror gaze mean duration . Time (sm) < 350ms

  24. Most common eye movements during the merging maneuver (ramp to US-1). Side mirror glance Back glance The average number of total glances during such maneuver is approximated 6. Gazes’ average duration: 553 ms for side mirror glance 842 ms for back glance But it varies depending on the incoming traffic. C onclusion

  25. Questions ?

More Related