International Journal of Transportation Science and Technology最新文献_第9页

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2024-12-16 DOI: 10.1016/j.ijtst.2024.11.009

Mujeeb Abiola Abdulrazaq , Wei David Fan

{"title":"Temporal dynamics of pedestrian injury severity: a seasonally constrained random parameters approach","authors":"Mujeeb Abiola Abdulrazaq , Wei David Fan","doi":"10.1016/j.ijtst.2024.11.009","DOIUrl":"10.1016/j.ijtst.2024.11.009","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 237-257"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2024-12-06 DOI: 10.1016/j.ijtst.2024.11.008

Chenjing Bi , Ye Li , Dominique Gruyer , Meiting Tu

{"title":"Who is more willing to use shared autonomous vehicles in first-mile-last-mile? A heterogeneity study on carbon incentive policy from China","authors":"Chenjing Bi , Ye Li , Dominique Gruyer , Meiting Tu","doi":"10.1016/j.ijtst.2024.11.008","DOIUrl":"10.1016/j.ijtst.2024.11.008","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 218-236"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incident duration reliability assessment using Monte-Carlo simulation and kernel density estimation of machine learning-based models 基于蒙特卡罗模拟和核密度估计的机器学习模型的事件持续时间可靠性评估

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2024-12-02 DOI: 10.1016/j.ijtst.2024.11.005

Lubna Obaid, Khaled Hamad, Samer Barakat

{"title":"Incident duration reliability assessment using Monte-Carlo simulation and kernel density estimation of machine learning-based models","authors":"Lubna Obaid, Khaled Hamad, Samer Barakat","doi":"10.1016/j.ijtst.2024.11.005","DOIUrl":"10.1016/j.ijtst.2024.11.005","url":null,"abstract":"<div><div>Traffic incidents are a major cause of non-recurrent congestion and delays, making accurate incident duration (ID) prediction essential for effective traffic management. While machine learning (ML) and deep learning (DL) models have been developed to predict ID and its sub-periods (verification, response, and clearance times), their reliability has not been systematically assessed. This study introduces a novel framework to evaluate the reliability of these predictions using 4 000 traffic incident records. Non-parametric kernel density estimation (KDE) effectively captured variations in the data, outperforming traditional parametric methods. Monte Carlo simulation (MCS) was then used to assess prediction reliability. Among the models tested, bagged ensemble trees provided the best balance between accuracy and complexity, showing strong reliability for predicting total ID and sub-periods. Adding 5–25% buffer adjustments further improved reliability by accounting for prediction uncertainties. This framework offers a robust tool for assessing prediction reliability, is adaptable to various ML and DL models, and represents a significant step forward in traffic incident management.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 157-177"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2024-10-19 DOI: 10.1016/j.ijtst.2024.10.005

Chenyu Zhang, Sam Huang, Ruwen Qin

{"title":"When segment anything model meets inventorying of roadway assets","authors":"Chenyu Zhang, Sam Huang, Ruwen Qin","doi":"10.1016/j.ijtst.2024.10.005","DOIUrl":"10.1016/j.ijtst.2024.10.005","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 1-14"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2025-01-06 DOI: 10.1016/j.ijtst.2024.12.002

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

{"title":"Conflict extraction and characteristics analysis at signalized intersections using trajectory data","authors":"Xuesong Wang , Ruolin Shi , Andreas Leich , Hagen Saul , Alexander Sohr , Xiaoxu Bei","doi":"10.1016/j.ijtst.2024.12.002","DOIUrl":"10.1016/j.ijtst.2024.12.002","url":null,"abstract":"<div><div>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 <em>K</em>-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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 300-320"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2024-10-21 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

{"title":"Enhanced in-situ measurement and evaluation methods for subgrade modulus utilizing falling weight deflectometer","authors":"Zhang Chen , Xiaoying Tong Jin , Huailei Cheng , Qingxiang Liu , Chengwei Xing , Lijun Sun , Xuefeng Jin , Fengcheng Jin","doi":"10.1016/j.ijtst.2024.10.002","DOIUrl":"10.1016/j.ijtst.2024.10.002","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 68-81"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2024-12-03 DOI: 10.1016/j.ijtst.2024.11.010

Hojat Behrooz, Mohammad Ilbeigi

{"title":"Adaptive emergency evacuation routing: a graph-based approach","authors":"Hojat Behrooz, Mohammad Ilbeigi","doi":"10.1016/j.ijtst.2024.11.010","DOIUrl":"10.1016/j.ijtst.2024.11.010","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 178-192"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2025-01-16 DOI: 10.1016/j.ijtst.2025.01.001

Yanna Sun , Jiawei Zhang , Lihan Li , Tong Lu

{"title":"Potential of a new warm asphalt mix by using soft asphalt and rock asphalt compound","authors":"Yanna Sun , Jiawei Zhang , Lihan Li , Tong Lu","doi":"10.1016/j.ijtst.2025.01.001","DOIUrl":"10.1016/j.ijtst.2025.01.001","url":null,"abstract":"<div><div>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 CO<sub>2</sub> 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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 336-347"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2024-10-19 DOI: 10.1016/j.ijtst.2024.10.008

Dongqin Zhou , Vikash V. Gayah

{"title":"A dictionary-based Bayesian approach to optimizing left-turn restriction locations in grid networks","authors":"Dongqin Zhou , Vikash V. Gayah","doi":"10.1016/j.ijtst.2024.10.008","DOIUrl":"10.1016/j.ijtst.2024.10.008","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 35-49"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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

International Journal of Transportation Science and Technology Pub Date : 2025-12-01 Epub Date: 2025-01-06 DOI: 10.1016/j.ijtst.2024.12.004

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

{"title":"Examining fine-grained commuting CO2 emission using cellular signaling data: insights from Shanghai, China","authors":"Bowen Li , Qian Yu , Xinghang Zhu , Zhongren Peng , Hongdi He","doi":"10.1016/j.ijtst.2024.12.004","DOIUrl":"10.1016/j.ijtst.2024.12.004","url":null,"abstract":"<div><div>Quantifying carbon dioxide (CO<sub>2</sub>) 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 CO<sub>2</sub> 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 CO<sub>2</sub> 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 CO<sub>2</sub> emissions at workplaces and residences. Increased bus stop density promotes an increase in home-based CO<sub>2</sub> emissions, but inhibits an increase in work-based CO<sub>2</sub> emissions. Besides, a balanced job-housing distribution and moderate land-use mixing have proved effective in reducing CO<sub>2</sub> 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.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"20 ","pages":"Pages 270-284"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0