An Enhanced Deep Neural Network Model for the Detection of Anomalous Behavior of Drivers in Road Traffic Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.1155/js/5295932
Over recent years, video‐surveillance systems have seen extensive adoption, largely driven by security imperatives, with radar‐based speed detection being a common feature in traffic monitoring. Despite its prevalence, broader anomaly detection in traffic patterns has not received equivalent focus. This research develops a sophisticated deep learning framework, drawing architectural inspiration from MobileNet, ResNet50, and VGG19, to not only detect and track vehicles but also analyze trajectory data to identify nonstandard behaviors. Specifically, our model detects four distinct anomalies: overspeeding, lingering in no‐stopping zones, insufficient spacing between vehicles, and violations of traffic light signals. To support this, we constructed a unique dataset comprising over 60,000 video frames. The YOLOv3 algorithm facilitated initial object recognition, which was complemented by data augmentation techniques to mitigate issues related to class imbalance and the limited availability of annotated datasets in this domain. Our enhanced model achieved an overall accuracy of 95%, with a detailed performance breakdown for each detected anomaly.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/js/5295932
- OA Status
- hybrid
- Cited By
- 1
- References
- 44
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4405577069Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1155/js/5295932Digital Object Identifier
- Title
-
An Enhanced Deep Neural Network Model for the Detection of Anomalous Behavior of Drivers in Road TrafficWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-01Full publication date if available
- Authors
-
Maleika Heenaye-Mamode Khan, Kapil Kumar Nagwanshi, Bhuheekhan Muhammad Azhar, Emerith Girish, Sunilduth Baichoo, G. R. Sinha, Amelia TaylorList of authors in order
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https://doi.org/10.1155/js/5295932Publisher landing page
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://doi.org/10.1155/js/5295932Direct OA link when available
- Concepts
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Artificial neural network, Computer science, Transport engineering, Artificial intelligence, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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44Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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