Sensor Coverage Aware Probabilistic Data Association to Track Multiple Traffic Participants Using Sparsely Placed Roadside Sensors
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- Publication code
- 20254644
- Paper/Info type
- International Journal of Automotive Engineering
Vol.16 No.4
- Pages
- 96-111(Total 16 p)
- Date of publication
- Oct 2025
- Publisher
- JSAE
- Language
- English
Detailed Information
| Category(E) | Research paper |
|---|---|
| Author(E) | 1) Eiichiro Ishibashi, 2) Kota Watanabe, 3) Takuma Ito |
| Affiliation(E) | 1) The University of Tokyo, Graduate School of Engineering, 2) The University of Tokyo, Graduate School of Engineering, 3) The University of Tokyo, Graduate School of Engineering |
| Abstract(E) | Traffic accidents on community roads, which frequently have intersections with poor visibility, are one of the social issues in Japan. Although safety technologies that utilize roadside sensors are expected to be effective for Japanese community roads, only a few roadside sensors and limited sensor coverage are available on community roads in practice. In such an environment, it is difficult to consistently track multiple traffic participants by associating sensor observations of them from one sensor coverage to another coverage. To address this difficulty, we propose a data association method for multi-target tracking on the assumption that targets can be outside the sensor coverage. The proposed method calculates the existence probability of each target being within the sensor coverage at each time step and incorporates it as a prior probability in the data association process. In the simulation experiments, comparisons with existing methods demonstrate that the proposed method achieves a higher association success rate in various conditions. Furthermore, real-world experiments validate the feasibility of the proposed method. |
