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Next-Generation Sensing, Computing, and System Engineering for Large-Scale Connected and...
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Next-Generation Sensing, Computing, and System Engineering for Large-Scale Connected and Automated Vehicle and Transportation: Celebrating the 70th Anniversary of Nanjing University of Aeronautics and Astronautics

A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 3857

Special Issue Editors

Prof. Dr. Yong Tian

E-Mail Website
Guest Editor
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: air traffic controller; airspace management; traffic flow; flight plans
Dr. Jiangchen Li

E-Mail Website
Guest Editor
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: connected and automated traffic flow; transportation systems for road and air traffics
Special Issues, Collections and Topics in MDPI journals
Dr. Bojia Ye

E-Mail Website
Guest Editor
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: trajectory control; vehicle dynamics; air traffic control; air traffic management and artificial intelligence
Dr. Mei Han

E-Mail Website
Guest Editor
College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: system and industrial engineering; statistical quality control and improvement; Bayesian optimization; simulation-based engineering design optimization

Special Issue Information

Dear Colleagues,

Nanjing University of Aeronautics and Astronautics (NUAA), established in 1952, enjoys well-balanced development of multiple disciplines in Natural Sciences, Humanities, Social Sciences, Management, etc., with the characteristics of Aeronautics, Astronautics, and Civil Aviation. NUAA is among the first batch of national key universities entitled to award doctoral, master’s, and bachelor’s degrees. It is one of the 55 universities offering graduate school in China, and it has also been listed as one of the “National Project 211” universities. In 2017, it entered the national “double first-class” construction sequence. The school is now part of the Ministry of Industry and Information Technology.

In celebration of the 70th anniversary of the NUAA, this Special Issue is dedicated to next-generation sensing, computing, and system engineering for large-scale connected and automated vehicle and transportation (CAV and CAT). As known, with the enormous and huge efforts from both academia and the industry, connected and automated transportation has a trend of moving to a new big picture: planning, operation, and maintenance for large-scale CAV and CAT systems in the following few decades. Cooperative shared CAVs are being utilized as robotaxis, autonomous trucks, and low-speed autonomous transit buses, among others. This Special Issue aims to provide a forum to welcome all the advances and efforts in promoting large-scale CAV and CAT. High-quality original technical papers or advanced review papers are welcome.

Topics for the Special Issue include, but are not limited to, the following:

  1. Next-generation sensing, vehicle perception, and sensor fusion.
  2. Bird’s-eye view perception, behavior perception, and prediction.
  3. Advanced connectivity and communication, 5G, 6G, and cooperative perception.
  4. Highly automated electric vehicles and connected autonomous electric vehicles.
  5. Deep learning, reinforcement learning, deep reinforcement learning, and attention models.
  6. Traffic flow theory and dynamics, autonomous and semi-autonomous intersection, and autonomous traffic signal control.
  7. Trajectory planning, vehicle platooning, and autonomous fleet management.
  8. Joint optimization of vehicle trajectories and traffic signals, signal-free traffic automation.
  9. Edge-based vehicle and signal automation, mobile edge computing, and multi-access edge computing.
  10. Urban air mobility, vertical-takeoff-and-landing aircraft, and highly automated aircraft.

Prof. Dr. Yong Tian
Dr. Jiangchen Li
Dr. Bojia Ye
Dr. Mei Han
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. Electronics 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

  • connected and automated vehicle
  • connected and automated transportation
  • autonomous intersection
  • vehicle platooning
  • mobile edge computing
  • traffic signal control

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Published Papers (2 papers)

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28 pages, 575 KiB  
Article
Estimating the Value of Airport Access Time in Developing Countries with a Case Study of Nanjing, China
by Renwei Zhu, Zhao Yang and Jun Chen
Electronics 2023, 12(5), 1120; https://doi.org/10.3390/electronics12051120 - 24 Feb 2023
Viewed by 1357
Abstract
The valuation of time is one of the most important public policy issues in project cost-benefit analysis. This paper estimates the value of airport access time and time variability in developing countries with a case study of Nanjing, China. An international meta-analysis is [...] Read more.
The valuation of time is one of the most important public policy issues in project cost-benefit analysis. This paper estimates the value of airport access time and time variability in developing countries with a case study of Nanjing, China. An international meta-analysis is being used to identify the factors that may affect heterogeneity in the value of travel time. Regression models are then established for the prediction of the value of travel time. The results provide some new insights into the impacts of survey region, traffic mode, and trip purpose on the value of travel time. Considering the significant influencing factors that were obtained, stated preference surveys are designed and used to collect data on preferred arrival time and decision choice under various hypothetical situations. A multivariate regression model is used with the data to explore the significant factors that influence the travelers’ preferred arrival time. Mixed logit models are developed to estimate the value of airport access time, value of schedule delay early, and value of schedule delay late by incorporating the effects of travel delay variability on users’ scheduling costs. The tax system is being used to illustrate the contribution of different income groups to social funds, which also calculates the social value of airport access time, social value of schedule delay early, and social value of schedule delay late. The results identify the significant factors that may affect the valuation of airport access time and provide reasonable estimates for these values. The findings also bring new enlightenment on the effects of the variation of airport access time. Full article
(This article belongs to the Special Issue Next-Generation Sensing, Computing, and System Engineering for Large-Scale Connected and Automated Vehicle and Transportation: Celebrating the 70th Anniversary of Nanjing University of Aeronautics and Astronautics)
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11 pages, 984 KiB  
Article
Fast L2 Calibration for Inexact Highway Traffic Flow Systems
by Jingru Huang, Yan Wang and Mei Han
Electronics 2022, 11(22), 3710; https://doi.org/10.3390/electronics11223710 - 12 Nov 2022
Cited by 2 | Viewed by 1704
Abstract
Transportation systems need more accurate predictions to further optimize traffic network design with the development and application of autonomous driving technology. In this article, we focus on highway traffic flow systems that are often simulated by the modified Greenshields model. However, this model [...] Read more.
Transportation systems need more accurate predictions to further optimize traffic network design with the development and application of autonomous driving technology. In this article, we focus on highway traffic flow systems that are often simulated by the modified Greenshields model. However, this model can not perfectly match the true traffic flow due to its underlying simplifications and assumptions, implying that it is inexact. Specifically, some parameters affect the simulation accuracy of the modified Greenshields model, while tuning these parameters to improve the model’s accuracy is called model calibration. The parameters obtained using the L2 calibration have the advantages of high accuracy and small variance for an inexact model. However, the method is calculation intensive, requiring optimization of the integral loss function. Since traffic flow data are often massive, this paper proposes a fast L2 calibration framework to calibrate the modified Greenshields model. Specifically, the suggested method selects a sub-design containing more information on the calibration parameters, and then the empirical loss function obtained from the optimal sub-design is utilized to approximate the integral loss function. A case study highlights that the proposed method preserves the advantages of L2 calibration and significantly reduces the running time. Full article
(This article belongs to the Special Issue Next-Generation Sensing, Computing, and System Engineering for Large-Scale Connected and Automated Vehicle and Transportation: Celebrating the 70th Anniversary of Nanjing University of Aeronautics and Astronautics)
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