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Driverless Cars: New Challenges and Possibilities for Future Human Mobility

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

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 9598

Special Issue Editors


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Guest Editor
Department of Civil Engineering and Architecture, University of Catania, 95123 Catania, Italy
Interests: modeling of road intersections; management of traffic lights and roundabouts; microsimulation methods of transport infrastructure networks; intelligent systems for the management of road traffic and transport infrastructure networks; automated vehicle systems
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Guest Editor

E-Mail Website
Guest Editor
Department of Civil Engineering and Architecture, University of Catania, 95123 Catania, Italy
Interests: Road asset management for sustainable development infrastructure monitoring

Special Issue Information

Dear Colleagues,

The driverless car theme has become a key focus of the industrial and technological world scenes. Considered with trepidation rather than anxiety, driverless cars will alter human mobility. They will put a strain on various sectors, in particular, public administration, which will be required to form new regulations and to determine the liability levels of these vehicles. At the same time, considering that several significant players in the automotive industry have shown their interest in this type of vehicle by developing prototypes and testing them in many contexts, an additional boost in the development of innovative algorithms, systems, and methodologies is necessary with straight employment not only for autonomous driving but also for advanced driver assistance systems.

For this Special Issue of Sustainability, we invite authors to submit high-quality and unpublished papers that strive to resolve open technical problems and challenges typical of driverless cars. The principal purpose is to combine innovative methods efficiently, integrating performance evaluation and the comparison with existing solutions. Both theoretical and experimental studies for typical scenarios related to driverless cars are encouraged, as well as high-quality review and survey papers.

Topics of interest include, but are not limited to

  • Vision, lidar and radar perception;
  • Special sensors for autonomous navigation;
  • Vehicle scene understanding;
  • Sensor technologies for driverless cars;
  • Wireless communications in connected vehicles;
  • Cooperative driving;
  • Vehicle navigation and localization systems;
  • Perception in challenging conditions;
  • Advanced driver assistance systems;
  • Software architecture for autonomous vehicles;
  • Assistive intelligent vehicles;
  • Vehicle dynamics and control;
  • Driver–vehicle interaction and assisted driving;
  • Human factors and human–machine interactions.

Prof. Dr. Alessandro Severino
Prof. Dr. Giovanni Pau
Dr. Giuseppina Pappalardo
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

  • intelligent vehicles
  • sensors
  • road user behavior modeling
  • sensor and information fusion
  • advanced driver assistance systems
  • image, radar, and LiDAR signal processing
  • human factors
  • Information and Communication Technologies (ICT)
  • wireless communications

Published Papers (3 papers)

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Research

16 pages, 2731 KiB  
Article
Managed Lane as Strategy for Traffic Flow and Safety: A Case Study of Catania Ring Road
by Salvatore Cafiso, Alessandro Di Graziano, Tullio Giuffrè, Giuseppina Pappalardo and Alessandro Severino
Sustainability 2022, 14(5), 2915; https://doi.org/10.3390/su14052915 - 02 Mar 2022
Cited by 7 | Viewed by 1738
Abstract
According to international traffic statistics, the quantity of daily traveling vehicles amounts to one billion, and it is estimated that in 2050 that amount will reach four billion. Urban population is growing especially in large metropolitan areas. This increase has different outgrowths concerning [...] Read more.
According to international traffic statistics, the quantity of daily traveling vehicles amounts to one billion, and it is estimated that in 2050 that amount will reach four billion. Urban population is growing especially in large metropolitan areas. This increase has different outgrowths concerning regular circulation, safety, and climatic perspectives. Therefore, the present and further increase of traffic flow is affecting the operational and safety performance of several roadway categories. Urban ring roads belong to a roadway category that is particularly subjected to congestion phenomena, but in many cases, public administrations are unable to afford required expenses to upgrade or build new roadways. Therefore, an intervention is needed that increases the capacity of existing infrastructures with limited cost results to be fundamental. In such a framework, the dynamic use of hard shoulder running (HSR) would represent a valid solution that both exploits existing infrastructures and facilitates traffic outflow by implementation of smart digital roads, with limited interventions on the physical infrastructure. Despite the expected improvements in traffic capacity, the HSR poses safety issues particularly in specific locations (e.g., interchanges) and for the operation of the transition phase for opening and closing the HSR. In this paper, the applicability and usefulness of microsimulation were tested with the Catania (Italy) ring road, as a case study, through the application of VISSIM traffic microsimulation software and SSAM traffic conflict tool, implementing different scenarios for the activation of the HSR. Full article
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13 pages, 1767 KiB  
Article
Decision Tree Method to Analyze the Performance of Lane Support Systems
by Giuseppina Pappalardo, Salvatore Cafiso, Alessandro Di Graziano and Alessandro Severino
Sustainability 2021, 13(2), 846; https://doi.org/10.3390/su13020846 - 16 Jan 2021
Cited by 51 | Viewed by 3242
Abstract
Road departure is one of the main causes of single vehicle and frontal crashes. By implementing lateral support systems, a significant amount of these accidents can be avoided. Typical accidents are normally occurring due to unintentional lane departure where the driver drifts towards [...] Read more.
Road departure is one of the main causes of single vehicle and frontal crashes. By implementing lateral support systems, a significant amount of these accidents can be avoided. Typical accidents are normally occurring due to unintentional lane departure where the driver drifts towards and across the line identifying the edge of the lane. The Lane Support Systems (LSS) uses cameras to “read” the lines on the road and alert the driver if the car is approaching the lines. Anyway, despite the assumed technology readiness, there is still much uncertainty regarding the needs of vision systems for “reading” the road and limited results are still available from in field testing. In such framework the paper presents an experimental test of LSS performance carried out in two lane rural roads with different geometric alignments and road marking conditions. LSS faults, in day light and dry pavement conditions, were detected on average in 2% of the road sections. A decision tree method was used to analyze the cause of the faults and the importance of the variable involved in the process. The fault probability increased in road sections with radius less than 200 m and in poor conditions of road marking. Full article
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16 pages, 1470 KiB  
Article
A Few Critical Human Factors for Developing Sustainable Autonomous Driving Technology
by José Fernando Sabando Cárdenas, Jong Gyu Shin and Sang Ho Kim
Sustainability 2020, 12(7), 3030; https://doi.org/10.3390/su12073030 - 09 Apr 2020
Cited by 4 | Viewed by 3403
Abstract
The purpose of this study is to develop a framework that can identify critical human factors (HFs) that can generate human errors and, consequently, accidents in autonomous driving level 3 situations. Although much emphasis has been placed on developing hardware and software components [...] Read more.
The purpose of this study is to develop a framework that can identify critical human factors (HFs) that can generate human errors and, consequently, accidents in autonomous driving level 3 situations. Although much emphasis has been placed on developing hardware and software components for self-driving cars, interactions between a human driver and an autonomous car have not been examined. Because user acceptance and trust are substantial for the further and sustainable development of autonomous driving technology, considering factors that will influence user satisfaction is crucial. As autonomous driving is a new field of research, the literature review in other established fields was performed to draw out these probable HFs. Herein, interrelationship matrices were deployed to identify critical HFs and analyze the associations between these HFs and their impact on performance. Age, focus, multitasking capabilities, intelligence, and learning speed are selected as the most critical HFs in autonomous driving technology. Considering these factors in designing interactions between drivers and automated driving systems will enhance users’ acceptance of the technology and its sustainability by securing good usability and user experiences. Full article
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