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Strategies of Sustainable Transportation in Urban Planning

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

Deadline for manuscript submissions: closed (20 September 2023) | Viewed by 6556

Special Issue Editor


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Guest Editor
School of Communication and Information Engineering, Institute of Smart City, Shanghai University, Shanghai 200444, China
Interests: artificial intelligence; big data processing; virtual reality

Special Issue Information

Dear Colleagues,

Urban planning and its relevant transportation deployment have a particularly profound influence on the sustainability and liveability of a city, and which will also be crucial to the quality of life of urban residents at the same time. It was also suggested that the conception of liveability should be extended to embrace the concerns associated with the sustainability. The connection between urban/regional traffic and urban behaviour has become one of the important focuses of urban research, and the traffic framework, linked to the rhythmic movement of urban entities, provides the key to restoring the organizational process and self-organization of urban complex systems. Often referred to as externalities, this connection determines the development, potential, constraints, and sustainability of urban entities—population, capital, behaviour, assets, scenarios, and even the sense of belonging and well-being of different social groups. Following the rising advancements in social communication and computer technologies in modern society, big data analysis technology, artificial intelligence technology, and virtual reality technology play an important role in urban planning for sustainable transportation. These methods include advanced decision-making policies for traffic control, autonomous vehicles approaches, and 3D urban reconstruction approaches for traffic planning.

This Special Issue will highlight new opportunities and challenges for sustainable transportation in urban planning, focusing on how to use big data analysis technology, autonomous vehicles technology and 3D reconstruction technology to improve and evaluate the transportation system in urban planning.

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

  • Analysis of the link between urban/regional traffic and urban behaviour;
  • Research on organizational processes and self-organized traffic frameworks and rhythmic movements of urban entities for the restoration of urban complex systems;
  • Big data applications to sustainable transport and traffic control modelling;
  • Data analysis on pedestrian flow and traffic flow, especially how to improve traffic flow capacity through big data processing technology;
  • Decision-making system to assist traffic control network managers in planning, monitoring, and managing;
  • Computer vision technology on scene recognition of road traffic;
  • Vehicle perception technology on road traffic environment;
  • Autonomous vehicles technology in transport safety and the driving behaviours;
  • 3D object recognition in urban traffic;
  • Optimizing the designs and operations of transportation facilities by 3D simulation. Evaluating the effectiveness of various measures on relieving traffic congestion, reducing traffic emission, and improving traffic sustainability.

We look forward to receiving your contributions.

Dr. Wanggen Wan
Guest Editor

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

  • urban planning
  • sustainable transportation
  • data analysis
  • artificial intelligence
  • virtual reality
  • autonomous vehicles
  • 3D reconstruction
  • object recognition
  • scene recognition
  • decision-making system

Published Papers (2 papers)

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30 pages, 9269 KiB  
Article
Models, Algorithms and Applications of DynasTIM Real-Time Traffic Simulation System
by Yong Lin
Sustainability 2023, 15(2), 1707; https://doi.org/10.3390/su15021707 - 16 Jan 2023
Viewed by 3814
Abstract
Intelligent Transportation Systems (ITS) have the potential to improve traffic conditions and reduce travel delays. As a decision support software system for ITS, DynasTIM is based on the principle of dynamic traffic assignment and developed for real-time online simulation, prediction and optimization of [...] Read more.
Intelligent Transportation Systems (ITS) have the potential to improve traffic conditions and reduce travel delays. As a decision support software system for ITS, DynasTIM is based on the principle of dynamic traffic assignment and developed for real-time online simulation, prediction and optimization of dynamic traffic flows in urban or expressway networks. This paper introduces the models, algorithms and some typical applications of DynasTIM. The main contents include: the functional architecture; the application architecture of the system; dynamic OD (Origin-Destination) flows estimation method with novel formula for assignment matrix computation; mesoscopic traffic model using variable-length speed influence region and calibrating speed online based on connected vehicles data; and parallel SPSA algorithm based urban area signal optimization method. The functions of DynasTIM are implemented basically through three main modules: state estimation (ES), state prediction and control strategy optimization (PS&CSO), and guidance strategy optimization (GSO). The case study is aimed at the populated Futian Central Business District (CBD) road network in Shenzhen, China, which has an area of about 7 square kilometers. Based on the archived turning counts collected from 359 video traffic detection locations, DynasTIM was calibrated offline for this network, in order to validate the capability of simulating actual traffic conditions, and to set up basic conditions for testing signal optimization methods. The results show that the simulation output flows of DynasTIM have fairly good matching accuracy with the real surveillance flows in the field. Furthermore, for the CBD network with 38 signalized intersections, the signal optimization method is evaluated and better signal timing plans are found which can reduce about 13% average travel delay, compared with the signal plans currently implemented in the field. Full article
(This article belongs to the Special Issue Strategies of Sustainable Transportation in Urban Planning)
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17 pages, 2607 KiB  
Article
Exploration and Prediction of the Elderly Travel Behavior Based on a Novel GR-GA-BP Hybrid Model
by Zhihong Li, Zinan Wang, Yanjie Wen and Li Zhao
Sustainability 2022, 14(20), 13448; https://doi.org/10.3390/su142013448 - 18 Oct 2022
Cited by 1 | Viewed by 1478
Abstract
With the aging trend in megacities, the travel behaviors of the elderly have attracted much attention. Accurate prediction of the travel behaviors of the elderly is a key link to meet the traffic demand and public facilities’ optimization. The aim of this paper [...] Read more.
With the aging trend in megacities, the travel behaviors of the elderly have attracted much attention. Accurate prediction of the travel behaviors of the elderly is a key link to meet the traffic demand and public facilities’ optimization. The aim of this paper was to explore the link between the travel characteristics and variables of the daily activities of the elderly. Based on a stratified sampling survey, the internal relationship between the characteristics of the elderly and their travel behavior was studied and discussed in this work. A novel grey correlation degree–genetic algorithm–back propagation (GR-GA-BP) hybrid model was proposed to predict the travel behavior of the elderly. Then, a grey correlation degree module was established and used to analyze the correlation between the individual elderly characteristics and their travel behavior. The results showed the following: (1) Both the times of weekly trips (y1) and average round-trip travel time (y2) were highly sensitive to the external environment, especially buses, subway stations, and recreational facilities. The size of the family was less sensitive to the travel behavior. (2) Referring to prediction of the times of weekly trips, the MRE of the proposed model was 23.12%, which was 15.22% less than the baseline models. (3) In terms of the prediction of round-trip travel time, the MRE of the proposed model was 7.13%, which was 14.00–69.41% lower than the baseline models. (4) The times of trips per week were 3.5. In summary, this paper provides technical support for formulating traffic demand policies and facilitates the configuration of cities for an aging society. Full article
(This article belongs to the Special Issue Strategies of Sustainable Transportation in Urban Planning)
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