Road Network Operations
& Intelligent Transport Systems
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Urban Traffic Control

Urban Traffic Control (UTC) systems require traffic signals, signal controllers, ramp meters and dynamic message signs (Variable Message Signs – VMS) to control traffic. They also require:

  • a communications system for the transfer of traffic sensor data to signal and equipment controllers
  • data communications between the different controllers
  • intelligent algorithms that use information about current traffic conditions to predict future traffic loads and support decisions on optimal traffic and network control measures – variously to minimise delays, improve traffic throughput, reduce the amount of stopping and starting, vehicle emissions and fuel consumption (See Urban Networks).

Different approaches and measures are used for real-time traffic management and control in urban areas.

Fixed-time Control Systems

Computer signal control systems first appeared in the 1960s when computers were first used to coordinate the traffic signal controllers for a group of intersections – but without the benefit of today’s “feedback” of information from the field detectors to the computers. In this type of system (known as open-loop control) the traffic plans that are implemented are not responsive to actual traffic demand. Instead, plans are developed “off-line” using data from historical traffic counts – and implemented according to time-of-the-day and the day of the week.

This system is quite basic, but it still offers several advantages including:

  • the ability to update signal plans from a central location – greatly facilitating implementation of new signal timing plans as the need arises;
  • the ability to store a large number of signal plans – that can be implemented depending on prevailing traffic conditions;
  • automatic detection of any malfunction in the operation of the controllers or the signal heads.

Systems with Feedback

The next level of sophistication is signal control systems where information from field traffic detectors is fed-back to the central computer. The computer uses the information on current traffic conditions to select the signal plan to be implemented (closed loop control). Plan selection is made according to one of the following methods.

Select a Plan from a Library of Pre-developed Plans

Here, the system has access to a database (library) that stores a large number of different traffic patterns along with the “optimal” signal plans (developed off-line) for each traffic pattern. Based upon information received from the traffic detectors, the computer matches the observed traffic pattern to patterns stored in the library, to identify the most similar pattern. The “optimal” plan associated with the identified pattern is then implemented. This type of adaptive traffic control system is often referred to as a First Generation system. Its distinguishing feature is that the plans, while responsive to traffic conditions, are still developed off-line. First Generation systems work on the basis of current traffic data and do not generally have traffic prediction capabilities.

Develop Plan On-line

In this method, the “optimal” signal plan is computed and implemented in real-time. The optimal signal timings are computed in real-time using current data on traffic conditions obtained from detector information. This requires sufficient computational power to make the necessary computations on-line. It also needs enough data from the vehicle detectors to make the calculations. The systems that develop plans on-line are classified as either Second-Generation or Third-Generation systems. They typically have a much shorter plan update frequency compared to First-Generation systems, typically every 5 minutes for Second-Generation systems, and from 3 to 5 minutes for Third-Generation systems. In addition, some Third-Generation systems use forecasts of traffic conditions obtained from feeding the detector information into a short-term traffic-forecasting algorithm.

Adaptive Traffic Control

There are a number of examples of adaptive traffic control systems in use around the world. Amongst the most widely accepted algorithms are SCOOT, SCATS and RHODES.


SCOOT (Split, Cycle, Offset Optimisation Technique) is an adaptive traffic control system developed by the United Kingdom’s Transport Research Laboratory (TRL) in the early 1980s. SCOOT operates by attempting to minimise a performance index (PI) – typically, the sum of the average queue length and the number of stops across the controlled network. In order to do this, SCOOT modifies the length of the cycle, the amount of green time given to each signal phase (known as the time “splits”), and the offset time for each set of signals (the time difference between the cycle start times at adjacent signals). SCOOT computes these calculations in real-time in response to the information provided by vehicle detectors.

The operation of SCOOT is based upon Cyclic Flow Profiles (CFP). These are presented as histograms (graphical representations of user-specified ranges) that show the variation in traffic-flow over a cycle – which is measured by loops and detectors that are placed midblock on every significant link in the network. Using the CFPs, the offset optimiser calculates the queues at the stop-line. The optimal splits and cycle length are then computed.

Several additional features have been added to SCOOT to improve its effectiveness and flexibility, including the ability to:

  • provide signal priority for public transport (transit) vehicles;
  • automatically detect the occurrence of incidents;
  • add-on an automatic traffic information database to feed historical data into SCOOT – enabling the model to run even if there are faulty detectors.


The Sydney Co-ordinated Adaptive Traffic System (SCATS) was developed in the late 1970s by the Roads and Traffic Authority of New South Wales in Australia. For operation, SCATS only requires stop-line traffic detection, not the midblock traffic detection that is necessary for SCOOT. This simplifies installation since the majority of existing signal systems are equipped with sensors only at stop-lines. SCATS is a distributed intelligence, hierarchical system that optimises cycle length, phase intervals (splits), and offsets in response to detected volumes. For control, the network of signals is divided into a large number of smaller subsystems, each ranging from one to ten intersections. The subsystems run individually unless traffic conditions require the “marriage” – or the integration – of the individual subsystems.


Since 1991, the University of Arizona has been developing a real-time adaptive control system called RHODES, which stands for Real-time Hierarchical Distributed Effective System. RHODES is designed to take advantage of the natural stochastic (random) variations in traffic flow, to improve performance – a feature which is missing from systems such as SCOOT and SCATS.

The RHODES system consists of a three-level hierarchy that decomposes the traffic control problem into three components: network loading, network flow control and intersection control:

  • at the highest level, a stochastic traffic equilibrium model is used to predict expected traffic loads on the links of the network;
  • the second level, Level 2, represents the high-level decision-making process for setting signal timing to optimise traffic flow. This recognises the unpredictable (stochastic) nature of traffic and attempts to take into account future expected traffic loads over the next few minutes. Level 2 is concerned with setting approximate phase sequences and splits for a given corridor (target timings).

Level 3 is concerned with intersection control – determining the optimal time to change traffic signals for the next phase sequence and whether the current phase should be shortened or extended. The time frame for control level 3 is typically in the order of seconds and minutes.

dynamic route guidance

Where there alternative routes available the problem of optimising traffic on the network can be tackled mathematically. For dynamic route guidance (DRG) the “objective function” (an equation expressing the operational function that needs to be maximised or minimised) – is the measure of the highway network’s performance that needs to be optimised. For example the objective might be to minimise the total travel time for all vehicles. The decision variables are the proportions of traffic that splits at each diversion point – to optimise network performance. The traffic-splits define how traffic should be distributed. The aim is to model traffic flow in the region and ensure that it is maintained at the nodes and along the links of the network, without congestion setting in. ITS software can then be used to solve the problem of optimising the objective function and recommending a routing strategy that will vary in real-time according to traffic conditions. Routing advice will be given in traffic broadcasts and on VMS, or with in-vehicle route guidance for those vehicles that are equipped.

Public Transport Priority

Public transport priority (known as Transit Signal Priority or TSP in the USA) is a measure aimed at reducing delay for public transport vehicles (buses, trams, taxis) at signalised intersections by giving their movements preferential treatment. The methods for doing this can be divided into passive and active strategies. The basic difference is whether specialised sensors and detectors are used to detect approaching public transport vehicles. Without supporting technologies to specifically identify these type of vehicles, passive TSP technology simply improves conditions for all vehicles along a public transport corridor.

Active technologies detect an approaching bus or tram (this is typically accomplished by having a transmitter on the vehicle that communicates with a receiver or detector on the roadside signal controller). Different algorithms or strategies are available for active bus priority. Amongst the most common are:

Green Extension: this extends the green time if a bus or tram is detected, to allow the priority vehicle to pass – up to a certain pre-determined limit. This strategy only benefits a small portion of vehicles, but the reduction in delay for beneficiaries is significant (equal to the length of the whole red interval)

Early Green: shortens the green time for conflicting phases, by a pre-defined amount of time – for example when the bus arrives whilst the traffic light is in its red phase. Early green benefits a large percentage of buses, but the saving per vehicle is not as large as for Green Extension

Phase Rotation: under this strategy, the sequence of green time for different manoeuvres at the intersection is changed so that the priority vehicle is not held up. One common modification – that allows the vehicle to cross the opposing traffic stream – involves swapping a dedicated turn signal at the start of the cycle (the “leading” phase) to the end of the cycle (the “lagging” phase).

Actuated Transit Phase(s): involves establishing transit phases, which are only active when a bus/tram is present. In this case, a special transit signal face would display, for example, a letter “B” for Bus or “T” for Tram.

Phase Insertion: this allows the same phase to appear more than once during the same cycle in order to serve the transit vehicle.

Reference sources

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