International Journal of Transportation Science and Technology最新文献

{"title":"Classification of traffic accidents’ factors using TrafficRiskClassifier","authors":"Wei Sun ,&nbsp;Lili Nurliyana Abdullah ,&nbsp;Fatimah binti Khalid ,&nbsp;Puteri Suhaiza binti Sulaiman","doi":"10.1016/j.ijtst.2024.05.002","DOIUrl":"10.1016/j.ijtst.2024.05.002","url":null,"abstract":"<div><div>The TrafficRiskClassifier model proposed in this study adopts an innovative approach integrating migration learning, image classification, and self-supervised learning, with the goal of significantly enhancing the accuracy and efficiency of traffic accident risk analysis. Compared with traditional traffic safety analysis techniques, this model focuses on utilizing contextual information and situational data from traffic accidents to achieve higher risk classification accuracy. The core of this approach is to deeply mine and analyze the detailed information in the accident environment, to provide more scientific and effective support for traffic accident risk prevention and response. Initially, by integrating migration learning with image classification techniques, the model efficiently extracts pivotal features from complex traffic scenarios and forms initial risk assessments. Subsequently, self-supervised learning is incorporated in this study, augmenting the model's capability to comprehend and categorize accident imagery. The TrafficRiskClassifier model exhibits a generalization ability of 91.82%, 85.16%, and 80.92% on individual classification tasks, respectively, signifying its robust learning capacity and proficiency in managing unseen data. Furthermore, the TrafficRiskClassifier model delineates a functional nexus between accident risk and variables such as weather, road conditions, and personal factors, employing a polynomial regression approach. This methodology not only amplifies the predictive precision of the model but also renders it versatile across diverse scenarios. Through analyzing various polynomial functions, the model achieves improved accuracy in classifying different risk levels. The outcomes demonstrate that the TrafficRiskClassifier model can efficaciously amalgamate contextual information within traffic scenarios, thereby achieving more precise classification of traffic accident risks, and consequently serving as an invaluable instrument for urban traffic safety management.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 328-344"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141039967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electric bus fleets during urban flash floods: A mixed bus fleet strategy","authors":"Sanghuiyu Yan ,&nbsp;Pengju Ren ,&nbsp;Guohong Wu ,&nbsp;Jian Li","doi":"10.1016/j.ijtst.2024.04.006","DOIUrl":"10.1016/j.ijtst.2024.04.006","url":null,"abstract":"<div><div>Bus electrification is widely cited as a key technique to reduce carbon emissions and mitigate climate change. In some Chinese cities, the electrification rate of buses has even reached 100%. However, compared with diesel buses (DBs), electric buses (EBs) cause scheduling problems during urban flash floods due to their limited wading performance. This study proposes a mixed EB-DB fleet strategy to mitigate bus fleet problems during urban flash floods. The difference in wading height thresholds between EBs and DBs is considered in the fleet schedule. Utilizing a two-fleet strategy, the requisite number of DBs for bus depots is calculated. The mixed bus assignment problem is then solved by linear programming to establish the optimal dispatch scheme for the individual bus route. This study emphasizes the advantages of mixed bus fleets in emergency response, and contributes to improving urban transportation resilience.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 224-237"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140770271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging public cloud infrastructure for real-time connected vehicle speed advisory at a signalized corridor","authors":"Hsien-Wen Deng ,&nbsp;M Sabbir Salek ,&nbsp;Mizanur Rahman ,&nbsp;Mashrur Chowdhury ,&nbsp;Mitch Shue ,&nbsp;Amy W. Apon","doi":"10.1016/j.ijtst.2024.03.004","DOIUrl":"10.1016/j.ijtst.2024.03.004","url":null,"abstract":"<div><div>In this study, we developed a real-time connected vehicle (CV) speed advisory application that uses public cloud services, and tested it on a simulated signalized corridor for different roadway traffic conditions. First, we developed a scalable serverless cloud computing architecture leveraging public cloud services offered by Amazon Web Services (AWS) to support the requirements of a real-time CV application. Second, we developed an optimization-based real-time CV speed advisory algorithm by taking a modular design approach, which makes the application automatically scalable and deployable in the cloud using the serverless architecture. Third, we developed a cloud-in-the-loop simulation testbed using AWS and an open-source microscopic roadway traffic simulator called simulation of urban mobility (SUMO). Our analyses based on different roadway traffic conditions showed that the serverless CV speed advisory application meets the latency requirement of real-time CV mobility applications. Besides, our serverless CV speed advisory application reduced the average stopped delay (by 77%) and the aggregated risk of collision (by 21%) at the signalized intersections of a corridor. These prove the feasibility as well as the efficacy of utilizing public cloud infrastructure to implement real-time roadway traffic management applications in a CV environment.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 131-147"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A weakly-supervised deep learning model for end-to-end detection of airfield pavement distress","authors":"Zefeng Tao,&nbsp;Hongren Gong,&nbsp;Liming Liu,&nbsp;Lin Cong,&nbsp;Haimei Liang","doi":"10.1016/j.ijtst.2024.02.010","DOIUrl":"10.1016/j.ijtst.2024.02.010","url":null,"abstract":"<div><div>Accurate and timely surveying of airfield pavement distress is crucial for cost-effective airport maintenance. Deep learning (DL) approaches, leveraging advancements in computer science and image acquisition techniques, have become the mainstream for automated airfield pavement distress detection. However, fully-supervised DL methods require a large number of manually annotated ground truth labels to achieve high accuracy. To address the challenge of limited high-quality manual annotations, we propose a novel end-to-end distress detection model called class activation map informed weakly-supervised distress detection (WSDD-CAM ). Based on YOLOv5, WSDD-CAM consists of an efficient backbone, a classification branch, and a localization network. By utilizing class activation map (CAM) information, our model significantly reduces the need for manual annotations, automatically generating pseudo bounding boxes with a 71% overlap with the ground truth. To evaluate WSDD-CAM, we tested it on a self-made dataset and compared it with other weakly-supervised and fully-supervised models. The results show that our model achieves 49.2% mean average precision (mAP), outperforming other weakly-supervised methods and even approaching state-of-the-art fully-supervised methods. Additionally, ablation experiments confirm the effectiveness of our architecture design. In conclusion, our WSDD-CAM model offers a promising solution for airfield pavement distress detection, reducing manual annotation time while maintaining high accuracy. This efficient and effective approach can significantly contribute to cost-effective airport maintenance management.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 67-78"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140274711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A fuzzy track-to-track association algorithm with dynamic time warping for trajectory-level vehicle detection","authors":"Siqi Wan ,&nbsp;Huaqiao Mu ,&nbsp;Ke Han ,&nbsp;Taesu Cheong ,&nbsp;Chi Xie","doi":"10.1016/j.ijtst.2024.03.001","DOIUrl":"10.1016/j.ijtst.2024.03.001","url":null,"abstract":"<div><div>Multi-source track-to-track association (TTTA), which identifies trajectories from multiple sensors or data sources of the same dynamic vehicle, is an important data fusion technique widely applied to vehicle detection in the fields of road, marine, and aviation transportation. However, issues such as time asynchrony, heterogeneous sampling intervals, and random sensing errors have posed considerable challenges to the accuracy and robustness of TTTA. Aiming to address these issues in an integrated manner, this paper proposes a TTTA algorithm that comprehensively calculates the similarity between trajectories using multiple trajectory features through dynamic time warping (DTW) and Cauchy distribution degree of membership function. Multiple experimental datasets were generated by randomly sampling real AIS trajectory data into two trajectory data sources and adding random errors. The average association accuracy of all scenarios and error levels of the proposed method reached 97.33%, far higher than other benchmark methods. Experimental results demonstrated the advantage of the proposed algorithm in various TTTA scenarios, especially its robustness in intricate trajectory situations. The results also indicated that more features can maintain the stability of associations in the presence of larger random errors, and DTW can improve association accuracy in intricate scenarios. This study provides a practical solution for the problem of time asynchrony, heterogeneous sampling intervals, and random errors in multi-source trajectory data fusion, showcasing promising applications across diverse domains.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 95-108"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140277952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unravelling route choices of large trucks using trajectory clustering and conditional Logit models","authors":"Yue Ma,&nbsp;Jan-Dirk Schmöcker,&nbsp;Wenzhe Sun,&nbsp;Satoshi Nakao","doi":"10.1016/j.ijtst.2024.04.007","DOIUrl":"10.1016/j.ijtst.2024.04.007","url":null,"abstract":"<div><div>The mobility of sizable trucks is often limited by their large size. They thus may have additional requirements on road types, road widths, and the turning radius at the intersection when travelling. Therefore, this study explores the unique needs and preferences of large truck drivers’ route choice with a focus on trip and road network characteristics. Global positioning system (GPS) trajectory data from the central Kansai area of Japan with numerous ports and freight terminals are used. Trajectories are considered to have the same origin (destination) if their starting (ending) coordinates are in the same 500 m × 500 m mesh. For the trajectories of the same pair of origin-destination (OD) meshes, several route clusters are obtained based on geographical configuration using a QuickBundles algorithm. Sampling techniques are employed to equalize the number of input points for each vehicle trajectory and the optimal number of clusters is determined automatically by our algorithm based on the silhouette coefficient. By taking the clusters as route choice options for an OD pair, a conditional logit model is used to identify the factors that influence the route choice considering both vehicle- and trip-specific attributes. The results quantify the preference of trucks for wider roads and toll routes, as well as aversion to long distances and turns. The heterogeneity in route choice based on vehicle type, trip time (date), and trip purpose is also evident. The findings of this study can provide insights for freight road network design and optimization.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 238-250"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140758354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance characterization of long-term aged bitumen: Field and laboratory investigation","authors":"S. Tejeshwini,&nbsp;K.H. Mamatha,&nbsp;S.V. Dinesh","doi":"10.1016/j.ijtst.2024.04.003","DOIUrl":"10.1016/j.ijtst.2024.04.003","url":null,"abstract":"<div><div>Aging of binder affects the service life of flexible pavements. Binder’s aging involves changes in its physical, rheological, chemical, and morphological characteristics, making it hard and brittle and resulting in pavement deterioration. Oxidation and volatalization are two main mechanisms involved in aging. Aging stiffens the binder as it increases the viscosity of binder resulting in pavement distresses like fatigue cracking, ravelling, and thermal cracking. Hence, it is obligatory to examine the aging effects on binder to predict the service life of flexible pavements. In this study, core samples are collected from 15 years aged in-service pavement section, and fresh binder was aged for varying aging duration in the laboratory to simulate field aging condition. Field aged and laboratory aged binders were subjected to physical, chemical, rheological, and morphological investigations for evaluating the variation of these properties with long-term aging (LTA). It is evident that the traffic speed influences the dynamic viscosity of binders. With aging, the rutting resistance of binders improved, and fatigue resistance of binders diminished considerably. 15 years field aging condition is simulated in the laboratory, and the results showed that the severity of aging in binder increases with the pavement depth in the field.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 175-191"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140763798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the impacts of right-turn-on-red, exclusive turn lanes, and pedestrian movements on the efficiency of urban transportation networks","authors":"Hao Liu,&nbsp;Zecheng Xiong,&nbsp;Vikash V. Gayah","doi":"10.1016/j.ijtst.2024.02.007","DOIUrl":"10.1016/j.ijtst.2024.02.007","url":null,"abstract":"<div><div>Previous studies demonstrated that restricting left turning movements can enhance transportation network efficiency. However, this strategy can lead to significant increases in the volume of right-turn movements. While these right-turn movements do not conflict with opposing through traffic, they still must interact with pedestrians in adjacent crosswalks. Further, their movement is influenced by the presence of right-turn-on-red (RTOR), which is commonly applied at signalized intersections to improve intersection capacity, and the presence of exclusive right-turn lanes. This paper examines the influence of these three factors (pedestrian activity, RTOR, and exclusive right-turn lanes) on vehicular operational performance at a network-wide level. Simple grid network structures are considered due to their generalizability and the performances of three network types are tested: two-way streets that accommodate left turns, two-way streets that prohibit left turns, and one-way streets. The results reveal that when there are no pedestrians, right-ROTR can improve the operational performance regardless of the existence of exclusive lanes, especially for the networks restricting left-turn movements, and the presence of exclusive turn lanes increases the benefits obtained by allowing RTPR. The results also suggest that allowing RTPR is more important than providing exclusive lanes when the traffic load is light; however, under heavier traffic, exclusive turn lanes become more important. The presence of pedestrians reduces overall network performance and the benefits provided by RTPR for most scenarios, as expected. This decrease in performance is larger for networks made up of two-way streets compared to those made up of one-way streets. Exclusive lanes are also found to be critical for two-way streets with left turns protected to maintain network efficiency. Overall, prohibiting left turns on two-way streets still provides the largest operational performance of all networks with these features considered.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 52-66"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139828623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement of public acceptance of TDM policies using public policy acceptance (PPA) and value belief norm (VBN) combination approach","authors":"Nindyo Cahyo Kresnanto","doi":"10.1016/j.ijtst.2024.02.006","DOIUrl":"10.1016/j.ijtst.2024.02.006","url":null,"abstract":"<div><div>One strategy to overcome the problem of imbalance between the demand and supply of road transportation that causes congestion is to apply transport demand management (TDM). TDM is a series of transportation policies aimed at achieving sustainable transportation by reducing the use of private vehicles and prioritizing public transport and/or non-motorized vehicles. The level of public acceptance of TDM largely determines the success of TDM implementation. Through the value belief norm (VBN) theory approach, it can be seen that public acceptance of TDM policies will be influenced by how high the norm of community partiality towards the environment. The level of public acceptance of a TDM regulation can also be measured by the public policy acceptance (PPA) model. The results show that the acceptance of TDM strategy implementation was significantly influenced by the pro-environment attitude of the community. The PPA model result showed that people tend to be skeptical of the implementation of TDM policies.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 39-51"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139829001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining causal factors of traffic conflicts at intersections using vehicle trajectory data","authors":"Xiaoyan Xu ,&nbsp;Xuesong Wang ,&nbsp;Ruolin Shi","doi":"10.1016/j.ijtst.2024.02.011","DOIUrl":"10.1016/j.ijtst.2024.02.011","url":null,"abstract":"<div><div>Conflict severity results from the complex interactions between the roadway and environmental characteristics and the vehicle motion. Understanding how and to what extent a vehicle is influenced by roadway and surrounding road users during a conflict is helpful in analyzing the causal mechanisms of collisions, thus providing insights into roadway safety improvement countermeasures. This study utilized the NGSIM vehicle trajectory datasets to investigate the causal factors in conflicts at intersections by analyzing roadway-to-vehicle and vehicle-to-vehicle interactions. In order to remove the outliers and white noise existing in the raw data, vehicle trajectories were reconstructed by applying discrete wavelet transform and Kalman filtering (KF). Generalized time-to-collision was adopted to detect and measure the severity of conflicts, by which 1127 conflict events were extracted. Path analysis (PA) models were then established to determine in exactly which ways the roadway-to-vehicle and vehicle-to-vehicle interactions were related to conflict severity. Various roadway and environmental characteristics such as traffic flow average speed, percentage of trucks, and intersection skew angle were included in the models. The results indicate that the roadway and environmental characteristics have both direct and indirect effects on conflict severity. In the indirect effects, the kinematics of conflicting vehicles such as the average and standard deviation of speed, plays an intermediate role in linking roadway factors and conflict outcome. The framework of this study can be used to assess roadway readiness for both human-driven and automated vehicles.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"17 ","pages":"Pages 79-94"},"PeriodicalIF":4.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140470257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}