Lightweight 2D Map Construction of Vehicle Environments Using a Semi-Supervised Depth Estimation Approach

Kashevnik, Alexey; Ali, Ammar

doi:10.3390/engproc2023033028

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…This subsection concisely describes our proposed monocular depth estimation method [25,26]. We have collected data from more than 10,000 videos recorded by our Drive Safely system [23] over a period of more than five years, capturing various scenes, lighting, and weather conditions.…”

Section: Methods For Out-cabin Video Analysismentioning

confidence: 99%

A Machine Learning-Based Correlation Analysis between Driver Behaviour and Vital Signs: Approach and Case Study

Othman,

Hamoud,

Kashevnik

et al. 2023

Sensors

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Driving behaviour analysis has drawn much attention in recent years due to the dramatic increase in the number of traffic accidents and casualties, and based on many studies, there is a relationship between the driving environment or behaviour and the driver’s state. To the best of our knowledge, these studies mostly investigate relationships between one vital sign and the driving circumstances either inside or outside the cabin. Hence, our paper provides an analysis of the correlation between the driver state (vital signs, eye state, and head pose) and both the vehicle maneuver actions (caused by the driver) and external events (carried out by other vehicles or pedestrians), including the proximity to other vehicles. Our methodology employs several models developed in our previous work to estimate respiratory rate, heart rate, blood pressure, oxygen saturation, head pose, eye state from in-cabin videos, and the distance to the nearest vehicle from out-cabin videos. Additionally, new models have been developed using Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) to classify the external events from out-cabin videos, as well as a Decision Tree classifier to detect the driver’s maneuver using accelerometer and gyroscope sensor data. The dataset used includes synchronized in-cabin/out-cabin videos and sensor data, allowing for the estimation of the driver state, proximity to other vehicles and detection of external events, and driver maneuvers. Therefore, the correlation matrix was calculated between all variables to be analysed. The results indicate that there is a weak correlation connecting both the maneuver action and the overtaking external event on one side and the heart rate and the blood pressure (systolic and diastolic) on the other side. In addition, the findings suggest a correlation between the yaw angle of the head and the overtaking event and a negative correlation between the systolic blood pressure and the distance to the nearest vehicle. Our findings align with our initial hypotheses, particularly concerning the impact of performing a maneuver or experiencing a cautious event, such as overtaking, on heart rate and blood pressure due to the agitation and tension resulting from such events. These results can be the key to implementing a sophisticated safety system aimed at maintaining the driver’s stable state when aggressive external events or maneuvers occur.

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Section: Methods For Out-cabin Video Analysismentioning

confidence: 99%

A Machine Learning-Based Correlation Analysis between Driver Behaviour and Vital Signs: Approach and Case Study

Othman,

Hamoud,

Kashevnik

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

Lightweight 2D Map Construction of Vehicle Environments Using a Semi-Supervised Depth Estimation Approach

Abstract: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Cited by 1 publication

References 14 publications

A Machine Learning-Based Correlation Analysis between Driver Behaviour and Vital Signs: Approach and Case Study

A Machine Learning-Based Correlation Analysis between Driver Behaviour and Vital Signs: Approach and Case Study

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