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Dan McCabe was awarded by USDOT the 2021 Student of the Year of C2Smart University Transportation Center (UTC). Congratulations to Dan!

Members of iUTS Lab, Jingxing Wang, Rong Fan, Yiran Zhang, Qiangqiang Guo, Dan McCabe, and Jeff Ban attend the 2019 INFORMS Annual Meeting in Seattle (Oct. 20-23). Some of them presented their research results (see blow) and they all had a great time to interact with researchers who are interesting in applying analytics methods to transportation and many other engineering fields.

1. Wang, J., Lu, S., Ban, X., 2019. Exploring insignificant OD pairs: a compressed sensing model for OD demand estimation. Presented at the INFORMS Annual Meeting, Seattle, WA, Oct. 20-23, 2019.
2. Li, W., Ban. X., 2019. Deep learning methods for real time traffic volume prediction for signalized intersections. Presented at the INFORMS Annual Meeting, Seattle, WA, Oct. 20-23, 2019.
3. Guo, Q., Ban, X., 2019. Reinforced learning based traffic signal control. Presented at the INFORMS Annual Meeting, Seattle, WA, Oct. 20-23, 2019.
4. Zhang, Y., Guo, Q., Ban, X., 2019. Simulating CAVs on urban transportation networks. Presented at the INFORMS Annual Meeting, Seattle, WA, Oct. 20-23, 2019.

Mr. Dan McCabe joined our iUTS lab from the Pacific Northwest Nuclear Laboratory (PNNL). Dan is interested in applying optimization methods and techniques to transportation and electricity networks. Welcome Dan!

Wan Li successfully defended her dissertation research on May 28, 2019. She will join the Oak Ridge National Lab (ORNL) in August, 2019. Congratulations to Dr. Li!

A group of iUTS graduate students (Yiran Zhang, Wan Li, Jingxing Wang, Rong Fan, Qiangqiang Guo) received award from TRB (Transportation Research Board) for their outstanding performance in the Transportation Forecasting Competition (TRANSFOR 19). The competition was organized by the TRB Standing Committee ABJ70 on Artificial Intelligence and Advanced Computing Applications, supported by IEEE ITSS Technical Activities Sub-Committee on “Smart Cities and Smart Mobility”, and Sponsored by Didi Chuxing (a ridesourcing company based in Beijing, China). The competition was about developing a traffic forecasting model by using 2-months data to predict the average speed for a road section in the City of Xi’an, China. There were 31 teams in total who participated in this competition. The iUTS team, iUTSgo, got the second prize in terms of the prediction accuracy and was invited, along with four other teams, to present their work at a big data workshop on Jan. 13, 2019 at TRB. The team finally got the 4th place of this competition.

iUTS faculty and graduate students attended the 98th Annual Meeting of Transportation Research Board (TRB) from Jan. 12 – Jan. 16 at Washington, DC. Members of iUTS presented 5 papers, and was invited to present their methods and results for two competitions:

1. Wang, J.P., Huang, H.J, Ban, X. 2019. Dynamic ridesharing with variable-ratio charging-compensation scheme for morning commute. Presented at the 98th Annual Meeting of Transportation Research Board, Washington, DC.
2. Wang, F., Wang, J., Cao, J., Chen, C., Ban, X., 2018. Extracting trips from multi-sourced data for mobility pattern analysis: An app-based data example. Presented at the 98th Annual Meeting of Transportation Research Board, Washington, DC.
3. Wang, J., Wang, F., Ban, X., Chen, C., 2018. Comparative analysis of big data and small (survey) data for deriving human mobility patterns. Presented at the 98th Annual Meeting of Transportation Research Board, Washington, DC.
4. Li, W., Ban, X., 2018. Connected vehicle based traffic signal coordination. Presented at the 98th Annual Meeting of Transportation Research Board, Washington, DC.
5. Li, W., Ban, X. 2018. A deep learning approach for lane-based traffic volume prediction at signalized intersection. Presented at the 98th Annual Meeting of Transportation Research Board, Washington, DC.
6. Li, W., Wang, J, Fan, R., Guo, Q., Zhang, Y. 2018. Short-term traffic speed prediction from latent structures. Presented at the 98th Annual Meeting of Transportation Research Board, Washington, DC.
7. Xiao, B., Wu, X., Zhang, Y., 2018. Demographic features and mode transfer patterns of TNC users: evidence from 2017 NHTS data. Presented at the 98th Annual Meeting of Transportation Research Board, Washington, DC.

Congratulations to iUTSgo team to win the 4th place in the Transportation Forecasting Competition organized by ABJ70 of TRB; see more details at https://ta.itss-ieee.org/transportation-forecasting-competition-transfor-19-call-for-participation-2019-trb-annual-meeting-workshop/

On October 18, 2018, Dr. Ban presented at the Symposium on Complexity in Transportation Science: Connectivity, Data & Automation, organized by The Center for the Study of Complex Systems at the University of Michigan. His presentation was on “Transportation big data: promises and issues in the era of connectivity, automation, and sharing”, which is one of the six invited speeches of the Symposium.

Ms. Yiran Zhang joined iUTS as a new Ph.D. student. She just completed her MS degree from the transportation program of UW. Welcome Yiran!

On July 12, 2018, Dr. Ban presented at The first SIGIR Workshop on Intelligent Transportation Informatics (held in conjunction with SIGIR’18) in Ann Arbor, Michigan, organized by Didi Chuxing. His presentation was on Promises and issues of transportation big data, which was one of the two keynote talks of the workshop.

On July 11, 2018, Dr. Ban presented at The 10th International Workshop on Computational Transportation Science (CTS-2018) in Beijing, China. His presentation was on Modeling dynamic user equilibria using differential complementarity systems, which was one of the keynote speeches of the workshop.