Award Abstract # 2038984
CPS: Medium: Hybrid Twins for Urban Transportation: From Intersections to Citywide Management

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK
Initial Amendment Date: September 3, 2021
Latest Amendment Date: August 7, 2022
Award Number: 2038984
Award Instrument: Standard Grant
Program Manager: Abhishek Dubey
adubey@nsf.gov
 (703)292-7375
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2021
End Date: March 31, 2026 (Estimated)
Total Intended Award Amount: $1,200,000.00
Total Awarded Amount to Date: $1,300,000.00
Funds Obligated to Date: FY 2021 = $1,200,000.00
FY 2022 = $100,000.00
History of Investigator:
  • Xuan Di (Principal Investigator)
    sharon.di@columbia.edu
  • Gil Zussman (Co-Principal Investigator)
  • Zoran Kostic (Co-Principal Investigator)
  • Qiang Du (Co-Principal Investigator)
Recipient Sponsored Research Office: Columbia University
615 W 131ST ST
NEW YORK
NY  US  10027-7922
(212)854-6851
Sponsor Congressional District: 13
Primary Place of Performance: Columbia University
500 West 120th Street, #610
New York
NY  US  10027-7003
Primary Place of Performance
Congressional District:
13
Unique Entity Identifier (UEI): F4N1QNPB95M4
Parent UEI:
NSF Program(s): GVF - Global Venture Fund,
Special Projects - CNS,
CPS-Cyber-Physical Systems
Primary Program Source: 01002122RB NSF RESEARCH & RELATED ACTIVIT
01002122DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7924, 120Z, 152E
Program Element Code(s): 054Y00, 171400, 791800
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070, 47.079

ABSTRACT

This Cyber-Physical Systems (CPS) grant will focus on the development of an urban traffic management system, which is driven by public needs for improved safety, mobility, and reliability within metropolitan areas. Future cities will be radically transformed by the Internet of Things (IoT), which will provide ubiquitous connectivity between physical infrastructure, mobile assets, humans, and control systems. In particular, IoT and smart traffic management have the potential to significantly improve increasingly faltering transportation systems that account for over 25% of greenhouse gas emissions and over one trillion dollars of annual economic and social loss. The project develops a hybrid twin that operates in parallel with the real world at real-time resolution, leveraging machine learning and edge computing, to monitor surrounding traffic, send safety warnings to connected vulnerable users, and provide learning-based controls to traffic lights and automated vehicles. As such, the broader impacts include advancing the understanding of urban traffic modeling, computation, and simulation, and enriching transportation science with data science. The accompanying educational plan aims to broaden participation in computing and engineering by underrepresented minorities and women via outreach programs, including programs for Harlem public school teachers and K-12 students, as well as new graduate course development.

The project?s goal is to develop a hierarchical and distributed hybrid twin to support urban traffic management systems while leveraging Artificial Intelligence (AI), edge cloud computing, and next generation communication networks. A hybrid twin consists of a virtual (i.e., existing traffic simulation) and a digital twin, which integrate physics-based models and assimilate data acquired from infrastructure and in-vehicle sensors for traffic modeling, prediction, and management. The foundational research contributions are data analytics and machine learning including real-time learning for control. The traffic management system will be validated and evaluated via computer simulation and experimentation in the NSF PAWR COSMOS city-scale wireless testbed that is being deployed in West Harlem next to the Columbia campus. This unique urban testbed will provide a realistic environment for the system design and evaluation process, and will also serve as a platform for local community outreach.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 23)
Ghasemi, Mahshid and Yang, Zhengye and Sun, Mingfei and Ye, Hongzhe and Xiong, Zihao and Ghaderi, Javad and Kostic, Zoran and Zussman, Gil "Video-Based Social Distancing: Evaluation in the COSMOS Testbed" IEEE Internet of Things Journal , 2023 https://doi.org/10.1109/JIOT.2023.3305587 Citation Details
Ghasemi, Mahshid and Yang, Zhengye and Sun, Mingfei and Ye, Hongzhe and Xiong, Zihao and Ghaderi, Javad and Kostic, Zoran and Zussman, Gil "Video-based social distancing evaluation in the cosmos testbed pilot site" MobiCom '21: Proceedings of the 27th Annual International Conference on Mobile Computing and Networking , 2021 https://doi.org/10.1145/3447993.3510590 Citation Details
Jain, Gaurav and Hindi, Basel and Xie, Mingyu and Zhang, Zihao and Srinivasula, Koushik and Ghasemi, Mahshid and Weiner, Daniel and Xu, Xin Yi and Paris, Sophie Ana and Tedjo, Chloe and Bassin, Josh and Malcolm, Michael and Turkcan, Mehmet and Ghaderi, Ja "Towards Street Camera-based Outdoor Navigation for Blind Pedestrians" , 2023 https://doi.org/10.1145/3597638.3614498 Citation Details
Jain, Gaurav and Hindi, Basel and Zhang, Zhiao and Srinivasula, Koushik and Xie, Mingyu and Ghasemi, Mahshid and Weiner, Daniel and Paris, Sophie_ Ana and Xu, Xin_Yi_Therese and Malcolm, Michael and Turkcan, Mehmet and Ghaderi, Javad and Kostic, Zoran and "StreetNav: Leveraging street cameras to support precise outdoor navigation for blind pedestrians" , 2023 Citation Details
Kostic, Zoran and Angus, Alex and Yang, Zhengye and Duan, Zhuoxu and Seskar, Ivan and Zussman, Gil and Raychaudhuri, Dipankar "Smart City Intersections: Intelligence Nodes for Future Metropolises" Computer , v.55 , 2022 https://doi.org/10.1109/MC.2022.3206273 Citation Details
Liu, Shuo and Wang, Yunhao and Chen, Xu and Fu, Yongjie and Di, Xuan "SMART-eFlo: An Integrated SUMO-Gym Framework for Multi-Agent Reinforcement Learning in Electric Fleet Management Problem" 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) , 2022 https://doi.org/10.1109/ITSC55140.2022.9922047 Citation Details
MahshidGhasemi, SofiaKleisarchaki "Real-timeMulti-CameraAnalytics forTrafficInformationExtractionandVisualization" IEEE PerCom'23 , 2023 Citation Details
Mo, Zhaobin and Li, Wangzhi and Fu, Yongjie and Ruan, Kangrui and Di, Xuan "CVLight: Decentralized learning for adaptive traffic signal control with connected vehicles" Transportation Research Part C: Emerging Technologies , v.141 , 2022 https://doi.org/10.1016/j.trc.2022.103728 Citation Details
Turkcan, M and Narasimhan, S and Zang, C and Je, G and Yu, B and Ghasemi, M and Ghaderi, J and Zussman, G and Kostic, Z "Constellation dataset: benchmarking high-altitude object detection for an urban intersection" , 2024 Citation Details
Zang, C and Turkcan, M and Zussman, G and Ghaderi, J and Kostic, Z "Data-driven traffic simulation for an intersection in a metropolis" , 2024 https://doi.org/10.48550/arXiv Citation Details
, Zhaobin Mo and , Xuan Di "Uncertainty Quantification of Car-following Behaviors: Physics-Informed Generative Adversarial Networks" the 28th ACM SIGKDD in conjunction with the 11th International Workshop on Urban Computing (UrbComp2022) , 2022 Citation Details
(Showing: 1 - 10 of 23)

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