Analytical Modeling for a Video-Based Vehicle Speed Measurement Framework

Author:

Dahl MattiasORCID,Javadi SalehORCID

Abstract

Traffic analyses, particularly speed measurements, are highly valuable in terms of road safety and traffic management. In this paper, an analytical model is presented to measure the speed of a moving vehicle using an off-the-shelf video camera. The method utilizes the temporal sampling rate of the camera and several intrusion lines in order to estimate the probability density function (PDF) of a vehicle’s speed. The proposed model provides not only an accurate estimate of the speed, but also the possibility of being able to study the performance boundaries with respect to the camera frame rate as well as the placement and number of intrusion lines in advance. This analytical model is verified by comparing its PDF outputs with the results obtained via a simulation of the corresponding movements. In addition, as a proof-of-concept, the proposed model is implemented for a video-based vehicle speed measurement system. The experimental results demonstrate the model’s capability in terms of taking accurate measurements of the speed via a consideration of the temporal sampling rate and lowering the deviation by utilizing more intrusion lines. The analytical model is highly versatile and can be used as the core of various video-based speed measurement systems in transportation and surveillance applications.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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2. Speed Detection using Haar-Cascade Classifier and Pixel per Meter;2023 2nd International Conference on Edge Computing and Applications (ICECAA);2023-07-19

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4. Vehicle-Related Distance Estimation Using Customized YOLOv7;Image and Vision Computing;2023

5. A Study on Real-Time Vehicle Speed Measurement Techniques;Lecture Notes in Networks and Systems;2023

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