Journal of Advanced Transportation最新文献

{"title":"Multitask Vehicle Signal Recognition With Dual-Speed Adaptive Weighting","authors":"Dianjing Cheng,&nbsp;Xiangyu Shi,&nbsp;Zhihua Cui,&nbsp;Xingyu Wu,&nbsp;Wenjia Niu","doi":"10.1155/atr/9961530","DOIUrl":"https://doi.org/10.1155/atr/9961530","url":null,"abstract":"<div>\u0000 <p>In mixed traffic environments, the accurate identification of vehicular devices’ modulation schemes, communication protocols, and emitter device information directly affects perception capabilities toward surrounding vehicles and infrastructure. However, existing studies predominantly focus on single-dimensional information analysis, resulting in limited completeness and accuracy in signal feature interpretation. This paper proposes a multitask learning framework (DSR-CNN-LSTM) for collaborative identification of this information. Furthermore, to mitigate task conflicts and noise interference, a dual-rate adaptive weight adjustment strategy is developed to optimize model performance through dynamic balancing of task learning rates and gradient update speeds. Experimental results demonstrate the superior performance of the DSR-CNN-LSTM framework in complex communication environments: Modulation recognition accuracy shows improvements of 20.67%, 10.38%, and 9.96% on three open-source datasets, while the weighted average recognition accuracy for communication protocols and emitter device information achieves enhancements of 45.52%, 72.21%, and 11.11%, respectively. The proposed model outperforms existing methods in both recognition precision and anti-interference capabilities, providing novel technical insights and solutions for the advancement of intelligent connected vehicle technologies.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9961530","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826767","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 Small Target Detection Algorithm for Autonomous Vehicle Scenarios","authors":"Sheng Tian,&nbsp;Kailong Zhao,&nbsp;Lin Song","doi":"10.1155/atr/8452511","DOIUrl":"https://doi.org/10.1155/atr/8452511","url":null,"abstract":"<div>\u0000 <p>In recent years, road traffic object detection has gained prominence in areas such as traffic monitoring, autonomous driving, and road safety. Nonetheless, existing algorithms offer room for improvement, particularly when detecting distant or inherently small targets, such as vehicles and pedestrians, from camera perspectives. By addressing the detection accuracy issues associated with small targets, this study introduces the YOLOv5s-LGC detection algorithm. This model incorporates a multiscale feature fusion network and leverages the lightweight GhostNet module to reduce model parameters. Furthermore, the GC attention module is employed to mitigate background interference, thereby enhancing the average detection accuracy across all categories. Through data analysis, target detection at different scales and sampling rates is determined. Experiments indicate that the YOLOv5s-LGC model surpasses the baseline YOLOv5s in detection accuracy on the Partial_BDD100K and KITTI datasets by 3.3% and 1.6%, respectively. This improvement in locating and classifying small targets presents a novel approach for applying object detection algorithms in road traffic scenarios.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/8452511","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826805","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 Improved Kernelized Correlation Filter for Extracting Traffic Flow in Satellite Videos","authors":"Dudu Guo,&nbsp;Hongbo Shuai,&nbsp;Jie Zhang,&nbsp;Yang Wang,&nbsp;Miao Sun","doi":"10.1155/atr/2728376","DOIUrl":"https://doi.org/10.1155/atr/2728376","url":null,"abstract":"<div>\u0000 <p>In satellite video vehicle tracking, due to the tracking failure and tracking loss caused by similar characteristics of the target and obstacle occlusion, respectively, the traffic flow extraction accuracy is reduced. To address these issues, an improved traffic flow extraction method for satellite video based on kernelized correlation filter (KCF) was proposed. First, we introduced a multifeature fusion strategy into the KCF based on the discrete Fourier transform (DFT) framework to enhance vehicle tracking accuracy and reduce tracking drift and jumps. Second, we utilized the Kalman filter for trajectory prediction to reduce the loss of target during vehicle tracking. Compared with other mainstream algorithms on the satellite video dataset, the results showed that the tracking accuracy and success rate of the proposed method reached 86.74% and 79.96%, respectively. Finally, the virtual detection line method was used to extract the traffic flow. The experimental results showed that compared with the real traffic flow data obtained by visual method, the accuracy of satellite video traffic flow extraction by virtual detection line was 98.48% under noncongestion condition and 90.18% under congestion condition.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/2728376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826806","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":"Induced Traffic Volume Prediction of a New Highway Based on the ESE Gravity Model","authors":"Yifan Li,&nbsp;Mengmeng Zhang","doi":"10.1155/atr/1189526","DOIUrl":"https://doi.org/10.1155/atr/1189526","url":null,"abstract":"<div>\u0000 <p>Induced traffic volume is an important indicator for evaluating the feasibility of traffic project construction and predicting traffic demand. However, among the many models used in engineering to predict induced traffic volume, the economic spillover effects of new projects are not considered. To enhance the rationality of induced traffic volume prediction and to refine the prediction model, this study takes into account the economic spillover effects based on an analysis of the factors influencing induced traffic volume. Based on models of accessibility and regional economic potential, an economic spillover effect gravity model is proposed that considers the impact of the economy on induced traffic volume. The prediction results are more sensitive to economic factors and can reflect the driving role of the economy in regional traffic.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/1189526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801704","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":"Intersection Complexity Quantification Considering Driver Behavior Characteristics and Subjective Cognition","authors":"Fengxiang Guo,&nbsp;Lei Yang,&nbsp;Chang’an Xiong,&nbsp;Wenchen Yang,&nbsp;Wei Li,&nbsp;Yiwen Zhou","doi":"10.1155/atr/6161135","DOIUrl":"https://doi.org/10.1155/atr/6161135","url":null,"abstract":"<div>\u0000 <p>Intersections with high complexity often present an increased risk of accidents, thereby reducing traffic safety. Current models for measuring intersection complexity primarily focus on objective factors that influence intersection operation. However, they fail to consider the impact of intersection complexity on driver behavior or the feedback mechanism drivers exhibit in response to complex traffic environments at intersections. This study aims to investigate the intrinsic connection between driver behavior and intersection complexity. A real-vehicle experiment was conducted using three two-phase signal-controlled level intersections, each varying in objective complexity. Data on seven indices related to driver behavior characteristics and subjective cognition were collected from 28 participants during the experiment. Two methods were employed to analyze the data: (1) a descriptive analysis of driving behavior characteristics under varying levels of intersection complexity and (2) an entropy-object topologically comprehensive evaluation method for measuring two-phase intersection complexity based on driver behavior characteristics and subjective cognition. The results indicated that (1) drivers’ subjective perceptions of the complexity of two-phase signal-controlled intersections significantly differed from the calculated objective complexity, (2) differences in the effects of varying signal transition methods on driver behavior at complex intersections were not statistically significant, and (3) a two-phase intersection complexity measurement model based on driver behavior characteristics and subjective perceptions was developed and validated. These findings contribute to understanding the intrinsic relationship between driver behavior and intersection complexity in urban settings. Future research could integrate intelligent algorithms to enhance the safety of autonomous vehicles navigating intersections.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/6161135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143793336","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":"Solving the Electric Share-A-Ride Problem Using a Hybrid Variable Neighborhood Search Algorithm","authors":"Vincent F. Yu,&nbsp;Sy Hoang Do,&nbsp;Pham Tuan Anh,&nbsp;Cheng-Ta Yeh","doi":"10.1155/atr/6687585","DOIUrl":"https://doi.org/10.1155/atr/6687585","url":null,"abstract":"<div>\u0000 <p>This paper extends the share-a-ride problem (SARP) by incorporating electric vehicles (EVs) to reduce greenhouse gas (GHG) emissions, thus addressing environmental concerns. We introduce this new extension as the electric share-a-ride problem (E-SARP). We aim to generate E-SARP routing plans where EVs serve all passenger and parcel requests while visiting charging stations (CSs) as necessary for recharging. The objective is to maximize total profit from fulfilling passenger and parcel requests. We develop a mixed-integer programming (MIP) model and propose a hybrid algorithm based on the variable neighborhood search (VNS) framework, integrated with a simulated annealing (SA) acceptance criterion (HVNS). The MIP model provides optimal solutions for small E-SARP instances using the CPLEX solver, while the HVNS algorithm is designed to solve larger E-SARP instances. Numerical experiments are conducted to assess the performance of the proposed HVNS and to provide managerial insights, demonstrating that the use of EVs can effectively address environmental concerns without significantly compromising the profitability of the transportation network.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/6687585","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143793334","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 Study of Mixed Platooning Considering Driver Perceptual Uncertainty","authors":"Junfeng Jiang,&nbsp;Yikang Rui,&nbsp;Bin Ran","doi":"10.1155/atr/5366331","DOIUrl":"https://doi.org/10.1155/atr/5366331","url":null,"abstract":"<div>\u0000 <p>Human-driven vehicles (HDVs) are the most critical element in mixed platoon research for their uncertainty. This paper presents a novel car-following model that considers the driver’s perceived uncertainty. A mixed platoon model of HDVs and connected and autonomous vehicles (CAVs) is established. Through data analysis, the stability of this model is validated. Additionally, a meticulous comparison and analysis regarding the platoon convergence ability and stable state under various platoon grouping forms and running speeds are carried out. Further, this paper introduces a virtual spring strategy to describe the car-following relationship between mixed platoon vehicles. Numerical simulations are then employed to explore the anti-interference capabilities of different mixed platoon modes and lengths. The results indicate that CAVs can effectively attenuate the randomness of HDVs. The platoon formation and operating speed impact the stability of mixed vehicle platoons. The platooning configuration “1 + <i>n</i> + 1” as the smallest platooning unit can help mixed vehicle platoons achieve a better stable state more quickly, with the optimal platoon length being four vehicles. However, as the platoon combinations grow more complex, the optimal platooning unit tends to shorten.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/5366331","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786791","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":"Modeling Lane Changes at Freeway On-Ramps With a Novel Car-Following Model Based on Desired Time Headways","authors":"Moritz Berghaus,&nbsp;Markus Oeser","doi":"10.1155/atr/9971254","DOIUrl":"https://doi.org/10.1155/atr/9971254","url":null,"abstract":"<div>\u0000 <p>The traffic flow at freeway on-ramps is influenced not only by the lane changes made by merging vehicles but also by the longitudinal behavior of the merging vehicles and vehicles in the main lane. Existing car-following models are not suitable to represent the longitudinal behavior during merging because they are based on the idea that vehicles intend to reach a steady state, that is, constant time headway and zero speed difference, as soon as possible. At on-ramps, however, merging vehicles have time to reach this steady state until they reach the end of the on-ramp. We therefore derive a novel car-following model based on desired time headways that is able to represent this continuous adaptation toward a steady state. From this car-following model, we derive a lane change model for freeway on-ramps with seven parameters. The lane change model includes a leader selection algorithm, which enables merging vehicles to pass or be passed by vehicles in the main lane. The model also includes components to predict the lane change start time based on surrogate safety measures and to describe the lateral behavior during the lane change. Due to the resemblance to car-following models, the methodology to calibrate the lane change model at the microscopic scale can be adopted from car-following models. To validate the model, we conduct traffic simulations and compare the simulated traffic flow with trajectory data from two German freeway on-ramps. The results show that the model accurately represents the longitudinal driving behavior of merging vehicles and their followers, although it slightly overestimates the number of merging vehicles passing a vehicle in the main lane under congested traffic conditions. The simulations yield accurate headway distributions, except in cases of very risky driver behavior, and realistically capture the macroscopic speed-density relationship at the on-ramp.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9971254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143762050","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":"Ethiopian Traffic Sign Recognition Using Customized Convolutional Neural Networks and Transfer Learning","authors":"Amlakie Aschale Alemu,&nbsp;Misganaw Aguate Widneh","doi":"10.1155/atr/9971499","DOIUrl":"https://doi.org/10.1155/atr/9971499","url":null,"abstract":"<div>\u0000 <p>Intelligent transportation systems rely greatly on their capacity to identify and recognize traffic signs. Traffic signs are important for modern transportation systems because they keep roads safe and help drivers, especially in areas like Ethiopia where sign designs are unique and diversified. In this study, we presented a convolutional neural network (CNN)–based model for Ethiopian traffic sign recognition (ETSR) purposes. We applied the transfer learning technique to fine-tune the pretrained models, namely, MobileNet, VGG16, and ResNet50. Both training and model hyperparameters are fine-tuned, and the 11,000 Ethiopian traffic sign images, which have 156 unique signs, are leveraged to build the new models. Optimizer, batch size, learning rate, and epoch are among the tuned training hyperparameters. All convolutional bases (learning layers) are trained using new weights. We built the fully connected layer of each model from two batch normalization layers and two dense layers. The output layer of the models has 156 units (neurons) with a softmax activation layer. The performances of newly developed models are rigorously compared with those of the base (pretrained) models. The best model was also selected after rigorous experiments. Based on the experiment, we achieved testing accuracy of 97.91%, 93.45%, and 80.18% for fine-tuned VGG16, MobileNet, and ResNet50, respectively.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9971499","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726797","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":"Resilience Assessment and Recovery Strategy for High-Speed Railway Networks Considering Spatiotemporal Dynamic Characteristics","authors":"Zhuo Li,&nbsp;Ruichun He,&nbsp;Wenxia Li,&nbsp;Juncheng Bai","doi":"10.1155/atr/9890906","DOIUrl":"https://doi.org/10.1155/atr/9890906","url":null,"abstract":"<div>\u0000 <p>The service link in a high-speed railway (HSR) network has an evident temporal attribute, and conventional research methods ignore the importance of temporal information in resilience assessments. Hence, in this study, an HSR service network model based on a temporal network framework is constructed, and an HSR service network resilience assessment method considering spatiotemporal dynamic characteristics is proposed. Considering the heterogeneity of train flow in different time periods and taking the time cost of the shortest temporal path as the network performance measure, a resilience assessment model is established based on the HSR temporal service network, and an algorithm for solving the network performance is designed. Taking China’s HSR network as a case study, the research results showed that the optimal recovery strategy exhibited a higher resilience value than four other recovery strategies. In different spatiotemporal dimensions, the impact of disturbance events on network resilience is different, and the corresponding optimal restoration sequence is also different, making the resilience of the HSR network to exhibit evident differences in the spatiotemporal distribution. In addition, an increase in the number of repair resources is not proportional to the improvement in network resilience. The railway emergency department should comprehensively consider the spatiotemporal characteristics of the disturbance distribution and reasonably determine the restoration sequence and the number of repair resources.</p>\u0000 </div>","PeriodicalId":50259,"journal":{"name":"Journal of Advanced Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/atr/9890906","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689739","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}