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Special Issue "Transport Sustainability and Resilience in Smart Cities"

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

Deadline for manuscript submissions: 31 May 2023 | Viewed by 4383

Special Issue Editors

Dr. Feng Zhu
E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: connected and automated vehicles; traffic flow; traffic control; traffic safety
Dr. Wenbo Zhang
E-Mail Website
Guest Editor
Department of Traffic Engineering, Southeast University, Nanjing 211189, Jiangsu, China
Interests: transportation big data; smart mobility; intelligent transportation management
Dr. Yuntao Guo
E-Mail Website
Guest Editor
Department of Traffic Engineering & Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai 201804, China
Interests: travel behavior; transportation policy; automated vehicles; travel safety
Prof. Dr. Jian Wang
E-Mail Website
Guest Editor
School of Transportation, Southeast University, Nanjing 211189, China
Interests: connected and autonomous transportation; transportation system modeling and analysis; data analytics for transportation systems

Special Issue Information

Dear Colleagues,

Population growth and economic expansion in urban area lead to various urbanization challenges, such as environmental degradation and traffic congestion. In addressing urbanization issues, the development of smart cities leverages information and communication technologies to optimize the efficiency of usage and distribution of social, economic, political, and environmental resources. Transportation systems play an important role in the thriving of smart cities as they enable the efficient transport of resources between different origins and destinations. However, along with the growth of urbanization, the environmental externalities of the transportation system also grow, as well as the potential for disruptions. It is essential to ensure that transportation systems in smart cities are sustainable to urbanization growth and resilient to potential disruptions.

We invite researchers to contribute to the Special Issue on the sustainability and resilience challenges associated with the development of transportation systems in smart cities. This Special Issue is intended to serve as an international forum covering broad aspects of science, engineering, technology, economy and the application of sustainability and resilience in urban transportation. Potential topics include but are not limited to:

  • Sustainable public transport policies;
  • Traveler behavioral analysis;
  • Travel demand management, capacity analysis;
  • Integration of smart grids and transportation;
  • Advances in green vehicles, electric vehicles, and vehicular emission reduction;
  • Active mobility modes (walking, cycling, and the use of personal mobility devices);
  • Innovative mobility service, car-sharing service;
  • Congestion mitigation measures;
  • Self-driving vehicles, connected and automated vehicles;
  • Risk assessment of critical transportation infrastructure;
  • Impact of critical transportation infrastructure failure;
  • Vulnerability analysis of transportation systems;
  • Data-driven models for transportation resilience;
  • Resilience of multimodal transportation;
  • Resilience and recovery of transportation systems under disruption.

Dr. Feng Zhu
Dr. Wenbo Zhang
Dr. Yuntao Guo
Prof. Dr. Jian Wang
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 2000 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 transport
  • sustainability
  • resilience
  • smart cities

Published Papers (6 papers)

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Research

Article
System Optimization of Shared Mobility in Suburban Contexts
Sustainability 2022, 14(2), 876; https://doi.org/10.3390/su14020876 - 13 Jan 2022
Viewed by 326
Abstract
Shared mobility is a viable choice to improve the connectivity of lower-density neighbourhoods or suburbs that lack high-frequency public transportation services. In addition, its integration with new forms of powertrain and autonomous technologies can achieve more sustainable and efficient transportation. This study compares [...] Read more.
Shared mobility is a viable choice to improve the connectivity of lower-density neighbourhoods or suburbs that lack high-frequency public transportation services. In addition, its integration with new forms of powertrain and autonomous technologies can achieve more sustainable and efficient transportation. This study compares four shared-mobility technologies in suburban areas: the Internal Combustion Engine, Battery Electric, and two Autonomous Electric Vehicle scenarios, for various passenger capacities ranging from three to fifteen. The study aims to provide policymakers, transportation planners, and transit providers with insights into the potential costs and benefits as well as system configurations of shared mobility in a suburban context. A vehicle routing problem with time windows was applied using the J-Horizon software to optimize the costs of serving existing intra-community demand. The results indicate a similar fleet composition for Battery Electric and Autonomous Electric fleets. Furthermore, the resulting fleet for all four technologies is dominated by larger vehicle capacities. Due to the large share of driver cost in the total cost, the savings using a fleet of Autonomous Electric Vehicles are predicted to be 68% and 70%, respectively, compared to Internal Combustion and Battery Electric fleets. Full article
(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)
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Article
Exploring Travel Mode Preference of External Trips for Smart City Transportation Planning: Sejong, Korea
Sustainability 2022, 14(2), 630; https://doi.org/10.3390/su14020630 - 06 Jan 2022
Viewed by 532
Abstract
In the face of growing concerns about urban problems, smart cities have emerged as a promising solution to address the challenges, for future sustainable societies in cities. Since the early 2000s, 67 local governments in Korea have been participating in smart city projects, [...] Read more.
In the face of growing concerns about urban problems, smart cities have emerged as a promising solution to address the challenges, for future sustainable societies in cities. Since the early 2000s, 67 local governments in Korea have been participating in smart city projects, as of 2019. The Sejong 5-1 Living Area smart city was selected as one of two pilot national demonstration smart cities. The main objectives of this study are to introduce the Sejong 5-1 Living Area smart city project that is currently in the planning stage, present travel and mode preferences focusing on external trips in a smart city context to be built, and analyze a mode choice model according to the socioeconomic characteristics of individual travelers. One of the distinguishing features of the Sejong smart city is its transportation design concept of designating a sharing car-only district within the city to limit private vehicle ownership to about one-third of residents, while bus rapid transit (BRT) plays a central role in mobility for external trips among four transport modes including private cars, BRT, carsharing, and ridesharing. This study was analyzed using the stated preference survey data under hypothetical conditions by reflecting the unique characteristics of the Sejong smart city transportation policy. Approximately two-thirds of respondents in the survey preferred to spend less than 1.25 USD, traveling less than 35 min on BRT trips. On the basis of the survey data, we developed a mixed logit mode choice model and found the overall model estimates to be statistically significant and reasonable. All people-specific variables examined in this study were associated with mode choices for external commuting trips, including age, income, household size, major mode, driving ability, and presence of preschoolers. Full article
(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)
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Article
Simulating the Impacts of Hybrid Campus and Autonomous Electric Vehicles as GHG Mitigation Strategies: A Case Study for a Mid-Size Canadian Post-Secondary School
Sustainability 2021, 13(22), 12501; https://doi.org/10.3390/su132212501 - 12 Nov 2021
Viewed by 489
Abstract
This paper presents how a post-secondary institution like University of British Columbia’s Okanagan (UBCO) campus can reduce its carbon footprint and be aligned with the government’s target through promoting virtual campus and autonomous electric vehicles (AEVs). Different virtual campus scenarios are developed: online [...] Read more.
This paper presents how a post-secondary institution like University of British Columbia’s Okanagan (UBCO) campus can reduce its carbon footprint and be aligned with the government’s target through promoting virtual campus and autonomous electric vehicles (AEVs). Different virtual campus scenarios are developed: online classes only, working-from-home only, and a hybrid of both. In the case of AEVs, alternative penetration rates for levels 2 and 5 are considered. A total of 50 scenarios are tested using a sub-area transport simulation model for UBCO, which is extracted from the regional travel demand forecasting model. The results suggest that a 40% AEV penetration rate coupled with fully in-person classes reduces GHG by ~36% compared to the 2018-level, which will help UBCO to achieve their 2030 emission reduction target and be aligned with the provincial target. The 50% AEV and 10% hybrid virtual campus reduces emissions by ~48%, which is aligned with the 2040 provincial target. A fully virtual campus will help to reach the 2050 provincial target by reducing GHG by ~76%. The results further demonstrate that level 5 AEVs produce lesser emissions than level 2 at a lower AEV penetration rate for the fully in-person campus scenario. At higher penetration rates, level 5 performs better only if it is coupled with 10% of students, faculties and staffs attending virtual campus scenario. Full article
(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)
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Article
More than Bike Lanes—A Multifactorial Index of Urban Bikeability
Sustainability 2021, 13(21), 11584; https://doi.org/10.3390/su132111584 - 20 Oct 2021
Viewed by 824
Abstract
The present study aims to deduce bikeability based on a collective understanding and provides a methodology to operationalize its calculation based on open data. The approach contains four steps building on each other and combines qualitative and quantitative methods. The first three steps [...] Read more.
The present study aims to deduce bikeability based on a collective understanding and provides a methodology to operationalize its calculation based on open data. The approach contains four steps building on each other and combines qualitative and quantitative methods. The first three steps include the definition and operationalization of the index. First, findings from the literature are condensed to determine relevant categories influencing bikeability. Second, an expert survey is conducted to estimate the importance of these categories to gain a common understanding of bikeability and merge the impacting factors. Third, the defined categories are calculated based on OpenStreetMap data and combined to a comprehensive spatial bikeability index in an automated workflow. The fourth step evaluates the proposed index using a multinomial logit mode choice model to derive the effects of bikeability on travel behavior. The expert process shows a stable interaction between the components defining bikeability, linking specific spatial characteristics of bikeability and associated components. Applied components are, in order of importance, biking facilities along main streets, street connectivity, the prevalence of neighborhood streets, green pathways and other cycle facilities, such as rental and repair facilities. The mode choice model shows a strong positive effect of a high bikeability along the route on choosing the bike as the preferred mode. This confirms that the bike friendliness on a route surrounding has a significant impact on the mode choice. Using universal open data and applying stable weighting in an automated workflow renders the approach of assessing urban bike-friendliness fully transferable and the results comparable. It, therefore, lays the foundation for various large-scale cross-sectional analyses. Full article
(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)
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Article
Junction Management for Connected and Automated Vehicles: Intersection or Roundabout?
Sustainability 2021, 13(16), 9482; https://doi.org/10.3390/su13169482 - 23 Aug 2021
Cited by 3 | Viewed by 1020
Abstract
The concept of signal-free management at road junctions is tailored for Connected and Automated Vehicles (CAVs), in which the conventional signal control is replaced by various right-of-way assignment policies. First-Come-First-Served (FCFS) is the most commonly used policy. In most proposed strategies, although the [...] Read more.
The concept of signal-free management at road junctions is tailored for Connected and Automated Vehicles (CAVs), in which the conventional signal control is replaced by various right-of-way assignment policies. First-Come-First-Served (FCFS) is the most commonly used policy. In most proposed strategies, although the traffic signals are replaced, the organization of vehicle trajectory remains the same as that of traffic lights. As a naturally signal-free strategy, roundabout has not received enough attention. A key motivation of this study is to theoretically compare the performance of signalized intersection (I-Signal), intersection using FCFS policy (I-FCFS), roundabout using the typical major-minor priority pattern (R-MM), and roundabout adopting FCFS policy (R-FCFS) under pure CAVs environment. Queueing theory is applied to derive the theoretical formulas of the capacity and average delay of each strategy. M/G/1 model is used to model the three signal-free strategies, while M/M/1/setup model is used to capture the red-and-green light switch nature of signal control. The critical safety time gaps are the main variables and are assumed to be generally distributed in the theoretical derivation. Analytically, I-Signal has the largest capacity benefiting from the ability to separate conflict points in groups, but in some cases it will have higher delay. Among the other three signal-free strategies, R-FCFS has the highest capacity and the least average control delay, indicating that the optimization of signal-free management of CAVs based on roundabout setting is worthy of further study. Full article
(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)
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Article
Investigation of Bus Drivers’ Reaction to ADAS Warning System: Application of the Gaussian Mixed Model
Sustainability 2021, 13(16), 8759; https://doi.org/10.3390/su13168759 - 05 Aug 2021
Viewed by 614
Abstract
Road crashes cause serious loss of life and property. Among all vehicles, buses are more likely to encounter crashes. In recent years, the advanced driving assistance system (ADAS) has been widely used in buses to improve safety. The warning system is one of [...] Read more.
Road crashes cause serious loss of life and property. Among all vehicles, buses are more likely to encounter crashes. In recent years, the advanced driving assistance system (ADAS) has been widely used in buses to improve safety. The warning system is one of the key functions and has proven effective in reducing crashes. However, drivers often ignore or overreact to ADAS warnings during naturalistic driving scenarios. Therefore, reactions of bus drivers to warnings need further investigation. In this study, bus drivers’ responses to lane departure warning (LDW) and forward collision warning (FCW) were investigated using 20-day naturalistic driving data. These reactions could be classified into three categories, namely positive, negative, and overreaction or emergency, by employing the Gaussian mixture model. The authors constructed a framework to quantify drivers’ reactions to the warning and study the reaction characteristics in different environments. The results indicate that drivers’ reactions to FCW were more positive than to LDW, drivers reacted more positively to LDW and FCW while driving on highways than on urban roads, and drivers reacted more positively at night to LDW and FCW than during daytime. This study gives support to an adaptive ADAS considering varying bus driver characteristics and environments. Full article
(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)
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