Prioritizing travel time reports in peer-to-peer traffic dissemination Conference

Szczurek, P, Xu, B, Wolfson, O et al. (2010). Prioritizing travel time reports in peer-to-peer traffic dissemination . 454-458. 10.1109/csndsp16145.2010.5580391

cited authors

  • Szczurek, P; Xu, B; Wolfson, O; Lin, J; Rishe, N



  • Vehicular ad-hoc networks (VANETs) is a promising approach to the dissemination of spatio-temporal information such as the current traffic condition of a road segment or the availability of a parking space. Due to the constraint of the communication bandwidth, only a limited number of information items may be transmitted upon a vehicle-to-vehicle communication opportunity. Ranking becomes critical in this situation, by enabling the most important information to be transmitted under the bandwidth constraint. In this paper we propose a method for online learning of spatio-temporal information ranking for a travel time dissemination application within a VANET. In this method, vehicles judge the relevance of incoming information items and use them as training examples for Naive Bayesian learning. Additionally, a separate machine learning algorithm is used to estimate the probability of a duplicate item being transmitted. The method is used in place of commonly used heuristics, and is shown to be superior in the application of travel time dissemination. © 2010 IEEE.

publication date

  • January 1, 2010

Digital Object Identifier (DOI)

International Standard Book Number (ISBN) 13

start page

  • 454

end page

  • 458