Latest revision as of 12:15, 15 February 2021

Abstract

Aiming to alleviate traffic congestion, many congestion avoidance and traffic optimization systems have been proposed recently. However, most of them suffer from three main problems. Firstly scalability: they rely on a centralized server, which has to perform intensive communication and computational tasks. Secondly unpredictability: they use smartphones and other sensors to detect the congested roads and warn upcoming vehicles accordingly. In other words, they are used to solve the problem rather than avoiding it. Lastly, infrastructure dependency: they assume the presence of pre-installed infrastructures such as roadside unit (RSU) or cellular 3G/4G networks. Motivated by the above-mentioned reasons, in this paper, we proposed a fully distributed and infrastructure-less congestion avoidance and traffic optimization system for VANET (Vehicular Ad-hoc Networks) in urban environments named DIFTOS (Distributed Infrastructure-Free Traffic Optimization System), in which the city map is divided into a hierarchy of servers. The vehicles that are located in the busy road intersections play the role of servers, thus DIFTOS does not rely on any centralized server and does not need internet connectivity or RSU or any kind of infrastructure. As far as we know, in the literature of congestion avoidance using VANET, DIFTOS is the first completely infrastructure-free congestion avoidance system. The effectiveness and scalability of DIFTOS have been proved by simulation under different traffic conditions.

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• http://dx.doi.org/10.3390/s18082567 under the license https://creativecommons.org/licenses/by

• http://dx.doi.org/10.3390/s18082567 under the license http://creativecommons.org/licenses/by/3.0/

• http://europepmc.org/articles/PMC6111977 under the license https://creativecommons.org/licenses/by/4.0

• https://dx.doi.org/10.3390/s18082567

• https://www.mdpi.com/1424-8220/18/8/2567/pdf

• http://www.mdpi.com/1424-8220/18/8/2567,

https://doaj.org/toc/1424-8220 under the license cc-by

• http://www.mdpi.com/1424-8220/18/8/2567/pdf,

http://dx.doi.org/10.3390/s18082567

• https://dblp.uni-trier.de/db/journals/sensors/sensors18.html#ZhangADA18,

https://www.ncbi.nlm.nih.gov/pubmed/30082595,

https://academic.microsoft.com/#/detail/2887625567 under the license https://creativecommons.org/licenses/by/4.0/