Vehicle speed estimation using two roadside passive infrared sensors

Vu, Van Quang; Ngo, Van Linh; Vu, Toan Thang; Doan, Van Phuc

doi:10.1142/s0217979220401517

Cited by 2 publications

(1 citation statement)

References 5 publications

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“…The roadside intelligent traffic perception device can obtain rich road traffic information, such as vehicle identification and capture, vehicle track tracking, Moving violation event monitoring and early warning, and building an intelligent transportation system to achieve intelligent control of road traffic [1] . Currently, common roadside perception sensors include cameras, millimeter wave radars, magnetic sensors [2] , infrared sensors [3] , and LiDAR [4] . By processing the data collected by these sensors, road vehicles can be perceived and recognized, and relevant traffic information such as position and speed can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Evaluation method for installation scheme of the radar-video integrated based on technique for order preference by similarity to ideal solution

Hou,

Wang,

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

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Roadside intelligent sensors can monitor road traffic status, and the installation method of sensing equipment greatly affects the richness and accuracy of traffic data information collection. The radar-video integrated machine integrates radar and camera, and is a new type of perception device. This paper conducted experimental analysis on the installation position, rotation angle, and other aspects of the radar-video integrated machine. Based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), an optimal solution was proposed. Firstly, before designing the installation plan, analyzed the main factors affecting the installation plan, which were used as a single variable to design 5 sets of operating conditions. Next, data collection and analysis were conducted based on the built the Radar-Video integrated machine platform, and 9 indicator parameters were selected to construct an evaluation system. Finally, comprehensive evaluation and optimization were conducted on each installation plan. This paper selected two on-site scenarios for experimental verification, and the results show that the proposed evaluation technology can successfully optimize the installation plan. However, according to different installation scenarios, such as lane width and installation height, the optimal installation plan may be adjusted.

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Section: Introductionmentioning

confidence: 99%

Evaluation method for installation scheme of the radar-video integrated based on technique for order preference by similarity to ideal solution

Hou,

Wang,

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

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An Improved Stereo Matching Algorithm for Vehicle Speed Measurement System Based on Spatial and Temporal Image Fusion

Yang

Song

et al. 2021

Entropy

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This paper proposes an improved stereo matching algorithm for vehicle speed measurement system based on spatial and temporal image fusion (STIF). Firstly, the matching point pairs in the license plate area with obviously abnormal distance to the camera are roughly removed according to the characteristic of license plate specification. Secondly, more mismatching point pairs are finely removed according to local neighborhood consistency constraint (LNCC). Thirdly, the optimum speed measurement point pairs are selected for successive stereo frame pairs by STIF of binocular stereo video, so that the 3D points corresponding to the matching point pairs for speed measurement in the successive stereo frame pairs are in the same position on the real vehicle, which can significantly improve the vehicle speed measurement accuracy. LNCC and STIF can be used not only for license plate, but also for vehicle logo, light, mirror etc. Experimental results demonstrate that the vehicle speed measurement system with the proposed LNCC+STIF stereo matching algorithm can significantly outperform the state-of-the-art system in accuracy.

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Vehicle speed estimation using two roadside passive infrared sensors

Cited by 2 publications

References 5 publications

Evaluation method for installation scheme of the radar-video integrated based on technique for order preference by similarity to ideal solution

Evaluation method for installation scheme of the radar-video integrated based on technique for order preference by similarity to ideal solution

An Improved Stereo Matching Algorithm for Vehicle Speed Measurement System Based on Spatial and Temporal Image Fusion

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