UMBC ebiquity

StreetSmart Traffic: Discovering and Disseminating Automobile Congestion Using VANET's

Authors: Sandor Dornbush

Date: August 01, 2006

Abstract: Automobile traffic is a major problem in developed societies. We collectively waste huge amounts of time and resources traveling through traffic congestion. Drivers choose the route that they believe will be the fastest; however traffic congestion can significantly change the duration of a trip. Drivers that know the location of areas of slow traffic can choose other, more efficient routes. We could save significant amounts of time if traffic congestion patterns could be effectively discovered and disseminated to the general public. Currently most people use a centralized system that is over 50 years old. This system is fairly effective, but it has significant problems. We propose a system that uses a standard GPS driving aid, augmented with peer-to-peer wireless communication. This system could provide more accurate and complete traffic monitoring than existing systems, and do so at almost no cost to the service provider. StreetSmart has been be evaluated in a simulation. The system uses a combination of clustering and epidemic communication to find and disseminate traffic information. This system is designed to accommodate dynamic traffic patterns. We ensure the privacy of the participating drivers so drivers will be willing to disclose their driving paths. This project could become a very useful system, saving millions of human hours and dollars.

Type: MastersThesis

Editors: Anupam Joshi

Organization: UMBC

Publisher: UMBC

Tags: clustering, data mining, vanet, ad hoc, gps, wifi

Google Scholar: search

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