Search

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process - Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS.

This paper reports on the research done under a National Aeronautics and Space Administration (NASA) Research Announcement task, “Assessment of System Safety Risks for NextGen Concepts and Technologies.” We describe the methods and tools used in the task and results from first-order analyses of two NextGen ground-based automation concepts. The first-order results demonstrate the ability of the assessment method developed in previous NASA research to address NextGen concepts and to link research results rigorously to systemwide risk. The method explicitly addresses response times and failures, and the results, while first-order, specifically identify the time criticality of tactical conflict detection and resolution. I. Introduction n this research, we extended and applied to automated NextGen concepts the separation assurance safety risk assessment method we developed for the NASA Research Announcement task, “Conduct Safety Analysis of the Separation Assurance Function in Today’s National Airspace System (NAS)” (Ref. 1). As in our previous work, we addressed the task objective in two ways. First, we established functional and quantitative frameworks to allow integration of the results of all forms of safety and risk research into a single risk assessment. Second, we identified sources of data and developed and tested modeling tools to demonstrate the feasibility of our analysis approach. We conducted first-order risk assessments of two NextGen concepts: a Ground-Automation Controlled (GAC) concept based on the Advanced Airspace Concept (AAC) proposed by Erzberger in Ref. 2, and a near-term GroundAutomation Assisted (GAA) concept based on the concept proposed by McNally et al. in Ref. 3. Both concepts are based on managing traffic with ground-based automation using data link communications to control aircraft on timebased four-dimensional trajectories (4DTs). This paper describes analysis of the fully operational concepts plus two abnormal conditions. The first abnormal condition is a loss of intent data condition, which could be caused by a weather or emergency disruption leading to open 4DTs or by a hardware failure leading to loss of transmitted intent data; the second is a single aircraft inoperative transponder condition, which could be caused by hardware failure or by being turned off. Both concepts include a ground-based strategic element, a ground-based tactical element, an airborne Traffic Alert and Collision Avoidance System (TCAS) element, and an airborne see-and-avoid element. The AAC concept includes a monitoring human controller element, while the human-based GAA concept includes an active human controller in the strategic and tactical elements. The paper is organized as follows: 1) Section II presents our aviation safety risk analysis method and introduces the two NextGen concepts assessed. 2) Section III discusses the conflict modeling tool and the conflict probability data used for the risk assessments.