No abstract

This paper explores the application of count models to represent the relationship between flight disruptions and weather. Throughout the world, flights are regularly disrupted by delays at airports and in the terminal airspace, and less frequently by diversions and cancelations. Many delay studies have been conducted for large American and European airports, in part due to the availability of high-quality data. However, such high-quality data is not as readily available for other airports throughout the world. In this study, excess-zero count models are built using a publicly available dataset for Iqaluit Airport (YFB) in Northern Canada, to determine the influence of different weather components on disruption counts. Visibility and crosswind speeds are shown to have the largest influence on flight disruptions. The models are also applied using Aviation System Performance Metrics (ASPM) flight data for Anchorage Airport (ANC) in Alaska; the data is systematically degraded to match completeness of the Iqaluit data to test the models. The results verify that an excess-zero model using incomplete data yields results similar to that of a count model with complete data, demonstrating that an excess-zero model can overcome data incompleteness to yield acceptable results. Although count models have been applied extensively in the transportation literature, the authors believe this to be the first application to flight disruptions, and the first quantitative model of operations at a northern Canadian airport. This paper demonstrates that challenges in data availability—the case for most airports throughout the world—can be addressed with novel statistical modeling applications, and thus, delay studies can be conducted for almost any airport.

With the growing population of the megacity, Dhaka is facing severe deficiency in transportation sector. For its cheap fare, the main mode of transport for the poor is bus. Also it is the only option available as public transport. But the level of service of bus is not satisfactory. In addition to the insufficient public transportation system, Dhaka also lacks in infrastructure. On top of that, car ownership is increasing pretty rapidly piling up the traffic congestion. These sum up to a longer travel time; a significant portion of which is spent halting either for congestion or for collecting passengers. This study focuses on the stopping time and the moving time of a bus trip. The discrepancy between demand and supply of public transport is quite severe in Dhaka. When the demand is higher than supply during the peak period or near CBD area, buses get full and overcrowded at earlier stoppages. In such cases, drivers skip the later bus stops where people need to wait longer for bus. But the scene is completely reversed when demand is less than supply. In such cases, drivers tend to wait longer intentionally at the earlier bus stops in the hope of collecting sufficient passengers, termed here as intentional waiting time. This study tries to understand and verify the situation. The result suggest that the intentional waiting time influences the total stopping time significantly. Most of which occurs in the earlier sections of the route and with increasing distance from the origin, the waiting tendency keeps decreasing. The passenger boarding trend follows similar trend. Lack of guideline is one of the main reasons for such behavior and the demand, land use pattern, bus occupancy etc. are some of the major factors influencing intentional waiting to a great extent.