Ting Bai, Ph.D.

Postdoctoral Research Associate at Cornell University

About Me

Postdoctoral Research Associate

I am a Postdoctoral Research Associate at IDS Lab , Cornell University, the United States, under the supervision of Prof. Andreas A. Malikopoulos. Prior to this position, I held a Postdoctoral Researcher position at KTH Rolyal Institute of Technology, Sweden, supervised by Prof. Jonas Mårtensson and Prof. Karl Henrik Johansson.

I am on the academic job market! Please feel free to get in touch.

  • Name: Ting Bai
  • Title: Postdoctoral Research Associate
  • E-mail: tingbai@cornell.edu
  • Institution: Cornell University, Ithaca, NY

 

Research Interests

My research interests include Cyber-Physical Systems (CPS), Networked Control Systems (NCS), Optimal control, Model predictive control (MPC), Dynamic Programming (DP), and their applications to large-scale transportation systems. Please refer to the Research Section for more details of my research.

I am open to research discussion and collaboration. Please feel free to reach out to me!

News

Biography

Education

Ph.D., Control Science and Engineering

Sep 2013 - Dec 2019

Shanghai Jiao Tong University (SJTU), Shanghai, China

Advisor: Prof. Shaoyuan Li

Dissertation: Design and Synthesis of Distributed Reconfigurable Predictive Control Systems

Award: Career Development Scholarship for Outstanding Doctoral Graduates in SJTU (2020-2022)

B.Eng., Automation

Sep 2009 - Jun 2013

Northwestern Polytechnical University (NPU), Xi'an, China

Thesis: Research on the Principle Prototype of Soft PLC based on Embedded Systems

Awards:

  • Special Award for New College Students (Top 1%)
  • Outstanding Graduate in NPU (2013)
  • Excellent Graduation Thesis in NPU (2013)

Work Experience

Postdoctoral Researcher

Nov 2024 - Present

Cornell University, New York, the United States

Advisors: Prof. Andreas A. Malikopoulos

Postdoctoral Researcher

Sep 2020 - Sep 2024

KTH Royal Institute of Technology, Stockholm, Sweden

Advisors: Prof. Jonas Måtersson, and Prof. Karl H. Johansson

Award: Future Digileaders selected by Digital Futures (2020)

Postdoctoral Researcher

Mar 2020 - Sep 2020

Shanghai Jiao Tong University (SJTU), Shanghai, China

Advisors: Prof. Shaoyuan Li, and Prof. Guangtao Xue

Award: Super Postdoctoral Fellow in Shanghai (2020)

Selected Research

Below are three selected interesting research I have done.

Rollout-Based Charging Strategy for Electric Trucks

Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and rest time regulations, known as hours-of-service (HoS) regulations. We study optimal charging problems of electric trucks with delivery deadlines under HoS constraints. We assume that a collection of charging and rest stations are given along a pre-planned route with known detours and that the problem data are deterministic. The goal is to minimize the total cost associated with the charging and rest decisions during the entire trip. This problem is formulated as a mixed integer program with bilinear constraints, resulting in a high computational load when applying exact solution approaches. To obtain real-time solutions, we develop a rollout-based approximate scheme, which scales linearly with the number of stations while offering solid performance guarantees. We perform simulation studies over the Swedish road network based on realistic truck data. The results show that our rollout-based approach provides near-optimal solutions to the problem in various conditions while cutting the computational time drastically.

Related Publications:


DP-Based Multi-Fleet Platoon Coordination Approach

The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefits of platooning, efficient dispatching strategies that facilitate the platoon formations across fleets are required. We present a distributed framework for addressing multi-fleet platoon coordination in large transportation networks, where each truck has a fixed route and aims to maximize its own fleet's platooning profit by scheduling its waiting times at hubs. The waiting time scheduling problem of individual trucks is formulated as a distributed optimal control problem with continuous decision space and a reward function that takes non-zero values only at discrete points. By suitably discretizing the decision and state spaces, we show that the problem can be solved exactly by dynamic programming (DP), without loss of optimality. The realistic simulation study performed over the Swedish road network with 5,000 trucks shows that, compared to single-fleet platooning, multi-fleet platooning provided by our method achieves around 15 times higher monetary profit and increases the CO2 emission reductions from 0.4% to 5.5%. In addition, it shows that the developed approach can be carried out in real time and thus is suitable for platoon coordination in large transportation systems.

Related Publications:


Platoon Coordination for Large Transport Systems

We consider the problem of hub-based platoon coordination for a large-scale transport system, where trucks have individual utility functions to optimize. An event-triggered distributed model predictive control method is proposed to solve the optimal scheduling of waiting times at hubs for individual trucks. Under this distributed framework, trucks are allowed to decide their waiting times independently and only limited information is shared between trucks. Both the predicted reward gained from platooning and the predicted cost for waiting at hubs are included in each truck's utility function. The performance of the coordination method is demonstrated in a simulation with one hundred trucks over the Swedish road network.

Related Publications:

Publications

Preprints

Distributed Charging Coordination for Electric Trucks under Limited Facilities and Travel Uncertainties
Under revision, 2024.
T. Bai, Y. Li, K. H. Johansson, and J. Mårtensson

 

Journal Papers

J10. Deeper and Stronger Feature PAP Network for Object Detection in Remote Sensing Images
IEEE Geoscience and Remote Sensing Letters, 14(8), 2024.
L. Jiang, Y. Li, and T. Bai J9. Large-Scale Multi-Fleet Platoon Coordination: A Dynamic Programming Approach
IEEE Transactions on Intelligent Transportation Systems, 24(12), 14427-14442, 2023.
T. Bai, A. Johansson, K. H. Johansson, and J. Mårtensson J8. Rollout-Based Charging Strategy for Electric Trucks with Hours-of-Service Regulations
IEEE Control Systems Letters, 7, 2167-2172, 2023. (Presented at the 62nd CDC, Dec. 13-15, 2023.)
T. Bai, Y. Li, K. H. Johansson, and J. Mårtensson J7. A Third-Party Platoon Coordination Service: Pricing under Government Subsidies
Asian Journal of Control, 1-14, 2023.
T. Bai, A. Johansson, S. Li, K. H. Johansson, and J. Mårtensson J6. Platoon Cooperation Across Carriers: From System Architecture to Coordination
IEEE Intelligent Transportation Systems Magazine, 15(3), 132-144, 2023.
A. Johansson, T. Bai, K. H. Johansson, and J. Mårtensson J5. RMAU-Net: Residual Multi-Scale Attention U-Net for Liver and Tumor Segmentation in CT Images
Computers in Biology and Medicine, 106838, 2023.
L. Jiang, J. Ou, R. Liu, Y. Zou, T. Xie, H. Xiao, and T. Bai J4. Distributed MPC for Reconfigurable Architecture Systems via Alternating Direction Method of Multipliers
IEEE/CAA Journal of Automatica Sinica, 8(7), 1336-1344, 2021.
T. Bai, S. Li, and Y. Zou J3. Block-Based Minimum Input Design for the Structural Controllability of Complex Networks
Automatica, 107, 68-76, 2019.
T. Bai, S. Li, Y. Zou, and X. Yin J2. Distributed Model Predictive Control for Networked Plant-Wide Systems with Neighborhood Cooperation
IEEE/CAA Journal of Automatica Sinica, 6(1), 108-117, 2019.
T. Bai, S. Li, and Y. Zheng J1. Minimum Input Selection of Reconfigurable Architecture Systems for Structural Controllability
Science China Information Sciences, 62, 019201:1–019201:3, 2019.
T. Bai, S. Li, and Y. Zou

 

Conference Papers

C6. Distributed Charging Coordination of Electric Trucks with Limited Charging Resources
22nd European Control Conference (ECC), Stockholm, Sweden, June 25-28, 2024.
T. Bai, Y. Li, K. H. Johansson, and J. Mårtensson C5. Approximate Dynamic Programming for Platoon Coordination under Hours-of-Service Regulations
61st IEEE Conference on Decision and Control (CDC), Cancún, Mexico, December 6-9, 2022.
T. Bai, A. Johansson, K. H. Johansson, and J. Mårtensson C4. A Pricing Rule for Third-Party Platoon Coordination Service Provider
13th Asian Control Conference (ASCC), Jeju Island, Korea, May 4-7, 2022.
T. Bai, A. Johansson, S. Li, K. H. Johansson, and J. Mårtensson C3. Event-Triggered Distributed Model Predictive Control for Platoon Coordination at Hubs in A Transport System
60th IEEE Conference on Decision and Control (CDC), Austin, Texas, USA, December 13-17, 2021.
T. Bai, A. Johansson, K. H. Johansson, and J. Mårtensson C2. Distributed MPC for Reconfigurable Architecture Systems via Alternating Direction Method of Multipliers
29th Chinese Process Control Conference (CPCC), Shenyang, China, July 27-30, 2018. (Best student paper--final list)
T. Bai and S. Li C1. Less Attention Event-Driven Model Predictive Control of Time-Delay System
10th Asian Control Conference (ASCC), Kota Kinabalu, Malaysia, May 31-June 3, 2015.
T. Bai, S. Li, and D. Huang

 

Notes

Coalitional Games
T. Bai, July 31, 2023, updated.
Stability and Feasibility Proof of Distributed Model Predictive Control
T. Bai, January 16, 2019.

Professional Services

Program Committee

Journal Reviewer

  • Automatica
  • IEEE Transactions on Automatic Control
  • IEEE Transactions on Intelligent Transportation Systems
  • IEEE Transactions on Transportation Electrification
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Intelligent Vehicles
  • IEEE Transactions on Control Systems Technology
  • IEEE/CAA Journal of Automatica Sinica
  • IEEE Internet of Things Journal
  • IEEE Control Systems Letters
  • ACM Transactions on Cyber-Physical Systems
  • Control Engineering Practice
  • Journal of the Franklin Institute
  • Systems & Control Letters
  • Energies

Conference Reviewer

  • IEEE Conference on Decision and Control (CDC)
  • American Control Conference (ACC)
  • European Control Conference (ECC)
  • IFAC World Congress (IFAC WC)
  • IFAC Symposium on Control of Power & Energy Systems (IFAC CPES)
  • IFAC Symposium on Control in Transportation Systems (IFAC CTS)
  • IEEE Conference on Intelligent Transportation Systems (ITSC)
  • IEEE Intelligent Vehicles Symposium (IV)
  • Learning for Dynamics & Control Conference (L4DC)
  • Asian Control Conference (ASCC)
  • Chinese Control Conference (CCC)

Supervision