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An Ant Inspired Dynamic Traffic Assignment for VANETs: Early Notification of Traffic Congestion and Traffic Incidents

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Date Issued:
2016
Summary:
Vehicular Ad hoc NETworks (VANETs) are a subclass of Mobile Ad hoc NETworks and represent a relatively new and very active field of research. VANETs will enable in the near future applications that will dramatically improve roadway safety and traffic efficiency. There is a need to increase traffic efficiency as the gap between the traveled and the physical lane miles keeps increasing. The Dynamic Traffic Assignment problem tries to dynamically distribute vehicles efficiently on the road network and in accordance with their origins and destinations. We present a novel dynamic decentralized and infrastructure-less algorithm to alleviate traffic congestions on road networks and to fill the void left by current algorithms which are either static, centralized, or require infrastructure. The algorithm follows an online approach that seeks stochastic user equilibrium and assigns traffic as it evolves in real time, without prior knowledge of the traffic demand or the schedule of the cars that will enter the road network in the future. The Reverse Online Algorithm for the Dynamic Traffic Assignment inspired by Ant Colony Optimization for VANETs follows a metaheuristic approach that uses reports from other vehicles to update the vehicle’s perceived view of the road network and change route if necessary. To alleviate the broadcast storm spontaneous clusters are created around traffic incidents and a threshold system based on the level of congestion is used to limit the number of incidents to be reported. Simulation results for the algorithm show a great improvement on travel time over routing based on shortest distance. As the VANET transceivers have a limited range, that would limit messages to reach at most 1,000 meters, we present a modified version of this algorithm that uses a rebroadcasting scheme. This rebroadcasting scheme has been successfully tested on roadways with segments of up to 4,000 meters. This is accomplished for the case of traffic flowing in a single direction on the roads. It is anticipated that future simulations will show further improvement when traffic in the other direction is introduced and vehicles travelling in that direction are allowed to use a store carry and forward mechanism.
Title: An Ant Inspired Dynamic Traffic Assignment for VANETs: Early Notification of Traffic Congestion and Traffic Incidents.
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Name(s): Arellano, Wilmer, author
Mahgoub, Imad, Thesis advisor
Florida Atlantic University, Degree grantor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2016
Date Issued: 2016
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 128 p.
Language(s): English
Summary: Vehicular Ad hoc NETworks (VANETs) are a subclass of Mobile Ad hoc NETworks and represent a relatively new and very active field of research. VANETs will enable in the near future applications that will dramatically improve roadway safety and traffic efficiency. There is a need to increase traffic efficiency as the gap between the traveled and the physical lane miles keeps increasing. The Dynamic Traffic Assignment problem tries to dynamically distribute vehicles efficiently on the road network and in accordance with their origins and destinations. We present a novel dynamic decentralized and infrastructure-less algorithm to alleviate traffic congestions on road networks and to fill the void left by current algorithms which are either static, centralized, or require infrastructure. The algorithm follows an online approach that seeks stochastic user equilibrium and assigns traffic as it evolves in real time, without prior knowledge of the traffic demand or the schedule of the cars that will enter the road network in the future. The Reverse Online Algorithm for the Dynamic Traffic Assignment inspired by Ant Colony Optimization for VANETs follows a metaheuristic approach that uses reports from other vehicles to update the vehicle’s perceived view of the road network and change route if necessary. To alleviate the broadcast storm spontaneous clusters are created around traffic incidents and a threshold system based on the level of congestion is used to limit the number of incidents to be reported. Simulation results for the algorithm show a great improvement on travel time over routing based on shortest distance. As the VANET transceivers have a limited range, that would limit messages to reach at most 1,000 meters, we present a modified version of this algorithm that uses a rebroadcasting scheme. This rebroadcasting scheme has been successfully tested on roadways with segments of up to 4,000 meters. This is accomplished for the case of traffic flowing in a single direction on the roads. It is anticipated that future simulations will show further improvement when traffic in the other direction is introduced and vehicles travelling in that direction are allowed to use a store carry and forward mechanism.
Identifier: FA00004566 (IID)
Degree granted: Dissertation (Ph.D.)--Florida Atlantic University, 2016.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Vehicular ad hoc networks (Computer networks)--Technological innovations.
Routing protocols (Computer network protocols)
Artificial intelligence.
Intelligent transportation systems.
Intelligent control systems.
Mobile computing.
Computer algorithms.
Combinatorial optimization.
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Links: http://purl.flvc.org/fau/fd/FA00004566
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00004566
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Owner Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.