A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications
Concerning roadside traffic detection applications, and to address the millimeter-wave radar’s missing data problem caused by target occlusion or the absence of features in low-speed conditions, this paper proposes a trajectory compensation method regarding car-following behavior. Referring to the i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/3/1515 |
| _version_ | 1797623229842456576 |
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| author | Rui Zhang Haiqing Liu Kunmin Teng |
| author_facet | Rui Zhang Haiqing Liu Kunmin Teng |
| author_sort | Rui Zhang |
| collection | DOAJ |
| description | Concerning roadside traffic detection applications, and to address the millimeter-wave radar’s missing data problem caused by target occlusion or the absence of features in low-speed conditions, this paper proposes a trajectory compensation method regarding car-following behavior. Referring to the installation scheme of the detector, a coordinate transformation method is presented to unify the radar spatial coordinates with the road coordinates. Considering the driver’s car-following behavior, the optimal velocity model (OV), full velocity difference model (FVD), and the full velocity difference and acceleration (FVDA) model are applied for tracking the vehicle’s trajectory related to the movement of the vehicle ahead. Finally, a data compensation scheme is presented. Taking actual trajectory data as samples, the proposed methods are verifiably useful for compensating for missing data and reconstructing target trajectories. Statistical results of different missing data trajectories demonstrate the rationality of the application of car-following models for the missing data compensation, and the FVDA model performs well compared with the OV and FVD models. |
| first_indexed | 2024-03-11T09:25:43Z |
| format | Article |
| id | doaj.art-e5fbf50afc404f95848b0b21a481422e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:25:43Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e5fbf50afc404f95848b0b21a481422e2023-11-16T18:02:12ZengMDPI AGSensors1424-82202023-01-01233151510.3390/s23031515A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection ApplicationsRui Zhang0Haiqing Liu1Kunmin Teng2College of Transportation, Shandong University of Science and Technology, Qingdao 266590, ChinaSchool of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 250399, ChinaCollege of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, ChinaConcerning roadside traffic detection applications, and to address the millimeter-wave radar’s missing data problem caused by target occlusion or the absence of features in low-speed conditions, this paper proposes a trajectory compensation method regarding car-following behavior. Referring to the installation scheme of the detector, a coordinate transformation method is presented to unify the radar spatial coordinates with the road coordinates. Considering the driver’s car-following behavior, the optimal velocity model (OV), full velocity difference model (FVD), and the full velocity difference and acceleration (FVDA) model are applied for tracking the vehicle’s trajectory related to the movement of the vehicle ahead. Finally, a data compensation scheme is presented. Taking actual trajectory data as samples, the proposed methods are verifiably useful for compensating for missing data and reconstructing target trajectories. Statistical results of different missing data trajectories demonstrate the rationality of the application of car-following models for the missing data compensation, and the FVDA model performs well compared with the OV and FVD models.https://www.mdpi.com/1424-8220/23/3/1515traffic detectionmillimeter-wave radarmissing data compensationcar-following model |
| spellingShingle | Rui Zhang Haiqing Liu Kunmin Teng A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications Sensors traffic detection millimeter-wave radar missing data compensation car-following model |
| title | A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications |
| title_full | A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications |
| title_fullStr | A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications |
| title_full_unstemmed | A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications |
| title_short | A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications |
| title_sort | trajectory compensation method considering the car following behavior for data missing of millimeter wave radar in roadside detection applications |
| topic | traffic detection millimeter-wave radar missing data compensation car-following model |
| url | https://www.mdpi.com/1424-8220/23/3/1515 |
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