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Abstract
Everyday billions of people around the world face the task of driving their vehicles in the traffic of their region. For many this entails entering very heavy traffic flows centered around large cities, with long commute times, on their way to work.
For others, the issue is that they need to drive to a special event, or are just driving through the city on the way to another destination.
Whatever the reason, drivers have a strong desire to know what the general traffic flow is along the route they plan to use.
Major cities employ traffic engineers to deal with the problem of managing the large traffic flows for which they are responsible. From routine highway and road maintenance, to redesigning existing interchanges, to constructing completely new throughways, city planners face the challenge of meeting the population's demand for efficient road networks.
For both sets of circumstances above, the desire for tools to make traffic-related decision-making easier is quite substantial. Microscopic traffic simulation has a lot to offer for modeling and forecasting traffic flows. These simulations are not only models of the overall flow of vehicles, but model the detailed interactions of the cars themselves, allowing for a depth of analysis not possible with other modeling techniques. Indeed, microscopic traffic simulation can offer prescriptive solutions to traffic problems, where, for example, city planners can try out different solutions for traffic design, without having to actually construct anything.
In order to build an effective and accurate traffic simulation model, there are many tasks that must be completed. The specific data for an area must be analyzed and used to build a realistic arrival model. A car-following model must be chosen, so that the vehicles in the simulation behave in a realistic manner. Finally, the various parameters of these models must be fine-tuned with a calibration technique so that the models are as accurate (or as efficient) as possible. This work analyzes the arrival problem, chooses two well-known car-following models, and applies several calibration methodologies in an effort to identify the best means by which to build the traffic simulation model.
Major cities employ traffic engineers to deal with the problem of managing the large traffic flows for which they are responsible. From routine highway and road maintenance, to redesigning existing interchanges, to constructing completely new throughways, city planners face the challenge of meeting the population's demand for efficient road networks.
For both sets of circumstances above, the desire for tools to make traffic-related decision-making easier is quite substantial. Microscopic traffic simulation has a lot to offer for modeling and forecasting traffic flows. These simulations are not only models of the overall flow of vehicles, but model the detailed interactions of the cars themselves, allowing for a depth of analysis not possible with other modeling techniques. Indeed, microscopic traffic simulation can offer prescriptive solutions to traffic problems, where, for example, city planners can try out different solutions for traffic design, without having to actually construct anything.
In order to build an effective and accurate traffic simulation model, there are many tasks that must be completed. The specific data for an area must be analyzed and used to build a realistic arrival model. A car-following model must be chosen, so that the vehicles in the simulation behave in a realistic manner. Finally, the various parameters of these models must be fine-tuned with a calibration technique so that the models are as accurate (or as efficient) as possible. This work analyzes the arrival problem, chooses two well-known car-following models, and applies several calibration methodologies in an effort to identify the best means by which to build the traffic simulation model.