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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 21381

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Special Issue Editors

Dr. Feng Zhu

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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
Special Issues, Collections and Topics in MDPI journals

Dr. Wenbo Zhang

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Guest Editor

Department of Traffic Engineering, Southeast University, Nanjing 211189, Jiangsu, China
Interests: transportation big data; smart mobility; intelligent transportation management

Dr. Yuntao Guo

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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 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 transport
sustainability
resilience
smart cities

Published Papers (10 papers)

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Research

15 pages, 1286 KiB

Open AccessArticle

Injury-Based Surrogate Resilience Measure: Assessing the Post-Crash Traffic Resilience of the Urban Roadway Tunnels

by Chenming Jiang, Junliang He, Shengxue Zhu, Wenbo Zhang, Gen Li and Weikun Xu

Sustainability 2023, 15(8), 6615; https://doi.org/10.3390/su15086615 - 13 Apr 2023

Cited by 6 | Viewed by 985

Abstract

Crash injuries not only result in huge property damages, physical distress, and loss of lives, but arouse a reduction in roadway capacity and delay the recovery progress of traffic to normality. To assess the resilience of post-crash tunnel traffic, two novel concepts, i.e., surrogate resilience measure (SRM) and injury-based resilience (IR), were proposed in this study. As a special kind of semi-closed infrastructure, urban tunnels are more vulnerable to traffic crashes and injuries than regular roadways. To assess the IR of the post-crash roadway tunnel traffic system, an over-one-year accident dataset comprising 8621 crashes in urban roadway tunnels in Shanghai, China was utilized. A total of 34 variables from 11 factors were selected to establish the IR assessment indicator system. Methodologically, to tackle the skewness issue in the dataset, a binary skewed logit (Scobit) model was found to be superior to a conventional logistic model and subsequently adopted for further analysis. The estimated results showed that 15 variables were identified to be significant in assessing the IR of the roadway tunnels in Shanghai. Finally, the formula for calculating the IR levels of post-crash traffic systems in tunnels was given and would be a helpful tool to mitigate potential trends in crash-related resilience deterioration. The findings of this study have implications for bridging the gap between conventional traffic safety research and system resilience modeling. Full article

(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)

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15 pages, 3120 KiB

Open AccessArticle

Relationship between Highway Geometric Characteristics and Accident Risk: A Multilayer Perceptron Model (MLP) Approach

by Jie Yan, Sheng Zeng, Bijiang Tian, Yuanwen Cao, Wenchen Yang and Feng Zhu

Sustainability 2023, 15(3), 1893; https://doi.org/10.3390/su15031893 - 18 Jan 2023

Cited by 4 | Viewed by 1466

Abstract

The traffic safety of mountain highway has always been one of the taking point. This study aims to collect road design data in large-scale research and analyzes the accident risk of highway geometric alignment. Accordingly, a method based on satellite maps and clustering algorithms is proposed to calculate the geometric alignment of the highway plane and its longitudinal section. The reliability of the method was verified on Nanfu highway in Chongqing, China. The planar and longitudinal sectional geometries of the four highways in Chongqing were obtained by the above method, and the corresponding 36,439 traffic accidents which occurred from 2010 to 2016 were used as the research objects. The accident risk of the highway geometry was analyzed based on the SHAP and MLP theories. The results show that the fitting and prediction abilities of the MLP model are better than those of the negative binomial model, and its correlation coefficient is improved by 33.2%. In addition, compared with the negative binomial model, the MLP model can estimate more accurately and flexibly the complex nonlinear relationship between the independent and the dependent variables. Full article

(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)

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19 pages, 7397 KiB

Open AccessArticle

Millimetre Wave and Sub-6 5G Readiness of Mobile Network Big Data for Public Transport Planning

by Okkie Putriani, Sigit Priyanto, Imam Muthohar and Mukhammad Rizka Fahmi Amrozi

Sustainability 2023, 15(1), 672; https://doi.org/10.3390/su15010672 - 30 Dec 2022

Cited by 1 | Viewed by 2278

Abstract

The need to solve public transport planning challenges using 5G is demanding. In 2019, the world started using 5G technology. Unfortunately, many countries have no equipment that is compatible with 5G infrastructures. There are two main deployment options for countries willing to accept 5G. They can directly venture to install relatively expensive infrastructure, called 5G SA (standalone access). However, more countries use the 5G NSA (non-standalone access) alternative, a 5G network supported by existing 4G infrastructure. One of the considerations for choosing NSA 5G is that it still performs 4G equalisation in its area. The data throughput is faster but still uses the leading 4G network. Interestingly, there are three types of 5G: low-band (sub-6), middle-band (sub-6), and high-band (millimetre-wave (mmWave)). The problem is determining the kind of 5G needed for public transport planning. Meanwhile, mobile network big data (MNBD) requires robust and stable internet access, with broad coverage in real time. MNBD movement includes the movement of people and vehicles, as well as logistics. GPS and internet connections track the activity of private vehicles and public transportation. The difference between mmWave and sub-6 5G can complement transportation planning needs. The density and height of buildings in urban areas and the affordability of the range of the connections determine 5G. This study examines the literature on 5G and then, using the bibliographic method, matches the network coverage obtained in Indonesia using nPerf data services. According to the data, urban areas are becoming more densely populated. Thus, this could show the differences in the data quality outside of metropolitan areas. This study also discusses the current conditions in terms of market potential and the development of smart cities and provides an overview of how real-time mobile data can support public transport planning. This article provides beneficial insight into the stability and adjustment of 5G, where the connectivity can be adequately maintained so that the MNBD can deliver representative data for analysis. Full article

(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)

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18 pages, 2879 KiB

Open AccessArticle

Analysis of the Social Capital in a Technological System of a Smart City Using a PLS-SEM Model

by Juliana Mejia, Eva Cristina Manotas and Santiago Quintero

Sustainability 2022, 14(18), 11238; https://doi.org/10.3390/su141811238 - 08 Sep 2022

Cited by 1 | Viewed by 1798

Abstract

In this paper, social capital was analyzed through the lens of the resources and capabilities theory, understanding it as a capability that has a role in the performance of the Smart City. Social capital relates to the technological capabilities and the technological learning process. The objective of this investigation was to build a representation model of the social capital resources and technological learning, taking social capital as a capability of the Smart City. First, on a methodological level, a preliminary exercise that shows the relation and the gaps between the concepts and the process to build the model are presented. Later, the Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to build the conceptual and measured model. Based on the configuration of the tangible variables, the model was tested with the information provided by the final users of the public urban bicycle system of the Medellín–EnCicla technological system. The impact of technological learning is interpreted by relating it to the sources of social capital, to its resources (trust, social interaction, and shared vision), and to the technological system chosen. As a result, the construction of an exploratory model is presented that interprets the resources of social capital and their relation to technological learning in a smart city. The investigation aims to contribute to the decision-making exercise in the public policies regarding the sustainable mobility of the smart city that was the object of study. Full article

(This article belongs to the Special Issue Transport Sustainability and Resilience in Smart Cities)

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19 pages, 1481 KiB

Open AccessArticle

System Optimization of Shared Mobility in Suburban Contexts

by Roxana Gandomani, Moataz Mohamed, Amir Amiri and Saiedeh Razavi

Sustainability 2022, 14(2), 876; https://doi.org/10.3390/su14020876 - 13 Jan 2022

Cited by 1 | Viewed by 1642

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 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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21 pages, 2583 KiB

Open AccessArticle

Exploring Travel Mode Preference of External Trips for Smart City Transportation Planning: Sejong, Korea

by Jin-Ki Eom, Kwang-Sub Lee, Sangpil Ko and Jun Lee

Sustainability 2022, 14(2), 630; https://doi.org/10.3390/su14020630 - 06 Jan 2022

Cited by 3 | Viewed by 2207

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, 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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14 pages, 798 KiB

Open AccessArticle

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

by Bijoy Saha and Mahmudur Rahman Fatmi

Sustainability 2021, 13(22), 12501; https://doi.org/10.3390/su132212501 - 12 Nov 2021

Cited by 2 | Viewed by 1581

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 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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17 pages, 26284 KiB

Open AccessArticle

More than Bike Lanes—A Multifactorial Index of Urban Bikeability

by Michael Hardinghaus, Simon Nieland, Marius Lehne and Jan Weschke

Sustainability 2021, 13(21), 11584; https://doi.org/10.3390/su132111584 - 20 Oct 2021

Cited by 8 | Viewed by 3752

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 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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18 pages, 1047 KiB

Open AccessArticle

Junction Management for Connected and Automated Vehicles: Intersection or Roundabout?

by Yuanyuan Wu and Feng Zhu

Sustainability 2021, 13(16), 9482; https://doi.org/10.3390/su13169482 - 23 Aug 2021

Cited by 11 | Viewed by 2555

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 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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19 pages, 4974 KiB

Open AccessArticle

Investigation of Bus Drivers’ Reaction to ADAS Warning System: Application of the Gaussian Mixed Model

by Wei Ye, Yueru Xu, Feixiang Zhou, Xiaomeng Shi and Zhirui Ye

Sustainability 2021, 13(16), 8759; https://doi.org/10.3390/su13168759 - 05 Aug 2021

Cited by 4 | Viewed by 1913

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 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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