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There are over 5 million reported motor vehicle collisions annually in the United States, and while crash rates and fatality rates have declined in the past decades, rates in work zones are disproportionately high. There are strict standards for evaluating the crashworthiness of temporary traffic control devices, but not for evaluating drivers’ comprehension of existing or novel device deployments. This dissertation presents a series of three experiments evaluating driver comprehension for existing and novel traffic control devices conducted in a work zone setting. This evaluation is further expanded by decomposing the task of comprehending traffic control into the three subtasks of detection, localization, and identification. Methods are proposed for conducting a computer-based experiment with still image stimuli to measure participant performance at each of these subtasks. Next, procedures for categorizing localization responses and accounting for variation in participants physical responses are explored. Lastly, an application of Item Response Theory toward the evaluation and comparison of participant comprehension is demonstrated. It is hoped that these methods and procedures can be used by future researchers and experimenters to compare novel temporary traffic control devices and systems to inform future design.

published_or_final_version / Psychology / Master / Master of Philosophy

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Air Traffic Control (ATC) is a complicated domain in which many specialists should collaborate and communicate with each other in order to guarantee safe and efficient air traffic. A significant number of air traffic control errors are associated with either faulty coordination between ATC actors, or a failure of some kind of team coordination. These errors are likely to increase in the future as aircraft density increases. Many researchers suggest that the introduction of team and teamwork concepts during the training phase of the ATC actors will be in help to reduce the amount of these errors. The objective of this research is to conceive, design, and implement a teamwork-oriented Air Traffic Control simulator that can be easily installed and used in ATC schools. The product of this thesis will be a complete software package that allows trainees in the different ATC specialties to work together in the same manner as they do "on-the-job" in order to collaboratively manage an air traffic situation. This type of simulator should allow air traffic control trainees to acquire more robust coordination skills and reduce the amount of traffic control errors caused by lack of teamwork in actual ATC training situations. / Tunisian Air Force author.

The National Airspace System in its current incarnation is nearing its maximum capacity. The Free Flight initiative, which would alter the current system by allowing pilots to select more direct routes to their destinations, has been proposed as a solution to this problem. However, allowing pilots to fly anywhere, as opposed to being restricted to planned jetways, greatly complicates the problem of ensuring separation between aircraft. In this thesis I propose using cooperative, multi-agent negotiation techniques in order to efficiently and pseudo-optimally resolve air traffic conflicts. The system makes use of software agents running in each aircraft that negotiate with one another to determine a safe and acceptable solution when a potential air traffic conflict is detected. The agents negotiate using the Monotonic Concession Protocol and communicate using aircraft to aircraft data links, or possibly the ADS-B signal. There are many benefits to using such a system to handle the resolution of air traffic conflicts. Automating CD&R will improve safety by reducing the workloads of air traffic controllers. Additionally, the robustness of the system is improved as the decentralization provided by software agents running in each aircraft reduces the dependence on a single ground based system to coordinate all aircraft movements. The pilots, passengers, and carriers benefit as well due to the increased efficiency of the solutions reached by negotiation.

Borrowing ideas from natural immunity, Artificial Immune Systems (AIS) offer a novel approach to solving many diagnosis, optimization and control problems. In the course of this research this paradigm was applied to the problem of optimizing urban traffic. The traffic was micro-simulated with each car on a two junction road system modeled individually. The cars themselves were programmed with 'personalities' to better simulate real traffic. A novel AIS was developed to detect, predict, and control anomalous traffic conditions. It was also used to optimize the flow of traffic through the road network. Benchmarking was performed against the well accepted TRANSYT traffic control system. Though the TRANSYT system performed better initially, the AIS control showed marked improvement over time as it adapted better to changing traffic conditions. This change was expected as TRANSYT is optimized for specific initial conditions unlike the AIS system which adapts to changes.

The purpose of this study was to include consideration for intersections into the previously created GIS traffic control planning tool. Available data for making intersection control calculations were collected and integrated into the design of the tool. The limitations created by required assumptions were addressed, as well as more advanced techniques for overcoming these problems. The tool can be use to estimate capacity calculations at any signalized intersection within the NCTCOG modeling region. These calculations can be used to inform users about the effects of a construction plan. Inputs for using dynamic traffic assignment to further understand these effects is then addressed, focusing on the development of a subnetwork to reduce computation time for multiple temporary traffic control plans. / text

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