Research on Vehicle Detection and Tracking Algorithm for Intelligent Driving

Chen, Jian; Dai, Luchuan

doi:10.1109/icsgea.2019.00078

Cited by 4 publications

(1 citation statement)

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“…CV technologies are being used, for example, for speed bump detection for intelligent vehicle systems [5], automated traffic management for vehicle detection [6], or tracking algorithms for intelligent driving systems [7].…”

Section: Introductionmentioning

confidence: 99%

IoT-Enabled Single-Camera Speed Sensor for Smart City Tasks

Gorobetz,

Timofejevs,

Potapovs

et al. 2024

Electronics

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This article presents an innovative IoT-enabled single-camera speed sensor designed for smart city applications. The research encompasses the development of both hardware and software components, focusing on a computer vision and artificial neural network-based system. A novel aspect of this study is the implementation of a distance-measuring algorithm that eliminates the need for expensive LIDAR sensors traditionally used in speed cameras. Instead, the system relies on convolutional neural networks (CNN) and computer vision algorithms to estimate vehicle speed accurately. Field testing was conducted in real conditions over several months, generating sufficient data to assess the device’s ability to function under various adverse conditions. The results demonstrate the system’s capability to perform vehicle speed detection consistently across diverse conditions, showcasing its potential as a scalable solution for urban traffic management. This makes the proposed system not only more affordable but also simpler to deploy and maintain, thereby enhancing its suitability for widespread use in smart city environments.

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Section: Introductionmentioning

confidence: 99%