Abstract

Wireless vehicular ad-hoc networks comprised solely of city taxis are investigated for their ability to deliver data across an urban environment. Openly available taxi trace datasets for Rome (Italy) and San Francisco (USA) are combined with respective building footprint and road network topology data from OpenStreetMap, to generate a realistic systems level model of a taxi V2V network. Analysis of LOS and NOLOS constraints on wireless transmission range suggests a minimum threshold of 50m is applicable to ensure LOS in over 90% of cases. Variations in taxi location sampling frequency and filtering techniques for the taxi trace datasets are also investigated. Overall vehicular network performance is computed for an all-to-one transmission scenario for both cities with varying taxi fleet size. Results suggest a non-linear relationship between increases in taxi fleet sizes and the reduction of end-to-end delay; doubling taxi fleet size (using a randomised data folding technique) reduces end-to-end delay by a factor of 0.6–0.7. However, doubling the fleet does not increase the fraction of delivered source messages, which saturates at 0.67–0.71 in most simulations. Finally it appears that taxi networks for delivering messages across urban environments are limited more by their routing than by the number of possible V2V exchanges. In a simulated one-to-all continuous V2V broadcast scenario, over 90% of the taxis within the fleet receive the source message within one hour of the original taxi passing the source node.


Original document

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

http://dx.doi.org/10.1109/vnc.2018.8628352
https://doi.org/10.1109/VNC.2018.8628352,
http://hdl.handle.net/1983/5b0b424c-8c6d-4030-8620-8d88f0980fdf,
https://research-information.bris.ac.uk/ws/files/181945840/VANET_simulations_no_IEEE_copyright_8pages.pdf,
http://www.scopus.com/inward/record.url?scp=85062548822&partnerID=8YFLogxK
https://research-information.bris.ac.uk/en/publications/large-scale-vanet-simulations-and-performance-analysis-using-real,
https://dblp.uni-trier.de/db/conf/vnc/vnc2018.html#CarnelliSW18,
https://academic.microsoft.com/#/detail/2912562119
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Published on 01/01/2019

Volume 2019, 2019
DOI: 10.1109/vnc.2018.8628352
Licence: CC BY-NC-SA license

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