Driven by the rapid development of information and vehicular technologies, we are on the cusp of a revolution in transportation on a scale not seen since the introduction of automobiles. For instance, smart mobile devices retrieve users’ geolocations, enable ubiquitous communications, and allow instant peer-to-peer interactions, giving rise to various on-demand mobility services for goods and people such as ridesourcing and ridesharing, as well as crowd-sourced urban delivery. Connected and automated vehicle (CAV) technologies will further revolutionize urban and rural mobility and support a range of uses, from sole vehicle ownership to shared ownership, ridership, and subscription services. These technologies hold the potential to substantially improve traffic safety, facilitate mobility, and reduce traffic congestion, fuel consumption, and emissions.

-Current Practice - Fixed time/actuated/adaptive Signal

-Detector-Free Signal Operation

  • Connected Vehicle Data Collection 
  • Intersection Map Generation with V2I Information
  • Traffic Volume Estimation at Signalized Intersections with CV Information
  • Eco-driving Advisory with V2I Information

Spatiotemporal Traffic Control

-Lane Reassignment

  • Maximum Capacity inteRsection Operation Scheme with Signals (MCRoss) 


  • Utilize all lanes of a road simultaneously
  • Lane assignment and green duration are dynamically assigned
  • Intersection reaches theoretical full capacity

-Signal-Free Intersection

  • Traffic signals are removed from the intersection
  • Reservation based control mechanism (e.g., FCFS), no optimality is guaranteed
  • Corridor level “signal free” intersection management with CAV
    • Car following, lane changing and collision avoidance within the intersections of each vehicle are modeled explicitly
    • All vehicle movements are allowed in each lane
    • A mixed integer linear programming (MILP) model is constructed to solve for delay minimization

- Resources

Papers in Refereed Journals: 
1. Zheng, J. and Liu, H.* (2017) Estimating Traffic Volumes for Signalized Intersections Using Connected Vehicle Data, Transportation Research Part C, 79. 347-362.
2. Yu, C., Feng, Y., Liu, H.X., Ma, W. and Yang, X., 2018. Integrated optimization of traffic signals and vehicle trajectories at isolated urban intersections. Transportation Research Part B: Methodological, 112, pp.89-112.
3. Feng, Y., Yu, C. and Liu, H.X., 2018. Spatiotemporal intersection control in a connected and automated vehicle environment. Transportation Research Part C: Emerging Technologies, 89, pp.364-383.
4. Feng, Y., Zheng, J. and Liu, H. X. (2018) ‘Real-Time Detector-Free Adaptive Signal Control with Low Penetration of Connected Vehicles’, Transportation Research Record.
5. Sun, W., Zheng, J., and Liu, H. (2017) A capacity maximization scheme for intersection management with automated vehicles, to be presented at the 22nd International Symposium of Transportation and Traffic Theory (ISTTT 22).