This paper describes a simulation modeling system we have developed, called Airport Capacity Analysis Through Simulation (ACATS). Airport capacity, in the sense of the average throughput obtainable during periods of high demand, is determined directly by simulating a constant flow of arrivals and departures for hundreds of hours. The user interface for ACATS provides a fast way to set up the elements of the airport that are essential for calculating runway capacity. It also supports the use of Air Traffic Control (ATC) separation rules that may become feasible as technology improves. The software in the user interface automatically converts the data for any airport into a standardized set of files that are then processed by the ACATS simulation software. At the core of the ACATS software is a simulation engine that is common to all airport analyses. That means that the simulation is driven by data representing the ATC rules, runway layout, and demand characteristics. The output of ACATS includes an animation of the simulation, statistics about the observed throughput, and a set of graphical analysis charts. The animation and graphical results produced by ACATS are important tools in explaining the analysis to the end user and in validating the results of the simulation. This paper will describe 1) the ACATS user interface tool that permits the user to easily describe the problem, 2) the ACATS simulation module, and 3) the methodology that governs the ACATS algorithms.

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As the first article of a two-part series, the purpose of this paper is to examine the functional factors that contribute to automobile accident occurrence and to model the causation structure in the form of a fault-tree. The fault-tree model provides an intuitive framework for qualitatively decomposing possible pathways to accident occurrence. Fault-tree analysis also provides a statistical representation of how interacting driver, vehicle, and environmental factors contribute to the likelihood of automobile accident occurrence. The application of this model facilitates pinpointing those factors that most contribute to accident causation and subsequently enables the identification and comparison of potential crash avoidance technologies.

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