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An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field
Driver disability has become an increasing factor leading to traffic accidents, especially for commercial vehicle drivers who endure high mental and physical pressure because of long periods of work. Once driver disability occurs, e.g., heart disease or heat stroke, the loss of driving control may l...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9915140/ https://www.ncbi.nlm.nih.gov/pubmed/36767644 http://dx.doi.org/10.3390/ijerph20032278 |
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author | Wang, Yuning Yang, Shuocheng Li, Jinhao Xu, Shaobing Wang, Jianqiang |
author_facet | Wang, Yuning Yang, Shuocheng Li, Jinhao Xu, Shaobing Wang, Jianqiang |
author_sort | Wang, Yuning |
collection | PubMed |
description | Driver disability has become an increasing factor leading to traffic accidents, especially for commercial vehicle drivers who endure high mental and physical pressure because of long periods of work. Once driver disability occurs, e.g., heart disease or heat stroke, the loss of driving control may lead to serious traffic incidents and public damage. This paper proposes a novel driving intervention system for autonomous danger avoidance under driver disability conditions, including a quantitative risk assessment module named the Emergency Safety Field (ESF) and a motion-planning module. The ESF considers three factors affecting hedging behavior: road boundaries, obstacles, and target position. In the field-based framework, each factor is modeled as an individual risk source generating repulsive or attractive force fields. Individual risk distributions are regionally weighted and merged into one unified emergency safety field denoting the level of danger to the ego vehicle. With risk evaluation, a path–velocity-coupled motion planning module was designed to generate a safe and smooth trajectory to pull the vehicle over. The results of our experiments show that the proposed algorithms have obvious advantages in success rate, efficiency, stability, and safety compared with the traditional method. Validation on multiple simulation and real-world platforms proves the feasibility and adaptivity of the module in traffic scenarios. |
format | Online Article Text |
id | pubmed-9915140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99151402023-02-11 An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field Wang, Yuning Yang, Shuocheng Li, Jinhao Xu, Shaobing Wang, Jianqiang Int J Environ Res Public Health Article Driver disability has become an increasing factor leading to traffic accidents, especially for commercial vehicle drivers who endure high mental and physical pressure because of long periods of work. Once driver disability occurs, e.g., heart disease or heat stroke, the loss of driving control may lead to serious traffic incidents and public damage. This paper proposes a novel driving intervention system for autonomous danger avoidance under driver disability conditions, including a quantitative risk assessment module named the Emergency Safety Field (ESF) and a motion-planning module. The ESF considers three factors affecting hedging behavior: road boundaries, obstacles, and target position. In the field-based framework, each factor is modeled as an individual risk source generating repulsive or attractive force fields. Individual risk distributions are regionally weighted and merged into one unified emergency safety field denoting the level of danger to the ego vehicle. With risk evaluation, a path–velocity-coupled motion planning module was designed to generate a safe and smooth trajectory to pull the vehicle over. The results of our experiments show that the proposed algorithms have obvious advantages in success rate, efficiency, stability, and safety compared with the traditional method. Validation on multiple simulation and real-world platforms proves the feasibility and adaptivity of the module in traffic scenarios. MDPI 2023-01-27 /pmc/articles/PMC9915140/ /pubmed/36767644 http://dx.doi.org/10.3390/ijerph20032278 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. 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/). |
spellingShingle | Article Wang, Yuning Yang, Shuocheng Li, Jinhao Xu, Shaobing Wang, Jianqiang An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field |
title | An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field |
title_full | An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field |
title_fullStr | An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field |
title_full_unstemmed | An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field |
title_short | An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field |
title_sort | emergency driving intervention system designed for driver disability scenarios based on emergency risk field |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9915140/ https://www.ncbi.nlm.nih.gov/pubmed/36767644 http://dx.doi.org/10.3390/ijerph20032278 |
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