Shivam Sharda , Nicole Viz , Venu M. Garikapati , Konstadinos G. Goulias , Katelyn Stenger
{"title":"Cross-sectoral synergies for household energy savings: the role of electric vehicles, solar photovoltaics, and remote work","authors":"Shivam Sharda , Nicole Viz , Venu M. Garikapati , Konstadinos G. Goulias , Katelyn Stenger","doi":"10.1080/19427867.2026.2613230","DOIUrl":"10.1080/19427867.2026.2613230","url":null,"abstract":"<div><div>Over the past two decades, new technologies and behavioral shifts – such as electric vehicles, solar photovoltaics, and increased work-from-home practices – have reshaped residential electricity consumption and cost. However, their combined or synergistic impact on a household’s electricity cost remains unexplored. Leveraging data from the 2020 Residential Energy Consumption Survey, this study uses a structural equation model to unravel the extent to which the bundled adoption of EV-PV and stay-at-home decisions impact the total electricity cost of households. Results indicate that adopting both EVs and PV reduces electricity costs by 31% despite a 16% rise in consumption. When combined with stay-at-home practices, households still experience a 13% cost reduction, even with a 25% increase in electricity consumption. These findings suggest that financial savings are not merely a byproduct of adopting new technologies or behavioral changes but could serve as a key consideration for household contemplating engagement with multiple modern energy solutions simultaneously.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 5","pages":"Pages 1049-1063"},"PeriodicalIF":3.3,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jian Du , Zhen Lin , Yang Li , Ran Zhang , Xinmiao Yu
{"title":"Bi-objective optimization for heterogeneous fleet deployment problem considering operational carbon intensity indicator","authors":"Jian Du , Zhen Lin , Yang Li , Ran Zhang , Xinmiao Yu","doi":"10.1080/19427867.2026.2615651","DOIUrl":"10.1080/19427867.2026.2615651","url":null,"abstract":"<div><div>The International Maritime Organization (IMO) implemented the operational Carbon Intensity Indicator (CII) certification starting in 2023 to advance carbon intensity peaking. Existing fleet deployment studies that sacrifice transport capacity for emission reduction no longer align with the latest CII requirements. From a carbon intensity management perspective, this study addresses the heterogeneous fleet deployment problem, accounting for variations in vessel age, capacity, equipment, fuel consumption, and speed. A bi‑objective mixed‑integer nonlinear programming model is developed to simultaneously optimize operating costs and carbon intensity, while complying with sulfur emission limits, operational CII guidelines, and the technical Energy Efficiency Existing Ship Index (EEXI). An enhanced NSGA‑II algorithm is proposed to obtain Pareto‑optimal solutions. Computational experiments based on real operational data from COSCO Shipping Lines demonstrate that: (1) the integrated CII‑EEXI framework effectively balances technical efficiency limits and operational carbon management; (2) the algorithm yields well‑distributed Pareto solutions, achieving a trade‑off between environmental and economic objectives; and (3) the carbon management framework supports shipping companies in meeting compliance requirements through coordinated fleet deployment and operational adjustments.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 5","pages":"Pages 1127-1155"},"PeriodicalIF":3.3,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Green efficiency deviation in ports: an empirical analysis of scale-greenness trade-offs in Zhejiang, China","authors":"Qingmei Liao , Yuanqiao Wen , Shijun Chen , Maxim A. Dulebenets , Yu Xie , Qiong Chen","doi":"10.1080/19427867.2026.2616623","DOIUrl":"10.1080/19427867.2026.2616623","url":null,"abstract":"<div><div>As global ports expand, balancing scale with green development grows crucial. While studies on conventional (CPE) and green port efficiency (GPE) is extensive, research on their efficiency deviation (ED) remains limited. Utilizing data from the <em>Zhejiang Province Port Energy Reporting System</em> for 2019–2024, this study evaluated CPE, GPE and the ED in Zhejiang ports using the Super-SBM model, and examines influencing factors through a multilevel regression model. Results indicate that cargo throughput influences ED through mediating and moderating mechanisms, with no direct effect. Cargo throughput’s impact on ED is realized through CPE; it indirectly increases ED by boosting CPE, and port location moderates the relationship between cargo throughput and ED. Large hub ports achieve higher CPE through technological collaboration, regulation-driven initiatives, and efficiency reinvestment, thereby accelerating GPE improvement. These findings offer valuable insights for port managers seeking to balance scale expansion with low-carbon transformation.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 5","pages":"Pages 1156-1172"},"PeriodicalIF":3.3,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yanan Li , Juan Wang , Jianji Ren , Yongliang Yuan , Yun Xin , Haiqing Liu
{"title":"An ensemble CNN-BiLSTM-attention and BiGRU adaptive-weighted model for state of charge prediction in real electric vehicles","authors":"Yanan Li , Juan Wang , Jianji Ren , Yongliang Yuan , Yun Xin , Haiqing Liu","doi":"10.1080/19427867.2025.2612228","DOIUrl":"10.1080/19427867.2025.2612228","url":null,"abstract":"<div><div>To guarantee safe electric vehicle system functioning and extend battery life, it is essential to estimate the state-of-charge (SOC) of electric vehicle battery systems. Existing SOC prediction models struggle to balance long-term trends and short-term dynamic changes in time series predictions. To address this issue, we propose a hybrid CNN-BiLSTM-Attention and BiGRU model (CABLG) that improves SOC prediction accuracy by integrating long- and short-term features. Validation using real-world and laboratory data shows superior performance compared to benchmark models. The experimental results indicate that CABLG model exhibits excellent performance. In real driving data, the model achieves the best prediction results in winter conditions with MAE of 0.0945, MSE of 0.0187, and RMSE of 0.1369. In laboratory conditions, the model performs well with MAE of 0.0018, MSE of 4.7962E-06, and RMSE of 0.0022. The results clearly indicate CABLG model’s excellent performance in SOC prediction and also demonstrate its potential in real-world applications.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 4","pages":"Pages 915-932"},"PeriodicalIF":3.3,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147807966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuchao Zhao , Tao Liu , Wen Meng , Zhuang Dai , Wenbo Fan
{"title":"Optimizing timetabling and platoon formation of shuttle transit with modular autonomous vehicles considering time-dependent passenger demand","authors":"Yuchao Zhao , Tao Liu , Wen Meng , Zhuang Dai , Wenbo Fan","doi":"10.1080/19427867.2025.2610232","DOIUrl":"10.1080/19427867.2025.2610232","url":null,"abstract":"<div><div>Traditional public transit with fixed vehicle capacity often leads to underutilization, especially during off-peak hours. Modular autonomous vehicles (MAVs) enable flexible capacity through coupling and decoupling. This study jointly optimizes timetabling and platoon formation for an MAV-based shuttle system under time-dependent demand. A bi-objective model balances operator and passenger costs, solved via the <em>ε</em>-constraint method to obtain Pareto-optimal solutions. A case study confirms the model’s effectiveness, demonstrating that the MAV system reduces total operating costs and improves service—achieving a 73.70% decrease in empty seat time and a 29.75% reduction in passenger waiting time compared to traditional fixed-capacity transit.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 4","pages":"Pages 823-840"},"PeriodicalIF":3.3,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147807974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Changfeng Zhu , Shengyun Xue , Jie Wang , Jinghao Fang , Runtian He
{"title":"Resilience of road transportation network in metropolitan areas","authors":"Changfeng Zhu , Shengyun Xue , Jie Wang , Jinghao Fang , Runtian He","doi":"10.1080/19427867.2025.2610873","DOIUrl":"10.1080/19427867.2025.2610873","url":null,"abstract":"<div><div>Global climate change has rendered transportation systems vulnerable to extreme weather conditions. A thorough assessment of network resilience is crucial to maintain the smooth operation of the road network. This study develops a three-dimensional resilience evaluation model that accounts for the impact of capacity degradation and sheds light on the resilience of road networks. We investigate the degradation mechanism of road network performance in a rainfall environment. Specific rainstorm weather scenarios were generated using the Monte Carlo simulation method. The road traffic network in the Chengdu metropolitan area was selected for validation and analysis. When meteorological conditions exceed the secondary intensity, the road network becomes more vulnerable to increased traffic flow. Betweenness and degree centrality are indicators of regional importance. Different recovery strategy priorities must be developed for different interference scenarios.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 4","pages":"Pages 883-897"},"PeriodicalIF":3.3,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147807977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Temporal patterns of paratransit usages: a case study of pre-, during-, and post-COVID-19 usage patterns using time-series clustering","authors":"Troyee Saha , Kate (Kyung) Hyun","doi":"10.1080/19427867.2025.2611083","DOIUrl":"10.1080/19427867.2025.2611083","url":null,"abstract":"<div><div>Paratransit services are vital for older adults and individuals with disabilities, whose mobility challenges worsened during COVID-19. However, limited research explores shifts in paratransit usage across pandemic phases and their future implications. This study addresses this gap by analyzing paratransit usage patterns using data from a Texas-based paratransit service, spanning January 2019 to December 2022. We employ time-series clustering to categorize users based on trip behaviors, revealing four distinct patterns. High-trip users reduced their frequency from 6 trips per week pre-pandemic to 4.7 during the pandemic but returned to pre-pandemic levels afterward. Moderate-trip users also saw a decline but only partially recovered post-pandemic. These varying recovery rates highlight the pandemic’s differing impacts, with high-frequency travelers rebounding most strongly. Notably, around 55% of users left the system post-pandemic, while 14% consistently used it. These insights emphasize the need for targeted service provision and strategic resource allocation by paratransit agencies.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 4","pages":"Pages 898-914"},"PeriodicalIF":3.3,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147807968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Huitao Lv , Haojie Li , Fan Zhang , Xue Bai , Tao Feng
{"title":"Integrating crowding and safety in the analysis of cyclists’ route preferences: insights from a hybrid choice model","authors":"Huitao Lv , Haojie Li , Fan Zhang , Xue Bai , Tao Feng","doi":"10.1080/19427867.2025.2606311","DOIUrl":"10.1080/19427867.2025.2606311","url":null,"abstract":"<div><div>In the context of future-oriented urban road infrastructure adaptation, it is crucial to understand the factors that influence cyclists’ route choice behavior to promote cycling effectively. However, the increase in bicycle usage can also lead to crowded cycling infrastructure and increased objective safety risks, which has not been thoroughly investigated in previous studies. This study examine how crowding, safety risks, and route attributes influence cyclists’ route choices, differentiating between e-bike and regular bike users. Using stated preference data from 784 cyclists in Nanjing and a hybrid choice model (HCM), the research integrates latent attitudinal variables and socio-demographic factors. Findings show regular cyclists are more sensitive to crowding and accident risk, while e-bike users prioritize dedicated cycling infrastructure over travel time and road characteristics. The results underscore the importance of including attitudinal variables in route choice models and provide valuable guidance to safely manage rising cycling demand and improve navigation systems.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 4","pages":"Pages 789-808"},"PeriodicalIF":3.3,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147807972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimization of rest area capacities considering driving fatigue: a resting behavior model approach","authors":"Ruixiang Zhou , Yoshinao Oeda","doi":"10.1080/19427867.2025.2610870","DOIUrl":"10.1080/19427867.2025.2610870","url":null,"abstract":"<div><div>Driving on expressways often requires extended travel durations, necessitating rest areas to mitigate driver fatigue. Observational reports in Japan reveal an uneven utilization of these facilities, with stopovers concentrated at specific rest areas. This study aimed to examine factors influencing resting behavior and to optimize rest area usage. A survey collected 1098 valid data points on drivers’ stopover patterns. A model was developed based on the hypothesis that resting behavior depends on the service quality at rest areas and the fatigue accumulated during continuous driving. The model successfully replicated key behavioral patterns, including driving duration before stopping and rest area selection. Using this model, parking spaces at rest areas were reallocated to better align with drivers’ fatigue conditions. Results indicated that this optimization approach could improve the overall occupancy rate of rest areas, enhancing their utilization efficiency and ultimately contributing to safer and more sustainable expressway travel.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 4","pages":"Pages 841-861"},"PeriodicalIF":3.3,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147807975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shikun Xie , Zhen Yang , Fang Yuan , Mingxuan Wang
{"title":"Analyzing pedestrian-vehicle interaction dynamics at unsignalized crosswalks: a game mode analysis through MCMC and BN modeling","authors":"Shikun Xie , Zhen Yang , Fang Yuan , Mingxuan Wang","doi":"10.1080/19427867.2025.2610871","DOIUrl":"10.1080/19427867.2025.2610871","url":null,"abstract":"<div><div>Insufficient traffic control at unsignalized crosswalks causes pedestrians and vehicles operations to rely on their perception of road conditions, environment, and potential risks, resulting in game-like interactions with strategic decisions and behavioral adjustments. However, the characteristics and mechanisms of these behaviors remain poorly understood. This study analyzes pedestrian-vehicle interaction patterns at unsignalized crosswalks using Unmanned Aerial Vehicle (UAV) data. Ten game types are identified and classified into no-game, single-game, and multi-game interactions. A Pedestrian-Vehicle Game Index (PVGI) is proposed to quantify interaction dynamics by integrating speed, acceleration, and distance. Markov-Chain Monte Carlo (MCMC) simulation determines the PVGI domain as [−4.0, 2.0], distinguishing pedestrian-yield [−4.0, 0] and vehicle-yield [0, 2.0]. A Bayesian Network (BN) model, combined with the Gaussian Mixture Model (GMM) and Expectation-Maximum (EM) algorithm predicts second-round game patterns with an accuracy of 83.78%. These findings provide actionable insights for improving traffic safety and efficiency at unsignalized crosswalks.</div></div>","PeriodicalId":48974,"journal":{"name":"Transportation Letters-The International Journal of Transportation Research","volume":"18 4","pages":"Pages 862-882"},"PeriodicalIF":3.3,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147807976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}