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Safety Performance of Automated Vehicles considering Conflicts with Human Driven Vehicles and Vulnerable Road Users

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 3025

Special Issue Editors


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Guest Editor
Qatar Trasnportation and Traffic Safety Center, & Department of Civil & Architectural Engineering, College of Engineering, Qatar University, PoBox 2713 Doha, Qatar
Interests: traffic safety; road user behaviour; road traffic control and operation; intelligenet transportation systems; road traffic simulation
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Guest Editor
Department of Environmental Engineering and Architecture, Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan
Interests: traffic safety; road user behaviour; traffic simulation modeling; road design; traffic operation

Special Issue Information

Dear Colleagues,

During the past few decades, the automotive industry has been transformed with new technological developments. To this end, autonomous vehicles (AVs) have become one of the most significant and innovative technologies in the automotive and mobility industries. AV technology is expected to change the existing issues in transport system, such as, improving traffic efficiency, reducing road traffic crashes and eliminating human errors. However, their functionality is still unclear and has generated much debate concerning how will AV perform in terms of safety considering conlficts with other road users such as human driven vehicles and vulnerable road users. For example, Pedestrian or cyclist risky behaviors due to distraction, aggression or misjudgment may provoke severe difficulties to AV controls, which may significantly limit their safety performance. Furthermore, harsh environmental conditions are also critical for AVs were their visibility or detection power might be significantly affected.

This Special Issue covers the different analysis that address the safety performance of AVs in mixed traffic streams considering conflcits with other road users. This special issue aims to shade light on the expected safety risks that AVs may encounter in real world traffic operations and how to enhance their control for safer operation. Thus, the topics of interest for this special issue include, but not limited to:

(1) Road user perception and reaction to AVs (human driven vehicles, pedestrians, cyclists, etc.)

(2) Simulation techniques for safety performance evaluation of AVs

(3) Decision making and control design of AVs

(4) Real-time motion planning for AVs

(5) Risk assessment

(6) Communication between AVs and road users

Dr. Wael Alhajyaseen
Dr. Miho Iryo-Asano
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • traffic safety
  • autonomous/automated vehicles
  • human vehicle interaction
  • vulnurable road users
  • simulation
  • risk assessment

Published Papers (1 paper)

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Research

11 pages, 1791 KiB  
Article
Vision-Based Ingenious Lane Departure Warning System for Autonomous Vehicles
by Sudha Anbalagan, Ponnada Srividya, B. Thilaksurya, Sai Ganesh Senthivel, G. Suganeshwari and Gunasekaran Raja
Sustainability 2023, 15(4), 3535; https://doi.org/10.3390/su15043535 - 14 Feb 2023
Cited by 3 | Viewed by 2551
Abstract
Lane detection is necessary for developing intelligent Autonomous Vehicles (AVs). Using vision-based lane detection is more cost-effective, requiring less operational power. Images captured by the moving vehicle include varying brightness, blur, and occlusion caused due to diverse locations. We propose a Vision-based Ingenious [...] Read more.
Lane detection is necessary for developing intelligent Autonomous Vehicles (AVs). Using vision-based lane detection is more cost-effective, requiring less operational power. Images captured by the moving vehicle include varying brightness, blur, and occlusion caused due to diverse locations. We propose a Vision-based Ingenious Lane Departure Warning System (VILDS) for AV to address these challenges. The Generative Adversarial Networks (GAN) of the VILDS choose the most precise features to create images that are identical to the original but have better clarity. The system also uses Long Short-Term Memory (LSTM) to learn the average behavior of the samples to forecast lanes based on a live feed of processed images, which predicts incomplete lanes and increases the reliability of the AV’s trajectory. Further, we devise a strategy to improve the Lane Departure Warning System (LDWS) by determining the angle and direction of deviation to predict the AV’s Lane crossover. An extensive evaluation of the proposed VILDS system demonstrated the effective working of the lane detection and departure warning system modules with an accuracy of 98.2% and 96.5%, respectively. Full article
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