Evolving Transportation Control Systems Toward Collaborative Mobility

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ALI HAJBABAIE, PH.D.
PROFESSOR AND ASSOCIATE HEAD FOR RESEARCH AND INFRASTRUCTURE
NORTH CAROLINA STATE UNIVERSITY

Evolving Transportation Control Systems Toward Collaborative Mobility

Transportation control systems are undergoing a fundamental transformation as vehicles and infrastructure become increasingly connected, automated, and computationally capable. Traditional traffic control architectures were designed around passive vehicles, local observability, and infrastructure-centered decision authority. Emerging sensing, communication, computation, and actuation capabilities now enable new forms of distributed and collaborative control in which vehicles and infrastructure jointly participate in decision-making.
Rather than treating traffic control as a collection of isolated algorithms, this talk frames it as an architectural problem: as vehicles, infrastructure, and data systems become more capable, decision authority, information flow, coordination, and constraint enforcement must also evolve. This lens connects several streams of our research on scalable optimization and control of transportation networks, moving from infrastructure-centered control toward coordinated and collaborative systems. The talk emphasizes how distributed and decomposition-based methods can make network-level control computationally tractable, how multiple infrastructure control domains can be coordinated under shared system objectives, and how mixed traffic streams of connected automated and human-driven vehicles create new opportunities and constraints for vehicle-infrastructure collaboration. The final part discusses uncertainty-aware formulations that account for sensing, communication, behavioral, and actuation uncertainty in these emerging control architectures.
The broader objective is to develop scalable, real-time, and reliable control architectures for next-generation transportation systems. These control architectures are designed to improve mobility, safety, traffic flow stability, and operational efficiency while explicitly addressing practical challenges related to computation, communication, mixed autonomy, and deployment readiness.