The Smartest Tools

This section describes the current status of the micro-simulation tools developed by the SMARTEST consortium.

AIMSUN2 (Advanced Interactive Microscopic Simulator for Urban and Non-urban Networks) is a software tool capable of reproducing real traffic conditions in an urban network which may contain both expressways and arterial routes. It is based on a microscopic simulation approach. The behaviour of every single vehicle in the network is continuously modelled throughout the simulation time period, according to several driver behaviour models (car following, lane changing, gap acceptance). AIMSUN2 is a combined discrete-continuous simulator: there are some elements of the transportation system (vehicles, detectors) whose state changes continuously over the simulated time period, while there are other elements (traffic lights, entrance points) whose state changes discretely at specific points during the simulation time. It provides very detailed modelling of the traffic network: it distinguishes between different types of vehicles and drivers; it can deal with a wide range of network geometries; it can also model incidents, conflicting manoeuvres, etc.

AIMSUN2 needs three types of input data: the network description, the traffic signal control plans and the traffic conditions. The network description contains information about the geometry of the network, turning movements, layout of links (or sections) and junctions and location of detectors. The traffic control plans define the signal stages and their duration for signal controlled junctions, the priority definition for unsignalized junctions and any required ramp-metering information. The essential inputs for the simulator are the traffic flows for the input links, the turning proportions at junctions and the initial state of the network.

Recently, as part of a DGXVII funded project, AIMSUN2 has been linked to the UK SCOOT UTC system. AIMSUN2 passes details of the vehicle flows in the network to SCOOT. SCOOT uses this flow data to calculate signal timings which are designed to minimise the amount of delay experienced by all the vehicles in the network. It passes these signal timings back to AIMSUN2 where they are implemented.

The outputs provided by AIMSUN2 include a continuously animated graphical representation of the traffic network, a printout of statistical data (flows, speeds, journey times, delays, stops, fuel consumption, pollution emissions), and data gathered by the simulated detectors (counts, occupancy, speeds, queue lengths).

AIMSUN2 is integrated into the GETRAM simulation environment (Generic Environment for Traffic Analysis and Modelling), which consists of a traffic network graphical editor, a network data base, static assignment models, temporal simulation models and a module for storing and presenting results.

A parallel version of AIMSUN2 has recently been completed (Barcelo, 1996), so that computationally expensive problems can be tackled. It uses a Sun SparcStation 1000 with 8 processors under Solaris 2.4 via Solaris threads. It was developed in the framework of the ESPRIT Programme, High Performance Computing Initiative, as a subproject of Project PACOS, PCI project EP-9602. The project was successfully concluded last September.

NEMIS was designed as a specific solution to the problem of on-street testing. Its ability to model urban networks in microscopic detail (individual vehicles, single intersections or road sections) makes it a valuable tool for testing traffic control strategies or techniques at local and area levels.

NEMIS is a scientific software package and, since its creation, it has been used principally for research and development work and for the technical assessment of traffic control strategies. It has been developed for the micro-simulation of urban traffic (private and public) in large scale networks. It is capable of modelling urban networks and vehicle behaviour in considerable detail, and is well structured to meet a variety of application needs. Its usefulness has been demonstrated for the following tasks:

Other areas where NEMIS may be used include:

A key feature of NEMIS is its ability to model each individual vehicle in the urban network. Vehicles may belong to two categories: private and public. Currently six classes of private vehicle are provided and two classes exist for public transport. Private vehicles may be fixed route or fixed origin and destination (O/D vehicles) or "floating" (i.e. vehicles used for route guidance strategies).

The main information maintained for each vehicle is:

Vehicle movement within the network is determined by:

Simulation occurs in increments of one second. Outputs include pollution emissions and fuel consumed by vehicles in the network.

An interface program has been produced to link NEMIS to both the SCOOT and SPOT UTC systems, allowing them to interact. NEMIS is able to receive, in real time, control strings for the traffic signals and to send back vehicle counts from sensors located in the simulated network in the format required by the UTC system.

SPEACS. SPEACS is a discrete time, single car micro-simulator of motorway corridor conditions. It was first developed under the PROMETHEUS Programme and has since been extended and enhanced so that the current version provides car movement in a 3-lane corridor, simulation of ICC functions and the effects of information provided through external ATT infrastructures. The model has been calibrated using data from the peri-urban motorway around Bari and the Padova-Mestre motorway corridor.

Each vehicle-driver pair is assigned parameters, such as maximum speed, acceleration, desired speed, driver attitude etc. The vehicle is moved according to an empirical car following law based on a model proposed by Gibbs, but improved to provide closer similarity to actual traffic density-flow characteristics. Behavioural and decisional rules are used to simulate manoeuvres such as overtaking, lane changing etc. These rules take account of vehicle-driver characteristics and preferences and the behaviour of surrounding vehicles.

The model is also able to simulate traffic sensor functions. It is possible, for example, to place 'inductive loops' along the motorway section at intervals of 200 m or more and thus divide the corridor into a series of equipped stretches.

The evolution of traffic conditions can be followed by means of an interactive graphics interface that allows immediate information to be obtained on any single vehicle or stretch of the motorway. The information is provided in the form of tables, histograms or the visual representation of single equipped stretches. The interface also permits incidents or hazards to be introduced in the course of the simulation. Despite the absence of a specific user manual, the program is very easy to use and training requirements are therefore minimal.

The SPEACS micro-simulator has been used to develop and assess speed control strategies for the EASY DRIVER system on the Padova-Mestre motorway corridor. It has also been used in PROMETHEUS and the DRIVE I DOMINC Project for the assessment of ICC functions. It has been interfaced with a car simulator model to assess the effects of longitudinal control.

DRACULA (Dynamic Route Assignment Combining User Learning and Micro-simulation) is a microscopic traffic network modelling suite, conceived and developed at the Institute for Transport Studies, University of Leeds over a five year period. It is part of the SATURN suite of programs developed at ITS and is exploited with WS Atkins consultants. The development, testing and validation of the model have been primarily funded by a large grant from the UK Engineering and Physical Sciences Research Council, although some early applications of the model were possible under funding from the EC's DRIVE II Telematics programme. Applications of this model in progress, or to commence shortly, include the study of congestion based road pricing, real time traffic signal control, dynamic route guidance, segregated busway design, emergency evacuation procedures (e.g. Following chemical explosions, floods), and strategic (inter-urban) modelling. Presently DRACULA is able to model the effect of policy, demand and network changes on route and departure time choice, but there are plans to extend this range of choices to cover "higher level" choices, concerning the mode of travel and residential/work location.

We refer to DRACULA as a "supermodel" because it incorporates a range of possible assumptions and levels of detail, which may be selected by the transport planner depending on the objectives of the study. For example, driver choices (e.g. of route) may be modelled at the level of the individual drivers or at an aggregate level; one second increment discrete micro-simulation may be used to move drivers along their chosen routes, or macroscopic traffic models may be used; route choice may be assumed to be the only choice open to drivers (or even be fixed), or we may model departure time choice, en route diversion in response to unexpected conditions, or the details of lane choice switching to avoid blocked or heavily queued lanes. A selection of a particular combination of supermodel parameters gives rise to a particular model within the DRACULA suite. (Of course, within such a model there will be model parameters which need to be calibrated to each particular network).

DRACULA differs from "traditional" equilibrium approaches in that it explicitly models the day-to-day dynamic evolution of driver behaviour and traffic conditions, as a discrete time stochastic process. At its most detailed and comprehensive level, DRACULA has the following structure:

  1. Initialisation. For each potential traveller in the network, assume initial perceived travel costs for each link in the network. Set day counter k=0.
  2. OD demand. Increment day counter: k=k+1. Generate the set of travellers who will actually make a car journey on day k.
  3. Travel choice. Each individual travelling on day k selects a departure time and route based on their currently perceived travel costs.
  4. Supply variability. Simulate day-to-day variability in characteristics of the traffic (supply) model, to represent rain/snow, accidents, parked vehicles, breakdowns, etc.
  5. Traffic model. Load the travel choices in step 3 onto the network using a one-second increment micro-simulation model, recording individual travel experiences. During this stage, en route diversion from the originally selected route may occur.
  6. Learning. Via some kind of learning mechanism, each individual forms an updated perceived (day-averaged) travel cost for each link/turn and arrival time interval. Return to step 2 to simulate the next day.
This stochastic process approach possesses a sound theoretical basis, and indeed has a number of advantages over its equilibrium counterpart. In rough terms, this theory establishes that under mild conditions, such a model will settle down, after an initial transient period, to a characteristic level of variability - this representing the real day-to-day variability in road conditions that we all know exists. From a practical viewpoint, the separation of traveller behaviour and traffic flow/congestion in the day-to-day approach is the key to the enormous flexibility and range of assumptions that DRACULA may incorporate, being highly suitable for further development.

In terms of modelling special events such as accidents, breakdowns or weather conditions having a severe effect on road capacity, DRACULA is ideal, being able to model how drivers respond in terms of en route diversions (when seeing queues or receiving radio information, for example), taking account of how they weight their typical experience (stored in their personal history file) compared to extreme conditions. On the traffic flow side, second-by-second micro-simulation using lane changing and gap acceptance models is the only feasible technique in existence for modelling severe queue spillback (as opposed to the vertical queue assumption of typical macroscopic and mesoscopic approaches), the effect on the details of driver behaviour (e.g. weaving through gaps in stationary cross-traffic at a junction, lane changing in response to accidents), and the dynamic propagation of congestion backwards in the system (often referred to as the shock wave phenomenon).

SITRA-B+. Developed by CERT, it is able to model medium sized urban networks including complex intersection topology and is particularly suited to the assessment of real time UTC strategies including bus priority and route guidance strategies.

SITRA-B+ is a urban TRAffic SImulation tool for the assessment of traffic control and route guidance strategies (vehicles are equipped with on-board devices and receive either dynamic impedances or optimal recommended routes towards their destination).

SITRA-B+ can also be used to assess off-line assignment techniques, building of infrastructure, public transport policy etc.

The simulation is microscopic, i.e. each vehicle is an individual entity. The change in the simulation states occurs in discrete moments, the car following law is a linear combination of relative velocity and headway between the considered and preceding vehicles.

The current version is written in the object oriented language C++.

SITRA-B+ enables the modelling of complex intersections, lanes in links, any type of vehicles, parks, sensors, etc.

The demand in the network is generated using either (i) flows Origin-Destination matrices or (ii) inputs flows associated with the turning movements at the intersections. By default, the internal traffic signal management strategy uses fixed plans.

Traffic signal management and route guidance strategies developed for assessment are independent from the simulator : a synchronisation protocol manages the communication (i) from data measured by SITRA-B+ sensors (magnetic loops, infra-red beacons, radio) to the external strategies and (ii) from controls elaborated by these external strategies (phases, routes, updated travel times) to SITRA-B+ (traffic lights and equipped vehicles).

The graphical interface (SUN workstation) and the organization by data files (from the user point of view) are two advantages of the user-friendly SITRA-B+ tool. Statistical results are available during and at the end of simulations, allowing the assessment of developed strategies.

References

Barcelo (1996) The parallelization of AIMSUN2 Microscopic Traffic Simulator for ITS applications, presented at the 3rd World Conference on Intelligent Transport Systems", held in Orlando on October 14-18, 1996.

Back to the Smartest Home Page.