Scalable Urban Traffic Control

Scalable URban TRAffic Control [1] (SURTRAC) is an adaptive traffic control system developed by researchers at the Robotics Institute , Carnegie Mellon University . SURTRAC dynamically optimizes the control of traffic signalsto Improve traffic flow for urban Both grids and corridors; optimization goals include less waiting, reduced traffic congestion , go short trips, and less pollution. The core control engine combines schedule-driven intersection control (SchIC) [2] with decentralized coordination mechanisms. [3] Since June 2012, A pilot implementation of the SURTRAC system [4] has been deployed on nine intersections in the East Liberty neighborhood of Pittsburgh , Pennsylvania . [5]SURTRAC has been reduced to an average of 40%. [6] [4] A second phase of the pilot program for the Bakery Square district has been running since October 2013. [7]


The SURTRAC system design has three characteristics. Citation needed ] First, decision making in SURTRAC proceeds in a decentralized manner. Decentralized control of individual intersections allows greater responsiveness to local real-time traffic conditions. Decentralization facilitates scalability by allowing the incremental addition of controlled intersections over time with little change to the existing adaptive network. It also reduces the possibility of a centralized computational bottleneck and avoids a single point of failure in the system.

A second characteristic of the SURTRAC design is an emphasis on real-time responsiveness to changing traffic conditions. SURTRAC Adopts the real-time view of prior model-based control methods intersection [8] qui attempt to compute intersection control Plans That optimize traffic actual inflows. By reformulating the optimization problem as a single engine scheduling problem, the core optimization algorithm, termed a schedule-driven intersection control algorithm, [2] is reliable to compute optimized intersection control planes over an extended horizon was second-by-second basis.

A third characteristic of the SURTRAC design is to manage urban (grid-like) road networks, Where there are multiple (Typically competing) dominating flows That shift dynamically through the day, and Where specific dominant flow can not be Predetermined (as in arterial or major Crossroad applications). The intersection controllers. The combination of competing dominant flows and densely spaced intersections presents a challenge for all adaptive traffic control systems. SURTRAC determines dominant flows dynamically by continually communicating projected outflows to downstream neighbors.


The SURTRAC system uses closed-circuit television cameras to sense traffic conditions. [9] Surveillance of public places with CCTV networks has been criticized as an enabling totalitarian forms of government by undermining people’s ability to move about anonymously . Images Gathered by CCTV cameras Can Be Analyzed by automatic number plate recognition software, Permitting fully automated tracking of vehicles by the license plates (number plates) They carry. Similarly, facial sensors can be analyzed to determine whether or not they are the same.

It has been suggested that the benefits of traffic optimization have never been scientifically justified. It inherently favors motorized traffic over alternate modes such as pedestrians, bicyclists, and transit users. [10] [11] It is suggested that an alternate approach could involve traffic calming , and a conceptual focus on the movement of people and goods rather than vehicles.

The WATERWAY system is designed to provide a warning signal that will not cause a warning signal. WALK signal, or else the pedestrian will be given a continuous “DO NOT WALK” signal, despite having a green light. Pedestrians are unlikely to ever reach an intersection that has already had a walk. This results in the same intersection, essentially making pedestrians second-class citizens of the streets. Also, many pedestrians are unaware that pushing the button is mandatory in order to receive a walk, and are confused when an entire light cycle occurs without ever being allowed to cross.

Because they require a continuous supply of electricity, automatic traffic signals are not suitable for use in places where the electric supply is sporadic or nonexistent. For example, traffic in Pyongyang, North Korea is guided by government workers who stand in the intersections under umbrellas. [12] [13]

When drivers become accustomed to automated traffic signals, they may forget how to properly yield the right of way, so that when the electric supply is interrupted, as when a disaster occurs, the traffic has never been used . [14] [ original research? ] This effect Could conceivably delay evacuation or Impede the movement of emergency vehicles.

The introduction of traffic signals and associated laws may undermine democracy by means of citizens to reflexively obey the signal lights. [15] [16] [ original research? ]

Roundabouts are an alternative to signaling systems. At a roundabout, motor traffic may not be able to come to a stop (so that drivers’ time and fuel may be saved), and crossing for pedestrians may be easier. Studies of intersections converted to roundabouts have found reductions in the frequency and severity of accidents. [17] However, these benefits may not be realized if a roundabout is poorly designed. Roundabouts typically require a concave demolition of adjacent structures, so doing such conversions in heavily built-up areas.

See also

  • Traffic optimization
  • Adaptive traffic control
  • Smart traffic signals
  • Traffic light control and coordination
  • Intelligent transportation system
  • Transportation demand management
  • Automated planning and scheduling

Other adaptive traffic control systems

  • Sydney Coordinated Adaptive Traffic System
  • InSync adaptive traffic control system


  1. Jump up^ Xiao-Feng Xie, S. Smith, G. Barlow. Smart and Scalable Urban Signal Networks: Methods and Systems for Adaptive Traffic Signal Control. US Patent No. 9,159,229, 2015.
  2. ^ Jump up to:a b Xiao-Feng Xie, Stephen F. Smith, Liang Lu, Gregory J. Barlow. Schedule-driven intersection control . Transportation Research Part C: Emerging Technologies, 2012, 24: 168-189.
  3. ^ Jump up to:a b Xiao-Feng Xie, Stephen F. Smith, Gregory J. Barlow. Schedule-driven coordination for real-time traffic network control . International Conference on Automated Planning and Scheduling (ICAPS), Sao Paulo, Brazil, 2012: 323-331.
  4. ^ Jump up to:a b Stephen F. Smith, Gregory J. Barlow, Xiao-Feng Xie, Zachary B. Rubinstein. Smart urban signal networks: Initial application of the SURTRAC adaptive traffic signal control system . International Conference on Automated Planning and Scheduling (ICAPS). Rome, Italy, 2013.
  5. Jump up^ Stephen F. Smith, Gregory Barlow, Xiao-Feng Xie, and Zack Rubinstein. SURTRAC: Scalable Urban Traffic Control. Transportation Research Board 92nd Annual Meeting Compendium of Papers, 2013.
  6. Jump up^ Walters, Ken (October 16, 2012). “Pilot Study on Traffic Lights Reduces Pollution, Traffic Clogs” . CMU website . Carnegie Mellon University . Retrieved January 31, 2013 .
  7. Jump up^ “Real-World Deployments – Bakery Square” .
  8. Jump up^ M. Papageorgiou, C. Diakaki, V. Dinopoulou, A. Kotsialos, and Y. Wang. Review of road traffic control strategies. Proceedings of the IEEE, 2003, 91 (12): 2043-2067.
  9. Jump up^ Walters, Ken (2012-10-16). “Smart Signals: Pilot Study on Traffic Lights Reduces Pollution, Traffic Clogs” . CMU Piper . Retrieved 2013-01-28 .
  10. Jump up^ Michael J. Vandeman,”Is Traffic Signal Synchronization Justifiable?” , April 15, 1994
  11. Jump up^ Meyer, Robinson. “Sorry, Los Angeles: Synchronizing Traffic Lights May Not Reduce Emissions” . . Retrieved 28 January 2013 .
  12. Jump up^ “Traffic Control Platform beneath Umbrella Installed at Intersections of Pyongyang” . KCNA. 2009-08-13 . Retrieved 2013-01-29 .
  13. Jump up^ “Meet The Ladies Of The Pyongyang Traffic Bureau” . 2010-03-05 . Retrieved 2013-01-29 .
  14. Jump up^ Remaly, Jake (2012-10-29). “Fallen Trees, Wires, Poles Wreak Havoc on I-287, Local Roads in Morris County – Jefferson, NJ Patch” . . Retrieved 2013-01-29 .
  15. Jump up^ “Houghton Mifflin Textbook – Chapter Outline” . . Retrieved 2013-01-29 .
  16. Jump up^ U. Houston: PSYCH 1300: Chptr_07 ” . . Retrieved 2013-01-29 .
  17. Jump up^ “Q & A: Roundabouts” . . Retrieved 2013-01-29 .

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