@inproceedings{5b0b424c8c6d403086208d88f0980fdf,
title = "Large-Scale VANET Simulations and Performance Analysis using Real Taxi Trace and City Map Data",
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 99\% 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.",
keywords = "Public transportation, urban areas, vehicular ad hoc networks, Roads, data models, buildings, Wireless communication, VANET, V2V, V2X, network simulator, delay tolerant, sensor networks",
author = "Pietro Carnelli and Mahesh Sooriyabandara and Eddie Wilson",
year = "2019",
month = jan,
day = "31",
doi = "10.1109/VNC.2018.8628352",
language = "English",
isbn = "9781538694299",
volume = "2018-December",
series = "IEEE Vehicular Networking Conference (VNC)",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
editor = "Mate Boban and Kate Lin and Hsin-Mu Tsai and Onur Altintas and Chih-Yu Wang and Taylan Sahin",
booktitle = "2018 IEEE Vehicular Networking Conference (VNC 2018)",
address = "United States",
note = "2018 IEEE Vehicular Networking Conference, VNC 2018 ; Conference date: 05-12-2018 Through 07-12-2018",
}