Comfortable awakening method for sleeping driver during autonomous driving

Yamabe, Shigeyuki; Kawaguchi, Shuichi; Anakubo, Masato

doi:10.1007/s13177-021-00291-0

Cited by 2 publications

(3 citation statements)

References 26 publications

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“…Yamabe et al [26] proposed a new comfortable awakening method for sleeping drivers. The proposed method is commonly used for automated driving systems.…”

Section: Related Workmentioning

confidence: 99%

Eye-Blink Event Detection Using a Neural-Network-Trained Frame Segment for Woman Drivers in Saudi Arabia

Al-Razgan,

Alruwaly,

Ali

2023

Electronics

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Women have been allowed to drive in Saudi Arabia since 2018, revoking a 30-year ban that also adhered to the traffic rules provided in the country. Conventional drivers are often monitored for safe driving by monitoring their facial reactions, eye blinks, and expressions. As driving experience and vehicle handling features have been less exposed to novice women drivers in Saudi Arabia, technical assistance and physical observations are mandatory. Such observations are sensed as images/video frames for computer-based analyses. Precise computer vision processes are employed for detecting and classifying events using image processing. The identified events are unique to novice women drivers in Saudi Arabia, assisting with their vehicle usage. This article introduces the Event Detection using Segmented Frame (ED-SF) method to improve the abnormal Eye-Blink Detection (EBD) of women drivers. The eye region is segmented using variation pixel extraction in this process. The pixel extraction process requires textural variation identified from different frames. The condition is that the frames are to be continuous in the event detection. This method employs a convolution neural network with two hidden layer processes. In the first layer, continuous and discrete frame differentiations are identified. The second layer is responsible for segmenting the eye region, devouring the textural variation. The variations and discrete frames are used for training the neural network to prevent segment errors in the extraction process. Therefore, the frame segment changes are used for Identifying the expressions through different inputs across different texture luminosities. This method applies to less-experienced and road-safety-knowledge-lacking woman drivers who have initiated their driving journey in Saudi-Arabia-like countries. Thus the proposed method improves the EBD accuracy by 9.5% compared to Hybrid Convolutional Neural Networks (HCNN), Long Short-Term Neural Networks (HCNN + LSTM), Two-Stream Spatial-Temporal Graph Convolutional Networks (2S-STGCN), and the Customized Driving Fatigue Detection Method CDFDM.

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“…Yamabe et al [26] proposed a new comfortable awakening method for sleeping drivers. The proposed method is commonly used for automated driving systems.…”

Section: Related Workmentioning

confidence: 99%

Eye-Blink Event Detection Using a Neural-Network-Trained Frame Segment for Woman Drivers in Saudi Arabia

Al-Razgan,

Alruwaly,

Ali

2023

Electronics

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“…However, with the improvement of indoor quietness and quality of sensibility, noise generated from the driving mechanism of interior parts, such as power windows, panoramic sunroofs, and power seats, which were previously not an issue, is relatively highlighted. In particular, as the power seat for automobiles is being developed as a seat system with multiple functions (e.g., swivel, belt in seat, long rail slide, and wireless power transmission) as the level of autonomous vehicles develops along with electric vehicles [1][2][3][4], improvement of the noise of the driving mechanism in the interior is gaining significance [5].…”

Section: Introductionmentioning

confidence: 99%

“…If psychoacoustic parameters do not follow the characteristics of hearing, new parameters are created by correcting parameter constants or combining parameters such as psychoacoustic annoyance or sensory pleasantness. The models of psychoacoustic annoyance and sensory pleasantness are presented in Equations ( 1) and (2).…”

Section: Introductionmentioning

confidence: 99%

Methodology for Sound Quality Analysis of Motors for Automotive Interior Parts through Subjective Evaluation

Kim

Ryu

Jun

et al. 2022

Sensors

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With the development of autonomous vehicles, activities in the indoor spaces of autonomous vehicles are diversifying. Therefore, as the operating range of the interior parts increases, the occupant becomes sensitive to the operating noise of autonomous vehicles. Therefore, to reduce operating noise, it is necessary to analyze the causal relationship between the mechanical/electrical noise characteristics of the motor and sound quality. In this paper, we propose a methodology to analyze the relationship between the noise frequency components and the sound quality of small motors used in automobile interior parts. Two types of motors were selected for this study, and noise measurements and analyses were performed by applying the design proposed in this study. Subjective sound quality evaluations were conducted using the 12 pairs of adjectives extracted from the survey. The results suggest that subjective sound quality evaluation scores should be converted to Z-scores to ensure the reliability of the statistical analysis. In addition, we present a critical sound quality value that can be used as a criterion for determining whether the sound quality is positive (good quality) or negative (bad quality). Sound quality regression models explain the causal relationship between rotational frequency components of the motor and subjective sound quality characteristics. Thus, a method for analyzing the effect of the rotational frequency component of the motor on the sound quality is presented, which suggests that it can be used as basic research data to improve the noise performance of the motor.

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Comfortable awakening method for sleeping driver during autonomous driving

Cited by 2 publications

References 26 publications

Eye-Blink Event Detection Using a Neural-Network-Trained Frame Segment for Woman Drivers in Saudi Arabia

Eye-Blink Event Detection Using a Neural-Network-Trained Frame Segment for Woman Drivers in Saudi Arabia

Methodology for Sound Quality Analysis of Motors for Automotive Interior Parts through Subjective Evaluation

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