Transportation Research Part D-transport and Environment最新文献_第4页

Understanding electric vehicle charging behavior: A multidisciplinary review and conceptual framework 理解电动汽车充电行为：多学科回顾和概念框架

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-23 DOI: 10.1016/j.trd.2026.105227

Farnoosh Roozkhosh, X. Angela Yao

EV charging behavior refers to the observable patterns and underlying decision processes through which drivers decide when, where, how often, and how much to charge, and which charging technologies to use. Despite rapid growth in empirical research, the term is operationalized inconsistently across disciplines (e.g., as load profiles, session dynamics, location choice, or socio-demographic differences), making evidence difficult to compare and limiting its transferability to infrastructure planning, grid management, and equity assessment. In this review, we synthesize the interdisciplinary literature on EV users’ charging behavior and propose a unified, behavior-centered framework that organizes studies into four complementary lenses with explicit units of analysis and boundaries: (1) spatiotemporal-based (when and where charging occurs), (2) EV-based (vehicle state and technical constraints), (3) user-based (heterogeneity in users and charging access), and (4) session-based (within-event dynamics). For each lens, we summarize common data types, methods, and application domains, highlight overlaps, and identify opportunities for integration across datasets and modeling traditions.

电动汽车充电行为是指可观察到的模式和潜在的决策过程，驾驶员通过这些决策过程决定何时、何地、多久、充电多少，以及使用哪种充电技术。尽管实证研究快速增长，但该术语在不同学科（例如，负载概况，会话动态，位置选择或社会人口差异）中的操作不一致，使得证据难以比较，并限制了其在基础设施规划，电网管理和公平评估中的可转移性。在这篇综述中，我们综合了关于电动汽车用户充电行为的跨学科文献，提出了一个统一的、以行为为中心的框架，将研究分为四个互补的视角，具有明确的分析单元和边界：(1)基于时空的（充电发生的时间和地点），(2)基于电动汽车的（车辆状态和技术约束），(3)基于用户的（用户和充电接入的异质性），以及(4)基于会话的（事件内动力学）。对于每个镜头，我们总结了常见的数据类型、方法和应用领域，突出了重叠部分，并确定了跨数据集和建模传统集成的机会。

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引用次数: 0

Causal effects of typhoons on mobility perturbations: environment and individual heterogeneity 台风对移动扰动的因果影响：环境和个体异质性

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-23 DOI: 10.1016/j.trd.2026.105234

Tianhua Lu , Wenbo Guo , Wenjia Zhang , Wen Zhang , Caicheng Niu

Understanding causal factors of typhoon-induced mobility disruption is crucial for urban resilience and protecting vulnerable groups. While studies link extreme weather events (EWEs) to mobility, causal evidence on policy intervention effects is lacking. This study applies an Interrupted Time Series (ITS) design to mobile phone data from Shenzhen, China, to quantify the causal effects of the extreme precipitation event Typhoon Haikui (September 7–8, 2023) on travel distance, while also evaluating heterogeneity across built-environment and individual attributes. Findings reveal government warnings and adverse weather were primary drivers, reducing travel by 32% and 34% respectively. Areas with higher land use mix and intersection density showed greater travel reductions, while retail and subway density mitigated these effects. Middle-aged individuals, women, and high-priced housing residents experienced significant perturbations. These insights identify vulnerable populations and low-resilience areas, informing targeted disaster policies and investments in resilient land use, pedestrian networks, and accessible subway stations.

了解台风导致交通中断的原因对城市恢复力和保护弱势群体至关重要。虽然研究将极端天气事件（ewe）与流动性联系起来，但缺乏关于政策干预效果的因果证据。本研究采用中断时间序列（ITS）设计对中国深圳的手机数据进行分析，量化极端降水事件“海葵”（2023年9月7-8日）对出行距离的因果影响，同时评估建筑环境和个体属性之间的异质性。调查结果显示，政府警告和恶劣天气是主要原因，分别减少了32%和34%的旅行。土地利用组合和十字路口密度较高的地区显示出更大的出行减少，而零售和地铁密度则缓解了这些影响。中年个体、女性和高价住房居民经历了显著的扰动。这些见解可以识别弱势群体和低恢复力地区，为有针对性的灾害政策和弹性土地使用、行人网络和无障碍地铁站的投资提供信息。

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引用次数: 0

Quantifying environmental impacts of cold chain interruptions using coupled CFD and LCA 利用耦合CFD和LCA量化冷链中断对环境的影响

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-22 DOI: 10.1016/j.trd.2026.105230

Teng Meng , Yue Huang , Anthony Whiteing , Yinpu Wang , Qidong Han

Cold chain interruptions (CCIs) can alter energy use and emissions in cold chain logistics (FCCL), yet their impacts are often overlooked in life cycle assessment (LCA). This study integrates computational fluid dynamics (CFD) with LCA to quantify CCI-related impacts, through a gate-to-gate case study of Zigui navel oranges from precooling to cold storage at destination. CFD reconstructs temperature histories, which are converted to stage-specific refrigeration energy usage and fed into LCA to quantify environmental burdens. Two types of CCIs were evaluated: refrigeration pauses have minimal effects, while ambient exposures, especially after precooling, increase global warming potential (GWP) by up to 5.94%. Overall, refrigerated transport contributes over 85% of total GWP, with a distance–GWP slope of 0.0014 kg CO₂-eq/km. Replacing diesel with B5 biodiesel (5% fatty acid methyl esters) reduces GWP by 3.95%. This CFD–LCA framework enables more accurate CCI impact assessments, supporting the design of sustainable FCCL systems.

冷链中断（cci）可以改变冷链物流（FCCL）的能源使用和排放，但其影响在生命周期评估（LCA）中往往被忽视。本研究将计算流体力学（CFD）与LCA相结合，通过对秭归脐橙从预冷到目的地冷藏的门到门的案例研究，量化cci相关的影响。CFD重建温度历史，将其转换为特定阶段的制冷能量使用，并输入LCA以量化环境负担。评估了两种类型的cci：制冷暂停影响最小，而环境暴露，特别是预冷后，可使全球变暖潜能值（GWP）增加5.94%。总体而言，冷藏运输对全球变暖潜能值的贡献超过85%，距离-全球变暖潜能值斜率为0.0014 kg CO2-eq/km。用B5生物柴油（5%脂肪酸甲酯）代替柴油可减少3.95%的全球升温潜能值。这种CFD-LCA框架能够更准确地评估CCI影响，支持可持续FCCL系统的设计。

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引用次数: 0

Shared electric scooter energy consumption modeling and influencing factor analysis 共享电动滑板车能耗建模及影响因素分析

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-22 DOI: 10.1016/j.trd.2025.105205

Yuqiu Yuan , Lei Zhu

The convenience and sustainability of shared electric scooters (e-scooters) position them as an emerging and popular form of micromobility. However, their environmental and energy benefits are still a matter of debate. A reliable and accurate estimation of e-scooter energy consumption (i.e., battery depletion) is required to evaluate e-scooter energy and environmental impacts. The shared e-scooter data in the city of Charlotte, North Carolina, provides an opportunity to explore potential influencing factors and model e-scooter energy consumption. This study developed an XGBoost-based e-scooter energy consumption model that captures non-linear relationships among influencing factors and quantifies their contributions in supporting modeling under varying data availability conditions. The proposed e-scooter energy classification model achieves an overall accuracy of up to 73.73%. It is found that Trip Distance, Trip Duration, Grade, Start Battery Percentage, Temperature and Standard Deviation of Speed are the most important features. The model accuracy under different trip distance ranges and with different descriptive variables is evaluated.

共享电动滑板车（e-scooters）的便利性和可持续性使其成为一种新兴的、受欢迎的微型交通工具。然而，它们的环境和能源效益仍然存在争议。为了评估电动滑板车对能源和环境的影响，需要对电动滑板车的能量消耗（即电池耗尽）进行可靠和准确的估计。北卡罗来纳州夏洛特市共享的电动滑板车数据为探索潜在的影响因素和模拟电动滑板车的能耗提供了机会。本研究开发了一个基于xgboost的电动滑板车能耗模型，该模型捕捉了影响因素之间的非线性关系，并在不同数据可用性条件下量化了它们对支持建模的贡献。所提出的电动滑板车能量分类模型总体准确率达到73.73%。发现行程距离、行程持续时间、等级、启动电池百分比、温度和速度标准差是最重要的特征。对不同行程距离范围和不同描述变量下的模型精度进行了评价。

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引用次数: 0

A double-filter driving cycle generation framework with dynamometer testing and analysis 一种双滤波器驱动循环生成框架，并进行了测功机测试和分析

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-20 DOI: 10.1016/j.trd.2026.105231

Nan Xu , Qiao Liu , Chengyin Yuan , Yongtao Yang , Yan Kong , Yifan Jia , Linhao Li , Jincheng Li

Standard driving cycles is the basis to obtain the vehicle type-approval energy consumption. However, for users, there is a gap between the type-approval results and their experiences. For manufacturers, limited number of test cycles cause sub-optimization related issues during the vehicle design and development; for testing organizations, deterministic test cycles lead to the risk of cheating in testing. Therefore, a novel double-filter method is proposed to generate multiple stochastic driving cycles that are energy consumption comparable. Using user data as reference, chassis dynamometer tests were designed for validation of the energy consistency. Results show that the maximum deviation from the user was 2.144%, and the minimum was only 0.465%. The method proposed enables customized families of test cycles, overcoming the limitations of deterministic, finite cycles, which contribute to vehicle economy optimization and provide a dependable foundation for energy consumption estimation for city transportation systems and related policy development.

标准行驶工况是获得整车型式认可能耗的依据。然而，对于用户来说，类型批准结果与他们的体验之间存在差距。对于制造商来说，在车辆设计和开发过程中，有限的测试周期导致了与次优化相关的问题；对于测试机构来说，确定性的测试周期会导致测试作弊的风险。为此，提出了一种新的双滤波方法来生成多个能耗可比较的随机驱动循环。以用户数据为参考，设计了底盘测功机试验，验证了能量一致性。结果表明，与用户的最大偏差为2.144%，最小偏差仅为0.465%。该方法克服了确定性、有限循环的局限性，实现了测试循环的定制化，有利于车辆经济性优化，为城市交通系统的能耗估算和相关政策制定提供了可靠的依据。

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引用次数: 0

When flexibility beats fixed routes: Quantifying microtransit efficiency-emission trade-offs using AMOID 当灵活性胜过固定路线：使用AMOID量化微交通效率-排放权衡

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-20 DOI: 10.1016/j.trd.2026.105229

Jin-Ming Yang , Wei Zhai , Hong-Wei Wang , Xiao-Fan Wei , Hong-Di He , Zhong-Ren Peng

Microtransit is emerging as a key solution for short-distance travel, yet the efficiency-environmental trade-offs between demand-responsive and fixed-route systems remain unclear. We introduce AMOID, a data-driven model leveraging individual travel trajectories to automate hybrid system planning and evaluation. Departing from aggregate data methods, AMOID tailors solutions to individual demand, considering multi-modal collaboration. In Tampa, Florida, demand-responsive microtransit achieves 229% higher operational efficiency, 183% more ridership, 40% lower greenhouse gas emissions than fixed-route systems. However, fixed-route systems dominate when demand exceeds 800 trips/(day·mile²). Operational scale dynamically shifts these thresholds: reducing the fleet by half lowers the efficiency crossover threshold for fixed-route dominance by 40–46%; conversely, expanding the service area by 135% decreases the threshold by 60%. These findings reveal how demand and operational scale mediate modal efficiency, providing insights for planners to optimize microtransit deployment. AMOID bridges the gap between theoretical models and practical decision-making, enabling sustainable urban mobility.

微交通正在成为短途旅行的关键解决方案，但需求响应系统和固定路线系统之间的效率和环境权衡仍不清楚。我们介绍了AMOID，这是一个数据驱动的模型，利用个人旅行轨迹来自动化混合系统的规划和评估。AMOID从聚合数据方法出发，根据个人需求量身定制解决方案，考虑多模式协作。在佛罗里达州坦帕市，需求响应型微交通系统的运营效率比固定线路系统提高了229%，客流量增加了183%，温室气体排放量减少了40%。然而，当需求超过800次/天·英里2时，固定路线系统占主导地位。运营规模动态地改变了这些阈值：减少一半的机队会使固定航线优势的效率交叉阈值降低40-46%；相反，如果业务面积扩大135%，则阈值降低60%。这些发现揭示了需求和运营规模如何调节模式效率，为规划人员优化微交通部署提供了见解。AMOID弥合了理论模型和实际决策之间的差距，实现了可持续的城市交通。

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引用次数: 0

The green gridlock: Projecting the unintended wildfire evacuation risks of EV adoption 绿色交通堵塞：预测电动汽车采用的意外野火疏散风险

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-20 DOI: 10.1016/j.trd.2026.105219

Khondhaker Al Momin, Arif Mohaimin Sadri, Kanthasamy K. Muraleetharan

The rapid adoption of electric vehicles (EVs), while crucial for climate goals, introduces complex challenges for emergency management. This study addresses the urgent, yet under-researched risk of wildfire evacuations in EV-dependent communities, whose mobility is tightly coupled with a vulnerable electrical grid. We develop a novel geospatial framework grounded in the Vulnerability-Exposure-Sensitivity model and operationalized through a Community Preparedness Index that integrates socioeconomic, demographic, mobility, and infrastructural characteristics. Hotspot analysis identifies spatial clusters of wildfire exposure, EV sensitivity, and community preparedness, enabling classification of evacuation risk profiles driven by transportation system dependence on electrified mobility. A Gaussian Process Regression informed S-curve forecasting approach estimates when communities are likely to reach critical risk levels as EV adoption increases. Results show significant spatial disparities, providing evidence to strategically deploy charging resources, grid hardening, and evacuation focused planning. The framework supports proactive, data-informed planning for resilient electrified transportation systems in wildfire-prone regions.

电动汽车的迅速普及虽然对气候目标至关重要，但也给应急管理带来了复杂的挑战。本研究解决了电动汽车依赖社区的紧急野火疏散风险，但研究不足，这些社区的机动性与脆弱的电网紧密相连。我们在脆弱性-暴露-敏感性模型的基础上开发了一个新的地理空间框架，并通过整合社会经济、人口、流动性和基础设施特征的社区准备指数进行操作。热点分析确定了野火暴露、电动汽车敏感性和社区准备的空间集群，实现了由电气化交通运输系统驱动的疏散风险概况的分类。高斯过程回归通知s曲线预测方法估计随着电动汽车采用率的增加，社区何时可能达到临界风险水平。研究结果显示了显著的空间差异，为战略部署充电资源、强化电网和集中疏散规划提供了依据。该框架支持在野火易发地区对弹性电气化运输系统进行前瞻性、数据知情的规划。

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引用次数: 0

Will pickup-truck buyers go electric? 小货车买家会选择电动车吗？

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-17 DOI: 10.1016/j.trd.2025.105170

Connor R. Forsythe , Kenneth T. Gillingham , Jeremy J. Michalek , Kate S. Whitefoot

Pickup trucks comprise the last U.S. light-duty vehicle segment to produce modern electric vehicle offerings, and they face unique engineering, economic and consumer acceptance challenges. To estimate adoption potential under engineering and economic projections, we conduct a discrete choice experiment with 534 U.S. pickup-truck buyers. We find a large majority (74%) of pickup truck buyers belong to latent classes that prefer or are indifferent to electric trucks when they offer comparable price, operating cost, range, towing and payload capacity with fast-charge capabilities. However, 26% are strongly opposed under any plausible vehicle technology trajectory. Price and range are the vehicle attributes that pose the largest barriers to increased adoption for most pickup truck buyers today. If electric pickup trucks achieve National Academies’ 2030 cost and range projections and are as widely available as conventional pickup trucks, our simulations suggest the majority of new U.S. pickup truck choices could be electric.

皮卡是美国最后一个生产现代电动汽车的轻型汽车领域，它们面临着独特的工程、经济和消费者接受方面的挑战。为了估计工程和经济预测下的采用潜力，我们对534 U.S.进行了离散选择实验皮卡的买家。我们发现，绝大多数（74%）皮卡买家属于潜在阶层，当电动卡车的价格、运营成本、续航里程、牵引和有效载荷能力与快速充电能力相当时，他们更喜欢或对电动卡车漠不关心。然而，26%的人强烈反对在任何可行的车辆技术轨迹下。价格和续航里程是目前阻碍大多数皮卡购买者购买皮卡的最大障碍。如果电动皮卡达到美国国家科学院2030年的成本和续航里程预测，并像传统皮卡一样广泛使用，我们的模拟表明，美国大多数新皮卡都可能是电动的。

引用次数: 0

Electrification of a bus system in a hilly city considering gradient impacts 考虑坡度影响的丘陵城市公交系统电气化研究

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-16 DOI: 10.1016/j.trd.2026.105223

Zili Tian , Jiaxing Liu , Shiqi Wang , Xiong Yang , Zhenhan Peng , Anthony Chen , Chengxiang Zhuge

Electrifying a bus system in hilly cities is challenging, as the road gradient plays a significant role in vehicular energy consumption, influencing the configuration of bus fleet and the layout of charging facilities. In response, this study developed a data-driven large-scale simulation optimization model that explicitly considers the impact of road gradients, aiming to determine the optimal electric bus fleet and charging infrastructure deployment, with Hong Kong (a typical hilly city) as the study area. Results indicated that neglecting gradient characteristics would underestimate the system cost and life-cycle emissions. Meanwhile, when accounting for gradient impacts, the required number of charging stations and fleet size increased by 27% and 3%, respectively. Moreover, the spatial distribution of charging stations could be greatly influenced. Further scenario analysis indicated that charging speed and infrastructure costs are influential in shaping bus electrification strategies. The outcomes can be helpful for bus electrification in hilly cities.

在丘陵城市实现公交系统的电气化是一项挑战，因为道路坡度对车辆能耗有重要影响，影响着公交车队的配置和充电设施的布局。为此，本研究以典型丘陵城市香港为研究区域，建立了一个明确考虑道路坡度影响的数据驱动的大规模仿真优化模型，旨在确定最优的电动巴士车队和充电基础设施部署。结果表明，忽略梯度特性会低估系统成本和全生命周期排放。同时，考虑梯度影响后，充电站数量和车队规模分别增加了27%和3%。此外，充电站的空间分布也会受到很大的影响。进一步的情景分析表明，充电速度和基础设施成本对公共汽车电气化战略的形成具有重要影响。研究结果对丘陵城市公交车电气化有一定的借鉴意义。

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引用次数: 0

Perceived accessibility across activity types and transport modes 感知跨活动类型和运输模式的可达性

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-16 DOI: 10.1016/j.trd.2026.105225

Willy Kriswardhana , Domokos Esztergár-Kiss

Recently, perceived accessibility has been proposed as a supplementary measure to traditional accessibility indicators to support more comprehensive policies for sustainable travel behavior. Previous studies explore perceived accessibility across trip purposes and conventional transport modes but overlook shared micro-mobility with such factors as walkability and bikeability. The current study addresses these gaps by examining how perceived walkability, bikeability, and access to shared transport modes influence perceived accessibility, which are closely related to the built environment. A web-panel survey is conducted, and the data are analyzed by using ordered logit models. The results highlight the influence of varied parameters, where socio-demographic factors significantly affect the perceived accessibility of public transport and cars, while mode-specific perceptions play a greater role in the case of active and shared mobility modes. The findings underline the importance of including and analyzing individuals’ perceptions of existing infrastructures to support a transition toward green travel behavior.

最近，可达性被提出作为传统可达性指标的补充措施，以支持更全面的可持续旅游行为政策。以往的研究探讨了出行目的和传统交通方式的感知可达性，但忽视了步行性和骑自行车性等共享微移动性因素。当前的研究通过研究感知步行性、骑自行车性和共享交通方式如何影响感知可达性来解决这些差距，这与建筑环境密切相关。通过网络面板调查，采用有序logit模型对数据进行分析。结果强调了各种参数的影响，其中社会人口因素显著影响公共交通和汽车的可达性，而特定模式的感知在主动和共享移动模式的情况下发挥更大的作用。研究结果强调了包括和分析个人对现有基础设施的看法对于支持向绿色出行行为过渡的重要性。

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引用次数: 0