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New Trends in Built Environment and Mobility
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New Trends in Built Environment and Mobility

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 3176

Special Issue Editor

Dr. Chaoying Yin

E-Mail Website
Guest Editor
College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Interests: built environment; mobility; quality of life; big data; urban planning; traffic management

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to provide a venue for networking and communication between scholars in the field of built environment (BE) and travel behavior. It comprises original research and reviews on built environment and mobilities with new conceptual and analytical perspectives coupled with new data or approaches. It focuses on complexity and multiplexity in built environment and mobility connections. Advanced analytical approaches, such as machine learning methods and deep learning methods, are encouraged to explore their complex relationships based on big data. In addition, some emerging mobilities, such as shared mobility and autonomous vehicles, may have impacts on the relationship between BE and mobility, which should be investigated. Furthermore, the underexplored data from heterogenous location data, multiple-city/region data, and longitudinal data remain novel for empirical studies. Exploring how the above relationships affect quality of life (i.e., subjective well-being and health) will enhance our understanding of built environment–mobility relationships.

The main topics to be covered include, but are not limited to:

  • Built environment and emerging mobility.
  • Advanced analytical approaches in urban planning.
  • Built environment, mobility, and subjective well-being.
  • Built environment, mobility, and health.
  • Longitudinal design for built environment and mobility.
  • Resilience in built environment.

Dr. Chaoying Yin
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. Buildings 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 2600 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

  • built environment
  • emerging mobility
  • advanced analytical approach
  • subjective well-being
  • longitudinal design

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

19 pages, 2948 KiB  
Article
Investigating the Nonlinear Relationship Between the Built Environment and Urban Vitality Based on Multi-Source Data and Interpretable Machine Learning
by Wenhao Liu, Zhen Yang, Chen Gui, Gen Li and Hongyi Xu
Buildings 2025, 15(9), 1414; https://doi.org/10.3390/buildings15091414 - 23 Apr 2025
Viewed by 207
Abstract
Optimizing the built environment to foster urban vitality is essential for effective urban planning and sustainable development. Previous studies have predominantly focused on analyzing the relationship between the built environment and urban vitality at either a macro or micro-scale, often assuming a predefined [...] Read more.
Optimizing the built environment to foster urban vitality is essential for effective urban planning and sustainable development. Previous studies have predominantly focused on analyzing the relationship between the built environment and urban vitality at either a macro or micro-scale, often assuming a predefined linear relationship. In this study, we investigate the potential non-linear interactions between the built environment and urban vitality by employing an interpretable spatial machine learning framework that integrates the XGBoost model with the SHapley Additive exPlanations (SHAP) algorithm. Additionally, we analyze the determinants of urban vitality across both micro and macro-scales using multi-source data, semantic segmentation models, and street view imagery. Our findings reveal the following key insights: (1) the distribution of urban vitality exhibits spatial heterogeneity within the main urban area of Shanghai, with high vitality areas concentrated in the Huangpu District and at intersections with neighboring districts, demonstrating a decline from the center to the periphery; (2) the XGBoost model outperforms other comparative models, showcasing superior capabilities in simulating and predicting urban vitality; (3) among the various built environment factors influencing urban vitality, building coverage, population density, and distance to the CBD exert the most significant effects, while the green view index and the number of bus stops contribute relatively less; (4) all built environment factors demonstrate nonlinear impacts and exhibit certain threshold effects on urban vitality. The analytical outcomes of this study provide valuable insights for optimizing the spatial layout and resource allocation within urban settings, offering references for urban planning and sustainable development initiatives. Full article
(This article belongs to the Special Issue New Trends in Built Environment and Mobility)
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13 pages, 316 KiB  
Article
Investment Assessments in the Adoption of Accessible and Assistive Technologies Within Built Environments for Persons with Disabilities
by Siny Joseph and Vinod Namboodiri
Buildings 2025, 15(6), 931; https://doi.org/10.3390/buildings15060931 - 15 Mar 2025
Viewed by 274
Abstract
Emerging trends in technology are providing opportunities for a broader range of accessible and assistive technologies (AATs) to positively impact persons with disabilities in terms of independent living and employment within and across built environments. However, such technologies typically require significant investments by [...] Read more.
Emerging trends in technology are providing opportunities for a broader range of accessible and assistive technologies (AATs) to positively impact persons with disabilities in terms of independent living and employment within and across built environments. However, such technologies typically require significant investments by entities that offer such options. It is not clear how such firms compete in a market with other firms that may not provide such options. Understanding such competition can help to promote greater investments in accessibility infrastructure within built environments by entities and provide insights into how federal efforts can further boost such efforts. To this end, this paper presents a game-theoretic framework of market competition between two firms where one invests in accessibility (bearing additional upfront costs) and compares it with another one that does not. Numerical evaluations demonstrate the range of parametric values where accessibility investments pay off. Furthermore, case studies are presented to demonstrate the practical feasibility of these parameter values. The results indicate that any firm considering making accessibility investments can expect to make profits and also gain an advantage over its competitors if the expected increase in the average user experience is significant (quantified as 20% or more for the parameters considered in this work) across all potential users. Full article
(This article belongs to the Special Issue New Trends in Built Environment and Mobility)
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37 pages, 17925 KiB  
Article
Nonlinear Impact Analysis of Urban Road Traffic Carbon Emissions Based on the Integration of Gasoline and Electric Vehicles
by Dongcheng Xie, Xingzi Shi, Kai Li, Jinwei Li and Gen Li
Buildings 2025, 15(3), 488; https://doi.org/10.3390/buildings15030488 - 4 Feb 2025
Viewed by 840
Abstract
With the rapid proliferation of electric vehicles (EVs) in China, the landscape of transportation carbon emissions has undergone significant changes. However, research on the impact of the built environment on the carbon emissions of mixed traffic from gasoline and electric vehicles remains sparse. [...] Read more.
With the rapid proliferation of electric vehicles (EVs) in China, the landscape of transportation carbon emissions has undergone significant changes. However, research on the impact of the built environment on the carbon emissions of mixed traffic from gasoline and electric vehicles remains sparse. This paper focuses on urban traffic scenarios with a mix of gasoline and electric vehicles, analyzing the spatiotemporal distribution of carbon emissions from both types of vehicles and their nonlinear association with the built environment. Utilizing trajectory data from gasoline-powered and electric taxis in Chengdu, China, we establish segment-level carbon emission estimation models based on the vehicle-specific power of gasoline vehicles and the equivalent energy consumption of electric vehicles. Subsequently, we employ the XGBoost algorithm and SHapley Additive ExPlanation (SHAP) to analyze the nonlinear relationships between 13 built environment variables and vehicle carbon emissions. This paper reveals that most built environment variables exhibit nonlinear relationships with traffic carbon emissions, with five factors—population density, road density, residential density, metro accessibility, and the number of parking lots—having a significant impact on road carbon emissions. Finally, we discuss the carbon reduction benefits of EV adoption and propose policy recommendations for low-carbon initiatives in the transportation field. Full article
(This article belongs to the Special Issue New Trends in Built Environment and Mobility)
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12 pages, 656 KiB  
Article
Which Neighborhood Matters? Estimating Multiple-Location Built Environment Effects on the Modality Style
by Yaoxia Ge, Chen Gui, Yunqian Zhuang, Chaoying Yin and Wenyun Tang
Buildings 2025, 15(2), 185; https://doi.org/10.3390/buildings15020185 - 10 Jan 2025
Viewed by 551
Abstract
The literature on the built environment (BE) and travel has offered evidence on both short- and long-term aspects of travel behavior with a main focus on home and work neighborhoods; however, the effects of the BE at the main activity space on the [...] Read more.
The literature on the built environment (BE) and travel has offered evidence on both short- and long-term aspects of travel behavior with a main focus on home and work neighborhoods; however, the effects of the BE at the main activity space on the modality style have remained largely unknown. Moreover, little is known about the inter-modal substitutions and how the substitution is affected by the satiation effects. Based on survey data from Beijing, a Multiple Discrete Continuous Extreme Value (MDCEV) model is adopted to reveal the effects of BE at home, work, and activity space locations on the modality style. Results show that BE features at the home, work, and main activity space neighborhoods are essential triggers of the modality style, among which home BE features play the most vital role. The satiation effects visualized from various travel modes suggest that car traveling remains the most preferred travel mode. These findings can provide refined BE planning implications according to local land-use patterns for urban planners and transport policymakers because a one-size-fits-all design is not a solution to regulate people’s travel behavior. Full article
(This article belongs to the Special Issue New Trends in Built Environment and Mobility)
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12 pages, 589 KiB  
Article
Interactive Effects of Built Environment and Parking Policy on Car Use: Examining Differences Between Work and Non-Work Trips
by Xiaoquan Wang, Yunlong Zhang, Jing Sun and Erjian Liu
Buildings 2024, 14(11), 3457; https://doi.org/10.3390/buildings14113457 - 30 Oct 2024
Viewed by 813
Abstract
Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across [...] Read more.
Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across trip purposes. We conducted a web-based survey in Beijing and collected data from 1036 respondents, including 517 male and 519 female respondents. This study estimates the interactive effects of BE and parking policy on car use for home-based work and non-work trips by employing multilevel logit models. The results show that BE variables at trip origins and destinations are important for shaping car use for both home-based work and non-work trips. Specifically, land use mixture (Coeff. = −0.121), bus stop density (Coeff. = −0.006), and population density (Coeff. = −0.009) at residential locations are negative factors affecting car use for work trips, whereas distance to local center (Coeff. = 0.012) and distance to the city center (Coeff. = 0.019) at residential locations are positive factors. Land use mixture (Coeff. = −0.323), bus stop density (Coeff. = −0.008), road density (Coeff. = −0.002), and population density (Coeff. = −0.007) at residential locations are negative factors of car use for non-work trips. Among BE factors at destinations, land use mixture (Coeff. = −0.319), bus stop density (Coeff. = −0.015), road density (Coeff. = −0.008), distance to the local center (Coeff. = −0.018), and population density (Coeff. = −0.012) are negative factors for car use for work trips, whereas the negative factors for non-work trips are land use mix (Coeff. = −0. 218), bus stop density (Coeff. = −0.038), road density (Coeff. = −0.003), distance to the city center (Coeff. = −0.121), and population density (Coeff. = −0.009). The effects of BE variables can be strengthened or weakened by free parking and parking convenience. Moreover, the results identify significant differences in the effects between work and non-work trips. These findings inform planners and policymakers of how to coordinate the BE and parking policies to decrease car dependence. Full article
(This article belongs to the Special Issue New Trends in Built Environment and Mobility)
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