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Communication

Pedestrian Detection in Blind Area and Motion Classification Based on Rush-Out Risk Using Micro-Doppler Radar

1
Department of Electronic and Computer Engineering, Ritsumeikan University, Shiga 525-8577, Japan
2
Department of Intelligent Robotics, Toyama Prefectural University, Toyama 939-0308, Japan
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Hayashi, S.; Saho, K.; Okinaka, H.; Meng, L.; Masugi, M. Detection and Classification of Human Motion in Blind Area Using Micro-Doppler Radar: Fundamental Experiments Toward the Prediction of Dash-Out from Blind Area. In Proceedings of the IEEE 2019 International Conference on Advanced Mechatronic Systems (ICAMechS), Shiga, Japan, 26–28 August 2019; pp. 224–228.
Academic Editor: Mengdao Xing
Sensors 2021, 21(10), 3388; https://doi.org/10.3390/s21103388
Received: 29 March 2021 / Revised: 28 April 2021 / Accepted: 11 May 2021 / Published: 13 May 2021
(This article belongs to the Section Radar Sensors)
Various remote sensing technologies have been applied in intelligent vehicles and robots for surrounding-environment recognition. However, these technologies experience difficulties in detecting pedestrians in blind areas and their motions, such as rush-out behaviors. To address this issue, we present a radar-based technique for the detection of pedestrians in blind areas and the classification of different risks of rush-out behaviors among detected pedestrians. We verify their ability to detect pedestrian motion in blind areas by conducting experiments in two environments with blind areas formed by outdoor cars and indoor walls. Then, the classification of motions with different risks of rush-out behaviors among pedestrians detected in the blind areas is demonstrated. We use the clustering method to accurately classify several types of behaviors with different rush-out risks in both environments. View Full-Text
Keywords: motion classification; blind area; micro-Doppler radar; prediction of rush-out motion classification; blind area; micro-Doppler radar; prediction of rush-out
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MDPI and ACS Style

Hayashi, S.; Saho, K.; Isobe, D.; Masugi, M. Pedestrian Detection in Blind Area and Motion Classification Based on Rush-Out Risk Using Micro-Doppler Radar. Sensors 2021, 21, 3388. https://doi.org/10.3390/s21103388

AMA Style

Hayashi S, Saho K, Isobe D, Masugi M. Pedestrian Detection in Blind Area and Motion Classification Based on Rush-Out Risk Using Micro-Doppler Radar. Sensors. 2021; 21(10):3388. https://doi.org/10.3390/s21103388

Chicago/Turabian Style

Hayashi, Sora, Kenshi Saho, Daiki Isobe, and Masao Masugi. 2021. "Pedestrian Detection in Blind Area and Motion Classification Based on Rush-Out Risk Using Micro-Doppler Radar" Sensors 21, no. 10: 3388. https://doi.org/10.3390/s21103388

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