International Journal of Transportation Science and Technology最新文献_第2页

Who is more willing to use shared autonomous vehicles in first-mile-last-mile? A heterogeneity study on carbon incentive policy from China 谁更愿意在“第一英里-最后一英里”中使用共享自动驾驶汽车？中国碳激励政策的异质性研究

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.11.008

Chenjing Bi , Ye Li , Dominique Gruyer , Meiting Tu

Encouraging and motivating travelers to opt for more efficient and low-carbon last-mile transportation options is a crucial strategy for increasing the share of public transportation. This study aims to understand travelers’ preferences for the new travel mode combination of “shared autonomous (SAVs) + subway” and to explore effective incentive policies to encourage heterogeneous population with diverse demographics to adopt this mode. Grounded in social cognitive theory (SCT) the study establishes a structural equation model (SEM) encompassing four latent variables: low-carbon knowledge, low-carbon habits influenced by policy incentives, external environmental factors, and low-carbon travel intention, to analyze the factors influencing individual transportation mode choice. Prospect theory is proposed to calculate prospect values rather than utility values, and a discrete choice model is constructed to estimate the risk preference coefficients of various traveler types under different incentive measures, facilitating a comparison of the effectiveness of these incentives. The findings indicate that residents of mega-cities and low-income groups are more responsive to policy incentives and more inclined to choose the combined transportation mode. In mega-cities, travelers show a higher preference for public transportation recharge rewards, whereas cash rewards are more attractive to travelers in second-tier cities and low-income groups. High-income groups exhibit a stronger preference for commodity shopping vouchers. Incorporating these insights into the incentive measures of decarbonization platforms will enhance the promotion and adoption of the combined transportation mode.

鼓励和激励旅行者选择更高效、低碳的最后一英里交通方式是提高公共交通份额的关键战略。本研究旨在了解乘客对“共享自主+地铁”新型出行方式组合的偏好，并探索有效的激励政策，以鼓励具有不同人口统计特征的异质人群采用这一模式。本研究以社会认知理论（SCT）为基础，建立了包含低碳知识、受政策激励影响的低碳习惯、外部环境因素和低碳出行意愿四个潜在变量的结构方程模型（SEM），分析影响个体交通方式选择的因素。提出了计算前景值而非效用值的前景理论，并构建了离散选择模型来估计不同激励措施下不同出行者类型的风险偏好系数，便于比较不同激励措施的有效性。研究结果表明，特大城市和低收入群体的居民对政策激励更敏感，更倾向于选择联运模式。在特大城市，出行者对公共交通充值奖励表现出更高的偏好，而现金奖励对二线城市和低收入群体的出行者更具吸引力。高收入群体对商品购物券的偏好更强。将这些见解纳入到脱碳平台的激励措施中，将加强联运模式的推广和采用。

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引用次数: 0

Temporal dynamics of pedestrian injury severity: a seasonally constrained random parameters approach 行人损伤严重程度的时间动态：季节性约束随机参数方法

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.11.009

Mujeeb Abiola Abdulrazaq , Wei David Fan

Pedestrians are the most at-risk group in the transportation system, experiencing a troubling and persistent rise in both the frequency and proportion of fatalities over the past decade. In 2022, pedestrian fatalities in the United States reached a record high since 1981. Despite extensive research examining crash severity models from various perspectives, there is a notable paucity of studies investigating the impact of seasonal variations. This study addresses this gap by examining the seasonal variation in potential contributing factors to pedestrian-vehicle crash severity, utilizing nine years of the most recent pedestrian crash data from North Carolina. Preliminary analysis shows higher crash frequencies during darker seasons, with the highest frequency observed in the fall. Seasonally temporally constrained random parameter logit models, incorporating heterogeneity in both means and variances, are employed to explain the unobserved heterogeneity inherent in the variables and to mitigate biased parameter estimation. The necessity for segmentation is corroborated through pairs of likelihood ratio tests. The model outcomes reveal significant seasonal variations in several important variables. For instance, hit-and-run incidents exhibit the highest marginal effects in the spring. During the summer, male drivers, weekends, and alcohol impairment for both drivers and pedestrians have the most substantial marginal effects. In the fall, young drivers (aged under 24), darkness irrespective of lighting, and work zones show the highest magnitude of marginal effects. This study offers a novel perspective on pedestrian safety analysis and provides data-driven recommendations to enhance safety planning, resource allocation, and overall improvements in the transportation system.

行人是交通系统中最危险的群体，在过去十年中，行人死亡的频率和比例都在持续上升，这令人不安。2022年，美国行人死亡人数达到1981年以来的最高水平。尽管有大量的研究从不同的角度考察了坠机严重程度模型，但调查季节变化影响的研究却明显缺乏。本研究利用北卡罗莱纳州最近9年的行人碰撞数据，通过研究行人与车辆碰撞严重程度的潜在影响因素的季节性变化，解决了这一差距。初步分析显示，在较暗的季节，坠机频率较高，秋天的坠机频率最高。采用季节性时间约束随机参数logit模型，包括均值和方差的异质性，来解释变量中固有的未观察到的异质性，并减轻参数估计的偏倚。通过对似然比检验证实了分割的必要性。模式结果揭示了几个重要变量的显著季节性变化。例如，肇事逃逸事件在春季表现出最高的边际效应。在夏季，男性司机、周末，以及对司机和行人的酒精损害都有最显著的边际影响。在秋季，年轻司机（24岁以下）、不顾照明的黑暗和工作区域显示出最大程度的边际影响。这项研究为行人安全分析提供了一个新的视角，并为加强交通系统的安全规划、资源分配和整体改进提供了数据驱动的建议。

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引用次数: 0

Conflict extraction and characteristics analysis at signalized intersections using trajectory data 基于轨迹数据的信号交叉口冲突提取与特征分析

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.12.002

Xuesong Wang , Ruolin Shi , Andreas Leich , Hagen Saul , Alexander Sohr , Xiaoxu Bei

Potential safety problems at signalized intersections can be recognized most effectively by identifying serious traffic conflict events and analyzing them in different scenarios. However, most studies extract conflicts using different threshold values, and lack thorough examinations and screening. An approach that may not reflect actual traffic conditions may result in the extraction of non-conflict events. Additionally, there lacks a of comprehensive conflict analysis that integrates diverse analyses across different scenarios and operational characteristics. Therefore, based on video data in Shanghai, China, this study provides a comprehensive method for extracting and analyzing serious conflicts. First, video recognition and trajectory reconstruction were conducted. Traffic conflict events were identified by integrating operational characteristics and road geometric design, and K-means++ was used to cluster the severity of these conflicts. Second, parameterized rear-end conflict, lane-changing conflict, and crossing conflict scenarios were reconstructed to analyze serious conflict events. These events were then analyzed separately from the perspectives of conflict distribution, path and turning modes, and vehicle types under three scenarios. The results show that the best clustering effect is achieved using jerk, longitudinal relative distance, and relative distance. Moreover, the validated time-to-collision (TTC) thresholds for classifying conflicts are 0.97 s for serious conflicts, 1.51 s for light conflicts, and 2.09 s for potential conflicts. The study also identifies rear-end conflicts, right-turn conflicts, and conflicts involving cars and trucks as the most serious. These findings support the extraction of key features from intersection scenarios, and facilitate the testing of hazardous scenarios for automated driving.

识别严重交通冲突事件，并在不同场景下进行分析，可以最有效地识别信号交叉口的安全隐患。然而，大多数研究使用不同的阈值提取冲突，缺乏彻底的检查和筛选。不能反映实际交通状况的方法可能导致提取非冲突事件。此外，缺乏综合的冲突分析，该分析集成了跨不同场景和操作特征的各种分析。因此，本研究基于中国上海的视频数据，提供了一种综合的方法来提取和分析严重冲突。首先，进行视频识别和轨迹重建。通过综合交通运行特征和道路几何设计来识别交通冲突事件，并利用k -means++对冲突的严重程度进行聚类。其次，重构参数化的追尾冲突、变道冲突和穿越冲突场景，分析严重冲突事件；然后分别从冲突分布、路径与转向方式、车辆类型三个角度对这些事件进行分析。实验结果表明，采用甩动、纵向相对距离和相对距离的聚类效果最好。此外，冲突分类的有效TTC阈值对于严重冲突为0.97秒，对于轻微冲突为1.51秒，对于潜在冲突为2.09秒。该研究还指出，追尾冲突、右转冲突以及涉及汽车和卡车的冲突是最严重的。这些发现支持从交叉路口场景中提取关键特征，并促进自动驾驶危险场景的测试。

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引用次数: 0

When segment anything model meets inventorying of roadway assets 当分段时，任何模型都会遇到道路资产的盘点

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.10.005

Chenyu Zhang, Sam Huang, Ruwen Qin

Automating the identification, localization, and monitoring of roadway assets distributed widely in the roadway network is critical for the traffic management system. It can efficiently provide up-to-date information in supporting transportation asset management (TAM). Collecting videos with vehicle-mounted cameras and processing the data with computer vision (CV)-based deep learning methods is garnering increased attention from transportation agencies. While promising, challenges arise due to the lack of high-quality annotations for roadway assets in images, difficulties in identifying these assets, and limited solutions. The segment anything model (SAM), a visual foundation model, demonstrates robust zero-shot capability for general image segmentation under various prompts. This study evaluates SAM’s applicability and efficiency in extracting roadway assets from images. Specifically, it examines the impacts of model size and prompt quality on SAM’s performance in segmenting roadway assets. Five state-of-the-art semantic segmentation models are trained and compared with SAM. Results show that a lightweight SAM with human-rendered prompts outperforms the five semantic segmentation models. Based on the evaluation results, future work will explore incorporating SAM into transportation asset management applications, promoting collaboration between human experts and artificial intelligence.

自动识别、定位和监控广泛分布在道路网络中的道路资产对交通管理系统至关重要。它可以有效地为运输资产管理提供最新的信息。利用车载摄像头收集视频，并利用基于计算机视觉（CV）的深度学习方法对数据进行处理，受到了交通部门的越来越多的关注。虽然前景看好，但由于缺乏图像中道路资产的高质量注释、识别这些资产的困难以及有限的解决方案，挑战也随之而来。分段任意模型（SAM）作为一种视觉基础模型，在各种提示条件下对一般图像分割具有鲁棒的零距能力。本研究评估了SAM在图像中提取道路资产的适用性和效率。具体来说，它考察了模型大小和提示质量对SAM分割道路资产性能的影响。训练了5个最先进的语义分割模型，并与SAM进行了比较。结果表明，具有人工呈现提示的轻量级SAM优于五种语义分割模型。基于评估结果，未来的工作将探索将SAM纳入交通资产管理应用，促进人类专家和人工智能之间的协作。

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引用次数: 0

Enhanced in-situ measurement and evaluation methods for subgrade modulus utilizing falling weight deflectometer 利用落重偏转计对路基模量的原位测量和评价方法进行了改进

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.10.002

Zhang Chen , Xiaoying Tong Jin , Huailei Cheng , Qingxiang Liu , Chengwei Xing , Lijun Sun , Xuefeng Jin , Fengcheng Jin

Falling weight deflectometer (FWD) tests have gained increasing popularity in evaluating the stiffness modulus of a pavement subgrade. This paper presents an enhanced method for in-situ testing and evaluation of subgrade moduli using FWD apparatus. The method comprises three components: 1) guidelines for conducting field FWD tests with appropriate loading magnitudes and repetitions; 2) selection of optimal deflection positions for modulus back-calculation; and 3) determination of the suitable depth of the semi-infinite rigid layer. This method was developed based on measurements and analysis of FWD data from five highway subgrade sites, covering various subgrade soil types and climatic conditions. The enhanced method helps to promote the robustness and accuracy of modulus back-calculation results. Furthermore, to validate the proposed method, the back-calculated modulus was compared with moduli obtained from the other two commonly used tests, named the portable seismic pavement analyzer (PSPA) modulus test and the triaxial modulus test. Comparison results indicate strong correlations between the modulus values obtained from the proposed method and those from the PSPA and triaxial modulus tests, affirming the practicality of the proposed method in determining subgrade stiffness moduli.

下落重量偏转计（FWD）试验在评价路面路基刚度模量方面得到了越来越广泛的应用。本文提出了一种利用FWD装置对路基模量进行原位测试和评价的改进方法。该方法包括三个部分：1)进行具有适当载荷大小和重复的FWD现场试验的指南；2)选取模量反算的最佳挠度位置；(3)确定半无限刚性层的合适深度。该方法是基于对五个公路路基场地的FWD数据的测量和分析而开发的，涵盖了不同的路基土壤类型和气候条件。改进后的方法提高了模量反算结果的鲁棒性和准确性。此外，为了验证所提出的方法，将反算模量与另外两种常用试验（便携式地震路面分析仪（PSPA）模量试验和三轴模量试验）获得的模量进行了比较。对比结果表明，该方法与PSPA和三轴模量试验的模量值具有较强的相关性，证实了该方法在确定路基刚度模量方面的实用性。

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引用次数: 0

Adaptive emergency evacuation routing: a graph-based approach 自适应紧急疏散路线：基于图的方法

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.11.010

Hojat Behrooz, Mohammad Ilbeigi

Emergency evacuation plays a vital role in disaster management operations. The existing solutions for planning and routing emergency evacuations rely on preplanning based on prior information and lack adaptability to unprecedented conditions. This study introduces a novel adaptive method for emergency evacuation routing that dynamically reshapes the road network by actively determining and adjusting the direction of road segments and assigning traffic flow to them in order to improve the maximum possible flow of traffic evacuated from a set of dangerous zones to a set of safe zones. The proposed adaptive method revolves around a novel dynamic graph-based algorithm that iteratively and recursively distributes the traffic flow across the road network using a depth first search (DFS) approach. When the algorithm assigns the traffic flow to the road segments, it also determines the direction of the road segments to dynamically improve the performance of the evacuation process. The proposed method was implemented in a real-world evacuation scenario in the road network of Hoboken, New Jersey. The outcomes indicated a significant improvement of more than 74% in the number of successfully evacuated vehicles when the proposed algorithm was used, compared to state-of-the-art methods for evacuation routing that are unable to adjust road directions. The outcomes of this study help decision-makers and first responders develop dynamic and adaptive emergency evacuation plans for successful disaster management operations.

紧急疏散在灾害管理行动中起着至关重要的作用。现有的紧急疏散规划和路径解决方案依赖于基于先验信息的预先规划，缺乏对前所未有的条件的适应性。本文提出了一种新的应急疏散路径自适应方法，该方法通过主动确定和调整路段方向并分配交通流来动态重塑路网，以提高从一组危险区域疏散到一组安全区域的最大可能流量。提出的自适应方法围绕一种新的基于动态图的算法，该算法使用深度优先搜索（DFS）方法迭代和递归地分布整个路网中的交通流。该算法在将交通流分配到路段的同时，还确定路段的方向，以动态提高疏散过程的性能。所提出的方法在新泽西州霍博肯市道路网络的真实疏散场景中实施。结果表明，与无法调整道路方向的疏散路线的最先进方法相比，使用该算法成功疏散车辆的数量显著提高了74%以上。本研究的结果有助于决策者和第一响应者制定动态和适应性的紧急疏散计划，以实现成功的灾害管理操作。

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引用次数: 0

Potential of a new warm asphalt mix by using soft asphalt and rock asphalt compound 用软沥青和岩石沥青混合料组成的新型温沥青混合料的潜力

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2025.01.001

Yanna Sun , Jiawei Zhang , Lihan Li , Tong Lu

Warm mix asphalt (WMA) has gained significant attention in the asphalt industry, traditionally dominated by Hot mix asphalt (HMA), due to its advantages in reducing energy consumption and lowering carbon emissions. This study introduces an innovative warm mix technology, soft-hard compound warm mix asphalt (SHC-WMA), which combines the low softening point of soft asphalt for effective coating of aggregate particles at reduced temperatures, with the high viscosity and aging resistance of rock asphalt to enhance the mixture’s overall performance. Unlike conventional WMA technologies, SHC-WMA was specifically developed with an optimized mixing temperature as a critical design parameter. Through extensive laboratory and field testing, this paper evaluates and compares the road performance, compaction efficiency, emissions reduction, energy savings, and cost-effectiveness of SHC-WMA against Sasobit Warm mix asphalt (SA-WMA) and HMA. The results highlight the superior performance of SHC-WMA, particularly in high-temperature stability and fatigue resistance. SHC-WMA demonstrates a 25% improvement in rutting resistance over HMA and a 15% increase in fatigue life compared to SA-WMA, making it highly suitable for long-term road applications. Furthermore, SHC-WMA significantly outperforms both HMA and SA-WMA in terms of environmental impact, achieving reductions in CO₂ emissions by 27.0%, particulate matter by 35.0%, and benzo[a]pyrene emissions by 55.3% compared to HMA. In terms of energy efficiency, SHC-WMA reduces diesel consumption for asphalt heating by 83.2% and heavy oil consumption for aggregate heating by 28.3% when compared to HMA. The cost of SHC-WMA is 7.7% higher than HMA, and represents 99.2% of the cost of SA-WMA. Additionally, SHC-WMA exhibits the lowest rut depth after eight years of service, indicating its superior long-term performance.

温拌沥青（WMA）由于具有降低能耗和降低碳排放的优势，在传统上以热拌沥青（HMA）为主的沥青行业中受到了广泛的关注。本研究引入了一种创新的温混合料技术——软-硬复合温混合沥青（SHC-WMA），该技术将软沥青的低软化点与岩石沥青的高粘度和耐老化性结合起来，在低温下有效地覆盖骨料颗粒，从而提高了混合料的整体性能。与传统的WMA技术不同，SHC-WMA是专门以优化的混合温度作为关键设计参数开发的。通过广泛的实验室和现场测试，本文评估和比较了SHC-WMA与Sasobit温混合沥青（SA-WMA）和HMA的道路性能、压实效率、减排、节能和成本效益。结果表明，SHC-WMA具有优异的高温稳定性和抗疲劳性能。与HMA相比，SHC-WMA的车辙阻力提高了25%，疲劳寿命比SA-WMA提高了15%，非常适合长期道路应用。此外，SHC-WMA在环境影响方面明显优于HMA和SA-WMA，与HMA相比，SHC-WMA的二氧化碳排放量减少了27.0%，颗粒物排放量减少了35.0%，苯并[a]芘排放量减少了55.3%。在能源效率方面，与HMA相比，SHC-WMA减少了用于沥青加热的柴油消耗83.2%，以及用于骨料加热的重油消耗28.3%。SHC-WMA的成本比HMA高7.7%，占SA-WMA成本的99.2%。此外，SHC-WMA在使用8年后车辙深度最低，表明其长期性能优越。

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引用次数: 0

A dictionary-based Bayesian approach to optimizing left-turn restriction locations in grid networks 基于字典的网格网络左转弯限制位置优化贝叶斯方法

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.10.008

Dongqin Zhou , Vikash V. Gayah

Left-turn movements at signalized intersections pose significant safety risks to drivers and raise efficiency concerns for traffic operations in urban networks. Restricting left-turn movements at selected locations has been shown to be effective at improving operational efficiency and mitigating safety concerns. However, determining optimal locations to restrict left-turns is a complex combinatorial optimization problem that is compounded by the lack of analytical forms for the objective function and constraints, as well as potential interdependencies among the decision variables. Following the common solution paradigm for this type of optimization problems, this paper presents a novel Bayesian approach that utilizes dictionary-based embeddings, and is tailored for high-dimensional combinatorial (or even mixed) spaces. Simulation studies conducted using the Aimsun software under perfect or imperfect grid networks demonstrate that the presented method can consistently find promising left-turn restriction configurations that outperform the all-or-nothing strategies (to restrict all or none left-turn movements at all intersections), as well as the population based incremental learning algorithm. In addition, the presented method often does so with less simulation cost, thus showcasing its potential for efficient solution of more general traffic optimization problems.

信号交叉口的左转弯给驾驶员带来了巨大的安全风险，并引起了城市交通网络中交通运行效率的担忧。在选定地点限制左转弯已被证明可有效提高操作效率和减轻安全问题。然而，确定限制左转的最佳位置是一个复杂的组合优化问题，由于缺乏目标函数和约束的分析形式，以及决策变量之间潜在的相互依赖性，使得问题更加复杂。遵循这类优化问题的常见解决范例，本文提出了一种新的贝叶斯方法，该方法利用基于字典的嵌入，并为高维组合（甚至混合）空间量身定制。使用Aimsun软件在完美或不完美网格网络下进行的仿真研究表明，所提出的方法可以始终找到有希望的左转限制配置，优于全有或全无策略（限制所有十字路口的全部或不左转运动），以及基于人口的增量学习算法。此外，所提出的方法通常以较少的模拟成本完成，从而显示出其有效解决更一般的交通优化问题的潜力。

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引用次数: 0

Understanding customer preferences for autonomous delivery vehicles in instant delivery: exploring the impact of delivery and personal attributes 了解客户对即时送货的自动送货车辆的偏好：探索送货和个人属性的影响

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.12.001

Chengyuan Huang , Miaojia Lu , Ran Wang , Rong Zhang

Various issues confront instant delivery, such as elevated labor expenses, low efficiency, and courier accidents. Consequently, e-commerce and logistics providers have turned their attention towards autonomous delivery vehicles (ADVs). There are no studies on customers who use instant delivery that focus on their preferences for ADVs in relation to cargo damage in conjunction with other delivery attributes such as instant delivery service use frequency and price of orders. The objective of this study is to examine customers’ preferences for ADVs in comparison to traditional courier delivery. To account for the heterogeneity of customers, this study employs the random parameter logit (RPL) model with interactions to quantify the relevance of attributes and their interaction effects. This study is the first to consider cargo damage as an alternative-specific attribute (ASA) in the context of preference studies for instant delivery modes. We also examine the interaction effects between delivery price and personal and delivery attributes, considering the significance and notable preference variations regarding delivery price across different populations. For data collection, a survey employing stated-preference (SP) approach was conducted in China, resulting in 309 effective surveys. The findings indicate that customer preference heterogeneity regarding delivery price and cargo damage both follow normal distributions. And gender, privacy, instant delivery service use frequency, and price of orders all show significant effects on customers’ preferences for ADVs. Analysis of the survey answers also revealed statistically significant positive interaction effects on delivery price associated with income and instant delivery service use frequency. This study contributes to understanding customer preferences for ADVs, thereby assisting logistics providers in identifying target customers for ADVs.

即时配送面临着人工成本上升、效率低下、快递事故等诸多问题。因此，电子商务和物流供应商将注意力转向了自动送货车辆（ADVs）。目前还没有针对使用即时送货的客户的研究，将他们对自动驾驶汽车的偏好与货物损坏以及其他送货属性（如即时送货服务的使用频率和订单价格）联系起来。本研究的目的是检验顾客对自动驾驶汽车的偏好与传统快递的比较。为了考虑客户的异质性，本研究采用随机参数logit （RPL）模型与交互来量化属性的相关性及其交互效应。本研究首次将货物损坏作为即时交付模式偏好研究背景下的一种选择特异性属性（ASA）。我们还研究了交割价格与个人和交割属性之间的交互效应，考虑了交割价格在不同人群中的显著性和显著性偏好变化。在数据收集方面，采用状态偏好（SP）方法在中国进行调查，得到309份有效调查。结果表明，顾客对交货价格和货物损坏的偏好异质性均服从正态分布。性别、隐私、即时配送服务使用频率、订单价格均对消费者的自动驾驶偏好有显著影响。对调查答案的分析也显示出统计上显著的正交互作用，与收入和即时配送服务使用频率相关的配送价格。本研究有助于了解客户对自动驾驶汽车的偏好，从而帮助物流供应商确定自动驾驶汽车的目标客户。

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引用次数: 0

Examining fine-grained commuting CO2 emission using cellular signaling data: insights from Shanghai, China 利用蜂窝信号数据研究细粒度的通勤二氧化碳排放：来自中国上海的见解

IF 4.8 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2025-12-01 DOI: 10.1016/j.ijtst.2024.12.004

Bowen Li , Qian Yu , Xinghang Zhu , Zhongren Peng , Hongdi He

Quantifying carbon dioxide (CO₂) emissions from commuting and the impact of investigating built environment are essential for urban traffic-related emission reduction. This study utilizes more than 11 million pieces of cellular signaling data to estimate CO₂ emissions from commuting without extensive survey work, and examines their association with the built environment at residences and workplaces. The results reveal that the impact of the built environment on CO₂ emissions at workplaces is more significant than that at residences, with spatial heterogeneity playing a stronger role in residences. Moreover, bus stop density has opposite effects on CO₂ emissions at workplaces and residences. Increased bus stop density promotes an increase in home-based CO₂ emissions, but inhibits an increase in work-based CO₂ emissions. Besides, a balanced job-housing distribution and moderate land-use mixing have proved effective in reducing CO₂ emissions. This empirical study provides a valuable framework to conduct fine-grained research to explore targeted strategies to reduce emissions by optimizing the built environment.

量化通勤过程中的二氧化碳排放和调查建筑环境对城市交通减排的影响是至关重要的。本研究利用超过1100万条的蜂窝信号数据来估算通勤产生的二氧化碳排放量，而无需进行广泛的调查工作，并研究了它们与住宅和工作场所建筑环境的关系。结果表明：建筑环境对工作场所CO2排放的影响大于居住环境，且居住环境的空间异质性作用更强；此外，公交车站密度对工作场所和住宅的二氧化碳排放有相反的影响。公交车站密度的增加促进了以家庭为基础的二氧化碳排放量的增加，但抑制了以工作为基础的二氧化碳排放量的增加。此外，平衡的职住分配和适度的土地混合使用已被证明是减少二氧化碳排放的有效方法。本实证研究提供了一个有价值的框架，可以进行细粒度的研究，探索通过优化建筑环境来减少排放的有针对性的策略。

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引用次数: 0