Critical Vehicle Detection for Intelligent Transportation Systems

Erkut Akdag, Egor Bondarev, Peter N. De With

2022

Abstract

An intelligent transportation system (ITS) is one of the core elements of smart cities, enhancing public safety and relieving traffic congestion. Detection and classification of critical vehicles, such as police cars and ambulances, passing through roadways form crucial use cases for ITS. This paper proposes a solution for detecting and classifying safety-critical vehicles on urban roadways using deep learning models. At present, a large-scale dataset for critical vehicles is not publicly available. The appearance scarcity of emergency vehicles and different coloring standards in various countries are significant challenges. To cope with the mentioned drawbacks and to address the unique requirements of our smart city project, we first generate a large-scale critical vehicle dataset, combining images retrieved from various sources with the support of the YOLO vehicle detection model. The classes of the generated dataset are: fire truck, police car, ambulance, military police car, dangerous truck, and standard vehicle. Second, we compare the performance of the Vision in Transformer (ViT) network against the traditional convolutional neural networks (CNNs) for the task of critical vehicle classification. Experimental results on our dataset reveal that the ViT-based solution reaches an average accuracy and recall of 99.39% and 99.34%, respectively.

Paper Citation

in Harvard Style

Akdag E., Bondarev E. and N. De With P. (2022). Critical Vehicle Detection for Intelligent Transportation Systems. In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-573-9, pages 165-171. DOI: 10.5220/0010968900003191

in Bibtex Style

@conference{vehits22,
author={Erkut Akdag and Egor Bondarev and Peter N. De With},
title={Critical Vehicle Detection for Intelligent Transportation Systems},
booktitle={Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2022},
pages={165-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010968900003191},
isbn={978-989-758-573-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Critical Vehicle Detection for Intelligent Transportation Systems
SN - 978-989-758-573-9
AU - Akdag E.
AU - Bondarev E.
AU - N. De With P.
PY - 2022
SP - 165
EP - 171
DO - 10.5220/0010968900003191