Transportation Research Part D-transport and Environment最新文献_第5页

A region-dependent e-hailing service pricing strategy for rapid massive evacuation 针对大规模快速疏散的区域性电子叫车服务定价策略

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-11-01 DOI: 10.1016/j.trd.2024.104399

Hang Su , Min Xu , Xiaolei Wang , Xiaoning Zhang

Unpredictable large amount of travel demands often occurs in urban area, and e-hailing services are often used as an important travel modal for mitigating such surge traffic. Effective pricing and scheduling strategies are urgently needed to optimize e-hailing vehicle supply and enhance evacuation efficiency during mass gathering events. Based on the method of Macroscopic Fundamental Diagram (MFD), mathematical models are presented to characterize the time-varying evolution of both e-hailing vehicles and other vehicles within a two-region transport system, and management approaches are also provided to improve the evacuation process. Considering drivers’ repositioning decisions and passengers’ demand dynamics, a region-dependent pricing strategy is developed for rapid massive evacuation. In the numerical examples, it is observed that the region-dependent pricing strategy effectively allocates a more balanced distribution of vacant vehicle supply, despite higher generalized wage for drivers and increased generalized cost for passengers. More importantly, the region-dependent pricing strategy can significantly shorten total evacuation time, and lead to more stable traffic condition.

城市地区经常出现不可预测的大量出行需求，而电子叫车服务通常被用作缓解这种激增交通流量的重要出行方式。在大规模聚集事件中，亟需有效的定价和调度策略来优化网约车车辆供给，提高疏散效率。本文基于宏观基本图（MFD）的方法，提出了数学模型来描述双区域交通系统中电召车辆和其他车辆的时变演化特征，并提供了改善疏散过程的管理方法。考虑到驾驶员的重新定位决策和乘客的需求动态，为快速大规模疏散制定了区域定价策略。从数值示例中可以看出，尽管司机的广义工资较高，乘客的广义成本增加，但与区域相关的定价策略有效地分配了更均衡的空置车辆供应。更重要的是，依赖区域的定价策略可以大大缩短总疏散时间，并带来更稳定的交通状况。

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引用次数: 0

Linking green transportation and technology, and environmental taxes for transport carbon emissions 将绿色交通与技术、交通碳排放环境税联系起来

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-11-01 DOI: 10.1016/j.trd.2024.104450

Mushtaq Ahmad , Zhang Jida , Izhar Ul Haq , Muhammad Tufail , Shah Saud

Climate change and global warming pose severe environmental challenges globally, with transportation and industrialization significantly contributing to CO2 emissions. This study investigates the interplay between green transport initiatives, environmental taxes, and CO2 emissions in energy transition countries from 1990 to 2020. Utilizing the Method of Moments Quantile Regression (MMQR), Fully Modified Ordinary Least Squares (FMOLS), and Feasible Generalized Least Squares (FGLS), the study reveals that environmental taxes (ETax) and green transport (GT) are strongly negatively correlated with CO2 emissions. These results underscore the potential of increasing environmental taxes and advancing green transportation technologies as effective strategies for mitigating environmental degradation. This study highlights that improvements in energy efficiency and renewable energy adoption further contribute to reducing CO2 emissions, while globalization (GI) also plays a role in decreasing emissions. This research adds to the existing literature by providing robust empirical evidence on the effectiveness of green policies and sustainable practices in reducing CO2 emissions, thereby offering policy recommendations for governments to enhance green transportation and promote environmental sustainability in the long term.

气候变化和全球变暖给全球带来了严峻的环境挑战，而交通和工业化则是造成二氧化碳排放的重要因素。本研究探讨了 1990 年至 2020 年能源转型国家的绿色交通措施、环境税和二氧化碳排放之间的相互作用。利用矩量回归法（MMQR）、完全修正普通最小二乘法（FMOLS）和可行广义最小二乘法（FGLS），研究揭示了环境税（ETax）和绿色交通（GT）与二氧化碳排放之间的密切负相关关系。这些结果突出表明，增加环境税和推进绿色交通技术有可能成为缓解环境恶化的有效策略。本研究强调，能源效率的提高和可再生能源的采用进一步促进了二氧化碳排放量的减少，而全球化（GI）也在减少排放量方面发挥了作用。这项研究为现有文献提供了有力的实证证据，证明了绿色政策和可持续实践在减少二氧化碳排放方面的有效性，从而为政府加强绿色交通和促进环境长期可持续发展提供了政策建议。

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引用次数: 0

Assessing port cluster resilience: Integrating hypergraph-based modeling and agent-based simulation 评估港口集群的复原力：基于超图的建模与基于代理的模拟相结合

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-11-01 DOI: 10.1016/j.trd.2024.104459

Lingyue Li , Chunzhu Wei , Jing Liu , Jindao Chen , Hongping Yuan

With increasing global trade and frequent occurrence of disruptive events, the resilience of port clusters has emerged as a critical area of concern. However, studies that focus on the resilience of port clusters considering their complex network structure and operational dynamics remain limited. This study proposes a novel model to assess port cluster resilience by integrating hypergraph-based modeling and agent-based simulation. The model captures the complex relationships among ports and vessels, enabling the dynamic modeling of disruption impacts on port cluster resilience. A case study of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) port cluster demonstrates the model’s applicability and effectiveness. Additionally, the significant impact of typhoon duration on resilience and the potential benefits of vessel port skipping behavior and port cargo handling capacity improvements are analyzed. These findings provide valuable insights for stakeholders in developing effective strategies to enhance the resilience of port clusters and the maritime transportation system.

随着全球贸易的不断增长和破坏性事件的频繁发生，港口集群的恢复能力已成为一个重要的关注领域。然而，考虑到港口集群复杂的网络结构和运营动态，针对港口集群复原力的研究仍然有限。本研究通过整合基于超图的建模和基于代理的模拟，提出了一种评估港口集群复原力的新型模型。该模型捕捉了港口和船舶之间的复杂关系，能够动态模拟干扰对港口集群复原力的影响。对粤港澳大湾区（GBA）港口群的案例研究证明了该模型的适用性和有效性。此外，还分析了台风持续时间对恢复能力的重大影响，以及船舶跳港行为和港口货物装卸能力提高的潜在效益。这些研究结果为利益相关者制定有效战略以提高港口群和海运系统的抗灾能力提供了宝贵的见解。

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引用次数: 0

Electric vehicle adoption in Brazil: Economical analysis and roadmap 巴西采用电动汽车的情况：经济分析和路线图

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-10-31 DOI: 10.1016/j.trd.2024.104483

Laene Oliveira Soares , José Ricardo Sodré , Luis Hernández-Callejo , Ronney Arismel Mancebo Boloy

This study explores the total cost of ownership (TCO) and green premium of electric vehicles (EVs), including plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles (HEVs), battery electric vehicles (BEVs), and conventional vehicles, focusing on top-selling models in Brazil. A roadmap is devised to ease EV integration into the Brazilian market. The TCO analysis reveals that PHEVs powered solely by gasoline cost up to $0.084 per kilometre, while using gasoline in dual-fuel mode with 80% biogas reduces costs to $0.038. HEVs saw costs drop from $0.077 per kilometre to $0.054 with bioethanol in dual-fuel mode with 80% biogas. Conventional vehicles using dual-fuel with 20% bioethanol and 80% biogas achieved cost reductions from $0.106 to $0.081 per kilometre. HEVs and conventional vehicles with biofuels demonstrated annual cost savings of up to 11.2% and 14.1%, respectively, compared to gasoline-only use. BEVs, however, showed significantly lower annual costs, being up to 63.7% and 55% less than gasoline-powered HEVs and PHEVs, respectively, and between 60.9% and 73% less than conventional vehicles. The study also outlines policy interventions and infrastructure development to promote EV adoption in Brazil, enhancing sustainable transportation.

本研究探讨了电动汽车（EV）的总拥有成本（TCO）和绿色溢价，包括插电式混合动力电动汽车（PHEV）、混合动力电动汽车（HEV）、电池电动汽车（BEV）和传统汽车，重点关注巴西的畅销车型。此外，还为电动汽车融入巴西市场制定了路线图。总拥有成本分析表明，仅使用汽油驱动的 PHEV 每公里成本高达 0.084 美元，而在双燃料模式下使用汽油和 80% 的沼气可将成本降至 0.038 美元。在使用生物乙醇和 80% 沼气的双燃料模式下，混合动力汽车的成本从每公里 0.077 美元降至 0.054 美元。使用 20% 生物乙醇和 80% 生物气体双燃料的传统汽车的成本从每公里 0.106 美元降至 0.081 美元。与仅使用汽油相比，使用生物燃料的混合动力汽车和传统汽车的年成本节约率分别高达 11.2% 和 14.1%。然而，生物燃料电动汽车的年成本明显更低，与汽油驱动的混合动力汽车（HEV）和新能源汽车（PHEV）相比，分别降低了 63.7% 和 55%，与传统汽车相比，降低了 60.9% 至 73%。研究还概述了在巴西推广电动汽车的政策干预和基础设施建设，以加强可持续交通。

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引用次数: 0

Analyzing spatiotemporal truck emission pattern using explainable machine learning: A case study in Xi’an, China 利用可解释机器学习分析时空卡车排放模式：中国西安案例研究

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-10-30 DOI: 10.1016/j.trd.2024.104489

Zhipeng Peng , Hao Ji , Said M Easa , Chenzhu Wang , Yonggang Wang , Hengyan Pan

This study investigates the spatial distribution pattern of CO₂ emissions from Heavy duty trucks (HDTs) in Xi’an City across different periods and their influencing factors. Five study periods were initially proposed considering the temporal distribution of emissions and the city’s traffic restriction policy. The study area was divided into 2,839 spatial grids. Then, CO₂ emissions from HDTs were calculated at the spatial grid scale, and variables related to road density, accessibility to freight hubs, POI density, and demographic indicators were also integrated into the spatial grids. Finally, five XGBoost models were constructed using the spatial data from different periods, and the spatial and temporal heterogeneity of each variable’s impact on CO₂ emissions was thoroughly analyzed using the SHAP (SHapley Additive exPlanations) explainer. The results demonstrate that the predictive ability of the XGBoost model surpasses that of the OLS model and the GWR model, providing better insight into the spatiotemporal heterogeneity.

本研究探讨了西安市不同时期重型卡车（HDT）二氧化碳排放的空间分布模式及其影响因素。考虑到排放的时间分布和城市交通限制政策，初步提出了五个研究时段。研究区域被划分为 2839 个空间网格。然后，在空间网格尺度上计算 HDT 的二氧化碳排放量，并将与道路密度、货运枢纽可达性、POI 密度和人口指标相关的变量纳入空间网格。最后，利用不同时期的空间数据构建了五个 XGBoost 模型，并使用 SHAP（SHapley Additive exPlanations）解释器深入分析了各变量对二氧化碳排放影响的时空异质性。结果表明，XGBoost 模型的预测能力超过了 OLS 模型和 GWR 模型，能更好地揭示时空异质性。

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引用次数: 0

Supporting inclusive debate on Advanced Air Mobility: An evaluation 支持关于先进空中机动性的包容性辩论：评估

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-10-29 DOI: 10.1016/j.trd.2024.104471

Angela Smith , Janet E. Dickinson , Taalia Nadeem , Ben Snow , Rama Permana , Tom Cherrett , Jason Drummond

Advanced Air Mobility (AAM) is being progressed, yet evidence suggests low levels of public salience and minimal debate. Efforts to engage the public have been framed around achieving acceptance made with little clarity of the potential impacts and benefits. This paper analyses an approach which sought to overcome low interest and to make technical information accessible to a general audience. The research used virtual reality (VR) to represent AAM technologies in public spaces proximal to where participants lived. During a second phase of research, additional supporting materials (an animation, a short game, and a recorded presentation) were developed to respond to gaps in understanding. The research was undertaken at five sites in England (N = 603). The representativeness of the sample is analysed, and the value of the VR, additional materials, and siting of the research are reviewed. Drawing upon detailed responses to open questions, the extent of meaningful involvement is explored showing how the additional supporting materials increased the depth of understanding amongst participants.

先进空中机动性（AAM）正在取得进展，但有证据表明，公众的关注度不高，讨论也很少。让公众参与的努力一直围绕着实现接受度而展开，对潜在的影响和益处却不甚了解。本文分析了一种旨在克服低兴趣并使普通受众了解技术信息的方法。这项研究利用虚拟现实技术（VR）在参与者居住地附近的公共空间展示人工影响评估技术。在第二阶段的研究中，还开发了额外的辅助材料（动画、小游戏和录制的演示文稿），以弥补理解上的不足。研究在英格兰的五个地点进行（N = 603）。对样本的代表性进行了分析，并对虚拟现实技术、补充材料和研究地点的价值进行了回顾。通过对开放性问题的详细回答，探讨了有意义的参与程度，显示了附加辅助材料如何提高了参与者的理解深度。

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引用次数: 0

Uncovering heterogeneous effects of link-level street environment on e-bike and e-scooter usage 揭示链接级街道环境对电动自行车和电动滑板车使用的异质性影响

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-10-25 DOI: 10.1016/j.trd.2024.104477

Yijia Hu , Mushu Zhao , Zhan Zhao

This study investigates how the street environment influences e-bike and e-scooter flows at the link level, considering their distinct spatial travel patterns. An angle-based spatial autoregressive quantile regression (SAQR) model is developed to analyze fine-scale street environments in Washington, D.C. We observe distinct spatial travel patterns between e-bikes and e-scooters, and e-scooter usage is more concentrated in city centers. Link design and network design have stronger impacts on the usage of e-bike and e-scooter than land use features. However, land use features are more likely to affect the flow of these two modes differently. Specifically, streets with dedicated bike lanes, traffic signals, wider width, higher betweenness centrality, and a higher proportion of entertainment and office land tend to attract more e-bike and e-scooter trips. In addition, bike-friendly facilities, particularly buffered bike lanes, exhibit more pronounced impacts. The findings provide policy implications for nuanced street design guidelines to facilitate electric micromobility usage.

考虑到电动自行车和电动滑板车不同的空间出行模式，本研究调查了街道环境如何在链路层面影响电动自行车和电动滑板车的流量。我们观察到电动自行车和电动滑板车之间不同的空间出行模式，而且电动滑板车的使用更集中在市中心。与土地使用特征相比，线路设计和网络设计对电动自行车和电动摩托车使用的影响更大。然而，土地使用特征更有可能对这两种交通方式的流量产生不同的影响。具体来说，拥有专用自行车道、交通信号灯、较宽的街道、较高的中心度（intervalness centrality）以及较高的娱乐和办公用地比例的街道，往往会吸引更多的电动自行车和电动摩托车出行。此外，自行车友好型设施，尤其是缓冲自行车道，会产生更明显的影响。研究结果为细微的街道设计指导方针提供了政策含义，以促进电动微型交通的使用。

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引用次数: 0

Evaluation of potential electric vehicles load-induced damage on flexible pavements 评估电动汽车负载对柔性路面可能造成的损坏

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-10-24 DOI: 10.1016/j.trd.2024.104475

Mohamad Yaman Fares, Ahmad Albdour, Michele Lanotte

The adoption of Electric Vehicles (EVs), driven by policies like the Zero Emission Vehicle (ZEV) mandate, is rapidly transforming transportation infrastructure. In 2021, over 1.25-million light-duty EVs were registered in the United States, signaling a shift that extends to heavy vehicle categories. This study evaluates the implications of this transition on road networks, focusing on the increased gross weight of EVs compared to traditional Internal Combustion Engine (ICE) vehicles and its impact on flexible pavement structures. The study investigates the deterioration patterns and potential damage to road infrastructures resulting from integrating EVs into the traffic mix, utilizing both the AASHTO 1993 and Mechanistic-Empirical (ME) pavement evaluation methodologies. The analyses reveal a significant acceleration in road degradation, necessitating urgent consideration of EV-induced stresses by transportation authorities. Recommendations for future research and practical strategies for mitigating these impacts are provided to guide policymakers and engineers in adapting to this evolving vehicular landscape.

在零排放汽车 (ZEV) 规定等政策的推动下，电动汽车 (EV) 的采用正在迅速改变交通基础设施。2021 年，在美国注册的轻型电动汽车超过 125 万辆，这标志着向重型汽车类别的转变。本研究评估了这一转变对道路网络的影响，重点关注与传统内燃机（ICE）汽车相比，电动汽车总重量的增加及其对柔性路面结构的影响。研究采用 AASHTO 1993 和力学-经验（ME）路面评估方法，调查了电动汽车融入交通组合后对道路基础设施造成的损坏模式和潜在损害。分析结果表明，道路退化速度明显加快，因此交通管理部门有必要紧急考虑电动汽车引起的压力。本文还提出了未来研究建议和减轻这些影响的实用策略，以指导政策制定者和工程师适应不断变化的车辆环境。

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引用次数: 0

Assessing energy consumption in scalable semi-autonomous destination-based E-platoons: A multiplayer approach 评估基于目的地的可扩展半自主电子车队的能耗：多玩家方法

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-10-24 DOI: 10.1016/j.trd.2024.104464

Aso Validi, Yuzhou Liu, Cristina Olaverri-Monreal

Recent developments in connected and automated vehicle technologies have opened up new possibilities but also posed enduring challenges. One of the primary challenges is the efficient coordination of vehicles in urban environments, specifically through scalable and destination-based platooning. While considerable research has focused on platooning with a limited number of vehicles demonstrating seamless connectivity and coordination on highways, there remains a significant gap in understanding and implementing scalable platoons in more dynamic urban settings. This paper bridges these gaps by developing a novel extension to the 3DCoAutosim simulation platform. Our model introduces ’Scalable Semi-autonomous Destination-based Multiplayer E-Platoons’, accommodating different automation levels and simulation characteristics of vehicles in five distinct platoons. We employed seven electric vehicles to create these platoons, each consisting of an autonomous lead vehicle, followers that are either autonomous or semi-autonomous (accompanied by drivers), customised according to the specific requirements of each platoon. Utilising Time Series Analysis, Multiple Linear Regression and a comprehensive, comparative scenario-based analysis, we assessed and validated our developed model’s impact on battery energy consumption under varying road slopes and car-following models. Our assessment employs real-world trip data from Upper Austria, with results indicating a potential reduction in total battery energy consumption when operating in platoon mode.

互联和自动驾驶汽车技术的最新发展带来了新的可能性，但也带来了持久的挑战。其中一个主要挑战是如何在城市环境中有效协调车辆，特别是通过可扩展的、基于目的地的排队。虽然大量研究都集中在有限数量的车辆在高速公路上展示无缝连接和协调的排车方面，但在更动态的城市环境中理解和实施可扩展排车方面仍存在巨大差距。本文通过对 3DCoAutosim 仿真平台进行新颖的扩展，弥补了这些差距。我们的模型引入了 "可扩展的基于目的地的半自主多人电子车队"，在五个不同的车队中适应不同的自动化水平和车辆模拟特性。我们使用了七辆电动车来创建这些排，每辆车由一辆自动驾驶的领头车、自动驾驶或半自动驾驶（由驾驶员陪同）的跟从车组成，并根据每个排的具体要求进行定制。利用时间序列分析、多元线性回归和基于场景的综合比较分析，我们评估并验证了所开发的模型在不同道路坡度和跟车模式下对电池能耗的影响。我们的评估采用了上奥地利州的实际行程数据，结果表明在排车模式下运行时，电池总能耗可能会减少。

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引用次数: 0

ChatEV: Predicting electric vehicle charging demand as natural language processing ChatEV：通过自然语言处理预测电动汽车充电需求

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2024-10-23 DOI: 10.1016/j.trd.2024.104470

Haohao Qu , Han Li , Linlin You , Rui Zhu , Jinyue Yan , Paolo Santi , Carlo Ratti , Chau Yuen

The increasing popularity of electric vehicles (EVs) in recent times has introduced considerable load conditions for urban power grids and transportation systems, which highlights the importance of accurately predicting charging demand to enhance charging efficiency. However, current forecasting methods still face challenges in effectively aligning diverse data and generating accurate predictions that can be applied to unseen scenarios. To overcome the challenges, this work introduces a novel perspective: employing large language models (LLMs) as EV charging demand predictors. First, we reformulate the prediction task into a text-to-text format, enabling seamless and effective alignment of various features within a unified language semantic space. Subsequently, we fine-tune a LLM using a meta-learning framework to adapt it specifically for EV charging prediction. Through comprehensive evaluations, it has been demonstrated that the proposed model, ChatEV, achieves outstanding performance in EV charging demand forecasting, particularly in scenarios with limited data.

近来，电动汽车（EV）的日益普及为城市电网和交通系统带来了巨大的负载条件，这凸显了准确预测充电需求以提高充电效率的重要性。然而，目前的预测方法在有效整合各种数据并生成可应用于未知场景的准确预测方面仍面临挑战。为了克服这些挑战，这项工作引入了一个新的视角：采用大型语言模型（LLM）作为电动汽车充电需求预测工具。首先，我们将预测任务重新表述为文本到文本格式，从而在统一的语言语义空间内无缝、有效地调整各种特征。随后，我们利用元学习框架对 LLM 进行微调，使其专门用于电动汽车充电预测。通过综合评估，证明了所提出的模型 ChatEV 在电动汽车充电需求预测方面，尤其是在数据有限的情况下，取得了出色的性能。

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引用次数: 0