IET Intelligent Transport Systems最新文献_第4页

Map-matching for cycling travel data in urban area 城市地区自行车出行数据的地图匹配

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-19 DOI: 10.1049/itr2.12567

Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn

{"title":"Map-matching for cycling travel data in urban area","authors":"Ting Gao, Winnie Daamen, Panchamy Krishnakumari, Serge Hoogendoorn","doi":"10.1049/itr2.12567","DOIUrl":"https://doi.org/10.1049/itr2.12567","url":null,"abstract":"To promote urban sustainability, many cities are adopting bicycle-friendly policies, leveraging GPS trajectories as a vital data source. However, the inherent errors in GPS data necessitate a critical preprocessing step known as map-matching. Due to GPS device malfunction, road network ambiguity for cyclists, and inaccuracies in publicly accessible streetmaps, existing map-matching methods face challenges in accurately selecting the best-mapped route. In urban settings, these challenges are exacerbated by high buildings, which tend to attenuate GPS accuracy, and by the increased complexity of the road network. To resolve this issue, this work introduces a map-matching method tailored for cycling travel data in urban areas. The approach introduces two main innovations: a reliable classification of road availability for cyclists, with a particular focus on the main road network, and an extended multi-objective map-matching scoring system. This system integrates penalty, geometric, topology, and temporal scores to optimize the selection of mapped road segments, collectively forming a complete route. Rotterdam, the second-largest city in the Netherlands, is selected as the case study city, and real-world data is used for method implementation and evaluation. Hundred trajectories were manually labelled to assess the model performance and its sensitivity to parameter settings, GPS sampling interval, and travel time. The method is able to unveil variations in cyclist travel behavior, providing municipalities with insights to optimize cycling infrastructure and improve traffic management, such as by identifying high-traffic areas for targeted infrastructure upgrades and optimizing traffic light settings based on cyclist waiting times.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 11","pages":"2178-2203"},"PeriodicalIF":2.3,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12567","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666095","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}

引用次数: 0

A multi-objective optimization model for RSU deployment in intelligent expressways based on traffic adaptability 基于交通适应性的智能高速公路 RSU 部署多目标优化模型

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-16 DOI: 10.1049/itr2.12568

Xiaorong Deng, Yanping Liang, Dongyu Luo, Jiangfeng Wang, Xuedong Yan, Jinxiao Duan

{"title":"A multi-objective optimization model for RSU deployment in intelligent expressways based on traffic adaptability","authors":"Xiaorong Deng, Yanping Liang, Dongyu Luo, Jiangfeng Wang, Xuedong Yan, Jinxiao Duan","doi":"10.1049/itr2.12568","DOIUrl":"https://doi.org/10.1049/itr2.12568","url":null,"abstract":"The intelligent expressway exemplifies a prominent application of intelligent transportation systems. Roadside units (RSUs), strategically deployed alongside roadways, serve as pivotal infrastructure in facilitating interactions within intelligent expressways. A well-planned RSU deployment strategy is crucial for enhancing service quality, it necessitates balancing performance improvements with significant financial costs due to the limited transmission range and high deployment expenses of RSUs. To tackle these challenges, an adaptive approach for RSU deployment is proposed, which takes into account economic feasibility, service requirements, and dynamic traffic demands. A traffic adaptability-based RSU deployment (TARD) model, which integrates factors such as deployment cost, the effectiveness of information coverage, road network topology, and traffic flow characteristics have been devised. The TARD aims to minimize deployment expenses while maximizing the benefits of information coverage and alignment with road traffic demands. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to solve this optimization model. To validate its efficacy, simulations are conducted on the G2 expressway in Shandong Province, China, demonstrating the superior performance of the TARD compared to three other deployment strategies. Ablation experiments further underscore the critical role of tunnel deployments and comprehensive coverage along long sections in bolstering network connectivity and elevating service quality.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 11","pages":"2204-2223"},"PeriodicalIF":2.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12568","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665892","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}

引用次数: 0

ADWNet: An improved detector based on YOLOv8 for application in adverse weather for autonomous driving ADWNet：基于 YOLOv8 的改进型检测器，用于恶劣天气下的自动驾驶应用

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-15 DOI: 10.1049/itr2.12566

Xinyun Feng, Tao Peng, Ningguo Qiao, Haitao Li, Qiang Chen, Rui Zhang, Tingting Duan, JinFeng Gong

{"title":"ADWNet: An improved detector based on YOLOv8 for application in adverse weather for autonomous driving","authors":"Xinyun Feng, Tao Peng, Ningguo Qiao, Haitao Li, Qiang Chen, Rui Zhang, Tingting Duan, JinFeng Gong","doi":"10.1049/itr2.12566","DOIUrl":"https://doi.org/10.1049/itr2.12566","url":null,"abstract":"Drawing inspiration from the state-of-the-art object detection framework YOLOv8, a new model termed adverse weather net (ADWNet) is proposed. To enhance the model's feature extraction capabilities, the efficient multi-scale attention (EMA) module has been integrated into the backbone. To address the problem of information loss in fused features, Neck has been replaced with RepGDNeck. Simultaneously, to expedite the model's convergence, the bounding box's loss function has been optimized to SIoU loss. To elucidate the advantages of ADWNet in the context of adverse weather conditions, ablation studies and comparative experiments were conducted. The results indicate that although the model's parameter count increased by 18.4%, the accuracy for detecting rain, snow, and fog in adverse weather conditions improved by 22%, while the FLOPs (floating point operations) decreased by 5%. The results of the comparison experiments conducted on the WEDGE dataset show that ADWNet outperforms other object detection models in adverse weather in terms of accuracy, model parameters and FLOPs. To validate ADWNet's real-world efficacy, data was extracted from a car recorder under adverse conditions on highways, visual inference was conducted, and its accuracy was demonstrated in interpreting real-world scenarios. The config files are available at https://github.com/Xinyun-Feng/ADWNet.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 10","pages":"1962-1979"},"PeriodicalIF":2.3,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12566","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524666","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}

引用次数: 0

Creep slope estimation for assessing adhesion in the wheel/rail contact 用于评估车轮/轨道接触面附着力的蠕变斜率估算

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-14 DOI: 10.1049/itr2.12561

Peter Hubbard, Tim Harrison, Christopher Ward, Bilal Abduraxman

引用次数: 0

Evaluation of large-scale cycling environment by using the trajectory data of dockless shared bicycles: A data-driven approach 利用无桩共享单车的轨迹数据评估大规模骑行环境：数据驱动法

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-10 DOI: 10.1049/itr2.12565

Ying Ni, Shihan Wang, Jiaqi Chen, Bufan Feng, Rongjie Yu, Yilin Cai

{"title":"Evaluation of large-scale cycling environment by using the trajectory data of dockless shared bicycles: A data-driven approach","authors":"Ying Ni, Shihan Wang, Jiaqi Chen, Bufan Feng, Rongjie Yu, Yilin Cai","doi":"10.1049/itr2.12565","DOIUrl":"https://doi.org/10.1049/itr2.12565","url":null,"abstract":"Cycling is increasingly promoted worldwide, but many urban areas lack satisfactory cycling environments. Assessing these environments is crucial, but existing methods face data challenges for large urban networks. This study proposes a data-driven framework using dockless shared bicycle data to efficiently evaluate large-scale cycling environments. First, critical cycling behaviour features that reflect cyclists’ perceptions are identified applying the fuzzy C-means and random forest model. Then, a distribution-oriented evaluation method is developed, ensuring the incorporation of cyclist heterogeneity and quantifying the quality differences among road segments by combining statistical analysis with a hierarchical clustering model. The evaluation framework is applied to Yangpu District, Shanghai, using Mobike data covering 114.9 km of cycling roads. Results show that indicators related to speed magnitude and fluctuation are critical, and an experimental study validates the effectiveness of the data-driven feature extraction method. A minimum trajectory sample size of 260 is required to account for cyclist heterogeneity for one road segment to be evaluated. Further analysis of lower-performing segments identifies vehicle-bicycle separation, on-street parking, and traffic volume as key influencing factors. The rationality of these findings further supports the reliability of the evaluation framework.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 10","pages":"1943-1961"},"PeriodicalIF":2.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12565","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524626","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}

引用次数: 0

The accessibility of public electric vehicle (EV) charging infrastructure: Evidence from the cities of Nottingham and Frankfurt 公共电动汽车（EV）充电基础设施的可达性：来自诺丁汉和法兰克福两个城市的证据

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-10 DOI: 10.1049/itr2.12564

Botakoz Arslangulova, Kostas Galanakis

{"title":"The accessibility of public electric vehicle (EV) charging infrastructure: Evidence from the cities of Nottingham and Frankfurt","authors":"Botakoz Arslangulova, Kostas Galanakis","doi":"10.1049/itr2.12564","DOIUrl":"https://doi.org/10.1049/itr2.12564","url":null,"abstract":"The distribution of public electric vehicle (EV) charging infrastructure is a widespread approach for promoting EV adoption and decarbonising transportation. A significant amount of literature explores the distribution of EV charging points at a country scale, but there is a lack of studies focusing on a district scale. This study aims to contribute to this gap by gaining insights into the distribution of EV charging points per district within cities, such as Nottingham and Frankfurt. The study investigates the current distribution of EV charging points across 38 postcode districts in Frankfurt and 9 postcode districts in Nottingham, using geographical data analysis and a linear regression approach. The following factors in response to the number of EV charging points per postcode district (ZIP code) are examined: the percentage of apartment buildings/floor area ratio, the availability of amenities, population, charging capacity (kW), area size, strategic approaches, including policy goals and principles. The results reveal disparities in access to EV charging infrastructure across districts and underscore the importance of expanding EV charging networks not only in districts located near urban centres or those with high availability of amenities but also ensuring that users without home charging options are not left behind.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 S1","pages":"3058-3068"},"PeriodicalIF":2.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12564","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860762","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}

引用次数: 0

Investigating the relative accuracy of GPS, GSM and CDR data for inferring spatiotemporal travel trajectories

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-09 DOI: 10.1049/itr2.12563

Khatun E. Zannat, Charisma F. Choudhury, Stephane Hess, David Watling

{"title":"Investigating the relative accuracy of GPS, GSM and CDR data for inferring spatiotemporal travel trajectories","authors":"Khatun E. Zannat, Charisma F. Choudhury, Stephane Hess, David Watling","doi":"10.1049/itr2.12563","DOIUrl":"https://doi.org/10.1049/itr2.12563","url":null,"abstract":"The potential of passively generated big data sources in transport modelling is well-recognised. However, assessing their accuracy and suitability for policymaking remains challenging due to the lack of ground-truth (GT) data for validation. This study evaluates the accuracy of inferring human mobility patterns from global positioning system (GPS), call detail records (CDR), and global system for mobile communication (GSM) data. Using outputs from an agent-based simulation platform (MATSim) as ‘synthetic GT’ (SGT), synthetic GPS, CDR, and GSM data were generated, considering their positional disturbances and conventional spatiotemporal resolutions. Mobility information, including activity location, departure time, and trajectory distance, derived from the synthetic data, was compared with SGT to evaluate the accuracy of passive trajectory data at both disaggregate and aggregate levels. The results indicated a higher accuracy of GPS data in identifying stay locations at high resolution. But, GSM data at a lower resolution effectively accounted for over 80% of the variability in stay locations. Comparisons of departure time distribution and travel distance revealed higher measurement errors in GSM and CDR data than in GPS data. The proposed simulation-based accuracy assessment framework will aid transport planners select the most suitable data for specific analyses and understand the potential margin of error involved.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 S1","pages":"3013-3033"},"PeriodicalIF":2.3,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12563","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860560","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}

引用次数: 0

9 to 5 or a new-normal? Cluster analysis of pre and post pandemic vehicle and cycle diurnal flow profiles 朝九晚五还是新常态？大流行前后车辆和周期昼夜流量分布的聚类分析

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-08 DOI: 10.1049/itr2.12558

Matthew Edward Burke, Margaret Bell, Dilum Dissanayake

{"title":"9 to 5 or a new-normal? Cluster analysis of pre and post pandemic vehicle and cycle diurnal flow profiles","authors":"Matthew Edward Burke, Margaret Bell, Dilum Dissanayake","doi":"10.1049/itr2.12558","DOIUrl":"https://doi.org/10.1049/itr2.12558","url":null,"abstract":"Commuting traffic associated with the “9 to 5” workday shaped the morning and evening peaks across the world. The COVID-19 pandemic led to unprecedented changes in travel behaviour such as an increase in cyclists and telecommuting, where employees worked from home during lockdown periods. Transport modellers, planners and policy makers need to know whether the 9 to 5 has returned, or we have entered a “New-normal” of more flexible working arrangements and increased cycling, key for delivering sustainability targets. In this research, the unsupervised machine learning technique k-means clustering investigates temporal patterns across the day and week, comparing the pre- and post-pandemic era across both motorised vehicles and bicycles. Results show that the total daily traffic flow has returned to pre-pandemic volumes, but more spread across the day. Mondays and Fridays have less-pronounced peaks compared to pre-pandemic, having implications for air quality modelling and assessment, traffic management and transport planning. Meanwhile, cycling has increased in volume and the time-of-day people are travelling has changed. Policy makers need to consider whether the additional capacity on the road, brought about by reduced peak traffic, could be reallocated to make roads safer for and reduce delay to cyclists, contributing towards net zero goals.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 S1","pages":"3041-3057"},"PeriodicalIF":2.3,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12558","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860703","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}

引用次数: 0

Optimization for route selection under the integration of dispatching and control at the railway station: A 0-1 programming model and a two-stage solution algorithm 火车站调度与控制一体化下的线路选择优化：0-1 程序设计模型和两阶段求解算法

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-07 DOI: 10.1049/itr2.12557

Liang Ma, Kun Yang, Jin Guo, Yuanli Bao, Wenqing Wu

{"title":"Optimization for route selection under the integration of dispatching and control at the railway station: A 0-1 programming model and a two-stage solution algorithm","authors":"Liang Ma, Kun Yang, Jin Guo, Yuanli Bao, Wenqing Wu","doi":"10.1049/itr2.12557","DOIUrl":"https://doi.org/10.1049/itr2.12557","url":null,"abstract":"At present, the mainstream studies on route selection optimization at the railway station rarely considered the overall punctuality of the operation plans and the seizing route resource between shunting operation and train running, which can endanger the running safety and reduce the efficiency at the station. Therefore, this paper proposes an optimization method for the route selection under the integration of dispatching and control at the railway station. Firstly, the station-type data structure, the route occupation conflict, and the operation task order were defined. Then, a 0-1 programming model was constructed to minimize the total delay time and shorten the total travel time of all operations. Finally, a two-stage solution algorithm based on depth-first search algorithm and genetic algorithm was designed, and two actual cases of a technical station in China were designed. The instance verification results show that the algorithm can find the satisfactory route scheme in 250 iterations; different delay factors and travel coefficients will get different route schemes, which can provide decision support for dispatchers and operators to select routes. Through comparative analysis of algorithms, it is found that the two-stage algorithm has higher solving efficiency than the individual depth-first search algorithm and individual genetic algorithm.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 11","pages":"2124-2151"},"PeriodicalIF":2.3,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12557","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665926","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}

引用次数: 0

Driver distraction and fatigue detection in images using ME-YOLOv8 algorithm 使用 ME-YOLOv8 算法检测图像中的驾驶员分心和疲劳情况

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-09-02 DOI: 10.1049/itr2.12560

Ali Debsi, Guo Ling, Mohammed Al-Mahbashi, Mohammed Al-Soswa, Abdulkareem Abdullah

{"title":"Driver distraction and fatigue detection in images using ME-YOLOv8 algorithm","authors":"Ali Debsi, Guo Ling, Mohammed Al-Mahbashi, Mohammed Al-Soswa, Abdulkareem Abdullah","doi":"10.1049/itr2.12560","DOIUrl":"https://doi.org/10.1049/itr2.12560","url":null,"abstract":"Driving while inattentive or fatigued significantly contributes to traffic accidents and puts road users at a significantly higher risk of collision. The rise in road accidents due to driver inattention resulting from distractive objects, for example, mobile phones, drinking, or tiredness, requires intelligent traffic monitoring systems to promote road safety. However, outdated detection technologies cannot handle the poor accuracy and the lack of real-time processing possibility especially when combined with the variations of driving environment. This paper introduces “ME-YOLOv8” which operates driver`s distraction and fatigue through a modified version of YOLOv8, which includes modules multi-head self-attention (MHSA) and efficient channel attention (ECA) modules applied, where the goal of MHSA is to improve the sensitivity of global features and the ECA attentions focus on critical features. Additionally, a dataset was created containing 3660 images covering multiple distracted and drowsy driver scenarios. The results reflect the enhanced detection capabilities of ME-YOLOv8 and demonstrate its effectiveness in real-time scenarios. This study demonstrates a significant advancement in the application of AI to public safety and highlights the critical role that state-of-the-art deep learning algorithms play in lowering the risks associated with distracted and tired driving.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 10","pages":"1910-1930"},"PeriodicalIF":2.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12560","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524585","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}

引用次数: 0