Development of an algorithm for estimating travel time in urban network using GPS-equipped vehicles

The emergence of Global Positioning System (GPS) has revolutionized data collection in transportation applications and is increasingly used in conducting different transportation studies. This thesis presents an application program developed by using a new algorithm for estimating the travel time between two nodes on a roadway segment in urban network using GPS data. Linear regression analysis is used as a tool in the algorithm to extract the GPS data point corresponding to a node in the base vector map. The data collection procedure uses GPS receivers to record the location coordinates and other attributes like time, speed, altitude, etc. associated with the location at an interval of one second. TransCAD---a transportation planning and GIS software---is used to display the collected GPS data. The data reduction procedure filters the data which is not necessary for estimating the travel time. The results obtained from the developed application are compared with the observed travel time; the observed travel time is found using traditional time study techniques. A statistical analysis is performed to verify the accuracy of the results produced by the application. It is found from the hypothesis test that the results produced by the application are acceptable at the 95% confidence level. A brief overview of the traditional methods of travel time data collection, GPS technology and TransCAD are also documented.