Sustainability

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21 pages, 14228 KiB

Open AccessArticle

Identifying Impacts of School-Escorted Trips on Traffic Congestion and the Countermeasures in Bangkok: An Agent-Based Simulation Approach

by Titipakorn Prakayaphun, Yoshitsugu Hayashi, Varameth Vichiensan and Hiroyuki Takeshita

Sustainability 2023, 15(23), 16244; https://doi.org/10.3390/su152316244 - 23 Nov 2023

Viewed by 1361

Abstract

The often-discussed issue of parental escorting of children to school and its potential disruption of traffic flow has been extensively examined in the literature. Still, the specific effects of traffic congestion remain understudied. To fill this gap, this study addresses the impacts of [...] Read more.

The often-discussed issue of parental escorting of children to school and its potential disruption of traffic flow has been extensively examined in the literature. Still, the specific effects of traffic congestion remain understudied. To fill this gap, this study addresses the impacts of school trips on traffic congestion. An agent-based model is applied to simulate various scenarios and assess their impact. Our findings indicate that the traffic speed without school trips is higher speed during peak hours by around 8% and average travel time in the city is reduced significantly. We examine countermeasures: Firstly, flexible working hours can lead to a morning traffic speed improvement of approximately 1.9%. Secondly, staggered school schedules can result in a 6.9% increase in traffic speed at 7 a.m. Optimizing school loading spaces can also enhance road capacity, mitigating road lane blockages during drop-off and pick-up periods. This research sheds light on the impact of parent-escorting travel existence and offers potential solutions to alleviate traffic congestion. Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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25 pages, 3403 KiB

Open AccessArticle

Influence of Urban Railway Network Centrality on Residential Property Values in Bangkok

by Varameth Vichiensan, Vasinee Wasuntarasook, Titipakorn Prakayaphun, Masanobu Kii and Yoshitsugu Hayashi

Sustainability 2023, 15(22), 16013; https://doi.org/10.3390/su152216013 - 16 Nov 2023

Cited by 2 | Viewed by 1023

Abstract

In recent decades, Bangkok has experienced substantial investments in its urban railway network, resulting in a profound transformation of the city’s landscape. This study examines the relationship between railway development and property value uplift, particularly focusing on network centrality, which is closely linked [...] Read more.

In recent decades, Bangkok has experienced substantial investments in its urban railway network, resulting in a profound transformation of the city’s landscape. This study examines the relationship between railway development and property value uplift, particularly focusing on network centrality, which is closely linked to urban structure. Our findings are based on two primary analyses: network centrality and spatial hedonic models. The network centrality analysis reveals that closeness centrality underscores the city’s prevailing monocentric structure, while the betweenness centrality measure envisions the potential emergence of urban subcenters. In our hedonic analysis of condominiums near railway stations, we formulated various regression models with different specifications, incorporating spatial effects and network centrality. With Bangkok’s predominant monocentric structure in mind, we found that the spatial regression model, including a spatial error specification and closeness centrality, outperforms the others. This suggests that the impact of railways on property values extends beyond station proximity and encompasses network centrality, intricately linked with the city’s urban structure. We applied our developed model to estimate the expected increase in property values at major interchange stations with high network centralities. These numerical values indicate a considerable potential for their evolution into urban subcenters. These insights offer valuable policy recommendations for effectively harnessing transit-related premiums and shaping the future development of both the railway system and the city. Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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27 pages, 5907 KiB

Open AccessArticle

Co-evolution of Smart Small Vehicles and Human Spatial Experiences: Case Study on Battery-Sharing Electric Two-Wheelers Experiment

by Chun-Chen Chou, Kento Yoh, Shotaro Hirokawa and Kenji Doi

Sustainability 2023, 15(20), 15171; https://doi.org/10.3390/su152015171 - 23 Oct 2023

Viewed by 980

Abstract

Small-format mobility services have been introduced in many cities to promote sustainable urban development. In some cities, these services are primarily seen as entertainment rather than significant transport modes. Research has studied the roles of experiential/hedonic and functional/instrumental motivations in users’ adoption intent [...] Read more.

Small-format mobility services have been introduced in many cities to promote sustainable urban development. In some cities, these services are primarily seen as entertainment rather than significant transport modes. Research has studied the roles of experiential/hedonic and functional/instrumental motivations in users’ adoption intent for such services. However, there is still a limited understanding of how actual spatial experiences of mobility travels shape travel behaviors. This study explores the role of spatial experience in mobility travels. Specifically, the research question revolves around whether better spatial knowledge leads to better spatial experiences, thereby satisfying users’ functional/instrumental and experiential/hedonic values for mobility trips. Additionally, we examine how spatial knowledge affects travel behaviors regarding trip chaining and vehicle charging. To assess road users’ spatial knowledge, we use sketch maps to examine changes after three months of using battery-sharing two-wheelers. A mixed-methods approach and multiple data sources are employed to provide deeper insights, including sketch maps, questionnaire surveys on attitudes, and a panel data analysis on activity-travel patterns. The results indicate that spatial experience significantly influences perceived values and, consequently, travel behaviors. Improved knowledge leads to greater satisfaction with mobility travel. Furthermore, an interaction effect is found between cognitive distance and cognitive direction concerning users’ satisfaction with the driving range and charging issues of electric vehicles. Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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22 pages, 5280 KiB

Open AccessArticle

The Spatial Distribution of Taxi Stations in Bangkok

by Suthikasem Weladee and Peamsook Sanit

Sustainability 2023, 15(19), 14080; https://doi.org/10.3390/su151914080 - 22 Sep 2023

Cited by 1 | Viewed by 1036

Abstract

Taxis play a crucial role as an on-demand transportation mode in developing countries due to perceived inefficiencies of cities’ public transportation systems. However, studies on the locational distribution of taxis in urban areas are limited, despite the need to improve passenger service quality [...] Read more.

Taxis play a crucial role as an on-demand transportation mode in developing countries due to perceived inefficiencies of cities’ public transportation systems. However, studies on the locational distribution of taxis in urban areas are limited, despite the need to improve passenger service quality by balancing the demand and supply of taxi services. Notably, taxi stations possess distinct characteristics compared with other public transport stations that serve passengers directly; in contrast, taxi stations solely support taxi drivers in locations where they begin and conclude their work. This study aims to determine the spatial distribution pattern and assess the agglomeration economies of taxi stations, using Bangkok as a case study, a city with a significant number of registered taxis and dispersed taxi stations. This research takes into account various spatial variables, including land price, land use mix index, population density, and gas station locations. The primary tool for analyzing the spatial distribution pattern was the spatial statistics model, employing ArcGIS 10.8 software. The analysis consisted of three steps: testing for clustered or dispersed patterns using Moran’s I, applying Anselin’s local Moran’s I (LISA) to examine the relationship between taxi station coordinates and spatial variables such as land price, land use mix index, and population density, and evaluating the relationship between taxi stations and energy service stations using the network analysis tool. The results revealed that taxi stations exhibited a spatially clustered pattern and were closely correlated with the land use mix index, land price, and population density, as indicated by Moran’s index values of 0.425, 0.328, and 0.373, respectively, especially those located within a 3000 m radius of gas stations. These findings elucidate the location selection of taxi stations, which tend to prioritize areas that can generate maximum profits for the taxi business rather than those with minimal location costs. They also tend to be situated in proximity to market areas. Additionally, the study recommends that the government consider promoting electric taxis as a sustainable mode of urban transport in the future to reduce the usage of natural gas (NGV) and liquefied petroleum gas (LPG). Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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19 pages, 9370 KiB

Open AccessArticle

Quality of Life Prediction in Driving Scenes on Thailand Roads Using Information Extraction from Deep Convolutional Neural Networks

by Kitsaphon Thitisiriwech, Teerapong Panboonyuen, Pittipol Kantavat, Boonserm Kijsirikul, Yuji Iwahori, Shinji Fukui and Yoshitsugu Hayashi

Sustainability 2023, 15(3), 2847; https://doi.org/10.3390/su15032847 - 3 Feb 2023

Cited by 2 | Viewed by 2423

Abstract

In the modern era, urban design and sustainable development are vital topics for megacities, as they are important for the wellbeing of its residents. One of the effective key performance indices (KPIs) measuring the city plan’s efficiency in quantity and quality factors is [...] Read more.

In the modern era, urban design and sustainable development are vital topics for megacities, as they are important for the wellbeing of its residents. One of the effective key performance indices (KPIs) measuring the city plan’s efficiency in quantity and quality factors is Quality of Life (QOL), an index that policymakers can use as a critical KPI to measure the quality of urbanscape design. In the traditional approach, the researchers conduct the questionnaire survey and then analyze the gathered data to acquire the QOL index. The conventional process is costly and time-consuming, but the result of the evaluation area is limited. Moreover, it is difficult to embed in an application or system; we proposed artificial intelligence (AI) approaches to solve the limitation of the traditional method in Bangkok as a case study. There are two steps for our proposed method. First, in the knowledge extraction step, we apply deep convolutional neural networks (DCNNs), including semantic segmentation and object detection, to extract helpful information images. Second, we use a linear regression model for inferring the QOL score. We conducted various state-of-the-art (SOTA) models and public datasets to evaluate the performance of our method. The experiment results show that our novel approach is practical and can be considered for use as an alternative QOL acquisition method. We also gain some understanding of drivers’ insights from the experiment result. Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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26 pages, 38141 KiB

Open AccessArticle

Exploring the Spatial Effects of Built Environment on Quality of Life Related Transportation by Integrating GIS and Deep Learning Approaches

by Pawinee Iamtrakul, Sararad Chayphong, Pittipol Kantavat, Yoshitsugu Hayashi, Boonserm Kijsirikul and Yuji Iwahori

Sustainability 2023, 15(3), 2785; https://doi.org/10.3390/su15032785 - 3 Feb 2023

Cited by 11 | Viewed by 2983

Abstract

Understanding the quality of life related to transportation plays a crucial role in enhancing commuters’ quality of life, particularly in daily trips. This study explores the spatial effects of built environment on quality of life related to transportation (QoLT) through the combination of [...] Read more.

Understanding the quality of life related to transportation plays a crucial role in enhancing commuters’ quality of life, particularly in daily trips. This study explores the spatial effects of built environment on quality of life related to transportation (QoLT) through the combination of GIS application and deep learning based on a questionnaire survey by focusing on a case study in Sukhumvit district, Bangkok, Thailand. The Geographic Information System (GIS) was applied for spatial analysis and visualization among all variables through a grid cell (500 × 500 sq.m.). In regard to deep learning, the semantic segmentation process that the model used in this research was OCRNet, and the selected backbone was HRNet_W48. A quality-of-life-related transportation indicator (life satisfaction) was implemented through 500 face-to-face interviews and the data were collected by a questionnaire survey. Then, multinomial regression analysis was performed to demonstrate the significant in positive and negative aspects of independent variables (built environment) with QoLT variables at a 0.05 level of statistical significance. The results revealed the individuals’ satisfaction from a diverse group of people in distinct areas or environments who consequently perceived QoLT differently. Built environmental factors were gathered by application of GIS and deep learning, which provided a number of data sets to describe the clusters of physical scene characteristics related to QoLT. The perception of commuters could be translated to different clusters of the physical attributes through the indicated satisfaction level of QoLT. The findings are consistent with the physical characteristics of each typological site context, allowing for an understanding of differences in accessibility to transport systems, including safety and cost of transport. In conclusion, these findings highlight essential aspects of urban planning and transport systems that must consider discrepancies of physical characteristics in terms of social and economic needs from a holistic viewpoint. A better understanding of QoLT adds important value for transportation development to balance the social, economic, and environmental levels toward sustainable futures. Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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17 pages, 8399 KiB

Open AccessArticle

A Novel Approach for Urban Road Network Maintenance Plans Using Spatial Autocorrelation Analysis and Roadside Conditions: A Case Study of Muroran City, Japan

by Takumi Asada, Tran Vinh Ha, Mikiharu Arimura and Shuichi Kameyama

Sustainability 2022, 14(23), 16189; https://doi.org/10.3390/su142316189 - 4 Dec 2022

Cited by 1 | Viewed by 1893

Abstract

Urban and residential roads play an integral role in the infrastructure system of a city. Although they take up a large proportion of the national road network, maintenance plans for urban roads are beset by many problems. These include difficulty in collecting enormous [...] Read more.

Urban and residential roads play an integral role in the infrastructure system of a city. Although they take up a large proportion of the national road network, maintenance plans for urban roads are beset by many problems. These include difficulty in collecting enormous volumes of data, implementing analyses, and interpreting results because of complicated frameworks. Thus, this study aims to introduce an effective and reliable method of formulating a maintenance plan using integrated criteria of spatial autocorrelation analysis and roadside conditions. The results demonstrate that defective pavements are clustered in certain areas, for example, mountainous and forested areas, which indicate environmental effects. Using a mixed index as a criterion for prioritization, approximately 55% of roadside residents (represented by the total residential housing floor area) and 90% of commercial and medical facilities surrounding critical sections gained benefit from maintenance activities in the second year. Importantly, the proposed method presents the advantages of simplifying implications and quantitative outcomes that could support local agents in not only implementing but also making decisions and interpreting such decisions for the community. Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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Other

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20 pages, 1586 KiB

Open AccessSystematic Review

Digital Bicycling Planning: A Systematic Literature Review of Data-Driven Approaches

by Parisa Zare, Christopher Pettit, Simone Leao and Ori Gudes

Sustainability 2022, 14(23), 16319; https://doi.org/10.3390/su142316319 - 6 Dec 2022

Cited by 3 | Viewed by 2118

Abstract

To increase the amount of bicycling as a mode of transport, many countries are developing placed based bicycling plans and strategies. However, this approach necessitates considering a fine-scale mapping of bicycling patterns and a detailed description of urban spaces. The rise of new [...] Read more.

To increase the amount of bicycling as a mode of transport, many countries are developing placed based bicycling plans and strategies. However, this approach necessitates considering a fine-scale mapping of bicycling patterns and a detailed description of urban spaces. The rise of new data and technologies offers much promise to planners and researchers to access diverse and richer sources of information to optimise the bicycling network design. This review aims to comprehensively examine the role of data and technology in bicycling planning, historical changes in using data-driven approaches, and current domains in the existing body of research in bicycling planning from 1990 to 2021. For this, a systematic literature review has been conducted according to PRISMA framework. A total number of 1022 studies was analysed and synthesised with the VOS Viewer and CiteSpace platforms. Upon completing the review, we extracted the most-used datasets, tools, and methodologies. The results of the systematic review reveal three evolutionary phases in using data-driven approaches from 1990 to 1999, 2000 to 2009, and 2010 to 2021. In addition, we identified six knowledge domains in using data-driven approaches in bicycling planning that is (i) smart city, (ii) infrastructure, (iii) built environment, (iv) decision making, (v) people, and (vi) safety. Full article

(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)

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