Transportation Research Part D-transport and Environment最新文献

英文中文

The impact of research on transportation and the environment 研究对交通和环境的影响

IF 7.6 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-28 DOI: 10.1016/j.trd.2026.105244

Robert B. Noland

引用次数: 0

Co-hub charging planning for electric bus and paratransit using fuzzy multi-objective optimization 基于模糊多目标优化的电动客车与辅助交通枢纽充电规划

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-27 DOI: 10.1016/j.trd.2026.105233

Bingkun Chen , Zhuo Chen , Xiaoyue Cathy Liu , Ran Wei , Arman Malekloo

Paratransit, a demand-responsive transit mode serving passengers with mobility challenges, is increasingly electrified to enhance urban transportation sustainability. However, high investments required for dedicated charging infrastructure and the scarcity of public charging resources remain significant hurdles to large-scale deployment. This study investigates a shared charging scheme that integrates paratransit electric vehicles (EVs) into existing electric bus (EB) charging networks. A fuzzy multi-objective optimization framework is proposed to identify optimal charging co-hub locations and EV assignments by balancing supply–demand dynamics. The framework incorporates two-step floating catchment area (2SFCA) and inverted 2SFCA (i2SFCA) methods to formulate objectives and constraints for EB and paratransit systems, respectively. Through fuzzy programming, trade-offs among supply–demand dynamics are resolved, yielding efficient shared-charging plans. The framework is validated with Utah Transit Authority data, demonstrating improved charging accessibility and operational efficiency while offering actionable insights for transit agencies in planning shared charging schemes among various public transport modes.

辅助交通（parattransit）是一种需求响应型交通模式，为出行困难的乘客提供服务，它越来越电气化，以提高城市交通的可持续性。然而，专用充电基础设施的高投资和公共充电资源的稀缺仍然是大规模部署的重大障碍。本研究探讨了一种将辅助交通电动汽车（ev）整合到现有电动巴士（EB）充电网络中的共享充电方案。提出了一种模糊多目标优化框架，通过平衡供需动态来确定最优充电中心位置和电动汽车分配。该框架采用两步浮动集水区（2SFCA）和倒2SFCA （i2SFCA）方法，分别为EB和辅助交通系统制定目标和约束。通过模糊规划，解决了供需动态之间的权衡，得到了高效的共享充电方案。该框架与犹他州交通管理局的数据进行了验证，展示了改进的收费可及性和运营效率，同时为交通机构规划各种公共交通模式之间的共享收费方案提供了可操作的见解。

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引用次数: 0

Profit-aware battery swapping station energy scheduling via hybrid hierarchical deep reinforcement learning 基于混合层次深度强化学习的利润感知换电池站能量调度

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-24 DOI: 10.1016/j.trd.2026.105236

Quanxu Zhou, Mengying Huang, Haoyu Tang, Jiapeng Cheng, Ji Wu

As urban transportation electrification advances, range anxiety has become a key concern for electric vehicles (EVs). Battery swapping stations (BSS) offer a fast and efficient solution, yet traditional scheduling methods struggle to balance profitability with operational risk in dynamic environments. To address this, we propose a data-driven optimization method. First, historical data is used to derive optimal operational decisions, and an EV battery swapping demand forecasting model is built. Based on the forecasted demand and historical strategies, a long short-term memory network predicts the BSS’s overall charging and discharging power. A double deep Q-network is then employed to allocate this power to individual batteries, ensuring timely swaps. Validation using real operational data from Chengdu, China, shows the proposed method effectively meets battery swapping demand, enhances scheduling efficiency and station profitability, and reduces peak loads and power fluctuations, demonstrating the potential for practical application in managing smart EV infrastructure.

随着城市交通电气化的推进，里程焦虑已成为电动汽车（ev）的一个关键问题。电池交换站（BSS）提供了一种快速高效的解决方案，但传统的调度方法难以在动态环境下平衡盈利能力和运行风险。为了解决这个问题，我们提出了一种数据驱动的优化方法。首先，利用历史数据推导最优运行决策，建立电动汽车换电池需求预测模型；基于预测需求和历史策略，建立了一个长短期记忆网络来预测BSS的整体充放电功率。然后采用双深q网络将该功率分配给单个电池，确保及时交换。利用中国成都的实际运行数据进行验证，表明该方法有效满足电池交换需求，提高调度效率和充电站盈利能力，降低峰值负荷和功率波动，展示了在智能电动汽车基础设施管理中的实际应用潜力。

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引用次数: 0

Road and eco-corridor conflict mitigation through multi-species wildlife crossings around national park 通过国家公园周围的多物种野生动物通道缓解道路和生态走廊的冲突

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-24 DOI: 10.1016/j.trd.2026.105235

Yuting Peng , Hongwei Zhang , Gaoru Zhu , Xing Yang , Xueyan Zhao , Huaping Liang

Road network expansion is a key factor driving fragmentation of wildlife habitats and threatening the biodiversity of national parks. Ecological corridors identification and wildlife crossing site selection based on MaxEnt and MCR model are an innovative pathway to coordinate the conflict. Taking Hainan Tropical Rainforest National Park and its circle road as a case, 145 ecological habitat sources of terrestrial, arboreal and amphibious reptile animals were identified, 298 ecological corridors were simulated using Linkage Mapper, and 585 conflict points between road and ecological corridor are identified with verification. Based on distance thresholds and species-specific behaviors, 274 wildlife crossing sites of terrestrial, arboreal and amphibian crossing were laid out along road with 1.7 km spacing, and 4 kind of wildlife crossing were designed according to animal habits. This study provides a theoretical framework for the combination of transportation network with ecological protection with wildlife crossings to improve the biodiversity of nature reserves.

道路网络的扩张是导致野生动物栖息地破碎化和威胁国家公园生物多样性的关键因素。基于MaxEnt和MCR模型的生态廊道识别和野生动物过境点选择是协调冲突的创新途径。以海南热带雨林国家公园及其环行公路为例，确定了145种陆生、树生和两栖爬行动物的生态栖息地来源，利用Linkage Mapper对298条生态廊道进行了模拟，识别并验证了585条道路与生态廊道的冲突点。基于距离阈值和种特异行为，沿道路布置了陆生、树栖和两栖类动物穿越点274个，间隔1.7 km，并根据动物习性设计了4种野生动物穿越点。本研究为交通网络与生态保护、野生动物通道相结合，提高自然保护区生物多样性提供了理论框架。

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引用次数: 0

Electric vehicle manufacturers’ operation of charging stations: Higher range, greater benefits 电动汽车厂商运营充电站：里程越长，效益越大

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-24 DOI: 10.1016/j.trd.2026.105232

Ruolin Yao , Shuai Ling , Qing Wang , Shiquan Zhong

To alleviate range anxiety among electric vehicle (EV) users, some EV manufacturers have begun operating charging stations in public areas, offering charging services to vehicle owners. Based on data from the Chinese EV market, we investigate how the strategy of operating charging stations influences demand for manufacturers’ own-brand EVs and examine its interaction with EV range, as well as the moderating effect of public charging infrastructure. Specifically, we integrate the strategy of operating charging stations as a model-specific charging service attribute, measure it using the scale of the charging stations, and incorporate it into a structural model. Our results indicate that this strategy enhances consumers’ willingness to purchase, although it increases their price sensitivity. Moreover, this willingness to purchase increases with EV range but decreases as public charging infrastructure improves. These findings offer valuable insights for the collaborative development of the EV and charging station industries.

为了缓解电动汽车用户的里程焦虑，一些电动汽车制造商开始在公共场所开设充电站，为车主提供充电服务。基于中国电动汽车市场的数据，我们研究了充电站运营策略如何影响制造商对自有品牌电动汽车的需求，并考察了充电站运营策略与电动汽车续航里程的交互作用，以及公共充电基础设施的调节作用。具体而言，我们将充电站运营策略作为一种特定于模型的充电服务属性进行整合，利用充电站的规模对其进行度量，并将其纳入结构模型。我们的研究结果表明，这种策略增强了消费者的购买意愿，尽管它增加了他们的价格敏感性。此外，这种购买意愿随着电动汽车续航里程的增加而增加，但随着公共充电基础设施的改善而降低。这些发现为电动汽车和充电站产业的协同发展提供了有价值的见解。

引用次数: 0

Sound event detection for modified-exhaust vehicles in urban environment 城市环境下改进型排气车辆声事件检测

IF 7.7 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment

Pub Date : 2026-01-24 DOI: 10.1016/j.trd.2026.105241

Zirun Wang, Huasa Zhu, Chuanqi Ma, Zhaojie Lu, Siqing Long, Yunjie Zhang, Ming Cai

Vehicles with illegally modified exhaust systems are a significant source of urban noise and air pollution. This study employs a Sound Event Detection (SED) framework for their automated identification. To address the lack of public data, we generated a dataset with Scaper library, embedding foreground events into authentic background recordings. We employed an SED Transformer and compared six backbones, with the Multi-Scale Residual Network (MSResNet) achieving the best performance. The model achieved an event-based F1-score of 0.7277 on the validation set and 0.6629 in the field test. A Shapley Additive Explanations (SHAP) analysis confirmed the model’s focus on meaningful acoustic features like acceleration harmonics and afterfire transients, while also revealing a temporal bias from the synthetic data. Analysis of computational performance and an event-covered localization error metric validated deployment feasibility. This work presents an end-to-end SED framework for automated urban noise enforcement, supporting data-driven policy beyond conventional classification.

非法改装排气系统的车辆是城市噪音和空气污染的重要来源。本研究采用声事件检测（SED）框架对其进行自动识别。为了解决公共数据的缺乏，我们使用Scaper库生成了一个数据集，将前景事件嵌入到真实的背景记录中。我们采用了一个SED变压器，并比较了六个主干网，其中多尺度残余网络（MSResNet）获得了最佳性能。该模型在验证集上的基于事件的f1得分为0.7277，在现场测试中为0.6629。Shapley加性解释（SHAP）分析证实了该模型对加速谐波和火灾后瞬态等有意义的声学特征的关注，同时也揭示了合成数据的时间偏差。计算性能分析和事件覆盖的定位误差度量验证了部署的可行性。这项工作为自动化城市噪声执法提供了一个端到端的SED框架，支持超越传统分类的数据驱动政策。

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引用次数: 0

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

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