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GENERIC ANIMATION TOOL FOR TRAFFIC SIMULATION

GENERIC ANIMATION TOOL FOR TRAFFIC SIMULATION

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GENERIC ANIMATION TOOL FOR TRAFFIC SIMULATION

ABSTRACT

Traffic simulation has become one of the most popular ways for traffic analysis in support of traffic system design and evaluation.

Although traffic flow models have been used to describe, simulate, and predict traffic for than a century, digital computer programmes to simulate traffic flow were developed in the 1950s.

Simulations began to include animation techniques as computer power increased. These animation approaches and visualisations allowed officials, decision makers, and the general public to see the overall performance of a traffic system design while also giving an outstanding means of presenting the result patterns from a simulation model in a relevant way.

This paper describes the development of an animation/visualization tool for road traffic simulation that is both independent (stand-alone/unrelated to a traffic simulator) and generic (can visualise output data from any traffic simulator).

Because this application uses Google Maps as its background, users can observe the animation of a simulation output on any target road. The animation’s source data is an XML file including vehicle information.

1.1 INTRODUCTION TO CHAPTER ONE

BACKGROUND OF THE RESEARCH
Simulations of any system allow users and decision makers to evaluate different system tactics before deploying them in the field. Since the 1950s, digital computer programmes that mimic traffic flow have been developed.

Because of 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 unique tool for capturing the complexities of traffic systems due to its capacity to imitate the time variability of traffic phenomena (Barcelo, 2010).

Numerous traffic-related research activities 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 development.

Traffic flow models can specifically reflect the physical distribution of traffic flows. Different traffic simulation models can be used to replicate large scale real-world scenarios in great detail.

Traffic flow models are divided into macroscopic, mesoscopic, and microscopic models based on their level of detail. The following are brief summaries of several model kinds.

1.1.1 MACROSCOPIC MODELS
Macroscopic models take a broad picture of traffic flow. In other words, these models are typically based on continuous traffic flow theory, with the goal of observing/assessing the time-space development of the variables representing traffic flows.

Volume, speed, and density are supposed to be defined at every instance in time t and at every location in space x. Since the 1960s, macroscopic models have sparked interest.

FREFLO – motorway FLOw (Payne, 1979), METANET – Modèle d’Ecoulement du Trafic Autoroutier: Network (Messmer et al., 1990-9), are examples of these types of models.
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1.1.2 MICROSCOPIC MODELS
This model focuses on individual cars and their interactions. It simulates driver/vehicle behaviours such as acceleration/deceleration and lane changes in reaction to traffic.

Such models attempt to answer questions such as the nature of a driver’s reaction to an incident, quantifying a driver’s sensitivity, and so on. Microscopic models include lane-changing models for multi-lane traffic as well as car-following models for single-lane traffic.

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) are some examples.

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

However, based on recent research, mesoscopic models have not received much attention. DYNAMEQ – Dynamic EQuilibrum, DYNMIT (Barcelo, 2010), and others are examples.

1.2 VISUALISATION OF ROAD TRAFFIC SIMULATOR
Because of the massive volumes of data held in traffic and transportation databases, as well as the amount of data created by simulation models, the visualisation component of road traffic simulation research is gaining significant interest from both academia and business (Shekar et al., 1997).

Data generated by simulation models is difficult to interpret for planners, policymakers, and even the modellers running the simulation, especially when it is vast.

This resulted in the incorporation of visualisation and related approaches into traffic modelling and simulation, allowing for the extraction of meaningful information from vast amounts of data.

The majority of available visualisation tools are either linked with traffic simulators or built specifically for traffic simulators. METROPOLIS (https://sourceforge.net/projects/transims-metro) is a visualisation tool built 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.

A variety of road design methodologies, ranging from graphs and charts to 2D/3D road network designs and maps (Open Street Map, Google 3 Earth), have been incorporated in road traffic visualisation tools.

Very few visualizers are stand-alone (that is, independent of the simulation model or software used) programmes that can input data describing the road network and vehicle trajectories and yet present their output in real time.

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

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

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

1.3 THE OBJECTIVE
This project aims to create an animation/visualization tool for road traffic simulation that is independent, generic (that is, it can visualise output data from any traffic simulator),

and has a realistic feel of traffic observation due to the incorporation of Google Maps in its dynamic form; the user only needs to pan to the road being observed on the map.

Because XML files can be rapidly read, transferred, and their format set in a standardised fashion using XML schema, they will be used as the data source for this visualisation.

1.4  STRUCTURE OF WORK

We organise our work as follows: The second chapter provides a study of the literature on Visualizers of Traffic Simulation and their implementation methodologies, while the third chapter presents our design methodology.

Our application’s implementation and testing are covered in Chapter 4. In Chapter 5, we complete our work, describe the constraints we encountered, and provide guidance for future work.

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