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Sustainable Transportation: Electrical Design Automation and Vehicle Navigation

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

Deadline for manuscript submissions: 9 September 2024 | Viewed by 535

Special Issue Editors


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Guest Editor
Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: autonomous driving, electric vehicles and intelligent systems; new generation clean propulsion control and optimisation, digital modelling and simulation; intelligent transportation system and artificial intelligence (AI) in engineering practice
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Automotive Engineering, Tongji University, Shanghai, China
Interests: vehicle dynamics control; ntelligent vehicle safety technology; intelligent vehicle testing and evaluation

E-Mail Website
Guest Editor
Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: shared control (i.e., human–machine interaction); development of advanced driver assistant system (adas); autonomous vehicles; traffic control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the world seeks sustainable solutions to address the developing challenges of urban congestion, energy consumption, and environmental degradation, the transportation sector emerges as a focal point of innovation and research. Embracing the principles of sustainability, we are witnessing the birth of electric vehicles (EVs) that promise a future with lower emissions and greater energy efficiency. However, the real potential lies in integrating electrical design automation and advanced vehicle navigation into these systems, ensuring a smarter, more efficient, and truly sustainable mode of transportation.

The anticipated outcome of this Special Issue is to foster an interdisciplinary dialogue that bridges electrical design automation with advanced vehicle navigation. By gathering contributions from leading researchers and professionals in the field, we aim to:

  • Establish a comprehensive understanding of the challenges and opportunities at the intersection of these domains;
  • Propose innovative solutions to enhance the sustainability of transportation;
  • Stimulate further research and collaboration in sustainable transportation solutions.

Scientific Questions of Interest:

  • How can electrical design automation enhance the energy efficiency and driving range of electric vehicles?
  • What are the most promising methodologies for integrating real-time navigation systems with electric drivetrains to optimize energy consumption?
  • How can vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication improve navigation efficiency and safety?

In a world increasingly leaning toward sustainable solutions, this Special Issue aims to be at the forefront of defining the next wave of transportation innovation. By integrating electrical design automation with vehicle navigation, we hope to pave the way for a future where transportation is not only sustainable but also smarter and more efficient.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

a. Electrical Design Automation in EVs:

  • Advanced battery management systems for longer life and better efficiency;
  • Intelligent charging solutions: on-the-go charging, fast charging, and energy regeneration;
  • System-on-chip (SoC) designs for EV-specific applications.

b. Advanced Vehicle Navigation Systems:

  • Real-time traffic prediction and energy-efficient route optimization;
  • Integration of advanced sensors and LiDAR for enhanced navigation capabilities;
  • Machine learning algorithms for predictive vehicle navigation.

c. Communication Protocols and Systems:

  • V2I and V2V communication standards for electric vehicles;
  • Infrastructure support for real-time navigation and energy optimization;
  • Data security and privacy concerns in vehicular communication networks.

d. Case Studies:

  • Real-world implementations of design automation in electric vehicles;
  • Success stories of navigation systems improving EV efficiency;
  • Challenges and solutions in integrating electrical design with navigation systems.

We look forward to receiving your contributions.

Dr. Yuanjian Zhang
Dr. Lin Zhang
Dr. Jingjing Jiang
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

  • electrical design automation in EVs
  • advanced vehicle navigation systems
  • communication protocols and systems

Published Papers (1 paper)

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Research

18 pages, 6729 KiB  
Article
Effects of the Amount of Information from Navigation Voice Guidance on Driving Performance
by Liping Yang, Xiaohua Zhao, Yang Bian, Mengmeng Zhang and Yajuan Guo
Sustainability 2024, 16(14), 5906; https://doi.org/10.3390/su16145906 - 11 Jul 2024
Viewed by 284
Abstract
Nowadays, navigation systems are widely used in public travel because they can instantly offer GPS-based route directions. Following the navigation prompt messages while driving is considered a secondary driving task, while vehicle control is regarded as a primary driving task. Navigation prompt messages [...] Read more.
Nowadays, navigation systems are widely used in public travel because they can instantly offer GPS-based route directions. Following the navigation prompt messages while driving is considered a secondary driving task, while vehicle control is regarded as a primary driving task. Navigation prompt messages with more information can deliver more cues to drivers, but they require a higher cognitive demand and vice versa. To systematically explore the effects of the amount of information from navigation voice prompts and further quantify the utility of voice prompts, four types of prompt messages with increasing amounts of information, denoted as a Single Message, Double Message, Triple Message, and Quadruple Message, were designed. A driving simulation experiment was conducted to obtain driving behavior data under different prompt messages. The one-way analysis of variance (ANOVA) and Kruskal–Wallis (KW) test were used to examine the differences in driving performance under the guidance of different prompt messages from multiple perspectives. Then, eight indicators were selected based on the functions of the navigation system and the driver’s response, and the grey near-optimal method was used to determine the utility of the four types of prompt messages. This study found that the four types of navigation prompt messages all began to take effect at about 200 m upstream of the stop bar. The differences between the four types of prompt messages were more significant in the zone from 100 m upstream and ended at 100 m downstream of the stop bar of the intersection. Drivers using Single and Double Messages exhibited more powerful deceleration than those using Triple and Quadruple Messages. The utility values of the four types of prompt messages increased with the increase in the amount of information. This study provides theoretical support for optimizing navigation information and lays a foundation for establishing navigation broadcast guidelines. Full article
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