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CTS Events
SEMINAR
November 14, 2012 Dr. Nebiyou Tilahun, UPP, presents a seminar entitled "An agent based model of origin destination estimation (ADOBE)" Wednesday, November 14th at 4:00 pm in Rm 1127 SEO
SEMINAR
November 7, 2012 Mr. Thomas Murtha, CMAP, will address the CTS-IGERT community at 4:00 p.m. in Room 1127 SEO.
SEMINAR
October 24, 2012 Please join us in welcoming Dr. Bo Zou, CME, on Wednesday, October 24th, Room 1127 SEO, 4:00 p.m.
CTS Happenings
September 25, 2012
Award Received by Joshua Auld, CTS-IGERT alumnus.
April 20, 2012
Congratulations to James Biagioni, CTS Fellow and CS PhD candidate, winner of the Dean's Scholar award.
January 2, 2012
James Biagioni, CTS Fellow, receives "Best Presentation Award" at SenSys2011
July 30, 2010
Dr. Ouri Wolfson, Dr. Phillip Yu, and Leon Stenneth, CS student and CTS Associate, recently had a paper accepted to the 6th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2010).
July 15, 2011
Karl Sturm, CTS-IGERT Fellow, PhD Candidate CME, will present a seminar entitled "An Evaluation of Driver Reactions to New Vehicle Parking Assist Technologies Developed to Reduce Driver Stress" at 2:30 in Rm 1000SEO. A wide range of advanced technologies are currently being introduced into production automobiles that are intended to increase safety and comfort. If effectively implemented, some of these advanced technologies also offer the possibility of reducing driver stress. This study employed heart rate as an objective physiological arousal measure along with more traditional self-report ratings to evaluate the extent to which two recently introduced technologies impact driver stress levels. The technologies evaluated were a semi-autonomous system for parallel parking that detects appropriately sized parking spaces and actively steers the vehicle into the parking space while the driver controls the throttle and brake and a cross traffic warning system designed to alert drivers of encroaching vehicles when backing out of parking spaces. Two separate samples of 42 participants each were employed in the analysis and each sample consisted of three gender balanced age groups (20-29, 40-49 and 60-69). In both experiments, each participant experienced multiple exposures to the parking maneuver with and without the technology (within subject design). After becoming familiar with the technology, participants rated their stress levels significantly lower when using the assistive parallel parking technology (p = .025) and physiological recordings showed an average heart rate 12.6 beats per minute lower (p < .001) providing confirmation of a lower state of arousal. These findings were consistent across gender and age groups. Mean self report and heart rate data were suggestive of some reduction in stress levels with the cross traffic warning system, although these differences were not statistically significant (p > .05). It was observed that drivers were more likely to appropriately stop and yield to an approaching vehicle during trials when the cross traffic alert system was active, potentially reducing the likelihood of accidents. While ratings of the systems were generally positive, some individuals experienced issues with the technologies. Additional analysis of self-report data and subgroups within the data study sample is ongoing. Developing a more complete understanding of why some individuals have issues interactingwith these types of new technologies may provide important insight into how further gains in technology adoption and stress reduction can be obtained. Biography: Karl Sturm is a first year Ph.D. student in the Department of Civil and Materials Engineering. His current research interest is in travel demand modeling, specifically in route choice modeling. Karl received a B.S. in Civil Engineering at Arizona State University in 2008. Over the past year he has worked in constructing and implementing freight establishment and GPS surveys to serve as inputs into freight models. To serve his planned route choice model, Karl is formulating a map-matching algorithm to analyze an existing GPS dataset. His advisors are Dr. Abolfazl (Kouros) Mohammadian and Dr. Kazuya Kawamura. |
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