Automatic Vehicle Location Successful Transit Applications

Introduction -- Planning framework -- Estimating BRT ridership -- Component features, costs, and impacts -- System packaging, integration, and assessment -- Land development guidelines.

In this study, a dynamic model for predicting bus arrival times is developed using data collected by a real-world Automatic Passenger Counter (APC) system. The model consists of two major elements. The first one is an artificial neural network model for predicting bus travel time between time points for a trip occurring at given time-of-day, day-of-week, and weather condition. The second one is a Kalman filter based dynamic algorithm to adjust the arrival time prediction using up-to-the-minute bus location (operational) information. Test runs show that the developed model is quite powerful in dealing with variations in bus arrival times along the service route.

Intelligent Transportation Systems (ITS) have transformed surface transportation networks through the integration of advanced communications and computing technologies into the transportation infrastructure. ITS technologies have improved the safety and mobility of the transportation network through advanced applications such as electronic toll collection, in-vehicle navigation systems, collision avoidance systems, and advanced traffic management systems, and advanced traveler information systems. In this book that focuses on different ITS technologies and applications, authors from several countries have contributed chapters covering different ITS technologies, applications, and management practices with the expectation that the open exchange of scientific results and ideas presented in this book will lead to improved understanding of ITS technologies and their applications.

This report documents Phase III of a four-phase project. The goals of the project are to study the feasibility of using advanced technology from other industries to improve he efficiency and safety of winter highway maintenance vehicle operations, and to provide travelers with the level of service defined by policy during the winter season at the least cost to the taxpayers. The results of the first phase of the research were documented in the Concept Highway Maintenance Vehicle Final Report: Phase One dated April 1997, which describes the desirable functions of a concept maintenance vehicle and evaluates its feasibility. Phase I concluded by establishing the technologies that would be assembled and tested on the prototype vehicles in Phase II. The primary goals of phase II were to install the selected technologies on the prototype winter maintenance vehicles and to conduct proof of concept in advance of field evaluations planned for Phase III. This Phase III final report documents the work completed since the end of Phase II. During this time period, the Phase III work plan was completed and the redesigned friction meter was field tested. A vendor meeting was held to discuss future private sector participation and the new design for the Iowa vehicle. In addition, weather and roadway condition data were collected from the roadway weather information systems at selected sites in Iowa and Minnesota, for comparison to the vehicles' onboard temperature sensors. Furthermore, the team received new technology, such as the mobile Frensor unit, for bench testing and later installation.