A histogram-based model for road traffic characterization in VANET

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

doi:10.1007/978-3-319-11167-4_5

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 proceeding › Conference contribution

5 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Internet of Vehicles - Technologies and Services - First International Conference, IOV 2014, Proceedings
Publisher	Springer Verlag
Pages	42-55
Number of pages	14
ISBN (Print)	9783319111667
DOIs	https://doi.org/10.1007/978-3-319-11167-4_5
Publication status	Published - 2014
Event	1st International Conference on Internet of Vehicles, IOV 2014 - Beijing, China Duration: Sept 1 2014 → Sept 3 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8662 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st International Conference on Internet of Vehicles, IOV 2014
Country/Territory	China
City	Beijing
Period	9/1/14 → 9/3/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Histograms
Route Guidance
Traffic Modeling
VANET

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-11167-4_5

Cite this

El-Sayed, H., Zhang, L., Hawas, Y., & El Kassabi, H. (2014). A histogram-based model for road traffic characterization in VANET. In Internet of Vehicles - Technologies and Services - First International Conference, IOV 2014, Proceedings (pp. 42-55). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8662 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-11167-4_5

A histogram-based model for road traffic characterization in VANET. / El-Sayed, Hesham; Zhang, Liren; Hawas, Yasser et al.
Internet of Vehicles - Technologies and Services - First International Conference, IOV 2014, Proceedings. Springer Verlag, 2014. p. 42-55 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8662 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

El-Sayed, H, Zhang, L, Hawas, Y & El Kassabi, H 2014, A histogram-based model for road traffic characterization in VANET. in Internet of Vehicles - Technologies and Services - First International Conference, IOV 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8662 LNCS, Springer Verlag, pp. 42-55, 1st International Conference on Internet of Vehicles, IOV 2014, Beijing, China, 9/1/14. https://doi.org/10.1007/978-3-319-11167-4_5

El-Sayed H, Zhang L, Hawas Y , El Kassabi H. A histogram-based model for road traffic characterization in VANET. In Internet of Vehicles - Technologies and Services - First International Conference, IOV 2014, Proceedings. Springer Verlag. 2014. p. 42-55. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-11167-4_5

El-Sayed, Hesham ; Zhang, Liren ; Hawas, Yasser et al. / A histogram-based model for road traffic characterization in VANET. Internet of Vehicles - Technologies and Services - First International Conference, IOV 2014, Proceedings. Springer Verlag, 2014. pp. 42-55 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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N2 - 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.

AB - 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.

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KW - Route Guidance

KW - Traffic Modeling

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A histogram-based model for road traffic characterization in VANET

Abstract

Publication series

Other

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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