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Improving turn movement count using cooperative feedback

Patrick Heyer Wollenberg (UGent) , Chengjin Lyu (UGent) , Ljubomir Jovanov (UGent) , Bart Goossens (UGent) and Wilfried Philips (UGent)
(2023) SENSORS. 23(24).
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Abstract
In this paper, we propose a new cooperative method that improves the accuracy of Turn Movement Count (TMC) under challenging conditions by introducing contextual observations from the surrounding areas. The proposed method focuses on the correct identification of the movements in conditions where current methods have difficulties. Existing vision-based TMC systems are limited under heavy traffic conditions. The main problems for most existing methods are occlusions between vehicles that prevent the correct detection and tracking of the vehicles through the entire intersection and the assessment of the vehicle’s entry and exit points, incorrectly assigning the movement. The proposed method intends to overcome this incapability by sharing information with other observation systems located at neighboring intersections. Shared information is used in a cooperative scheme to infer the missing data, thereby improving the assessment that would otherwise not be counted or miscounted. Experimental evaluation of the system shows a clear improvement over related reference methods.
Keywords
Electrical and Electronic Engineering, Biochemistry, Instrumentation, Atomic and Molecular Physics, and Optics, Analytical Chemistry, Turn Movement Count (TMC), cooperative vision, vehicle count, smart, intersection, traffic analysis

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MLA
Heyer Wollenberg, Patrick, et al. “Improving Turn Movement Count Using Cooperative Feedback.” SENSORS, vol. 23, no. 24, 2023, doi:10.3390/s23249772.
APA
Heyer Wollenberg, P., Lyu, C., Jovanov, L., Goossens, B., & Philips, W. (2023). Improving turn movement count using cooperative feedback. SENSORS, 23(24). https://doi.org/10.3390/s23249772
Chicago author-date
Heyer Wollenberg, Patrick, Chengjin Lyu, Ljubomir Jovanov, Bart Goossens, and Wilfried Philips. 2023. “Improving Turn Movement Count Using Cooperative Feedback.” SENSORS 23 (24). https://doi.org/10.3390/s23249772.
Chicago author-date (all authors)
Heyer Wollenberg, Patrick, Chengjin Lyu, Ljubomir Jovanov, Bart Goossens, and Wilfried Philips. 2023. “Improving Turn Movement Count Using Cooperative Feedback.” SENSORS 23 (24). doi:10.3390/s23249772.
Vancouver
1.
Heyer Wollenberg P, Lyu C, Jovanov L, Goossens B, Philips W. Improving turn movement count using cooperative feedback. SENSORS. 2023;23(24).
IEEE
[1]
P. Heyer Wollenberg, C. Lyu, L. Jovanov, B. Goossens, and W. Philips, “Improving turn movement count using cooperative feedback,” SENSORS, vol. 23, no. 24, 2023.
@article{01HKNCJ38BGPZKD6VC1X1PGDPY,
  abstract     = {{In this paper, we propose a new cooperative method that improves the accuracy of Turn Movement Count (TMC) under challenging conditions by introducing contextual observations from the surrounding areas. The proposed method focuses on the correct identification of the movements in conditions where current methods have difficulties. Existing vision-based TMC systems are limited under heavy traffic conditions. The main problems for most existing methods are occlusions between vehicles that prevent the correct detection and tracking of the vehicles through the entire intersection and the assessment of the vehicle’s entry and exit points, incorrectly assigning the movement. The proposed method intends to overcome this incapability by sharing information with other observation systems located at neighboring intersections. Shared information is used in a cooperative scheme to infer the missing data, thereby improving the assessment that would otherwise not be counted or miscounted. Experimental evaluation of the system shows a clear improvement over related reference methods.}},
  articleno    = {{9772}},
  author       = {{Heyer Wollenberg, Patrick and Lyu, Chengjin and Jovanov, Ljubomir and Goossens, Bart and Philips, Wilfried}},
  issn         = {{1424-8220}},
  journal      = {{SENSORS}},
  keywords     = {{Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry,Turn Movement Count (TMC),cooperative vision,vehicle count,smart,intersection,traffic analysis}},
  language     = {{eng}},
  number       = {{24}},
  pages        = {{16}},
  title        = {{Improving turn movement count using cooperative feedback}},
  url          = {{http://doi.org/10.3390/s23249772}},
  volume       = {{23}},
  year         = {{2023}},
}
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