Journal of Advanced Transportation最新文献

{"title":"Service Attribute Preferences of Air–HSR Transfer Process From a Combined Perspective of Resource-Matching, Perceived Risk, and Value Theories","authors":"Yi-Ao Liu,&nbsp;Yun Jing,&nbsp;Si-Ye Guo","doi":"10.1155/atr/7498989","DOIUrl":"https://doi.org/10.1155/atr/7498989","url":null,"abstract":"<p>As an indispensable component of the modern high-quality national comprehensive three-dimensional transport network, air and high-speed rail intermodal transportation (Air–HSR) plays a pivotal role in advancing “transportation integration.” The transfer process in Air–HSR represents a critical touchpoint of service experience, and the investigation into passengers’ preferences for transfer service attributes is instrumental in providing civil aviation enterprises with a more personalized foundation for product development. First, six resource-matching attributes of Air–HSR are extracted by introducing the resource-matching theory (RMT) and drawing on the consumer behavior analytical methods. Subsequently, incorporating the perceived risk theory (PRT) and perceived value theory (PVT), a quantitative framework for passengers’ preferences for service attributes of Air–HSR transfer (RPP-F) is proposed from the dual perspectives of perceived risk (PR) and perceived value (PV). Then, an analysis model (PR–PV–SEM) is constructed with PR and PV as mediating latent variables to examine passengers’ preferences for service attributes of Air–HSR transfer, and the preferences are analyzed through the lens of latent variables. Finally, based on measurement data of passengers’ diverse preferences, passengers’ heterogeneous preferences are analyzed and interpreted through the lenses of latent variables and socioeconomic attributes via multisampling approaches, and the internal preference structures of different attribute groups are deeply explored. The model results demonstrate that the PR–PV–SEM with PR and PV as mediating latent variables exhibits excellent model fit with its explanatory power for passengers’ adoption intention reaching 73%. This finding reveals the mediating mechanism between objective services and subjective willingness via PR and PV and provides a novel perspective for subsequent analysis of travel service preferences.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/7498989","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145224378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Impact of Climate Change on Road Fatalities: A Macroscopic Panel Data Analysis","authors":"Qirui Hu,&nbsp;Yajie Zou,&nbsp;Shubo Wu,&nbsp;Siyang Zhang,&nbsp;Yue Zhang,&nbsp;Lingtao Wu","doi":"10.1155/atr/4693354","DOIUrl":"https://doi.org/10.1155/atr/4693354","url":null,"abstract":"<p>The present road traffic safety situation faces significant challenges. Examining the influences of diverse contributing factors on road traffic crashes is of crucial importance. However, different factors may have different influences as the change of location and time and the neglect of potential heterogeneity while modelling the frequency of traffic crashes may lead to biases in parameter estimation and incorrect inference. To address the unobserved spatiotemporal heterogeneity and accurately explore the correlations between contributing factors and fatal traffic crashes, a fixed effects panel model with structural breaks is applied to identify the influences of crucial factors on fatal traffic crashes from a macroscopic level. A multisource dataset, including fatal crash numbers, socioeconomic factors, laws and regulations and climate factors is collected from the United States spanning 45 years (from 1977 to 2021). The climate change events (i.e., El Niño–Southern Oscillation phenomena) are examined for their influences on fatal traffic crashes. The experimental results illustrate that high temperatures and frequent meteorological disasters have increasing impacts on fatal crash numbers. High precipitation shows a decreasing one from a macroscope level because of the lagged effect of precipitation on crashes across days. Particularly, the climate change events (including EP E1 Niño, CP E1 Niño and La Niña) represent an adverse impact on road traffic safety. Additionally, the states with similar meteorological characteristics are categorized as high temperature, high precipitation and frequent meteorological disaster subsets for separate analysis. Under these subsets, rural trip proportion becomes a more pronounced factor that affects fatal road traffic crashes, and helmet laws are more efficient in reducing fatal crash frequency. The research findings reveal an increasingly complex road traffic safety environment in the context of global warming, offering valuable perspectives for enhancing road traffic safety.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/4693354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145224526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Two-Stage Multiobjective Optimization Approach for Expressway Guide Sign Information Selection","authors":"Yutong Wei,&nbsp;Ronggui Zhou,&nbsp;Weihan Zhang,&nbsp;Yu Qian,&nbsp;Jian Zhang","doi":"10.1155/atr/4270467","DOIUrl":"https://doi.org/10.1155/atr/4270467","url":null,"abstract":"<p>The selection of information for expressway guide signs requires a consideration of multiple factors, including geographical location, traffic demand, network cost, and information relevance. As expressway networks continue to expand and their topologies become increasingly complex, relying solely on expert experience for guide sign information selection has become insufficient. To address this issue, a novel two-stage multiobjective optimization framework is proposed. In the first stage, a route-swapping algorithm is employed to solve a transformed system optimization equilibrium model to generate the link flow distribution. This distribution then serves as parameter input for the second stage, where a multiobjective mixed integer linear programming (MILP) model is formulated to decide guide sign information. We consider three objectives of maximizing consistency between guidance information and traffic flow distribution, maximizing continuity of guidance information, and minimizing driver’s recognition time. The Pareto optimal solution set of the multiobjective model is identified through parametric search, and the TOPSIS method is applied to determine the global optimal solution, generating the guide sign information scheme for newly constructed expressway segments. Validation on the case-study expressway shows that the proposed framework provides a scheme that satisfies all hard constraints while exhibiting high consistency with geographical and traffic flow distribution patterns, strong information coherence, and effective control of redundant information. This study presents an efficient, standardized methodology for optimizing expressway guide sign information selection.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/4270467","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Roadside Safety With Computer Vision: FHWA Ratings as the Key Predictor of Rural Road Departure Crashes and Severity","authors":"Abhishek Kumar Subedi,&nbsp;Abbas Rashidi,&nbsp;Nikola Marković","doi":"10.1155/atr/5559576","DOIUrl":"https://doi.org/10.1155/atr/5559576","url":null,"abstract":"<p>This is the first study to evaluate the effectiveness of the Federal Highway Administration (FHWA) roadside safety rating system in predicting Road Departure (RD) crashes on rural roads. The research employs a two-step framework: first, a computer vision model was used to extract detailed information on clear zones, rigid obstacles, side slopes, and safety barriers from roadway images. Next, the extracted data was integrated with crash records for statistical analysis. The FHWA safety rating system, which combines these features, shows a significant correlation with rural RD crash frequency and severe injury rates, as confirmed by Spearman correlation coefficients. Furthermore, using the negative binomial regression model, the safety rating emerged as the strongest predictor of rural RD crashes and their severity compared to individual roadside features, underscoring its value in assessing crash risk. With its seven categories, the FHWA safety rating system provides a more comprehensive predictor of rural RD crash risk, making it an essential tool for identifying high-risk locations and prioritizing safety interventions.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5559576","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145172021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of Transit Route and Frequency for Integrated Urban–Rural Transit Network","authors":"Yao Liu,&nbsp;Guangmin Wang,&nbsp;Shihui Jia","doi":"10.1155/atr/9728885","DOIUrl":"https://doi.org/10.1155/atr/9728885","url":null,"abstract":"<p>The integration of urban and rural transit networks is a prerequisite for the integration of urban and rural transportation systems. With the promotion of rural revitalization and new urbanization, the existing transit network operated separately in urban and rural areas is insufficient in meeting the travel demands of urban and rural residents. It is necessary to plan the urban and rural transit network rationally and to enhance the overall system performance of the urban and rural transit network. This paper proposes a biobjective model to optimize the integrated urban–rural transit network. The model minimizes both passengers’ and bus operators’ costs by optimizing the bus routes and frequencies simultaneously. Furthermore, we propose a subregional operations model and explore a performance comparison between the integrated and subregional optimization approaches. The genetic algorithm is developed to solve the proposed models. Finally, we conduct numerical experiments to identify the efficacy of the proposed models and algorithms. The results indicate that the integrated operation of the urban–rural transit network has more optimization space than the subregional operation, and can effectively reduce the number of transfers. Furthermore, under integrated operations, changes in operating costs have a more pronounced impact on total passenger travel time. When the demand is within a particular range, the integrated operation generates a shorter total passenger travel time than the subregional operation for the exact operating cost. In addition, the Pareto-optimal solution generated under varying interregional demands provides a trade-off between the total passenger travel time and the operating costs of the bus operator.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9728885","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145111239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shortest Path Planning in Multimodal Metropolitan Transportation Networks Under Timetable and Label Constraints","authors":"Xirong Chen,&nbsp;Jinrun Wang,&nbsp;Haowei Deng,&nbsp;Bin Zhao","doi":"10.1155/atr/3365603","DOIUrl":"https://doi.org/10.1155/atr/3365603","url":null,"abstract":"<p>This study proposes a label-setting shortest-path algorithm with timetable and label constraints to address the path-planning problem in multimodal urban agglomeration transportation networks. The proposed algorithm addresses the limitations of traditional shortest-path methods, which are often challenged by complex conditions, including transfer constraints, timetable dependencies, and restrictions on the number of transfers. By analyzing the characteristics of urban agglomeration trip chains, this study constructed a multimodal network model incorporating six transportation modes: walking, buses, intercity coaches, metro, intercity railways, and private vehicles. A deterministic finite automaton was introduced to constrain feasible mode sequences, ensuring that path planning aligns with real-world travel patterns. The algorithm incorporates time-window constraints to simulate the effects of static timetables in scheduled transportation modes, such as railways and coaches. By improving the label-correcting algorithm via topological sorting and applying state-dominance rules to reduce redundant computations, it achieves optimal path planning under multiple constraints. Case studies demonstrate that the algorithm effectively balances transfer frequency and travel cost, reducing total cost by approximately 5% while ensuring feasibility, thereby validating the synergistic advantages of multimodal transportation networks. Therefore, the proposed algorithm can theoretically support multimodal traffic selection behavior or mixed traffic network modeling.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/3365603","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GL-LoiterDNet: A Hybrid Model for Ship Trajectory Prediction in Loitering Activity Scenarios","authors":"Liang Huang,&nbsp;Peng Zou,&nbsp;Yuanqiao Wen,&nbsp;Tengda Sun,&nbsp;Yamin Huang,&nbsp;He Lin","doi":"10.1155/atr/5582889","DOIUrl":"https://doi.org/10.1155/atr/5582889","url":null,"abstract":"<p>In loitering activity scenarios, vessels frequently execute course changes within localized maritime spaces, often exhibiting extreme turning maneuvers that generate ultralong, dense, and highly nonlinear spatiotemporal trajectories. Traditional prediction models demonstrate limitations in processing dynamically changing trajectory features, leading to insufficient prediction accuracy under such loitering conditions. To address this challenge, this study proposes a GL-LoiterDNet, a hybrid deep learning–based vessel trajectory prediction model. The model incorporates multidimensional trajectory characterization features including speed fluctuations, navigational positions, and course differentials. It integrates 1D convolutional neural networks (1D-CNN), bidirectional gated recurrent units (BiGRU), and bidirectional long short-term memory (BiLSTM) networks to capture both localized abrupt variations and long-term evolutionary patterns in loitering trajectories, thereby mitigating feature degradation phenomena. Experimental validation using trajectory data from vessels in Sagami Bay, Japan, demonstrates that the GL-LoiterDNet model outperforms 14 baseline models in prediction accuracy and robustness. The model exhibits rolling multistep trajectory prediction capability for loitering scenarios, achieving an average positioning error below 0.7 km within 10-min prediction windows. This research can provide reliable theoretical and data-driven support for continuous vessel positioning and monitoring in complex maritime operation scenarios.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5582889","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Pandemic Wave on Work Patterns and Commuting Frequency: A Retrospective Survey Analysis of COVID-19 Data in Shanghai","authors":"Meiping Yun,&nbsp;Yijia Dong,&nbsp;Yue Ma","doi":"10.1155/atr/6070065","DOIUrl":"https://doi.org/10.1155/atr/6070065","url":null,"abstract":"<p>Public health crises profoundly impact work activities and commuting behaviors. The multiple waves of COVID-19 outbreaks across cities worldwide have demonstrated that people voluntarily or involuntarily adapt their work patterns, such as shifting to remote work, and adjust their commuting choices. This study investigates changes in commuting behaviors among urban residents during three pandemic wave stages: prewave, outbreak, and postwave, focusing on work patterns, commuting frequency, and key influencing factors. A retrospective longitudinal survey was conducted in Shanghai after the first wave of COVID-19 outbreak to collect information on respondents’ work, commuting, pandemic-related, and sociodemographic characteristics. Descriptive analysis and statistical tests revealed a 35% increase in telecommuting and a 50% decrease in commuting trips during the outbreak, with near-normal levels postwave. Multinomial logit models identified key factors influencing commuting frequency, such as telecommuting, weekly working hours, and direct commutes to workplaces. Telecommuting increased commuting frequency prewave, decreased it during the outbreak, and continued to reduce it postwave. Work intensity consistently increased commuting frequency, with the most significant impact prewave and the least during the outbreak. The findings provide insights for policymakers to better understand and enhance strategies in response to unforeseen public events, including potential future pandemics like Disease X.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/6070065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Traffic and Weather Data Fusion for Traffic Prediction in Sustainable Cities","authors":"Aram Nasser,&nbsp;Vilmos Simon","doi":"10.1155/atr/1580010","DOIUrl":"https://doi.org/10.1155/atr/1580010","url":null,"abstract":"<p>Anticipating traffic patterns is a vital component in efficiently managing traffic within smart cities. This proactive approach contributes to alleviating traffic congestion, promoting environmental preservation, reducing commute times, and strengthening overall safety measures. Numerous studies have verified that external factors, such as weather conditions, exert an influence on traffic patterns. Therefore, utilizing these factors as supplementary variables can improve traffic prediction accuracy. This paper presents a novel prediction model called the multi-input sequential multihead attention (MI-SMHA) model. This model integrates weather condition information into traffic prediction tasks, aiming to enhance prediction accuracy and computational efficiency. It utilizes advanced techniques from sequential modeling and attention mechanisms, specifically tailored to handle traffic and weather data such as temperature, wind speed, precipitation, visibility, and humidity. This integration aims to leverage the complementary nature of weather conditions in forecasting traffic patterns, yet it remains flexible enough to be generalized to support a wide range of multivariate time series prediction tasks. Data from real-life traffic detectors are utilized to perform experiments and comparisons with two baseline models and three state-of-the-art models to validate and assess the efficiency of the proposed model. The MI-SMHA model was efficient and reliable in forecasting future traffic flow, significantly reducing errors compared to the other models.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1580010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145021879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Passenger Immersive Experiences in Autonomous Vehicles: A Comprehensive Review and Proposed Framework","authors":"Yufei Zhang,&nbsp;Bingjian Liu,&nbsp;Matthew Pike,&nbsp;Chengbo Wang,&nbsp;Xu Sun","doi":"10.1155/atr/4874071","DOIUrl":"https://doi.org/10.1155/atr/4874071","url":null,"abstract":"<p>This study investigates key factors influencing the immersive experience of passengers in autonomous vehicles (AVs) and proposes a novel theoretical model. In this model, four core dimensions were identified: (1) Emotional and Sensory Experience, (2) Interaction and Engagement Experience, (3) Trust and Safety Experience and (4) Dispositional Experience. It is found that Emotional and Sensory factors, such as lighting and sound, primarily affect passenger comfort and mood. In contrast, the Interaction and Engagement factors that focus on human–machine interaction (HMI) and AR/VR devices enhance passengers’ engagement. As for trust and safety factors, passengers’ confidence towards AVs is addressed through clear communication during driving processes. Dispositional factors, including technology acceptance and personalisation, contribute to passengers’ overall satisfaction in AVs. In addition, external factors such as intelligent transportation systems (ITSs), intelligent connected vehicles (ICVs) and smart city infrastructure further impact passengers’ experiences in safety and efficiency. The study highlights several emerging research areas requiring further investigation, such as multisensory feedback, dynamic personalisation and cultural inclusivity differences in AV experience. The proposed theoretical model serves as a foundation for future work aimed at enabling the design of AV systems that are more attentive and accommodating to passengers by sourcing control both domestically and externally, ultimately enhancing the passengers’ experience.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/4874071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145012336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}