The Channel as a Traffic Sensor: Vehicle Detection and Classification based on Radio Fingerprinting
Ubiquitously deployed automatic vehicle classification systems will catalyze data-driven traffic flow optimization in future smart cities and will transform the road infrastructure itself into a dynamically sensing (). Although a wide range of different traffic sensing systems has been proposed, the existing solutions are not yet able to simultaneously satisfy the multitude of requirements, e.g., accuracy, robustness, cost-efficiency, and privacy preservation. In this paper, we present a novel approach, which exploits radio fingerprints – multidimensional attenuation patterns of wireless signals – for accurate and robust vehicle detection and classification. The proposed system can be deployed in a highly cost-efficient manner as it relies on off-the-shelf embedded devices which are installed into existing delineator posts. In a comprehensive field evaluation campaign, the performance of the radio fingerprinting-based approach is analyzed within an experimental live deployment on a German highway, where it is able to achieve a binary classification success ratio of more than 99% and an overall accuracy of 93.83% for a classification task with seven different classes.
- Published in:
IEEE Internet of Things Journal - Type:
Article - Authors:
B. Sliwa, N. Piatkowski, C. Wietfeld - Year:
2020
Citation information
B. Sliwa, N. Piatkowski, C. Wietfeld: The Channel as a Traffic Sensor: Vehicle Detection and Classification based on Radio Fingerprinting, IEEE Internet of Things Journal, 2020, 7, 8, 7392-7406, https://doi.org/10.1109/JIOT.2020.2983207, Sliwa.etal.2020a,
@Article{Sliwa.etal.2020a,
author={B. Sliwa, N. Piatkowski, C. Wietfeld},
title={The Channel as a Traffic Sensor: Vehicle Detection and Classification based on Radio Fingerprinting},
journal={IEEE Internet of Things Journal},
volume={7},
number={8},
pages={7392-7406},
url={https://doi.org/10.1109/JIOT.2020.2983207},
year={2020},
abstract={Ubiquitously deployed automatic vehicle classification systems will catalyze data-driven traffic flow optimization in future smart cities and will transform the road infrastructure itself into a dynamically sensing (). Although a wide range of different traffic sensing systems has been proposed, the existing solutions are not yet able to simultaneously satisfy the multitude of requirements, e.g.,...}}