Efficient and Selective Upload of Data from Connected Vehicles

Zaryab Khan, Christian Prehofer

Abstract

Vehicles are evolving into a connected sensing platform, generating enormous amounts data about themselves and their surroundings. In this work, we focus on the efficient data collection for connected vehicles, exploiting the fact that the context data of cars on the same road is often redundant. This is for instance relevant for applications which need roadside data for map updating. We propose a vehicular data dissemination architecture with a central coordination scheme to avoid redundant uploads. It also uses roadside WiFi hotspots opportunistically. To evaluate the benefits, we use the SUMO simulator to benchmark our results against a baseline solution, showing improvements of factor 10 up to 20.

Download


Paper Citation


in Harvard Style

Khan Z. and Prehofer C. (2020). Efficient and Selective Upload of Data from Connected Vehicles.In Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-419-0, pages 559-566. DOI: 10.5220/0009790105590566


in Bibtex Style

@conference{vehits20,
author={Zaryab Khan and Christian Prehofer},
title={Efficient and Selective Upload of Data from Connected Vehicles},
booktitle={Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2020},
pages={559-566},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009790105590566},
isbn={978-989-758-419-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Efficient and Selective Upload of Data from Connected Vehicles
SN - 978-989-758-419-0
AU - Khan Z.
AU - Prehofer C.
PY - 2020
SP - 559
EP - 566
DO - 10.5220/0009790105590566