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. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection
Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_33509 |
Contributors | 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 |
Publisher | Florida Atlantic University |
Source Sets | Florida Atlantic University |
Language | English |
Detected Language | English |
Type | Electronic Thesis or Dissertation, Text |
Format | 128 p., application/pdf |
Rights | 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., http://rightsstatements.org/vocab/InC/1.0/ |
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