Multi modal design of an Intelligent Transportation System

Abstract

An Intelligent Transportation System (ITS) plays a major role in generating and#64257;ne grained vehicular traffic information for city wide or larger region. The real time traffic information is used to optimize traffic movement in a road network. However, due to the high cost of deployment and maintenance, limited ITS infrastructure is available in developing countries like India, and it is difficult to generate real time traffic information at large scale. Hence, there is a need for cost eand#64256;ective ITS solution. newline newlineThe cellular network is widely deployed in India covering a major part of the road network. However, cellular network based positioning data has large location error (250500 meters) making it unsuitable for the edge level travel time or speed estimation. Due to the increasing penetration of GPS enabled vehicles and smart phone users, the GPS probe data is considered an attractive source for real time travel speed estimation. However, the low penetration and only speciand#64257;c kinds of vehicles (cars and buses) having GPS make it inappropriate for developing countries like India. On Indian arterial roads, two wheelers form approximately 75% of the overall vehicle population. newline newlineIn this dissertation, we study the problem of generating real time traffic information in a cost eand#64256;ective manner. There have been a variety of proposals in the literature that use one or more alternate sources of traffic information and are evaluated for various traffic conditions. Most of these solutions either use cellular network data alone and report a high error in the generated traffic information, or use data from other sources with or without fusion. This dissertation puts forward a novel mechanism of amalgamating widely available cellular network data, GPS probe data, and the data from limited ITS infrastructure for generating accurate traffic information... newline