A histogram-based model for road traffic characterization in VANET

Hesham El-Sayed, Liren Zhang, Yasser Hawas, Hadeel El Kassabi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


This paper presents a new route guidance algorithm and a compact road traffic model that can be easily obtained and transmitted in real-time by individual vehicles while they are travelling on streets or queuing in road cross junctions. The proposed algorithm uses histograms as the network traffic model that captures the arrival rate distribution in VANET. In addition, the paper presents an analysis method that works directly with the histogram model to obtain the queue occupancy distribution at cross-junctions or traffic signals using a finite queue model. A microscopic simulation model is utilized to assess the effectiveness of the traffic model in detecting traffic congestion and directing vehicles to choose better paths. Results show that the proposed road traffic model provides a good prediction of road traffic status, and can be used in conjunction with any standard shortest path algorithms to provide an efficient mechanism for selecting fastest road path.

Original languageEnglish
Title of host publicationInternet of Vehicles - Technologies and Services - First International Conference, IOV 2014, Proceedings
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783319111667
Publication statusPublished - 2014
Event1st International Conference on Internet of Vehicles, IOV 2014 - Beijing, China
Duration: Sept 1 2014Sept 3 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8662 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other1st International Conference on Internet of Vehicles, IOV 2014


  • Histograms
  • Route Guidance
  • Traffic Modeling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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