May 3, 2022
Fully Online
Queries:
ayan.mukhopadhyay@vanderbilt.edu
rahulbhadani@email.arizona.edu
The 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities (DI-CPS)
After a successful DI-CPS workshop at CPS-IoT Week 2021, we are back with the second iteration of the workshop. This year, our focus is restricted to Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities.
Check your email from CPS-IoT Week 2022 Registrar for Zoom link.
Schedules in multiple time zone can be found on https://cpsiotweek.neslab.it/program_login.php#0.
| (Milano Time; GMT+2, CDT+7) | |
|---|---|
| Time | Agenda |
| 14:00 - 14:15 | Opening Remarks |
| 14:15 - 15:15 | Session 1: Keynote How to control highway traffic using connected and automated vehicles in theory and practice Speaker: Karl Henrik Johansson |
| 15:15 - 15:30 | Break |
| 15:30 - 16:30 | Session 2: Public transportation CPS |
| 1. E. Taya, et al., Estimating congestion in train cars by using BLE Signals | |
| 2. A. Dubey, et al., Optimizing Electrification of Public Transit | |
| 3. F. Paparella, et al., Joint Design and Operation of an Electric Autonomous Mobility-on-Demand System | |
| 16:30 - 16:45 | Break |
| 16:45 - 17:45 | Session 3: Data-driven CPS |
| 4. J. Veselsky, et al., Establishing Trust in Vehicle-to-Vehicle Coordination: A Sensor Fusion Approach | |
| 5. R. Bhadani, et al., Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface | |
| 6. A. Richardson, et al., Intelligent Structuring and Semantic Mapping of Dash Camera Footage and CAN Bus Data | |
| 17:45 - 18:00 | Break |
| 18:00 - 19:00 | Session 4: Vehicles in a smart-city environment |
| 7. G. Gunter, et al., Experimental testing of a control barrier function on an automated vehicle in live multi-lane traffic | |
| 8. T. Li and R. Stern, Robustness of vehicle identification via trajectory dynamics to noisy measurements and malicious attacks | |
| 9. M. Bunting, et al., Data from the Development Evolution of a Vehicle for Custom Control |
Smart cities are emerging as a priority for Cyber-Physical Systems (CPS) research and development across the world. Artificial Intelligence and Machine Learning algorithms have played a large part in automating and advancing city operations and aiding the development of CPS in cities. Increasingly, data-driven modeling and intelligent decision-making under uncertainty are forming the basis for advancing transportation, safety, connectivity, and health services. For example, advanced traffic solutions, improved public transportation systems, smart emergency response, energy modeling, and autonomous driving are some of the applications that have benefited from data-driven approaches to principled decision-making. Data is extremely valuable in determining human behavior both at the scale of the entire population as well as at the level of individual persons navigating the infrastructure landscape.
With the advent of Internet of Things (IoT), sensor data is being generated at a pace and volume that is difficult to process and use for inference. With several data modalities in the picture, new opportunities and challenges arise in terms of data collection, validation, analysis, and inference. For example, these additional data enable the development of novel models of traffic behavior at different geographical locations and time points, as well as what factors are consequential human driving behavior. At the same time, there is a growing need for automated applications to be fair, secure, and resilient. Participants in the workshop will exchange ideas on these and allied topics, including data science and open-source data sets for smart cities, decision making for smart cities, design of intelligent systems in smart cities, and challenges in deployment, equity, and fairness in smart cities, as well as security and privacy in AI for cities.
The Workshop on Data-Driven and Intelligent Cyber-Physical Systems (DI-CPS) was started in 2021 in conjunction with CPS-IoT Week. After a successful workshop this year, we seek to continue the workshop at CPS-week next year, albeit with a specific focus on intelligent CPS for smart cities. The 2020 edition of DI-CPS received 10 submissions and had a total attendance of approximately 30. This year, we are also introducing a best paper award based on reviewer scores. Also, in addition to having experienced faculty members as part of the PC, we are nominating senior graduate students to the PC to provide them with experience in participating in program committees of academic events. Papers assigned to graduate students will have an extra reviewer chosen from the senior members of the PC. The workshop invites researchers and practitioners from academia, industry, and government to submit original research papers, papers describing lessons learned, concept papers, or descriptions of software tools on the following categories:
We welcome long papers (8 pages), short papers (4 pages), and concept papers (2 pages) including appendices and references. Submissions must use the IEEE conference format. Only PDF or latex-zipped files will be accepted. There is no requirement to anonymize the submissions; Authors may choose to submit anonymously or not. Accepted papers will be published with IEEE and appear on IEEE Xplore; however, authors can choose to opt out of formal proceedings. We welcome prior work published in conferences or journals (authors will have to opt out of publication in case the submitted work does not add to the previously published version, but can still present their work at the workshop). Each accepted paper must be presented by a registered author. Submissions not meeting these guidelines risk immediate rejection. For questions about these policies, please contact the chairs.