Microscopic Traffic SIMmulator Model Research Paper

Introduction

For two decades traffic management strategies have benefited from the development of simulation tools. These applications are often used for verification, improvement, and testing of these strategies. Unfortunately, these models are not suitable for ITS applications and large-scale traffic networks. The operational level causes most problems, so a significant effort is made to upgrade these systems. With new ITS developments, incident management, mainline traffic control, and real-time route guidance become possible for traffic management systems.

A variety of new traffic simulation technologies has become available in recent times, with more models coming in the future. These models include DYNASMART, INTEGRATION, and THOREAU. DYNASMART and INTEGRATION are focused on dynamic traffic assignment applications, and their simulation model can be described as mesoscopic. On the other hand, THOREAU is developed as a microscopic model for evaluation. Its running time is too long for comfortable use, but a variety of similar models are about to be introduced for modeling of Automated Highway Systems.

This paper will focus on one such model called Microscopic Traffic SIMmulator, or MITSIM for short. It was created to simulate integrated traffic networks that are supported by surveillance and advanced traffic control systems. Advanced Traveller Information Systems and Advanced Traffic Management Systems are tested and evaluated using MITSIM. This model provides a detailed representation of road networks, while also using lane changing, traffic signal responding logic, and car following to simulate vehicle movements. The route guidance system provides real-time traffic information to capture driver’s route choice decisions by utilizing a probabilistic route choice model.

Simulation Output

The output of MITSIM can be divided into five categories:

1. Information related to vehicles (average speed, travel time, miles traveled) that get measured when a vehicle comes to its destination node;
2. Traffic sensor information (occupancy, traffic counts, speed, travel times, incident information, and vehicle classification);
3. Information about traffic on a specific segment of the road (average speed, density of traffic, travel times) which is reported at a fixed frequency or on simulation completion;
4. Messages about errors and warnings;
5. Display of graphical representations of segment traffic data and vehicle movements.

The amount of data gathered from such testing is often enough to start developing measures of effectiveness for evaluation purposes. Such as queue lengths, emissions, fuel consumption, travel times, and safety.

Hardware and Software Environment

MITSIM is a flexible model, and its code can be extended and modified which leads to continuous upgrades and validation procedures. This flexibility is made possible by its implementation in C++ with the use of the object-oriented programming paradigm. MITSIM is versatile able to run on a variety of operating systems including UNIX, X Windows, XFree86, and Linux, as well as workstations like DEC, SUN, HP, SGI, and IMB. Also, its code can be compiled by multiple compilers like the GNU C++ compiler. The amount of objects that MITSIM can implement is only limited by memory restrictions. Subsequently, the running time is dependent on the number of simultaneous simulations and the size of the network.

User Interface

MITSIM utilizes a graphical user interface to display its data. Network data governs geometry, connectivity, positions of surveillance, control devices, and link type. Vehicle data shows average speed, density, classification, and other traffic data. While surveillance and operations of traffic control are demonstrated by the state of signs and signals, and detection of vehicle passage by detectors.

Although the GUI has an adverse effect on the speed of the MITSIM simulation, its use provides a reliable way to check for errors in input data, and provides a visualization of data that is usually abstract. This feature was used for debugging during the development of MITSIM.

Direction, the speed of segments, and the presence of tunnels determine the color of the road network. Changes in lane regulations are shown by changing colors of lane marks, while special icons are used to show the lane-use privilege. Visualization of the network is updated on every redraw command, such as a change in display mode, zoom, or pan. The GUI is dynamic and shows the current information which is updated with a fixed frequency. MITSIM presents the state of surveillance sectors with colors, and this information is also refreshed at set time intervals. Special icons are used for the traffic control devices to indicate their current state, while incidents are color coded and use a different set of images. Vehicles are represented by colored rectangles with proportional dimensions. Each vehicle has specific information attached to it. This information can include classification, car-following regime, lane changing, turning movement status, speed, and acceleration. MITSIM can be paused at any moment to view the information on individual vehicles.

Conclusion

MITSIM is a microscopic traffic simulation model which is used to evaluate advanced control and surveillance systems. It models integrated traffic networks in detail and uses lane changing, car following, signal, and event responding logic to simulate vehicle behavior. This simulator has a graphical user interface, can communicate with other modules and supports distributed implementation. At the moment, MITSIM is being calibrated at a multitude of facilities by utilizing traffic control and driver behavior data.