Large-scale Traffic Simulation Research Articles

Transforming GIS Data into Functional Road Models for Large-Scale Traffic Simulation

There exists a vast amount of geographic information system (GIS) data that model road networks around the world as polylines with attributes. In this form, the data are insufficient for applications such as simulation and 3D visualization-tools which will grow in power and demand as sensor data become more pervasive and as governments try to optimize their existing physical infrastructure. In this paper, we propose an efficient method for enhancing a road map from a GIS database to create a geometrically and topologically consistent 3D model to be used in real-time traffic simulation, interactive visualization of virtual worlds, and autonomous vehicle navigation. The resulting representation provides important road features for traffic simulations, including ramps, highways, overpasses, legal merge zones, and intersections with arbitrary states, and it is independent of the simulation methodologies. We test the 3D models of road networks generated by our algorithm on real-time traffic simulation using both macroscopic and microscopic techniques.

Development of a Large-Scale Traffic Simulation Model for Hurricane Evacuation—Methodology and Lessons Learned

This paper focuses on traffic modeling of large-scale hurricane evacuation networks. Several research efforts to date have addressed the evacuation problem from a local perspective. The largest network found in the open literature on microscopic simulation of evacuation operations was of an area 45 miles long and 15 miles wide. The current study models 10 cities with a total length of approximately 2,000 miles of roadway including freeways, arterials, and local streets in two regions in Virginia--the Hampton Roads region and the city of Richmond. This research accomplished the following objectives: (1) estimate the traffic performance of evacuation routes and other major arterial streets; (2) locate the major bottlenecks, congestion, or other operational difficulties in the network; (3) estimate the total network evacuation time; and 4) recommend amendments to the traffic control plan to improve the traffic performance. The simulation results led to the following conclusions: (1) for a category 4 storm with high hotel occupancy, almost all vehicles (99%) were able to exit the network by the end of 27 h; (2) traffic demand on I-64 exceeded capacity for the section between I-64/Fort Eustis Blvd. and I-64/I-295 interchanges, significantly reducing the speed of evacuating vehicles; (3) the reversed lanes can carry more vehicles than their current assigned demand; and (4) for a category 3 storm, the throughput values for different evacuation routes are nearly the same with or without lane reversal. The modeling lessons learned from this research are also documented in the paper. For the network model development, geographic information system maps and a text processing scripting language (e.g., PERL) are shown to be useful tools. Parallel processing is recommended, especially for conducting statistical analysis of output data, given the enormously high run times (25-30 h in the current research) for the detailed simulations. The limitations of microscopic simulation in handling large-scale networks are identified and remedies are suggested.

A Distributed Processing Architecture Using Driver Behavior and a Physical Model for Large-Scale Traffic Simulation

A Distributed Processing Architecture Using Driver Behavior and a Physical Model for Large-Scale Traffic Simulation

A distributed modelling framework for large-scale microscopic traffic simulation

Simulation modelling is an increasingly popular and effective tool for analysing transportation problems, which are not amendable to study by other means. In this paper, we examine the need for distributed simulation from the perspective of computational speedup and development of large-scale network simulation contexts and datasets. After an overview of the general techniques for the distributed discrete-event simulation and previous efforts on the distributed traffic simulation, we present the general architecture of the proposed distributed modelling framework. Two categories of modelling strategies, namely, light global control/independent subnets versus heavy global control/coordinated subnets are described. We have implemented the distributed scheme of light global control/independent subnets and the implemented details, such as communication techniques and vehicle transferring across the boundary of two subnets are discussed. Unlike the previous studies using the dedicated high performance machines, our efforts are to utilise the low-cost networked PCs that are commonly available. By using the Application Programming Interface (API) functions supported by off-the-shelf microscopic traffic simulation software Paramics, we are able to distribute the computational load of microscopic simulation to multiple single-processor PCs without access the proprietary source codes of the simulation program. Performance testing and analysis of the implemented prototype demonstrate that the proposed framework is very promising.

Large-Scale Traffic Simulation Tools for Planning and Operations Management

Traffic simulation tools are becoming increasingly popular for evaluating short-term transportation planning and traffic operations management strategies. Planners and managers may choose from a range of available simulation tools that differ in the accuracy (i.e. fidelity) of their representation of real-world demand and supply phenomena. These tools can generally be classified as microscopic, mesoscopic or macroscopic, representing a decreasing order in level of detail and realism. In this paper, we showcase TransModeler, a simulation model that can handle all three fidelity levels on the same network. This hybrid simulation approach, unique to TransModeler, allows agencies to simulate very large urban networks while choosing the links, segments or corridors that require a detailed, microscopic focus. We present some methodological concepts behind TransModeler, its equilibrium capabilities, and illustrative case studies on real-world networks.

Simulation Program Aims to Model Traffic within Entire Cities

Japanese researchers have announced the development of a simulation program that they claim allows them to model traffic patterns in large cities. The article describes the program by researchers at IBM’s Tokyo Research Laboratory and Kyoto University. The simulator, known as the Large-Scale Multi-Agent Traffic Simulation System, is considered the first of its kind and allows users to determine how changes in mass transit, traffic flow and traffic regulations can influence congestion. It can also simulate emergency evacuations, large-scale events, or the effect on traffic of potentially new commercial establishments. The article describes the systems used in the new simulator, the simulator’s testing in Kyoto last October, and its ability to model aspects as various as speeds, vehicle positions, distances between vehicles, as well as common characteristics of younger versus older drivers.