Transportation Research Part D-transport and Environment最新文献_第3页

Multidimensional comparative analysis of future climate change impacts on pavement infrastructure aging

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-11 DOI: 10.1016/j.trd.2025.104702

Runhua Zhang , Lijun Sun , Yaning Qiao , Jo E. Sias , Eshan V. Dave

{"title":"Multidimensional comparative analysis of future climate change impacts on pavement infrastructure aging","authors":"Runhua Zhang , Lijun Sun , Yaning Qiao , Jo E. Sias , Eshan V. Dave","doi":"10.1016/j.trd.2025.104702","DOIUrl":"10.1016/j.trd.2025.104702","url":null,"abstract":"<div><div>This study examines how rising temperatures affect asphalt pavement aging, long-term performance, and maintenance costs across four cities under medium and high emissions scenarios during historical and future periods (2025–2099). The results show that a 1℃ increase in average temperature facilitates asphalt pavement aging rate by 3% to 4%, significantly increasing pavement damage, maintenance frequency and costs. For instance, maintenance costs in New Delhi are projected to increase by up to 22.2% under SSP585 compared to historical period. Global road maintenance costs are projected to rise by $16.5–$33.0 billion, with U.S. costs increasing by $0.5–$1.0 billion. High-performance mixes, such as polymer-modified asphalt, can effectively mitigate the impact of future climate change by improving asphalt elasticity and slowing its aging process, thereby reducing the maintenance frequency and costs. Although their higher initial material cost may present economic trade-offs, the extended service life and reduced maintenance costs can offset these costs. Policymakers can utilize these findings to optimize maintenance investments, while engineers may adopt adaptive designs or materials to reduce climate-related impacts on road infrastructure.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104702"},"PeriodicalIF":7.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transition to near-zero emission shipping fleet powered by alternative fuels under uncertainty

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-11 DOI: 10.1016/j.trd.2025.104689

Yadong Wang , Çağatay Iris

引用次数: 0

Fuel consumption of hybrid electric vehicles under real-world road and temperature conditions

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-10 DOI: 10.1016/j.trd.2025.104691

Ye Zhang , Pengfei Fan , Hongyu Lu , Guohua Song

{"title":"Fuel consumption of hybrid electric vehicles under real-world road and temperature conditions","authors":"Ye Zhang , Pengfei Fan , Hongyu Lu , Guohua Song","doi":"10.1016/j.trd.2025.104691","DOIUrl":"10.1016/j.trd.2025.104691","url":null,"abstract":"<div><div>Hybrid electric vehicles (HEVs) and internal combustion engine vehicles (ICEVs) exhibit distinct fuel consumption variations under real-world conditions like temperature and road type (due to different powertrain architectures). As laboratory experiments face limitations in capturing the temporal and spatial variability of vehicle activities, this study employed high-resolution and large-scale real-world data, conducted an in-depth analysis. Specifically, this study analyzed the variation in vehicle fuel consumption factors (FCF) through a Vehicle Specific Power (VSP)-based descriptive analysis and a machine learning-based correlation analysis; the network-wide HEV carbon reduction potential was assessed considering the impact of temperature and road type. Findings show that HEVs can reduce vehicle average FCF by 39.3% on freeways & expressways and 58.0% on arterial compared to ICEVs, with seasonal FCF reduction varying (52.8% in spring, 42.4% in winter). This study provides case-based evidence for the HEV carbon reduction potential and offers valuable insights into enhancing vehicle fuel economy.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104691"},"PeriodicalIF":7.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Heat and mobility: Machine learning perspectives on bike-sharing resilience in Shanghai

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-10 DOI: 10.1016/j.trd.2025.104692

Zeyin Chen , Renlu Qiao , Siying Li , Shiqi Zhou , Xiuning Zhang , Zhiqiang Wu , Tao Wu

{"title":"Heat and mobility: Machine learning perspectives on bike-sharing resilience in Shanghai","authors":"Zeyin Chen , Renlu Qiao , Siying Li , Shiqi Zhou , Xiuning Zhang , Zhiqiang Wu , Tao Wu","doi":"10.1016/j.trd.2025.104692","DOIUrl":"10.1016/j.trd.2025.104692","url":null,"abstract":"<div><div>Global climate change has increased extreme heat events, impacting urban mobility, particularly bike-sharing. This study examines the urban mobility resilience (UMR) of bike-sharing to extreme heat in Shanghai’s urban center, analyzing how the built environment and other factors influence UMR through machine learning. The model has an explanatory power of 73.5% and 63.7% on weekdays and weekends. Results indicate that extreme heat has a stronger effect on weekends. Key factors like development intensity, public transportation accessibility, and functional diversity positively affect resilience, with building density increases from 0 to 0.3 promoting UMR by nearly 0.1 (out of 1). Proximity to metro stations (within 1,000–1,500 m) also promotes resilience. The reasonable aggregation of socio-economic factors can also effectively enhance resilience. However, greening and road density sometimes play a negative role. The research provides more references for urban planners and managers to customize strategies to enhance UMR in the context of climate change.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104692"},"PeriodicalIF":7.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Public preferences for stationary wired and dynamic wireless electric vehicle charging technologies

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-08 DOI: 10.1016/j.trd.2025.104680

Kenny Chandra Wijaya , Prasanna Humagain , Konstantina Gkritza

{"title":"Public preferences for stationary wired and dynamic wireless electric vehicle charging technologies","authors":"Kenny Chandra Wijaya , Prasanna Humagain , Konstantina Gkritza","doi":"10.1016/j.trd.2025.104680","DOIUrl":"10.1016/j.trd.2025.104680","url":null,"abstract":"<div><div>The adoption of electric vehicles (EVs) supports United Nations’ sustainable development goals. Dynamic wireless power transfer (DWPT) technology, which allows EV charging while driving, addresses issues such as range anxiety. However, studies on public perception of DWPT compared to wired technologies are limited. To explore this, a choice experiment was conducted with 203 experienced EV users (those who have leased or owned an EV) and 1,008 inexperienced users (non-EV users) in Indiana, U.S., assessing preferences for DWPT, Level 2, and Level 3/direct current fast charging (DCFC) for a 100-mile trip. Results showed that experienced users preferred DCFC over DWPT, with Level 2 rated the lowest. In contrast, inexperienced users ranked DWPT the lowest, favoring Level 2. Attitudes toward environment and positive EV features and convenience influenced these preferences. Recommendations include promoting DWPT benefits, offering firsthand DWPT experiences, and enhancing public charging ecosystem to increase user satisfaction and encourage EV adoption.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104680"},"PeriodicalIF":7.3,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-speed rail, technological improvement, and carbon emission efficiency

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-06 DOI: 10.1016/j.trd.2025.104685

Weijian Su , Xiabing Li , Yepeng Zhang , Quanfei Zhang , Tao Wang , Małgorzata Magdziarczyk , Adam Smolinski

{"title":"High-speed rail, technological improvement, and carbon emission efficiency","authors":"Weijian Su , Xiabing Li , Yepeng Zhang , Quanfei Zhang , Tao Wang , Małgorzata Magdziarczyk , Adam Smolinski","doi":"10.1016/j.trd.2025.104685","DOIUrl":"10.1016/j.trd.2025.104685","url":null,"abstract":"<div><div>Reducing carbon emissions and improving carbon efficiency are global responsibilities, and high-speed rail (HSR), as a new form of transportation infrastructure, plays a crucial role in this process. This paper employs the difference-in-difference model to assess the impact of HSR connectivity on carbon emission efficiency. The results show that HSR connectivity, as well as the number of stations and routes, increased carbon emission efficiency by 0.4%, 0.2%, and 0.3%, respectively. The effect is more pronounced in smaller cities and regions with lower marketization. Micro-level data reveals that the effective impact radius of HSR is 2000 m. HSR increases fossil energy consumption in firms while reducing electricity consumption. The primary mechanism by which HSR reduces overall carbon emissions is by improving the fossil energy carbon emission efficiency of firms. Parallel trend tests, placebo tests, and endogeneity analyses all support these findings. The results provide valuable insights for the location of industrial parks near HSR stations and highlight that power rationing may limit the speed of carbon reduction.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104685"},"PeriodicalIF":7.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time air quality prediction using traffic videos and machine learning

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-06 DOI: 10.1016/j.trd.2025.104688

Laura Deveer , Laura Minet

{"title":"Real-time air quality prediction using traffic videos and machine learning","authors":"Laura Deveer , Laura Minet","doi":"10.1016/j.trd.2025.104688","DOIUrl":"10.1016/j.trd.2025.104688","url":null,"abstract":"<div><div>Machine learning techniques are yielding better results than traditional statistical techniques to estimate traffic-related air pollutant (TRAP) concentrations. However, required data inputs, particularly complex traffic data, are costly and rarely collected in real-time. This study leverages real-time object detection techniques to accurately predict TRAP concentrations by extracting traffic variables solely from videos. Fine particulate matter (PM<sub>2.5</sub>), nitrogen dioxide (NO<sub>2</sub>) and ozone (O<sub>3</sub>) concentrations are recorded by low-cost sensors, with traffic data extracted using object detection and tracking algorithms. Extreme Gradient Boosting, random forest, and multilinear regression models are employed to predict concentrations across different predictor combinations. Our optimal models accurately predict PM<sub>2.5</sub>, NO<sub>2,</sub> and O<sub>3</sub> concentrations with R<sup>2</sup> values of 0.94, 0.95, and 0.92, respectively. This study demonstrates a cost-effective approach with high accuracies in predicting real-time TRAP using a low-cost and low-maintenance tool: a video camera. Cities could similarly track TRAP using traffic camera infrastructure without additional sensor deployment.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104688"},"PeriodicalIF":7.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analyzing disparities in app-hailed travel during extreme heat in New York City

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-04 DOI: 10.1016/j.trd.2025.104650

Mahtot Gebresselassie, Jeremy Michalek, Destenie Nock, Corey Harper

引用次数: 0

A Copula-ECAC model for estimating aviation noise around airports

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-03-03 DOI: 10.1016/j.trd.2025.104666

Wentao Guo , Weili Zeng , Yadong Zhou

引用次数: 0

The heterogeneity of travel mode choice behavior under unplanned metro service disruptions

IF 7.3 1区工程技术

Transportation Research Part D-transport and Environment Pub Date : 2025-02-28 DOI: 10.1016/j.trd.2025.104683

Qing-Chang Lu , Xin-Yu Zuo , Chao Chen , Zhi Dong , Peng-Cheng Xu , Jing Li

{"title":"The heterogeneity of travel mode choice behavior under unplanned metro service disruptions","authors":"Qing-Chang Lu , Xin-Yu Zuo , Chao Chen , Zhi Dong , Peng-Cheng Xu , Jing Li","doi":"10.1016/j.trd.2025.104683","DOIUrl":"10.1016/j.trd.2025.104683","url":null,"abstract":"<div><div>With the increasing frequency of unplanned service disruptions in metro system, understanding the travel mode choice behavior is essential for the improvement of passenger evacuation strategies and enhancement of metro system security. Individuals’ choice behavior may exhibit heterogeneity, particularly when faced with diverse activities and multimodal transport modes. Based on the survey data of Xi’an, China, an error component mixed logit model was developed to explore the decision-making mechanism of mode choices and heterogeneous preferences for multimodal transport modes. The results indicate that activity-dependent attributes significantly influence mode choices. Longer travel distance increases the likelihood of individuals continuing metro travel. Activity urgency level has a significant negative effect on waiting for service resumption, but positively influences the choice of taxis. Furthermore, significant heterogeneity is observed in waiting tolerance and preferences for intermodal transport modes. These findings provide insights for the emergency management of metro system under unplanned service disruptions.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104683"},"PeriodicalIF":7.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0