Transportation Research Part D-transport and Environment最新文献_第8页

Real-time air quality prediction using traffic videos and machine learning 利用交通视频和机器学习进行实时空气质量预测

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 分析了在纽约市极端高温期间，应用程序受到欢迎的旅行差异

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

Performance metrics for resilience of airport infrastructure 机场基础设施弹性性能指标

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.2025.104676

Robert Horton , Benjamin D. Trump , Joshua Trump , Hal S. Knowles , Igor Linkov , Pierce Jones , Greg Kiker

{"title":"Performance metrics for resilience of airport infrastructure","authors":"Robert Horton , Benjamin D. Trump , Joshua Trump , Hal S. Knowles , Igor Linkov , Pierce Jones , Greg Kiker","doi":"10.1016/j.trd.2025.104676","DOIUrl":"10.1016/j.trd.2025.104676","url":null,"abstract":"<div><div>Recent disruptions in transportation systems resulting from natural disasters, cyber accidents, and other factors clearly show the fragility of the airports and underscore the need for building resilience. This study introduces a comprehensive framework for evaluating the resilience of airport infrastructure, integrating critical functions and performance indicators in the context of specific missions that the airport needs to achieve. By focusing on the Dallas-Fort Worth International Airport (DFW) as a case study, the paper outlines a multi-criteria decision analysis (MCDA) methodology for identifying and assessing the critical functions of airports as well as their ability to recover and adapt under different threat scenarios including threat-agnostic situation. The methodology and its application to the DFW case study offer insights into the resilience of airport operations, highlighting key areas for improvement and the potential for policy intervention. This study provides a robust tool for airport administrators and policymakers to enhance infrastructure resilience through a detailed analysis and visualization of airport performance indicators, thereby contributing to the broader discourse on transportation system sustainability and disaster preparedness.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104676"},"PeriodicalIF":7.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783724","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

A Copula-ECAC model for estimating aviation noise around airports 机场周围航空噪声估计的Copula-ECAC模型

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 意外地铁服务中断下出行方式选择行为的异质性

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

Promoting community resident support for private charging pile sharing: A micro survey 促进社区居民对私人充电桩共享的支持：一个微观调查

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.2025.104675

Lei Shi , Meirong Guo , Xiaohui Lyu , Shanliang Li

{"title":"Promoting community resident support for private charging pile sharing: A micro survey","authors":"Lei Shi , Meirong Guo , Xiaohui Lyu , Shanliang Li","doi":"10.1016/j.trd.2025.104675","DOIUrl":"10.1016/j.trd.2025.104675","url":null,"abstract":"<div><div>The Chinese government promotes private charging pile sharing (PCPS) as a model of the sharing economy in the transport sector, but there are barriers to its widespread adoption. Through a survey with 2,578 responses and by employing an ordered probit model, we analyzed the factors influencing PCPS adoption. Our research shows that PCPS and urban public charging piles serve different charging needs: daily convenient slow charging and emergency rapid charging, respectively, precluding direct competition. Residents’ main concerns about adopting PCPS include unfamiliar vehicles entering the community, safety risks, and unclear liability in accidents. Understanding of policy boosts support for PCPS, and residents residing in relatively older neighborhoods with self-owned houses exhibit more pronounced support. Our findings suggest that policy awareness promotion, enhanced management of unfamiliar vehicles by property companies, and targeted promotion to residents with self-owned houses but no parking spaces can effectively foster the development of the PCPS model.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104675"},"PeriodicalIF":7.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521186","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

Quantifying carbon emissions in cold chain transport: A real-world data-driven approach 量化冷链运输中的碳排放：现实世界数据驱动的方法

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.2025.104679

Hung-Jui Lin , Pei-Ci Chen , Hsuan-Po Lin , I-Yun Lisa Hsieh

{"title":"Quantifying carbon emissions in cold chain transport: A real-world data-driven approach","authors":"Hung-Jui Lin , Pei-Ci Chen , Hsuan-Po Lin , I-Yun Lisa Hsieh","doi":"10.1016/j.trd.2025.104679","DOIUrl":"10.1016/j.trd.2025.104679","url":null,"abstract":"<div><div>Sustainable urban development necessitates advanced low-carbon transportation strategies, particularly within the cold chain logistics sector, where transporting perishable goods significantly contributes to environmental emissions. This study addresses the gap in empirical research by deploying real-world data from 128 long-haul trips, provided by a logistics company, to develop a comprehensive bottom-up operational-level carbon emission model. Our model quantifies emissions through various operational phases—loading, unloading, and transport—capturing contributions from vehicle operation (driving and idling), refrigeration processes (including transmission, infiltration, and pre-cooling), and refrigerant leakage. It further assesses the impact of ambient temperature on emissions and examines the effectiveness of decarbonization strategies such as employing shore power for pre-cooling and adopting low-carbon refrigerants. Validated against actual fuel consumption with an impressive accuracy of −1.84%, our findings significantly advance green logistics practices, offering practical insights for a transition towards net-zero emissions and improving the sustainability of cold chain transportation systems.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104679"},"PeriodicalIF":7.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521185","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

Integrated optimization of charging infrastructure, electric bus scheduling and energy systems 充电基础设施、电动公交调度、能源系统集成优化

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.2025.104664

Arsalan Najafi , Kun Gao , Omkar Parishwad , Georgios Tsaousoglou , Sheng Jin , Wen Yi

{"title":"Integrated optimization of charging infrastructure, electric bus scheduling and energy systems","authors":"Arsalan Najafi , Kun Gao , Omkar Parishwad , Georgios Tsaousoglou , Sheng Jin , Wen Yi","doi":"10.1016/j.trd.2025.104664","DOIUrl":"10.1016/j.trd.2025.104664","url":null,"abstract":"<div><div>The adoption of Battery Electric Buses (BEBs) in electric public transit systems presents a significant opportunity for advancing sustainable transportation. This study introduces a holistic framework for joint optimization of charging infrastructure, charging scheduling, and integration of renewable energy resources (RES), considering impacts on Power distribution network (PDN). To address the complex optimization, a decomposition approach is employed to linearize the problem and divide it into master and subproblems for efficient resolution. A case study in Skövde, Sweden demonstrates that the proposed methodology optimizes charging infrastructure deployment and scheduling to reduce the overall system costs. Meanwhile, high charging demand from BEBs in some periods to fulfil operation scheduling may result in violation of technical constraints of the PDN (more than 4%), without RES. The incorporation and optimization of RES with battery energy storage can cater to spatiotemporal charging demand of BEB while enhancing stability and safety of PDN.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"141 ","pages":"Article 104664"},"PeriodicalIF":7.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of full-process VOCs emissions of on-road vehicles considering individual parking behaviors 考虑个体停车行为的道路车辆全过程VOCs排放评价

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.2025.104678

Xinru Yang , Dawen Yao , Rui Xu , Yuzhuang Pian , Shikun Liu , Yonghong Liu

{"title":"Assessment of full-process VOCs emissions of on-road vehicles considering individual parking behaviors","authors":"Xinru Yang , Dawen Yao , Rui Xu , Yuzhuang Pian , Shikun Liu , Yonghong Liu","doi":"10.1016/j.trd.2025.104678","DOIUrl":"10.1016/j.trd.2025.104678","url":null,"abstract":"<div><div>Vehicle-emitted volatile organic compounds (VOCs) significantly contribute to ozone (O<sub>3</sub>) formation, affecting health and environment. Prior studies focused on exhaust emissions, often overlooking evaporative emissions due to a lack of detailed parking behaviors, underestimating total VOCs. Using automated vehicle identification (AVI) data from Xuancheng, this study developed a full-process VOCs emission model covering both exhaust and evaporative emissions. Findings show that 80 % of vehicles are parked for over 90 % of the day, with parking behaviors causing significant emissions variations among vehicles. Total VOCs emissions were 44.46 tons from April 15 to May 15, 2022. Specifically, exhaust, diurnal, running losses, and hot soak emissions were 59.2 %, 24.2 %, 14.9 %, and 1.7 %, respectively, with parking emissions at 25.9 %. During Labor Day, reduced traffic and increased parking raised daily VOCs emissions, with parking emissions rising to 33.4 %. This underscores the need to consider evaporative emissions and parking behaviors in emission management and pollution control.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104678"},"PeriodicalIF":7.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511049","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

Eco-driving for connected automated hybrid electric vehicles in learning-enabled layered transportation systems 联网自动混合动力汽车在分层交通系统中的生态驾驶

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.2025.104677

Su Yan , Jiayi Fang , Chao Yang , Ruihu Chen , Hui Liu

{"title":"Eco-driving for connected automated hybrid electric vehicles in learning-enabled layered transportation systems","authors":"Su Yan , Jiayi Fang , Chao Yang , Ruihu Chen , Hui Liu","doi":"10.1016/j.trd.2025.104677","DOIUrl":"10.1016/j.trd.2025.104677","url":null,"abstract":"<div><div>Eco-driving strategies have the potential to enhance energy savings, safety, and transportation efficiency by optimizing vehicle interactions with dynamic traffic environments. This study addresses the challenge of balancing computational efficiency and optimization effectiveness amid the high-dimensional state and control variables driven by extensive traffic information. The novelty different from existing methods lies in developing an eco-driving strategy within a traffic information cyber–physical system. The cyber-layer maps simulated road segments for training vehicles equipped with the Proximal Policy Optimization (PPO) algorithm, enabling effective planning of economical speeds. During vehicle operation, the cyber-layer maps the real-time physical environment, providing a predictive state sequence for the vehicle’s adaptive equivalent fuel consumption minimization strategy. Then, optimizing the efficiency factor in a rolling manner further improves fuel economy. A comparative analysis with existing methods across different scenarios shows that the proposed strategy significantly improves fuel economy while ensuring real-time speed planning and reliable speed-tracking performance.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104677"},"PeriodicalIF":7.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521188","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