Abstract

The introduction of urban rail transit and high performance/quality/capacity bus transit systems throughout the world has dramatically improved the mobility of residents of cities in which they operate. The objectives of this work are: to provide a technical resource for transit planners and designers in developing cities in their public transport capacity and performance analysis work irrespective of mode. This report recommends methods of achieving practical transit capacity during normally encountered operating conditions. Where capacity is influenced by a measure of dispersion of some characteristic such as stop dwell time or vehicle headway, this is also noted. The purpose of measuring capacity is not just to provide a measure of system capability to transport passengers but also to provide some insight into the effect of service and physical design on customer service quality. When the demand for a service exceeds its schedule design capacity, service quality deteriorates either due to overcrowding on vehicles or at station platforms or diminished ability of customers to board the next arriving transport vehicle since it is already fully loaded, increased dwell times and hence decrease revenue speeds. The importance of service quality in transit capacity analysis cannot be overstated. Transit operators should be mindful that the urban transportation marketplace is more competitive. While it might be technically possible to design a service using a loading standard of 7 or 8 passengers per square meter, a number of customers will find that level intolerable and will seek alternate means of travel including walking (in the case of short distance trips), riding with someone else, riding taxis or purchasing a motorcycle or car. Accordingly, such loading standards should be thought of as interim measures until higher capacity at lower crowding can be achieved. Document type: Book

Abstract

The tendency of buses to bunch is a problem that was defined almost 50 years ago. Since then, there has been a significant amount of work done on the problem; however, the tendency of the current literature is either to only focus on the surface causes or to rely on simulation to create results instead of model formulation. With GPS installed on many buses throughout the world, the data is only being used for monitoring and informing the user. This research proposes a new approach to solving the problem that uses the GPS data to directly counteract the cause of the bunching by allowing the buses to cooperate with each other and determine their speed based on relative position. A continuum approximation model is presented as a tool to systematically analyze the behavior of the system and test the proposed control. In order to validate the model and the control, a simulation tool is used to model the system in a more realistic, discrete way. The control is shown to produce bounded deviations in spacing consistent with those predicted by the model. The resulting bus system will not bunch with only a small reduction in commercial speed.