Research

18 pages, 3113 KiB

Open AccessArticle

Impact of Carbon Trading Mechanism Considering Blockchain Technology on the Evolution of New Energy Vehicle Industry in the Post-Subsidy Era

by Wenhui Zhao, Yimeng Liu, Jiansheng Hou and Lifang Liu

Sustainability 2023, 15(17), 13190; https://doi.org/10.3390/su151713190 - 01 Sep 2023

Cited by 1 | Viewed by 1208

Abstract

The incentives for the new energy vehicle industry have been decreasing year by year, and the industry has gradually returned from being “government-oriented” to “market-oriented”. In this context, motivating car companies and consumers to choose new energy vehicles to reach the dual-carbon goal [...] Read more.

The incentives for the new energy vehicle industry have been decreasing year by year, and the industry has gradually returned from being “government-oriented” to “market-oriented”. In this context, motivating car companies and consumers to choose new energy vehicles to reach the dual-carbon goal is an urgent problem to be solved. In this study, we consider using blockchain technology to include the new energy vehicle industry in carbon trading, analyze the strategic choices of the government, automobile manufacturers, and consumers from the perspective of evolutionary games, and use MATLAB 2017b to conduct simulation analysis. The results show that (1) the implementation of a carbon trading mechanism by the government is favorable to automobile manufacturers and consumers in choosing new energy vehicles, but it is greatly influenced by the costs of technology implementation; (2) the government can induce consumers and automakers to choose new energy vehicles through total control and initial carbon quotas; and (3) the additional investment costs of automobile manufacturers will affect their willingness to produce new energy vehicles, and the government can adjust the existing “double points” policy to encourage automobile manufacturers to choose to produce new energy vehicles. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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18 pages, 2427 KiB

Open AccessArticle

The Impacts of Low-Carbon Incentives and Carbon-Reduction Awareness on Airport Ground Access Mode Choice under Travel Time Uncertainty: A Hybrid CPT-MNL Model

by Mengru Shao, Chao Chen, Qingchang Lu, Xinyu Zuo, Xueling Liu and Xiaoning Gu

Sustainability 2023, 15(16), 12610; https://doi.org/10.3390/su151612610 - 20 Aug 2023

Viewed by 990

Abstract

Developing strategies to incentivize travelers towards adopting sustainable mobility options is one of the effective approaches to mitigate carbon emissions. Using Xi’an Xianyang International Airport as a case study, this study aims to explore the effects of low-carbon incentives and carbon-reduction awareness on [...] Read more.

Developing strategies to incentivize travelers towards adopting sustainable mobility options is one of the effective approaches to mitigate carbon emissions. Using Xi’an Xianyang International Airport as a case study, this study aims to explore the effects of low-carbon incentives and carbon-reduction awareness on airport ground access mode choices. In addition, to account for the complex road environment, an innovative stated preference choice experiment was designed, integrating the factor of travel time uncertainty. Then, a hybrid cumulative prospect theory–Multinomial Logit (CPT-MNL) model was also developed. The estimated results revealed that travelers increasingly prioritize emissions reduction and consciously prefer sustainable mobility options to reach the airport. Furthermore, the potential of low-carbon incentives to encourage public transport usage over private vehicles has been highlighted. Notably, travel time uncertainty had a significant impact on the choice of private cars. When the travel time to the airport is uncertain, travelers exhibit a greater inclination towards selecting public transport. The findings of this study offer nuanced insights for transportation authorities, aiding them in fostering the adoption of sustainable mobility options and achieving carbon reduction objectives. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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13 pages, 563 KiB

Open AccessArticle

Gender Representation and Leadership in Local Transport Decision-Making Positions

by Lena Winslott Hiselius, Annica Kronsell, Lena Smidfelt Rosqvist, Christian Dymén and Olga Stepanova

Sustainability 2023, 15(14), 11280; https://doi.org/10.3390/su151411280 - 20 Jul 2023

Viewed by 754

Abstract

This paper aims to analyse and further capture nuances of gender representation in local political decision-making bodies, focusing on implications for transport policy. Since gender is highly relevant for both attitudes towards transport policy as well as political votes, data on the gender [...] Read more.

This paper aims to analyse and further capture nuances of gender representation in local political decision-making bodies, focusing on implications for transport policy. Since gender is highly relevant for both attitudes towards transport policy as well as political votes, data on the gender and political colour of executives (members of presidiums) of transport-related committees, councils, and boards is analysed. The study is aimed at the local level, since municipal transport policy decisions include areas with clear differences between masculinity and femininity norms. The mapping of representation reveals, in line with other studies, that women are underrepresented in the most leading position (as chairperson of the City Board 31–37%), and that presidiums of transport-related committees, especially, are highly dominated by men (72–74%) with no clear positive trend in female representation identified over the studied years. The result suggests that transport-related decisions are disproportionally shaped by men as well as masculine norms, with implications for the transition towards transport sustainability. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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14 pages, 4261 KiB

Open AccessArticle

Aging in Place or Moving to Higher Ground: Older Adults’ Adaptation to Sea Level Rise in Honolulu, Hawaii

by Suwan Shen, Karl Kim and Dingyi Liu

Sustainability 2023, 15(12), 9535; https://doi.org/10.3390/su15129535 - 14 Jun 2023

Viewed by 1120

Abstract

Coastal communities face escalating risks from rising sea levels and the increasing growth of vulnerable, aging populations in high-risk zones. These threats are expected to intensify as population growth and aging trends continue. In response to these challenges, this study represents a novel [...] Read more.

Coastal communities face escalating risks from rising sea levels and the increasing growth of vulnerable, aging populations in high-risk zones. These threats are expected to intensify as population growth and aging trends continue. In response to these challenges, this study represents a novel investigation into the synergistic impacts of demographic shifts and climate change in shaping the vulnerability of coastal communities, particularly focusing on elderly populations. This study’s primary objectives are to assess the potential impacts of these threats on vulnerable older adults and to explore effective adaptation strategies. To achieve these objectives, we used census tract data from Hawaii and the Hamilton–Perry cohort-component method to project the elderly population trends in each census tract for Honolulu in 2050. The vulnerabilities of older adults were estimated under different sea level rise level conditions and mapped according to three planning scenarios: (1) maintaining the status quo; (2) relocating or redeveloping vulnerable elderly residents to safer, low-density neighborhoods; (3) relocating or redeveloping vulnerable elderly residents to secure, high-density areas with amenities for older adults. We further evaluated transportation accessibility to emergency services in these scenarios. The findings reveal that with a projected sea level rise of 1.1 feet, the number of elderly individuals without timely access (within 8 min) to emergency and healthcare services would double by 2050. This is primarily attributed to reduced transportation access and increased aging in high-risk areas. Compared to the status quo, both relocation (or redevelopment) strategies significantly improve the vulnerable elderly population’s access to emergency and healthcare services, even without enhancements in transportation and infrastructure. Given that many developments and aging trends are yet to fully unfold, we propose that existing adaptation strategies should prioritize land use development, along with housing and transportation solutions that align with development scenarios 2 and 3, to support age-friendly activities and lifestyles. By directing population growth towards less vulnerable zones in the coming decades, we can achieve protective effects equivalent to those of future relocation efforts, but without incurring substantial protection or relocation costs. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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23 pages, 8477 KiB

Open AccessArticle

A Traffic Parameter Extraction Model Using Small Vehicle Detection and Tracking in Low-Brightness Aerial Images

by Junli Liu, Xiaofeng Liu, Qiang Chen and Shuyun Niu

Sustainability 2023, 15(11), 8505; https://doi.org/10.3390/su15118505 - 24 May 2023

Viewed by 1131

Abstract

It is still a challenge to detect small-size vehicles from a drone perspective, particularly under low-brightness conditions. In this context, a YOLOX-IM-DeepSort model was proposed, which improved the object detection performance in low-brightness conditions accurately and efficiently. At the stage of object detection, [...] Read more.

It is still a challenge to detect small-size vehicles from a drone perspective, particularly under low-brightness conditions. In this context, a YOLOX-IM-DeepSort model was proposed, which improved the object detection performance in low-brightness conditions accurately and efficiently. At the stage of object detection, this model incorporates the data enhancement algorithm as well as an ultra-lightweight subspace attention module, and optimizes the number of detection heads and the loss function. Then, the ablation experiment was conducted and the analysis results showed that the YOLOX-IM model has better mAP than the baseline model YOLOX-s for multi-scale object detection. At the stage of object tracking, the DeepSort object-tracking algorithm is connected to the YOLOX-IM model, which can extract vehicle classification data, vehicle trajectory, and vehicle speed. Then, the VisDrone2021 dataset was adopted to verify the object-detection and tracking performance of the proposed model, and comparison experiment results showed that the average vehicle detection accuracy is 85.00% and the average vehicle tracking accuracy is 71.30% at various brightness levels, both of which are better than those of CenterNet, YOLOv3, FasterR-CNN, and CascadeR-CNN. Next, a field experiment using an in-vehicle global navigation satellite system and a DJI Phantom 4 RTK drone was conducted in Tianjin, China, and 12 control experimental scenarios with different drone flight heights and vehicle speeds were designed to analyze the effect of drone flight altitude on speed extraction accuracy. Finally, the conclusions and discussions were presented. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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20 pages, 1937 KiB

Open AccessArticle

Examining the Relationship between Transportation Infrastructure, Urbanization Level and Rural-Urban Income Gap in China

by Meseret Chanieabate, Hai He, Chuyue Guo, Betelhem Abrahamgeremew and Yuanji Huang

Sustainability 2023, 15(10), 8410; https://doi.org/10.3390/su15108410 - 22 May 2023

Cited by 8 | Viewed by 2541

Abstract

The development of transportation infrastructure plays a pivotal role in the regional economy from multiple dimensions. The aim of this paper is to examine the relationship between transportation infrastructure development and income inequality in urban and rural areas of China. The study utilizes [...] Read more.

The development of transportation infrastructure plays a pivotal role in the regional economy from multiple dimensions. The aim of this paper is to examine the relationship between transportation infrastructure development and income inequality in urban and rural areas of China. The study utilizes panel data from 30 provinces, spanning the years 2010 to 2020, and employs the spatial Dubin model to measure and test the impact of transportation infrastructure on the urban-rural income gap. Furthermore, an intermediary effect test method is used to investigate the potential mediating effect of urbanization in this relationship. The results indicate that transportation infrastructure has a significantly negative direct, indirect, and total effect on the urban-rural income gap, with the indirect effect being greater than the direct effect. This suggests that transportation infrastructure can effectively reduce income disparities, with a noticeable spatial spillover effect. The level of urbanization plays a significant intermediary effect on the effect of transportation infrastructure on the urban-rural income gap, highlighting the role of transportation infrastructure in improving urbanization and narrowing income disparities. These findings underscore the importance of enhancing both the level of urbanization and cooperation between neighbouring regions in order to maximize the benefits of transportation infrastructure development for reducing income disparities and promoting regional balance in China. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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12 pages, 6859 KiB

Open AccessArticle

Research Context and Prospect of Green Railways in China Based on Bibliometric Analysis

by Weiya Chen, Xiaoqi Shi, Xiaoping Fang, Yongzhuo Yu and Shiying Tong

Sustainability 2023, 15(7), 5773; https://doi.org/10.3390/su15075773 - 26 Mar 2023

Cited by 4 | Viewed by 1309

Abstract

The CiteSpace bibliometric software was used to quantitatively analyze the research papers on green railways retrieved from the China National Knowledge Infrastructure (CNKI) database during 1985–2021. Combined with content association analysis, the development stages, frontier hotspots, and evolutionary trends of green railway research [...] Read more.

The CiteSpace bibliometric software was used to quantitatively analyze the research papers on green railways retrieved from the China National Knowledge Infrastructure (CNKI) database during 1985–2021. Combined with content association analysis, the development stages, frontier hotspots, and evolutionary trends of green railway research in China were summarized in the Chinese context. The results show that in the past 36 years, China’s green railway research has experienced four main stages: the emerging stage (1985–1997), the horizontal expansion stage (1998–2010), the vertical deepening stage (2010–2015), and integrated expansion stage (2016–present). The research topics emerging in the four stages are green design and green construction, green channel and green logistics, energy conservation and emission reduction and green evaluation, multimodal transportation, and green development. In general, the research topics are diversified, but green construction of railway infrastructures and green manufacturing of railway equipment have been the research hotspots all the time. Both external and internal paths drive the transmutation of academic frontiers, and the push effect of the external path is more evident than the internal path. Interdisciplinary integration and innovation gradually become a new force to promote green railway research. As the railway development slowly enters a “big operation era”, it can be inferred that the development trend of green railway research could throw light on the following three areas: from the research perspective and topics, it should be based on a framework of life cycle management to explore, systematically and deeply, the correlation and integration of railway green design, green construction, green operation and maintenance; in terms of the research content, more focus should be on new theories, new methods, and new technologies of railway green operation and green maintenance on the basis of railway green design, construction, and manufacturing research, such as railway green operation strategies and evaluation systems and green transportation organization theories and methods; from innovation paths, academic progress still needs both external and internal paths, interdisciplinary integration and innovation as the primary internal driving force to promote green railway research, and more focus on the use of big data and artificial intelligence and other technologies to innovate green railway development. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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23 pages, 3508 KiB

Open AccessArticle

Collaborative Decision-Making Method of Emergency Response for Highway Incidents

by Junfeng Yao, Longhao Yan, Zhuohang Xu, Ping Wang and Xiangmo Zhao

Sustainability 2023, 15(3), 2099; https://doi.org/10.3390/su15032099 - 22 Jan 2023

Cited by 3 | Viewed by 1748

Abstract

With the continuous increase in highway mileage and vehicles in China, highway accidents are also increasing year by year. However, the on-site disposal procedures of highway accidents are complex, which makes it difficult for the emergency department to fully observe the accident scene, [...] Read more.

With the continuous increase in highway mileage and vehicles in China, highway accidents are also increasing year by year. However, the on-site disposal procedures of highway accidents are complex, which makes it difficult for the emergency department to fully observe the accident scene, resulting in the lack of sufficient communication and cooperation between multiple emergency departments, making the rescue efficiency low and wasting valuable rescue time, and causing unnecessary injury or loss of life due to the lack of timely assistance. Thus, this paper proposes a multi-agent-based collaborative emergency-decision-making algorithm for traffic accident on-site disposal. Firstly, based on the analysis and abstraction of highway surveillance videos obtained from the Shaanxi Provincial Highway Administration, this paper constructs an emergency disposal model based on Petri net to simulate the emergency on-site disposal procedures. After transforming the emergency disposal model into a Markov game model and applying it to the multi-agent deep deterministic strategy gradient (MADDPG) algorithm proposed in this paper, the multiple agents can optimize the emergency-decision-making and on-site disposal procedures through interactive learning with the environment. Finally, the proposed algorithm is compared with the typical algorithm and the actual processing procedure in the simulation experiment of an actual Shaanxi highway traffic accident. The results show that the proposed emergency-decision-making method could greatly improve collaboration efficiency among emergency departments and effectively reduce emergency response time. This algorithm is not only superior to other decision-making algorithms such as genetic algorithm (EA), evolutionary strategy (ES), and deep Q network (DQN), but also reduces the disposal processes by 28%, 28%, and 42%, respectively, compared with the actual disposal process in three emergency disposal cases. In summary, with the continuous development of information technology and highway management systems, the multi-agent-based collaborative emergency-decision-making algorithm will contribute to the actual emergency response process and emergency disposal in the future, improving rescue efficiency and ensuring the safety of individuals. Full article

(This article belongs to the Special Issue The Sustainable Development of Transportation)

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