GENERIC ANIMATION TOOL FOR TRAFFIC SIMULATION

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ABSTRACT

Traffic simulation has become one of the most used approaches for traffic analysis in support of the design and evaluation of traffic systems. Although traffic flow models have been applied for almost a century to describe, simulate and predict traffic, digital computer programs to simulate traffic flow have been developed from the 1950s. With the increasing power of computers, simulations began to incorporate animation techniques. These animation techniques and visualizations allowed viewing the overall performance of a traffic system design while providing an excellent means of communicating the result patterns from a simulation model to officials, decision makers and the general public in a meaningful way.


This work presents the design of an animation/visualization tool for road traffic simulation, which is independent (stand-alone/separate from a traffic simulator) and generic (that is, can visualize output data from any traffic simulator). This tool implements Google Maps as its background, thereby enabling users to view the animation of a simulation output on any target road. The source data for the animation is an XML file which holds vehicle information.


TABLE OF CONTENTS

ABSTRACT
LIST OF FIGURES

CHAPTER 1: RESEARCH CONTEXT
1.1       INTRODUCTION
1.1.1    MACROSCOPIC MODELS
1.1.2    MICROSCOPIC MODELS
1.1.3    MESOSCOPIC MODELS
1.2       VISUALIZATION FOR ROAD TRAFFIC SIMULATORS
1.3       OBJECTIVE
1.4       STRUCTURE OF WORK

CHAPTER 2: LITERATURE REVIEW
2.1       INTRODUCTION TO TRAFFIC M&S
2.2       GRAPHICAL TRAFFIC SIMULATIONS
2.2.1    SUMO
2.2.2    VISUAL TRAFFIC SIMULATION
2.2.3    3-D VISUALIZATION FOR MICROSCOPIC DATA SOURCES
2.3       PROJECT PROPOSAL

CHAPTER 3: DESIGN METHODOLOGY
3.1       OVERVIEW
3.2       DESIGN CONCEPT
3.2.1    SOFTWARE COMPONENTS

CHAPTER 4: IMPLEMENTATION AND TESTING
4.1       INTRODUCTION
4.2       CODE TRANSLATION
4.2.1    JAVA CODE
4.2.2    THE HTML FILE
4.2.3    THE XML FILE
4.3       SYSTEM PROCESS
4.3.1    ALTERNATIVE APPROACH
4.4       TESTING
4.4.1    FIRST APPROACH
4.4.2    ALTERNATIVE APPROACH

CHAPTER 5: GENERAL CONCLUSION
5.1       OBSERVATION
5.2       ASSUMPTIONS AND LIMITATIONS
5.3       FUTURE WORK
REFERENCES


CHAPTER 1
RESEARCH CONTEXT


1.1        INTRODUCTION

Simulations of any system give users and decision makers an opportunity to appraise alternative strategies of the system before implementing them in the field. Digital computer programs to simulate traffic flow have been developed from the 1950s. The increasing power of computer technologies, the advances in software engineering and the advent of intelligent transport systems prompted traffic simulation to be one of the most used approaches for traffic analysis in support of the design and evaluation of traffic systems. The ability of traffic simulation to emulate the time variability of traffic phenomena makes it a unique tool for capturing the intricacy of traffic systems (Barcelo, 2010).

Numerous research activities that have been carried out on traffic systems have concentrated on modelling, simulation and visualization/animation of rural and urban traffic by taking advantage of advances in computer technology, either to assess alternatives in traffic management or to assist traffic system construction in urban development. The physical dissemination of traffic flows can be specifically depicted using traffic flow models. By utilizing different traffic simulation models, one can simulate large scale real-world situations in great detail. Depending on the level of detailing, traffic flow models are classified into macroscopic, mesoscopic and microscopic models. Brief descriptions of these model types are illustrated below.

1.1.1    MACROSCOPIC MODELS


Macroscopic models view the traffic flow in general. That is, these models are usually based on the continuous traffic flow theory whose objective lies in observing/assessing the time-space development of the variables describing the traffic flows. These variables are volume, speed and density, which are assumed to be defined at every instance in time t and every point in space x. Macroscopic models gained interest since the 1960s. Examples of these types of models include FREFLO – FREeway FLOw (Payne, 1979), METANET – Modèle d’Ecoulement du Trafic Autoroutier: Network (Messmer et al., 1990-9).....


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