I am Mingfeng Shang, Ph.D., an Assistant Research Professor in the Department of Civil & Architectural Engineering & Mechanics at the University of Arizona. I serve as Core Faculty with the Center for Applied Transportation Sciences (CATS) and Affiliated Faculty with the Arizona Transportation Institute (AZTI). I earned my Ph.D. from the University of Minnesota in June 2024 under Dr. Raphael E. Stern.

My research focuses on integrating mathematical modeling, control theory, and AI to understand heterogeneous and mixed-autonomy traffic systems, enabling safer, more efficient, sustainable, and cyber-resilient transportation networks.

News

• Jan. 2024: Our paper, ‘‘A Two-Condition Continuous Asymmetric Car-Following Model for Adaptive Cruise Control Vehicles,’’ was published in IEEE Transactions on Intelligent Vehicles. Early access can be found here.
• Nov. 2023: I received the 2023 ITS Minnesota Educational Scholarship from ITS Minnesota

Research 🔬

My research integrates mathematical modeling, control theory, and artificial intelligence (AI) to develop safer, more efficient, sustainable, and cyber-resilient transportation systems.

Featured Publications 📚

• Shang, M., Wang, S., Stern, R. A two-condition continuous asymmetric car-following model for adaptive cruise control vehicles.
  IEEE Transactions on Intelligent Vehicles, 2024.
• Shang, M., Wang, S., Stern, R. Extending ramp metering control to mixed autonomy traffic flow with varying degrees of automation.
  Transportation Research Part C, 2023.
• Shang, M., Rosenblad, B., Stern, R. A novel asymmetric car-following model for driver-assist enabled vehicle dynamics.
  IEEE Transactions on Intelligent Transportation Systems, 2022.
• Shang, M., Stern, R. Impacts of commercially available adaptive cruise control vehicles on highway stability and throughput.
  Transportation Research Part C, 2021.

Other Papers

• Li, T., Shang, M., Wang, S., Stern, R. Detecting subtle cyberattacks on adaptive cruise control vehicles: A machine learning approach.
  IEEE Open Journal of Intelligent Transportation Systems, 2024.
• Wang, S., Shang, M., Stern, R. Analytical characterization of cyberattacks on adaptive cruise control vehicles.
  IEEE Transactions on Intelligent Transportation Systems, 2024.
• Wang, S., Shang, M., Levin, M., Stern, R. A general approach to smoothing nonlinear mixed traffic via control of autonomous vehicles.
  Transportation Research Part C, 2023.
• Jeon, H., Benekohal, R., Garshasebi, B., Shang, M. Comparison of an adaptive signal system to a time-based coordination plan along a signalized arterial.
  Advances in Transportation Studies, 2022.
• Levin, M., Shang, M., Stern, R. Effects of short-term travel on COVID-19 spread: A novel SEIR model and case study in Minnesota.
  PLOS ONE, 2021.

Manuscripts Under Review

• Geffen, G., Shang, M., Wu, Y.J. Evaluating factors influencing post-crash traffic speeds and predictive machine learning models.
• Geffen, G., Shang, M., Wu, Y.J. Novel weather severity classifications based on speed variations using machine learning techniques.
• Zare, A., Shang, M., Kan, D., Stern, R. Generalized multi-phase car-following model for vehicles with adaptive cruise control: Behavioral dynamics and experimental validation for electric vehicles.
• Rosenblad, B., Shang, M., Stern, R. Extending existing ramp metering control in the field for mixed-autonomy traffic.

Sponsored Projects 📝

• SPR-792: State of the Practice of a Data Management Office Within DOTs
  Role: Principal Investigator (PI)
  Sponsor: Arizona Department of Transportation (ADOT)

• Impact of Transportation Electrification on Air Quality and Health in Arizona
  Role: Co-PI
  Sponsor: University of Arizona, Technology and Research Initiative Fund (TRIF)

• Pilot Study of Connected Vehicle Applications to Enhance Incident Response and Roadway Safety
  Role: Co-PI
  Sponsor: City of Phoenix

Teaching 👨‍🏫

Instructor at the University of Arizona

• Fall 2025: CE 363: Transportation Engineering and Pavement Design
• Fall 2024: CE 463/563: Traffic Flow and Capacity Analysis

Connect with me 😊

I enjoy collaborating with colleagues, agencies, and students on advancing safer, smarter, and more sustainable transportation systems.
If you’re interested in partnerships, projects, or just exchanging ideas, I’d be glad to connect.

Research Collaborations
Welcome opportunities to co-develop research projects and grant proposals that connect academic insights with real-world impact.

Talks & Engagements
Available for invited talks, workshops, and guest lectures that bridge research with real-world applications in mobility, data, and infrastructure.

Get in Touch
Feel free to reach out anytime:

• Email: mfshang at arizona dot edu