Latest revision as of 03:55, 23 March 2021

Abstract

Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research.

Document type: Article

Full document

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.3390/s16020157 under the license https://creativecommons.org/licenses/by

• http://europepmc.org/articles/PMC4801535 under the license https://creativecommons.org/licenses/by/4.0

• https://dx.doi.org/10.3390/s16020157

• https://www.mdpi.com/1424-8220/16/2/157/pdf

• http://www.mdpi.com/1424-8220/16/2/157,

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

• http://www.mdpi.com/1424-8220/16/2/157/pdf,

http://dx.doi.org/10.3390/s16020157

• https://www.mdpi.com/1424-8220/16/2/157,

https://www.ncbi.nlm.nih.gov/pubmed/26828489,

https://dblp.uni-trier.de/db/journals/sensors/sensors16.html#Nellore016,

https://www.mdpi.com/1424-8220/16/2/157/pdf,

https://repository.up.ac.za/handle/2263/52618,

https://europepmc.org/articles/PMC4801535,

https://core.ac.uk/display/89923541,

https://doaj.org/article/ab16683fe11b42be92c1e8fbaef7398a,

https://dx.doi.org/10.3390/s16020157,

https://doi.org/10.3390%2fs16020157,

[=citjournalarticle_511127_9 https://www.safetylit.org/citations/index.php?fuseaction=citations.viewdetails&citationIds[]=citjournalarticle_511127_9],

https://academic.microsoft.com/#/detail/2258465644 under the license https://creativecommons.org/licenses/by/4.0/