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Simulations of any system allow users and decision makers to evaluate different system techniques prior to their implementation in the field. Digital computer programmes for simulating traffic flow have been developed since the 1950s.

With the rising capacity of computer technology, developments in software engineering, and the introduction of intelligent transportation systems, traffic simulation has become one of the most widely used methodologies for traffic analysis in support of traffic system design and evaluation.

Traffic simulation is a one-of-a-kind technique for capturing the complexities of traffic systems because of its capacity to replicate the time variability of traffic phenomena.

Numerous research activities on traffic systems have focused on modelling, simulation, and visualization/animation of rural and urban traffic using advances in computer technology, either to assess alternatives in traffic management or to assist traffic system construction in urban areas.

Traffic flow models can be used to precisely portray the physical distribution of traffic flows. Using several traffic simulation models, one may simulate large-scale real-world scenarios in great depth.

Traffic flow models are characterised as macroscopic, mesoscopic, or microscopic according to their level of detail. Brief descriptions of various model types are shown below.

1.1.1 Macroscopic Models

Macroscopic models depict traffic flow in general. That is, these models are typically based on continuous traffic flow theory, which aims to observe/assess the time-space evolution of the variables that describe traffic flows.

These variables are volume, speed, and density, and they are supposed to be defined at every point in space x and time t. Macroscopic models have gained popularity since the 1960s.

Examples of these models include FREFLO – motorway FLOw (Payne, 1979) and METANET – Modèle d’Ecoulement du Trafic Autoroutier: Network (Messmer et al., 1990-9).


This type of model focuses on individual cars and their interactions. It simulates driver/vehicle movements such as acceleration/deceleration and lane changes in reaction to surrounding traffic.

Such models attempt to answer concerns such as the nature of a driver’s response to an event, determining a driver’s sensitivity, and so on. Microscopic models include car-following models for single-lane traffic and lane-changing models for multi-lane traffic.

Examples include FRESIM – motorway micro-SIMulator, CORSIM – CORridor SIMulation, VISSIM – a German abbreviation for “Traffic in Towns – Simulation,” and TRANSIMS – TRansportation Analysis and Simulation System (Sharon et al., 2001).

1.1.3 Mesoscopic Models

This model combines both microscopic and macroscopic components of traffic flow models. As a result, they have higher computational efficiency than microscopic models.

However, based on current trends, mesoscopic models have received little academic interest. Examples include DYNAMEQ, Dynamic EQuilibrum, and DYNMIT (Barcelo, 2010).

1.2 Visualisation for Road Traffic Simulators.

The visualisation component of road traffic simulation research is gaining traction in academia and business due to the massive volumes of data held in traffic and transportation databases, as well as the amount of data created by simulation models (Shekar et al., 1997).

Data generated by simulation models, particularly when vast, is difficult to interpret for planners, policymakers, and even the modellers who run the simulation. This resulted in the integration of visualisation and related approaches into traffic modelling and simulation, allowing usable information to be extracted from vast amounts of data.

The majority of available visualisation tools are either connected with or created specifically for traffic simulations. For example, METROPOLIS is a visualisation tool intended for TRANSIMS simulation output (, whereas SUMO (Simulation of Urban MObility – an open-source microscopic, multi-modal traffic simulation) has its visualizer/GUI embedded in its programme.

Road traffic visualisation technologies use several methodologies, including graphs, charts, 2D/3D network designs, and maps (e.g., Open Street Map, Google Earth). Very few visualizers are stand-alone (i.e., not a traffic simulator and unaffected by the simulation model or software used) software that can input data describing the road network and vehicle trajectories while still rendering output in real time.

One such example is vtSim.VIEW, a module created for the vtSim (Validating Environment for Traffic Simulation) data and simulation management framework (Wenger et al., 2013).

Based on the research and reviews conducted during this project, it was discovered that the majority of these visualizers’ road networks were manually designed or constructed, with various mathematical calculations performed to simulate an almost exact geometry of the road network being observed.

For the few visualisation tools that use or incorporate Google Maps, Google Earth, or OpenStreetMap as a background, the map data is either converted to a simulator-specific road network format using a tool in its package (SUMO) or the map is used as a background photo with the model overlaid (VISSIM) (Matthew et al., June 2007).

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