Journal of Advanced Transportation最新文献

{"title":"A Systematic Review of VANET Routing Protocols for Intelligent Transport Systems (ITSs)","authors":"Roopa Tirumalasetti,&nbsp;Sunil Kumar Singh,&nbsp;Pradeep Kumar Roy,&nbsp;Sanket Mishra","doi":"10.1155/atr/7999623","DOIUrl":"https://doi.org/10.1155/atr/7999623","url":null,"abstract":"<p>The swift improvement of wireless communication technology has aided the creation of vehicular ad hoc networks (VANETs) as a revolutionary option for the realization of intelligent transportation systems (ITSs). VANETs facilitate seamless communication between vehicles and infrastructure (V2I) and among the vehicles themselves (V2V). These networks can enhance safety and traffic control while providing various infotainment options. To ensure stable and efficient communication in highly dynamic and quickly changing vehicular contexts, effective data packet routing is a crucial component of VANETs. This survey delves further into the VANET routing algorithms for ITS. The study aims to evaluate the effectiveness and acceptability of various routing protocols suggested for VANETs while considering their unique requirements and difficulties. The review covers ad hoc on-demand distance vector (AODV) and dynamic source routing (DSR), as well as more current strategies designed specifically for VANETs, such as geographic routing, cluster-based routing, and hybrid routing protocols. The review assesses the routing algorithms based on several vital parameters, including packet delivery ratio (PDR), end-to-end delay, throughput, network overhead, scalability, and robustness. This detailed assessment supports aspiring researchers in acquiring a better knowledge of the benefits and drawbacks of the routing algorithms currently used in VANETs.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/7999623","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569373","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":"Unified Identification Method for Different Types of Traffic Conflicts Based on Vehicle Projection","authors":"Jingan Wu,&nbsp;Shunying Zhu,&nbsp;Qiucheng Chen,&nbsp;Yixuan Wang","doi":"10.1155/atr/9929178","DOIUrl":"https://doi.org/10.1155/atr/9929178","url":null,"abstract":"<p>As a common method for identifying traffic risks, the traffic conflict technique needs to be more uniform in identifying different types of traffic conflicts and comparing the effectiveness of different conflict identification methods. To establish a unified identification method for traffic conflicts, this study describes the conditions under which vehicles collide through vehicle projection and constructs the Traffic Conflict of Unified Identification (TU) based on the time of vehicle collision to estimate the degree of risk of collision between vehicles. Using HighD high-resolution traffic flow trajectory data with traffic conflict counts and cumulative exposure collision times, the differences and causes of different methods for all-type and subtype conflict recognition were comparatively analyzed. From the perspective of a single traffic conflict, the correlation between conflict severity and the intensity of risk-avoidance behaviors is proposed to compare and analyze the capability of the identification methods. The results show that (1) the unified identification method can better identify traffic conflicts without distinguishing the type of traffic conflicts, reducing the misjudgment of following conflicts and omission of lane changing conflicts to a greater extent, and being less affected by the predetermination of conflict types. (2) Compared with the traditional time to collision (TTC), TU has a better correlation between conflict severity and the intensity of vehicle-avoidance behaviors, regardless of whether the conflict severity is characterized by the minimum collision time or the cumulative exposure collision time. The unified identification method improves the accuracy of traffic conflict identification, expands the scenario applicability of traffic conflict technology, and provides a new way for real-time traffic conflict technology risk prediction for autonomous driving.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9929178","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568746","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 CVaR-Based Optimal Perimeter Control Framework With Consideration of Boundary Queue Length","authors":"Ying Zhang,&nbsp;Zhenwu Lei,&nbsp;Yuntao Shi,&nbsp;Yan Wang,&nbsp;Xiang Yin","doi":"10.1155/atr/7280111","DOIUrl":"https://doi.org/10.1155/atr/7280111","url":null,"abstract":"<p>Perimeter control is a method used to manage clusters of intersections at regional boundaries, based on the macroscopic fundamental diagram (MFD). However, the MFD-based model of urban traffic networks often contains parameter uncertainty and system noise, leading to excessive queues at regional boundaries and reducing the effectiveness of perimeter control. To address these challenges, this paper proposes an optimized control framework for urban traffic networks based on the Conditional Value at Risk (CVaR). The framework includes a Markov jump linear system model to simulate the traffic network and uses CVaR to measure congestion risk caused by uncertainty. The CVaR-based optimization objectives and the regional boundary queue model are established to enhance control strategies. The proposed CVaR-based optimal perimeter control framework is compared with no control, bang–bang control, and stochastic model predictive control through simulation. Results show that the CVaR-based framework significantly reduces the number of vehicles and travel time, outperforming the other three control strategies in alleviating congestion. This study demonstrates the potential of CVaR-based control in improving urban traffic management.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/7280111","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569006","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":"Research on the Network Hierarchy Structure Based on Train Schedules","authors":"Yihan Zhang,&nbsp;Guorong Liao,&nbsp;Yanling Sheng,&nbsp;Xiaohu Zhang","doi":"10.1155/atr/5712800","DOIUrl":"https://doi.org/10.1155/atr/5712800","url":null,"abstract":"<p>China’s high-speed rail (HSR) system has expanded rapidly, with stations now serving nearly all major cities across the country. The network is structured around the “Eight Verticals and Eight Horizontals” framework, which possesses several distinct characteristics. This study utilizes train schedule data to extract station information for constructing an origin–destination (O/D) matrix. Methods including centrality measurement, edge strength analysis, correlation analysis, and GIS visualization are employed to examine the hierarchical structure of China’s HSR network at both national and urban agglomeration scales. The findings reveal that (1) most cities have limited train services and low connectivity, while cities with high connectivity are relatively few and concentrated in regions such as Beijing–Tianjin–Hebei (BTH) and the Yangtze River Delta (YRD). The degree distribution follows an exponential pattern and aligns with the “80/20” rule, and the network exhibits small-world properties. (2) Based on nodal degree, HSR cities are classified into four tiers, which exhibit a pyramid-shaped distribution in terms of both quantity and proportion. Geographically, these cities are predominantly located southeast of the “Heihe–Tengchong Line,” with notable clusters along the Yangtze River and coastal areas. (3) Network edges are also categorized into four levels. First-level edges connect economically developed cities such as Beijing, Shanghai, and Shenzhen, while second-level edges are mainly distributed along the Yangtze River corridor. (4) Among the major urban agglomerations, the YRD and Mid-Yangtze River (MYR) regions show the highest centrality, followed by BTH and the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The Chengdu–Chongqing (CC) region ranks the lowest. Relative centrality analysis indicates a clear hierarchical distribution within agglomerations such as YRD, whereas GBA and CC display more fragmented connectivity patterns. The network structures across regions are diverse: YRD is oriented east–west, MYR forms a triangular layout, CC exhibits a radial pattern, BTH resembles a “Z” shape, and GBA is structured like a tree.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5712800","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568871","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":"Multimode Traffic Network Equilibrium and System Optimization With Tradable Credit Scheme","authors":"Shixu Liu,&nbsp;Yijian Xu,&nbsp;Said M. Easa,&nbsp;Guoliang Huang,&nbsp;Jiacheng Zhong,&nbsp;Haoyan Sun","doi":"10.1155/atr/2029741","DOIUrl":"https://doi.org/10.1155/atr/2029741","url":null,"abstract":"<p>In this paper, the equilibrium problem of multimode traffic networks (auto and transit networks) with the tradable credit scheme (TCS) is studied. The mathematical programming model with the Logit function as the mode-split function is proposed to study the users’ travel mode and route choice behavior in the multimode network under the TCS. Based on the proposed network equilibrium model, Pareto-improving is further investigated. Research shows that the Pareto-improving under the TCS is a sufficient condition for reducing the system’s total cost. A Pareto-improving scheme for specific user categories is developed. For the Pareto-improving scheme, all users do not become worse and some or all users become better. In addition, a bilevel programming model is also proposed. The upper level minimizes the social total and transit operating costs by optimizing the number of free credits issued and the frequency of transit departure. The lower level is the traffic equilibrium assignment model of the multimode networks to determine traffic flows. The model is solved by combining the genetic algorithm (GA) and the heuristic algorithm based on the Method of Successive Averages (MSAs). The correctness and validity of the models, propositions, and algorithms are verified using two numerical examples.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/2029741","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568870","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 Redistribution Based on Rolling Horizon Optimization in Multimodal Emergency Evacuation of Transportation Hubs","authors":"Zhiman Xu,&nbsp;Yuqi Shao,&nbsp;Páraic Carroll,&nbsp;Davis Bencolias Tinka,&nbsp;Zhi Dong,&nbsp;Qiang Bai","doi":"10.1155/atr/3287477","DOIUrl":"https://doi.org/10.1155/atr/3287477","url":null,"abstract":"<p>Passenger emergency evacuation is a critical aspect of operations at multimodal transportation hubs. When a large number of passengers gather within the hub, it is necessary to evacuate them efficiently from multimodal transfer points to ensure their safe departure and to prevent unforeseen incidents such as stampedes. To improve the efficiency of emergency evacuation under limited evacuation capacity conditions, passenger redistribution can be adopted as a strategy to optimize the evacuation process. This study proposes a passenger redistribution model based on a rolling horizon optimization framework for the emergency evacuation of multimodal transportation hubs. The model is formulated as a multiobjective optimization problem with two objectives: (1) minimizing the total evacuation time to maximize the overall evacuation efficiency and (2) minimizing differences in waiting times among different travel modes to reduce imbalance across them. The problem is solved using the NSGA-II algorithm. A case study based on Terminal 3 of Beijing Capital International Airport is conducted to demonstrate the effectiveness of the proposed passenger redistribution model. The results show that the proposed model can generate effective passenger redistribution plans for emergency evacuation of the transportation hubs. Furthermore, the findings indicate that passenger redistribution is particularly suitable when there is a significant mismatch between evacuation capacity and evacuation demand. However, its effectiveness is limited when a large number of passengers are initially stranded, while it proves to be more effective when the initial number of stranded passengers is relatively small.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/3287477","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568246","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":"Unlocking the Nexus of Carbon Reduction in China’s Road Transportation: A Two-Stage Decomposition Analysis","authors":"Guan Wang,&nbsp;Jingyi Ji,&nbsp;Ming Chen,&nbsp;Xiao Liu","doi":"10.1155/atr/4325821","DOIUrl":"https://doi.org/10.1155/atr/4325821","url":null,"abstract":"<p>China faces urgent road transportation carbon emission (RTC) reduction under its “dual carbon” goals. Achieving RTC reduction necessitates not only identifying key driving factors but also clarifying the sectoral linkages closely associated with RTC. Within an input–output framework, this study integrated structural decomposition analysis (SDA) and production-theoretical decomposition analysis (PDA) to construct a two-stage decomposition method. Applying this approach, we examined the drivers and sectoral connections of RTC from 2002 to 2020. The findings reveal that (1) due to its service-oriented nature, 72.6% of RTC stemmed from transportation services fulfilling intermediate demand from other sectors, with the construction sector exhibiting the largest intermediate demand and thus contributing most significantly to RTC. (2) The final demand effect was the dominant driver behind RTC growth, accounting for a cumulative increase of 590.3 Mt, though its influence has weakened since 2017. (3) The steady decline in emission intensity served as the primary factor reducing RTC, resulting in a cumulative decrease of 190.8 Mt, attributable mainly to advances in energy technology, improved energy efficiency, and shifts in energy structure. We recommend that the transportation department should strive to improve energy technology and enhance efficiency, thereby effectively reducing carbon emission intensity. Meanwhile, government should actively adjust industrial structure and optimize transportation layout to further reduce RTC.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/4325821","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568090","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":"An Approach of Highway Toll Revenue Calculation Based on the Prediction of OD Matrix","authors":"Jian Wan,&nbsp;Yinghao Chen,&nbsp;Mengyu Jiang,&nbsp;Hua Tong,&nbsp;Runsheng Wang","doi":"10.1155/atr/5583538","DOIUrl":"https://doi.org/10.1155/atr/5583538","url":null,"abstract":"<p>Accurate toll revenue calculation is essential for highway operation management and construction planning. Reliable forecasting requires a thorough understanding of evolving traffic flow patterns and regional origin–destination (OD) distributions. However, challenges such as incomplete data collection and difficulties in capturing transit traffic patterns often hinder accurate OD estimation. To address this, we propose a bidirectional long short-term memory (Bi-LSTM)–based method for OD matrix estimation in highway revenue prediction. Using real-world data from the Hanghui Highway in China, the proposed model is evaluated against eight benchmark approaches, including traditional machine learning and deep learning models. Results show that Bi-LSTM achieves the best performance, with a root mean squared error (RMSE) of 2.8922 and a mean absolute error (MAE) of 1.1890, outperforming all comparison methods. These findings demonstrate not only the precision and robustness of the Bi-LSTM approach but also its novelty in bridging OD estimation with revenue forecasting, providing new insights for the intelligent highway management and operation as well as the highway revenue prediction and analysis.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5583538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568088","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 Multiview-Integrated Framework for Traffic Scene Understanding Based on YOLO and LLM","authors":"Yixuan Zhao,&nbsp;Tian Ma,&nbsp;Zihe Wang,&nbsp;Ziyu Zhang,&nbsp;Chenxi Li,&nbsp;Shuai Liu,&nbsp;Zhiyong Cui,&nbsp;Mengqi Lv,&nbsp;Haiyang Yu,&nbsp;Zixi Peng","doi":"10.1155/atr/2814128","DOIUrl":"https://doi.org/10.1155/atr/2814128","url":null,"abstract":"<p>Traffic scene understanding plays a crucial role in reasoning about and predicting relationships among entities in traffic images. It focuses on analyzing behavioral interaction patterns and global semantic associations to support higher-level traffic requirements. However, few existing frameworks can achieve comprehensive scene understanding and semantic description in complex traffic environments. In particular, effective multiview semantic association modeling is still lacking. To address these challenges, we propose multiview large language model (MVLLM), which integrates YOLO-based object detection with the reasoning ability of large language models (LLMs). Through prompt engineering, MVLLM utilizes the visual information extracted by YOLO to constrain the semantic space and guide the reasoning behavior, thereby enhancing the scene parsing capability. Meanwhile, we design a Chain-of-Thought (CoT) reasoning mechanism to establish spatiotemporal associations across multiple views and to integrate their scene understanding with semantic descriptions. The framework enables intent understanding for vehicles in dynamic environments, enhancing driving safety. It also provides comprehensive semantic descriptions for traffic management agencies, supporting holistic analyses of vehicles, roads, and environmental contexts.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/2814128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315610","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":"Trajectory Semanticization: A Method of Accompany Vehicle Discovery Inspired by Semantic Similarity","authors":"Xinpeng Xu,&nbsp;Junhao Li,&nbsp;Weiguo Wu","doi":"10.1155/atr/1464526","DOIUrl":"https://doi.org/10.1155/atr/1464526","url":null,"abstract":"<p>The study of accompanying vehicles is a hot topic in the field of intelligent transportation. Because of the multiple selectivity of the traffic path and the loss of sampling in traditional companion vehicles discovery, the method based on path similarity mining will result in the omission of the companion candidates. This paper recognizes that the upstream and downstream relevance of trajectory intentions in traffic is similar to the contextual relevance of text semantics, as inspired by the semantic similarity of texts. Simultaneously, taking into account the generalization and tolerance of semantic processing, a companion vehicle discovery method based on “trajectory semantics” similarity is proposed. First, this paper proposes a trajectory semantic vectorized representation method trajectory semantic to vector (TS2vec), which realizes the low-dimensional dense vectorization of the trajectory in the context of dynamic time slicing of the trajectory, fusion of the temporal and spatial characteristics of the trajectory, and text information. Then, based on the “trajectory pair,” this paper proposes the trajectory pair bidirectional GRU (TPBi-GRU) model. This paper constructs forward and reverse subnetworks using the trajectory pair set—which is made up of the actual trajectory and ts sampled trajectories—realizes parameter transfer and contribution during training; gains a thorough understanding of trajectory semantics; and mines the internal relationship between vehicles more effectively. Finally, given the difference in the degree of contribution of the road shape in forming the adjoint pattern, and the sensitivity of the attention mechanism to local features, the attention mechanism is used to weigh the key nodes that affect the trajectory shape in order to obtain a more accurate trajectory representation. The experimental results show that the method in this paper can discover local and overall concomitant patterns more effectively and effectively overcome the interference of multiple selectivity of traffic paths on concomitant pattern mining.</p>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2026 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1464526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147320827","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}