Problem Motivation
Conventional urban traffic signal control relies on centralized coordination, limited local autonomy, and incomplete real-time awareness. These constraints reduce robustness under demand surges, incidents, sensor noise, and network disruptions, and limit cost-effective scaling across a city.
Goal
DALI-TCS investigates a distributed, autonomous alternative that augments existing traffic infrastructure with software-defined intelligence. The objective is an adaptive and scalable traffic control system that works with standard sensing at intersections (e.g, inductive loops), supports incremental deployment, and remains practical to operate and maintain at city scale.
Core Research Contributions
- Intersection agents: An agent-based control layer that enhances each intersection controller with autonomous decision logic.
- Agent to agent coordination: A communication model that uses available connectivity among controllers to support cooperative behavior.
- Distributed adaptive strategy: A multi-agent control strategy for real-time coordination across intersections, with an emphasis on measurable performance gains, robustness, and scalability.
- Deployment-ready architecture: A system architecture designed for incremental rollout across cities of varying size and infrastructure maturity.
Deployment Evidence
DALI has been deployed in the City of Richardson, where field results show meaningful reductions in delay. Expanded sensing coverage and higher-fidelity sensor data (e.g., from cameras) strengthen the system’s situational awareness and can further improve performance.
Research Recognition
(callout box – as a right-hand callout aligned with the bottom of the section content or below the Deployment Evidence section)
Research on DALI TCS began in 2015, building on earlier foundational concepts and architectures. The work has led to patented technology, multiple research awards, and local and international recognition. DALI TCS represents the first academically documented deployment of a real-time collaborative traffic control based on direct agent-to-agent communication in the United States.