science

Scalable Urban Traffic Control

Scalable Urban Traffic Control is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Scalable Urban Traffic Control rather than just read about it. In short: Scalable Urban Traffic Control (SURTRAC) is an adaptive traffic control system developed by researchers at the Robotics Institute, Carnegie Mellon University. SURTRAC dynamically optimizes the control of traffic signals to improve traffic flow for both urban grids and corridors; optimization goals include less waiting, reduced traffic congestion, shorter trips, and less pollution.

Key takeaways

Scalable Urban Traffic Control belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Scalable Urban Traffic Control to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Scalable Urban Traffic Control from memory before moving on to harder problems.

Reference excerpt

Scalable Urban Traffic Control (SURTRAC) is an adaptive traffic control system developed by researchers at the Robotics Institute, Carnegie Mellon University. SURTRAC dynamically optimizes the control of traffic signals to improve traffic flow for both urban grids and corridors; optimization goals include less waiting, reduced traffic congestion, shorter trips, and less pollution. The core control engine combines schedule-driven intersection control with decentralized coordination mechanisms. Since June 2012, a pilot implementation of the SURTRAC system has been deployed on nine intersections in the East Liberty neighborhood of Pittsburgh, Pennsylvania. SURTRAC reduced travel times by more than 25% on average, and wait times were reduced by an average of 40%. A second phase of the pilot program for the Bakery Square district has been running since October 2013. In 2015, Rapid Flow Technologies was formed to commercialize the SURTRAC technology. The lead inventor of this technology, Dr. Xiao-Feng Xie, states that he has no association with and does not provide technical support for this company.

Design The SURTRAC system design has three characteristics. First, decision-making in SURTRAC proceeds in a decentralized manner. The decentralized control of individual intersections enables 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 perspective of prior model-based intersection control methods which attempt to compute intersection control plans that optimize actual traffic inflows. By reformulating the optimization problem as a single machine scheduling problem, the core optimization algorithm termed a schedule-driven intersection control algorithm, is able to compute optimized intersection control plans over an extended horizon on a second-by-second basis. A third characteristic of the SURTRAC design is to manage urban (grid-like) road networks, where multiple competing dominant flows shift dynamically through the day, and where specific dominant flows cannot be predetermined (as in arterial or major crossroad applications). Urban networks also often have closely spaced intersections requiring tight coordination of the intersection controllers. The combination of competing for 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. This information gives each intersection controller a more informed basis for locally balancing competing inflows while simultaneously promoting the establishment of larger "green corridors" when traffic flow circumstances warrant.

Criticism The SURTRAC system employs closed-circuit television (CCTV) cameras to monitor traffic conditions. This use of CCTV networks in public spaces has sparked debate, with some critics arguing that such surveillance can contribute to an erosion of privacy and potentially facilitate more authoritarian forms of governance by reducing the anonymity of individuals in public areas. Moreover, CCTV footage can be processed with technologies like automatic number plate recognition software, enabling the tracking of vehicles based on their license plates. Facial recognition software can also analyze these images to identify individuals by their facial features. However, it is noted that the resolution of the cameras utilized in the SURTRAC system is reportedly not high enough to enable the detection of license plates or the recognition of individual faces. There has also been discussion regarding the overall efficacy and impact of traffic optimization systems. Critics have suggested that the benefits of such systems have not been conclusively proven through scientific study. Additionally, concerns have been raised that these systems might inherently favor motorized traffic, potentially leading to disadvantages for pedestrians, bicyclists, and public transit users, and could inadvertently encourage increased use of automobiles.

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

References

External links SURTRAC adaptive traffic signal control Information about core algorithms and further developments

Worked examples

Example 1 — a first encounter with Scalable Urban Traffic Control

Start with the simplest possible case. Write down what Scalable Urban Traffic Control claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Scalable Urban Traffic Control before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Scalable Urban Traffic Control ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Scalable Urban Traffic Control

In research: Scalable Urban Traffic Control appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Scalable Urban Traffic Control in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Scalable Urban Traffic Control is common in secondary-school and first-year university syllabi. It links to neighbouring topics Intelligent transportation systems, Traffic signals, Traffic simulation, so understanding it makes those chapters shorter.
In everyday life: Look for Scalable Urban Traffic Control outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Scalable Urban Traffic Control in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Scalable Urban Traffic Control means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Scalable Urban Traffic Control out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Scalable Urban Traffic Control in simple terms?

Why does Scalable Urban Traffic Control matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Scalable Urban Traffic Control?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Scalable Urban Traffic Control.