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

Hayashi, Shigehiko; Saho, Kenshi; Daiki, Isobe; Masugi, Masao

doi:10.3390/s21103388

Cited by 6 publications

(3 citation statements)

References 22 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They showed that it is possible to detect moving road users outside the direct line-of-sight with reflected radar measurements by using building facades or parked vehicles as relay walls. In [34], the authors explicitly addressed the detection of fully occluded, darting out pedestrians with radar. They designed an experimental setup with a static radar sensor in an indoor area (behind a corner) and an outdoor area (behind a van).…”

Section: B Radar Based Approachesmentioning

confidence: 99%

Detecting Darting Out Pedestrians With Occlusion Aware Sensor Fusion of Radar and Stereo Camera

Palffy

Kooij

Gavrila

2023

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

Early and accurate detection of crossing pedestrians is crucial in automated driving in order to perform timely emergency manoeuvres. However, this is a difficult task in urban scenarios where pedestrians are often occluded (not visible) behind objects, e.g., other parked vehicles. We propose an occlusion aware fusion of stereo camera and radar sensors to address scenarios with crossing pedestrians behind such parked vehicles. Our proposed method adapts both the expected rate and properties of detections in different areas according to the visibility of the sensors. In our experiments on a real-world dataset, we show that the proposed occlusion aware fusion of radar and stereo camera detects the crossing pedestrians on average 0.26 seconds earlier than using the camera alone, and 0.15 seconds earlier than fusing the sensors without occlusion information. Our dataset containing 501 relevant recordings of pedestrians behind vehicles will be publicly available on our website for non-commercial, scientific use.

show abstract

Section: B Radar Based Approachesmentioning

confidence: 99%

Detecting Darting Out Pedestrians With Occlusion Aware Sensor Fusion of Radar and Stereo Camera

Palffy

Kooij

Gavrila

2023

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

show abstract

“…Many approaches have been suggested to minimize the line of sight-related traffic hazards. One approach is based on ensuring intelligent collaboration between infrastructure and vehicles, such as vehicle-to-vehicle and vehicle-to-infrastructure communication [4]. However, this approach is more realistic in urban areas as it is economically hard to extend to most non-urban and rural roadways.…”

Section: Introductionmentioning

confidence: 99%

“…However, this approach is more realistic in urban areas as it is economically hard to extend to most non-urban and rural roadways. A second approach is based on the propagation characteristics of radio waves at blind areas such as in [4]. However, these techniques assumed that radio waves reach blind areas through multiple reflections by walls on a side of the road.…”

Section: Introductionmentioning

confidence: 99%

Traffic-Induced Vibration Monitoring Using Laser Vibrometry: Preliminary Experiments

et al. 2022

View full text Add to dashboard Cite

Traffic monitoring technologies have become crucial for modern manned and autonomous vehicles. They aim to ensure the maximum level of safety and dependability. The commonly used monitoring technologies based on conventional LIDAR (laser imaging, detection, and ranging), vision and ultrasound sensors are effective if there is a clear line of sight for the surrounding traffic field. However, some potential accidents and traffic hazards beyond the line of sight cannot be detected by the aforementioned sensors. Thus, dedicated sensors require means to detect other traffic participants even if they are not visible due to obstacles. In this paper, a new traffic monitoring concept for detecting nearby traffic activities occurring beyond the line of sight is introduced. The principle is based on a portable laser Doppler vibrometer (LDV), which is mounted on the vehicle to measure the roadway’s vibration noise induced by nearby traffic activities. First proof-of-concept field tests were conducted using a commercial LDV and realistic public traffic conditions. A statistical classification method based on the frequency features of pavement vibration measurements showed quite good performance for identifying traffic conditions.

show abstract

Adaptive Cruise Control Utilizing Noisy Multi-Leader Measurements: A Learning-Based Approach

Ni,

Knoop,

Kooij

et al. 2024

IEEE Open J. Intell. Transp. Syst.

View full text Add to dashboard Cite

A substantial number of vehicles nowadays are equipped with adaptive cruise control (ACC), which adjusts the vehicle speed automatically. However, experiments have found that commercial ACC systems which only detect the direct leader amplify the propagating disturbances in the platoon. This can cause severe traffic congestion when the number of ACC-equipped vehicles increases. Therefore, an ACC system which also considers the second leader further downstream is required. Such a system enables the vehicle to achieve multi-anticipation and hence ensure better platoon stability. Nevertheless, measurements collected from the second leader may be comparatively inaccurate given the limitations of current state-ofthe-art sensor technology. This study adopts deep reinforcement learning to develop ACC controllers that besides the input from the first leader exploits the additional information obtained from the second leader, albeit noisy. The simulation experiment demonstrates that even under the influence of noisy measurements, the multi-leader ACC platoon shows smaller disturbance and jerk amplitudes than the one-leader ACC platoon, indicating improved string stability and ride comfort. Practical takeaways are twofold: first, the proposed method can be used to further develop multi-leader ACC systems. Second, even noisy data from the second leader can help stabilize traffic, which makes such systems viable in practice.

show abstract

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

Cited by 6 publications

References 22 publications

Detecting Darting Out Pedestrians With Occlusion Aware Sensor Fusion of Radar and Stereo Camera

Detecting Darting Out Pedestrians With Occlusion Aware Sensor Fusion of Radar and Stereo Camera

Traffic-Induced Vibration Monitoring Using Laser Vibrometry: Preliminary Experiments

Adaptive Cruise Control Utilizing Noisy Multi-Leader Measurements: A Learning-Based Approach

Contact Info

Product

Resources

About