Bus & Tram
Government strategy for transport is to tackle congestion and pollution by improving all types of transport. This includes examining transport as a whole to form integrated transport solutions, and modernising the transport network to make it better, safer, cleaner and quicker.
Traffic models are very useful for investigating the maximum improvements to travel time and reliability that can be attained from implementing priority measures. From bus lanes to guided bus, to bus gates, to selective vehicle priority at junctions and to queue relocation, traffic models can determine the benefits of any combination of priority measures along a whole route.
Fox Traffic Simulation has a wealth of experience in building and using traffic models to assess and maximise the benefits of public transport priority schemes.
Micro-simulation models are excellent for assessing bus priority systems.
Aimsun Micro is particularly good for investigating the benefits of bus priority. It has standard built-in methods for providing priority at signals. This is simple pre-emption logic that can be used to test basic priority methods without the need of additional signal logic programming. This pre-emption logic in Aimsun Micro uses detectors to provide the priority. One detector is used to request a priority stage at a junction and another detector is used to cancel the priority request once the tram or bus has passed through the junction. The priority requests can be limited to specified tram or bus routes. Additional parameters can be set to inhibit further demand requests until a specific time has passed following a priority stage or to maintain signal co-ordination with adjacent junctions or to specify whether to allow stages to be skipped before the priority stage is served.
If the user needs to model more sophisticated priority methods Aimsun Micro also has an Applications Programmable Interface (API) that lets a user code up any signal logic they need to test. The interface has a comprehensive range of functions for interrogating the state of the network, e.g. through detectors or radio beacons or GPS and setting signals, VMS, route guidance, vehicle speeds etc. The logic can be written using the general purpose C++ or Python programming languages. A user can also write code with the API that enables their Aimsun Micro models to interact with external applications, such as signal control systems (SCOOT, MOVA etc), ramp metering systems, dynamic route guidance systems, incident management systems etc.
Trams and LRT
Tram systems are becoming increasingly popular as a means of helping to solve the problems of congestion in the major cities of the UK. Road space is extremely limited in most cities. Tram systems work by reallocating space from the private car to the far more space-efficient public transport. Two hundred passengers in a tram take up much less road space than the equivalent number in private cars. Time spent at stops can be reduced by level boarding and by passengers not having to queue to buy tickets from the driver. Traffic management and special lanes for trams can ensure that the service will not be held up in congestion. These traffic management measures can also have the effect of reducing private car movements in the area, further helping to reduce accidents, noise and air pollution. Stated preference surveys have revealed that car drivers are much more likely to change mode to use a tram than to switch to other forms of public transport such as trolley or high quality buses.
When designing a new tram system it is important to be able to estimate the operational characteristics of any proposed design. Run times need to be calculated so that they can be fed into economic models that predict patronage levels. The ability of any priority measures to reduce travel times and to help maintain headways between tram services is often a critical issue. The modelling of tram delays as a result of traffic signals or of congestion associated with traffic signals is considered a significant element within the overall analysis of tram operations. Within networks of closely spaced traffic signals, it is usually necessary to take into account the requirements of other road users including buses and general traffic and to achieve an acceptable balance between competing demands when designing a signal control strategy.
One of the most accurate ways of predicting the performance of a new tram system is to use Aimsun Micro. Its ability to model complex road junctions and congested networks, and at the same time provide a visual representation of the proposed effects on traffic operations makes it the ideal tool. The visual representation of problem and solution in a format understandable to layman and professional can be a powerful way to gain more widespread acceptance of complex strategies. Some of the proposed solutions, such as selective vehicle priority at traffic signals, are often difficult to model with conventional methods. Some proposals may offer relatively small improvements to travel conditions but yet still be able to achieve significant benefits in terms of increased capacities, a better environment, or safer travelling conditions.
SPRUCE is a new traffic control system that was initially developed by Leeds City Council and Sheffield City Council within the government sponsored Urban Traffic Management & Control (UTMC) programme. Having successfully trialled a prototype version of the software in both Sheffield (on trams) and Leeds (on buses) the City Council, in recognition of the importance of the system in the delivery of its transport policies, is currently funding the final phase of software development, which will see SPRUCE become a software product available to any local authority.
SPRUCE is a control system which can be programmed, using logic functionality well understood by designers of traffic signal controllers, so as to achieve specific control techniques applicable to particular networks. Strictly not a ‘strategy’ in itself, more a ‘strategy implementer’, SPRUCE is designed to provide a means of solving most control situations - ultimately limited more by the imagination of the user than by software. Experience has shown that developing specific strategies is a detailed process, which sensibly involves the use of micro-simulation modelling techniques. Aimsun Micro played a key role in the development of the SPRUCE strategies in both Sheffield and Leeds. Aimsun Micro models of the study networks were built and the SPRUCE strategies were developed and fine tuned using the Aimsun models before being implemented on-street.
A study has also been carried out to investigate the use of SPRUCE in Croydon. The principal aim of the study was to investigate the feasibility of introducing traffic signal co-ordination between the five signal controlled junctions on Wellesley Road for buses and general traffic while providing a level of priority for trams. An Aimsun micro-simulation model of these five signalised junctions along Wellesley Rd was developed in order to test the new SPRUCE tram priority strategies. The study showed that there is definite potential for a new signal control strategy on Wellesley Road that links the operation of the signals for buses and general traffic without compromising current tram performance. Through the Aimsun simulation it has been shown that the devised strategy would reduce delay and stops on Wellesley Road for buses and general traffic by as much as 40% compared with the delays measured on site in the PM peak. At the same time tram delays through the same network would not be increased.