Vehicle speed measurement technique using various speed detection instrumentation

Adnan, Muhammad Akram; Zainuddin, Nor Izzah; Sulaiman, Norliana; Besar, Tuan Badrul Hisyam Tuan

doi:10.1109/beiac.2013.6560214

Cited by 40 publications

(20 citation statements)

References 2 publications

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“…Nowadays, the most established sensing solutions have become available for speed limit enforcement, e.g. millimeter-wave radar and Lidar technologies [10]. Both instruments have the advantage of high accuracy and reliability which makes them appropriate tools for vehicle speed measurement.…”

Section: E Comparison With Related Workmentioning

confidence: 99%

“…They have the benefits of lower maintenance costs, a wider field of view and providing better documentation proofs [8]. Moreover, considering recent improvements in image/video processing algorithms, there has been a great interest to utilize computer vision techniques to process the images of vehicles captured by these cameras, known as vision-based approaches [10]. Since the speed of a Copyright © 2019 MECS I.J.…”

Section: Introductionmentioning

confidence: 99%

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Motion-based Vehicle Speed Measurement for Intelligent Transportation Systems

Tourani¹,

Shahbahrami²,

Akoushideh³

et al. 2019

IJIGSP

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Video-based vehicle speed measurement systems are known as effective applications for Intelligent Transportation Systems (ITS) due to their great development capabilities and low costs. These systems utilize camera outputs to apply video processing techniques and extract the desired information. This paper presents a new vehicle speed measurement approach based on motion detection. Contrary to featurebased methods that need visual features of the vehicles like license-plate or windshield, the proposed method is able to estimate vehicle's speed by analyzing its motion parameters inside a pre-defined Region of Interest (ROI) with specified dimensions. This capability provides realtime computing and performs better than feature-based approaches. The proposed method consists of three primary modules including vehicle detection, tracking, and speed measurement. Each moving object is detected as it enters the ROI by the means of Mixture-of-Gaussian background subtraction method. Then by applying morphology transforms, the distinct parts of these objects turn into unified filled shapes and some defined filtration functions leave behind only the objects with the highest possibility of being a vehicle. Detected vehicles are then tracked using blob tracking algorithm and their displacement among sequential frames are calculated for final speed measurement module. The outputs of the system include the vehicle's image, its corresponding speed, and detection time. Experimental results show that the proposed approach has an acceptable accuracy in comparison with current speed measurement systems.

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Section: E Comparison With Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Motion-based Vehicle Speed Measurement for Intelligent Transportation Systems

Tourani¹,

Shahbahrami²,

Akoushideh³

et al. 2019

IJIGSP

View full text Add to dashboard Cite

show abstract

“…There are two types of speed guns [6]: Stationary and moving radar. For the stationary radar, a signal with a frequency equal to this difference is created by mixing the received radio signal with a little of the transmitted signal.…”

Section: A Doppler Effectmentioning

confidence: 99%

“…The term is a portmanteau of "light" and "radar." The police uses LiDAR [6] speed guns for speed limit enforcement, which in turn use LiDAR technology to detect the speed of a vehicle. Unlike radar speed guns, which rely on doppler shifts to measure the speed of a vehicle, these devices allow a police officer to measure the speed of an individual vehicle within a stream of traffic.…”

Section: Lidar Speed Gunmentioning

confidence: 99%

“…Several methods have been implemented to calculate this parameter, for example: Global Positioning System (GPS)localization [5], the Laser Doppler Techniques [6], or Received-Signal-Strength(RSS) [5]. Most of these methods need additional devices for their calculation such as directional antenna [7] or GPS module that can increase the cost of deployment.…”

Section: Introductionmentioning

confidence: 99%

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Calculating the Speed of Vehicles Using Wireless Sensor Networks

Alfandi

Bochem

Gurabi

et al. 2016

Annals of Computer Science and Information Systems

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Abstract-Speed measurement is an important issue for some types of Wireless Sensor Networks (WSN), especially for Vehicular Ad-hoc Networks (VANETs). However, calculating this value is error-prone and costly. This report intends to demonstrate the calculation of speed of an object without the use of any additional devices or sensor boards, only using Received Signal Strength Indication (RSSI) for localization of the vehicles and time calculation using synchronization. We implemented these methods in actual IRIS motes, and tested them. The results show that, while not perfectly accurate, our method proved to be reliable and close to the real speed. In addition, the results do not have any linear correlation in divergence of real speed and calculated speed, which means the system avoids systematic errors.

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