Smart Infrastructure for Future Urban Mobility
| Autor: | Stephen F. Smith |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Multi-agent system Scalable Urban Traffic Control SIGNAL (programming language) 02 engineering and technology Pedestrian Transport engineering Artificial Intelligence Control system Automated planning and scheduling 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Three-phase traffic theory Intersection (aeronautics) |
| Zdroj: | AI Magazine. 41:5-18 |
| ISSN: | 2371-9621 0738-4602 |
| DOI: | 10.1609/aimag.v41i1.5290 |
| Popis: | Real-time traffic signal control presents a challenging multiagent planning problem, particularly in urban road networks where, unlike simpler arterial settings, there are competing dominant traffic flows that shift through the day. Further complicating matters, urban environments require attention to multimodal traffic flows (vehicles, pedestrians, bicyclists, buses) that move at different speeds and may be given different priorities. For the past several years, my research group has been developing and refining a real-time, adaptive traffic signal control system to address these challenges, referred to as scalable urban traffic control (Surtrac). Combining principles from automated planning and scheduling, multiagent systems, and traffic theory, Surtrac treats traffic signal control as a decentralized online planning process. In operation, each intersection repeatedly generates and executes (in rolling horizon fashion) signal-timing plans that optimize the movement of currently sensed approaching traffic through the intersection. Each time a new plan is produced (nominally every couple of seconds), the intersection communicates to its downstream neighbors what traffic it expects to send their way, allowing intersections to construct longer horizon plans and achieve coordinated behavior. Initial evaluation of Surtrac in the field has demonstrated significant performance improvements, and the technology is now deployed and operating in several U.S. cities. More recent work has focused on integrating real-time adaptive signal control with emerging connected vehicle technology, and exploration of the opportunities for enhanced mobility that direct vehicle (or pedestrian) to infrastructure communication can provide. Current technology development efforts center on vehicle route sharing, smart transit priority, safe intersection crossing for pedestrians with disabilities, real-time incident detection, and integrated optimization of signal control and route choice decisions. This article provides an overview of this overall research effort. |
| Databáze: | OpenAIRE |
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