IET Intelligent Transport Systems最新文献

Graph neural networks as strategic transport modelling alternative ‐ A proof of concept for a surrogate 图神经网络作为战略运输建模的替代方案--替代方案的概念验证

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-08-08 DOI: 10.1049/itr2.12551

Santhanakrishnan Narayanan, Nikita Makarov, Constantinos Antoniou

{"title":"Graph neural networks as strategic transport modelling alternative ‐ A proof of concept for a surrogate","authors":"Santhanakrishnan Narayanan, Nikita Makarov, Constantinos Antoniou","doi":"10.1049/itr2.12551","DOIUrl":"https://doi.org/10.1049/itr2.12551","url":null,"abstract":"Practical applications of graph neural networks (GNNs) in transportation are still a niche field. There exists a significant overlap between the potential of GNNs and the issues in strategic transport modelling. However, it is not clear whether GNN surrogates can overcome (some of) the prevalent issues. Investigation of such a surrogate will show their advantages and the disadvantages, especially throwing light on their potential to replace complex transport modelling approaches in the future, such as the agent‐based models. In this direction, as a pioneer work, this paper studies the plausibility of developing a GNN surrogate for the classical four‐step approach, one of the established strategic transport modelling approaches. A formal definition of the surrogate is presented, and an augmented data generation procedure is introduced. The network of the Greater Munich metropolitan region is used for the necessary data generation. The experimental results show that GNNs have the potential to act as transport planning surrogates and the deeper GNNs perform better than their shallow counterparts. Nevertheless, as expected, they suffer performance degradation with an increase in network size. Future research should dive deeper into formulating new GNN approaches, which are able to generalize to arbitrary large networks.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comfortable driving control for connected automated vehicles based on deep reinforcement learning and knowledge transfer 基于深度强化学习和知识转移的互联自动驾驶汽车的舒适驾驶控制

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-08-08 DOI: 10.1049/itr2.12540

Chuna Wu, Jing Chen, Jinqiang Yao, Tianyi Chen, Jing Cao, Cong Zhao

{"title":"Comfortable driving control for connected automated vehicles based on deep reinforcement learning and knowledge transfer","authors":"Chuna Wu, Jing Chen, Jinqiang Yao, Tianyi Chen, Jing Cao, Cong Zhao","doi":"10.1049/itr2.12540","DOIUrl":"https://doi.org/10.1049/itr2.12540","url":null,"abstract":"With the development of connected automated vehicles (CAVs), preview and large‐scale road profile information detected by different vehicles become available for speed planning and active suspension control of CAVs to enhance ride comfort. Existing methods are not well adapted to rough pavements of different districts, where the distributions of road roughness are significantly different because of the traffic volume, maintenance, weather, etc. This study proposes a comfortable driving framework by coordinating speed planning and suspension control with knowledge transfer. Based on existing speed planning approaches, a deep reinforcement learning (DRL) algorithm is designed to learn comfortable suspension control strategies with preview road and speed information. Fine‐tuning and lateral connection are adopted to transfer the learned knowledge for adaptability in different districts. DRL‐based suspension control models are trained and transferred using real‐world rough pavement data in districts of Shanghai, China. The experimental results show that the proposed control method increases vertical comfort by 41.10% on rough pavements, compared to model predictive control. The proposed framework is proven to be applicable to stochastic rough pavements for CAVs.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141925850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced motorway capacity estimation considering the impact of vehicle length on the fundamental diagram 考虑车辆长度对基本图的影响，加强高速公路通行能力估算

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-08-08 DOI: 10.1049/itr2.12547

Erik Giesen Loo, R. Corbally, Lewis Feely, Andrew O'Sullivan

{"title":"Enhanced motorway capacity estimation considering the impact of vehicle length on the fundamental diagram","authors":"Erik Giesen Loo, R. Corbally, Lewis Feely, Andrew O'Sullivan","doi":"10.1049/itr2.12547","DOIUrl":"https://doi.org/10.1049/itr2.12547","url":null,"abstract":"The ability to understand the underlying fundamentals of traffic flow behaviour facilitates improved planning and decision‐making for road operators. This paper presents an overview of the various models which can be used to describe the interaction between the different parameters governing traffic flows. 5‐years of measured data from Ireland's M50 motorway are used to demonstrate the application of traffic flow theory using real data, and a detailed investigation of factors affecting the fundamental traffic behaviour is presented. The road capacity is shown to be impacted by different traffic behaviour during morning and evening‐peak periods, during dry vs. wet weather conditions and between lanes on the approach to junctions. It is demonstrated that the mean vehicle length is an important factor to consider when using traffic flow models. A novel 3‐dimensional fundamental diagram model linking mean vehicle speed, mean vehicle length, and density is introduced which enhances capacity estimation and illustrates the importance of considering vehicle length when using the fundamental diagram to interpret traffic flows and estimate the capacity of the motorway.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Road user opinions and needs regarding small modular autonomous electric vehicles: Differences between elderly and non-elderly in Norway 道路使用者对小型模块化自动驾驶电动汽车的意见和需求：挪威老年人与非老年人之间的差异

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-08-04 DOI: 10.1049/itr2.12545

Claudia Moscoso, Isabelle Roche-Cerasi

{"title":"Road user opinions and needs regarding small modular autonomous electric vehicles: Differences between elderly and non-elderly in Norway","authors":"Claudia Moscoso, Isabelle Roche-Cerasi","doi":"10.1049/itr2.12545","DOIUrl":"https://doi.org/10.1049/itr2.12545","url":null,"abstract":"This study examines road user opinions regarding small modular autonomous electric vehicles, focusing on the differences between the elderly and non-elderly populations in Norway. The data allowed for a comparison between 193 respondents under 65 years old and 208 respondents over 65 years old. The results highlighted significant differences between the two groups about the vehicles, their usability, and the likeliness of using them as public transport if implemented in the future. Traffic safety and personal security were found to be decisive aspects, for respondents over 65 years old being more worried about safety and security than their counterparts. Trust that the authorities will ensure the safe implementation of such vehicles in the current transportation system was also significantly different between the two groups, with the younger generations having more trust in the authorities than the older group. The results shed light on road user opinions about a small modular transport mode, particularly on those over 65 years old, indicating a need for research efforts to better identify how this new form of public transport should be implemented in the future to improve the mobility of all travellers and meet the needs of the seniors.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12545","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165573","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

Deep learning-based location prediction in VANET 基于深度学习的 VANET 位置预测

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-31 DOI: 10.1049/itr2.12529

Nafiseh Rezazadeh, Mohammad Ali Amirabadi, Mohammad Hossein Kahaei

{"title":"Deep learning-based location prediction in VANET","authors":"Nafiseh Rezazadeh, Mohammad Ali Amirabadi, Mohammad Hossein Kahaei","doi":"10.1049/itr2.12529","DOIUrl":"https://doi.org/10.1049/itr2.12529","url":null,"abstract":"In recent years, Vehicular Ad-hoc Network (VANET) has become an essential component of intelligent transportation systems that, along with the previous systems such as traffic condition, accident alert, automatic parking, and cruise control, use the communication of vehicle to vehicle and vehicle to the roadside unit to facilitate road transportation. Several challenges hinder efforts to improve traffic conditions and reduce traffic fatalities through VANET. A critical challenge is achieving highly accurate and reliable vehicle localization within the VANET. Additionally, the frequent unavailability of Global Positioning System (GPS), particularly in tunnels and parking lots, presents another significant obstacle. Traditional methods like Dead Reckoning offer low accuracy and reliability due to accumulating errors. Similarly, GPS positioning, map matching with mobile phone location services, and other existing solutions struggle with accuracy and economic feasibility. In this article, two Kalman filter approaches are used based on signal statistical information and the other learning-based networks, including traditional neural network, deep neural network and LSTM (long short-term memory) to locate the car. The prediction error of car position with root mean square measures. The squared error and distance prediction error are evaluated. It is shown that in terms of prediction time and processing time of vehicle localization, all the vehicle localization methods are efficient in terms of response time for localization, and Kalman filter methods, traditional neural network and deep neural network are faster than LSTM method. Also, in terms of localization error, Kalman filter works better than learning-based methods, and in learning-based methods, both deep neural network and LSTM methods perform better than traditional neural network in terms of localization error.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12529","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165794","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

Development of a framework for assessing train passengers' post-boarding behaviours based on their perceptions 根据乘客的感知制定评估火车乘客上车后行为的框架

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-31 DOI: 10.1049/itr2.12546

Jie Yang, Nirajan Shiwakoti, Richard Tay

{"title":"Development of a framework for assessing train passengers' post-boarding behaviours based on their perceptions","authors":"Jie Yang, Nirajan Shiwakoti, Richard Tay","doi":"10.1049/itr2.12546","DOIUrl":"https://doi.org/10.1049/itr2.12546","url":null,"abstract":"While existing literature has focused on modelling pedestrian movement on platforms, there is a lack of understanding of passengers' perceptions, motivations, and influential factors that shape their on-board behaviours and choices. This study developed a conceptual framework to assess passengers' post-boarding behaviours and perceptions, specifically focusing on their actions and choices inside the train carriages. The conceptual framework was tested through survey data of 429 passengers in Melbourne, Australia. The result shows that door access is the most influential factor when passengers choose where to stand or sit on board, followed by comfort, safety, privacy, and random factors. Furthermore, the study explores the relationship between the post-boarding behaviour variables and travellers’ personal and trip characteristic variables. The analysis shows that carrying large items has a more significant effect on many post-boarding behaviour variables. Gender, age group, travel frequency, waiting time, and carrying small items also play significant roles. However, variables such as travel time and frequency of group travel have lesser effects. These novel findings offer valuable insights, laying the groundwork for future modelling activities. Moreover, the understanding derived from passenger perceptions can guide transport agencies and operators in shaping strategies to improve onboard services.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12546","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165791","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

Two-stage algorithm for traffic signal optimization and web-service system development 交通信号优化和网络服务系统开发的两阶段算法

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-26 DOI: 10.1049/itr2.12542

Seungyeop Lee, Myungeun Eom, Byung-In Kim

{"title":"Two-stage algorithm for traffic signal optimization and web-service system development","authors":"Seungyeop Lee, Myungeun Eom, Byung-In Kim","doi":"10.1049/itr2.12542","DOIUrl":"10.1049/itr2.12542","url":null,"abstract":"Efficient control of traffic signals for vehicles and pedestrians at intersections is critical for relieving traffic congestion. Considering the unique characteristics of intersections, such as the number of roads, the presence or absence of crosswalks, road geometric shapes, and traffic demand patterns, an appropriate phase sequence and duration for traffic signals must be established at each intersection. This paper proposes a simulation-based two-stage algorithm comprising integer-constrained Adam (ICA) and tabu search (TS) to optimize the phase sequence and duration for arbitrary intersections with arbitrary traffic-demand patterns. The ICA promptly identifies a promising region in which a global optimal solution is likely to be obtained, whereas TS determines the best solution near the region. The performance of the proposed algorithm that optimizes phase durations with fixed phase sequence is evaluated against several baseline methods using 24 instances across six actual intersections. Experimental results show that the proposed algorithm reduces the average travel time by 20.2% compared with existing traffic signals within a computation time of 4 min, thus providing a near-optimal solution eight times faster than commonly used population-based metaheuristics. Furthermore, the algorithm demonstrates robust performance across heterogeneous vehicles and recommends the best phase sequence that effectively alleviates congestion in current traffic signal systems. The optimized phase sequence with best phase durations further reduces the average travel time by approximately 11.3% compared with the existing phase sequence with best phase durations at an actual intersection. To facilitate its widespread use, a free, open web-service system named “Smart Intersection for Traffic Efficiency” is developed, which enables users to optimize traffic signal systems without requiring optimization background or simulation knowledge.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12542","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801773","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 simulation-based impact assessment of autonomous vehicles in urban networks 基于模拟的自动驾驶汽车对城市网络的影响评估

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-22 DOI: 10.1049/itr2.12537

Hashmatullah Sadid, Constantinos Antoniou

{"title":"A simulation-based impact assessment of autonomous vehicles in urban networks","authors":"Hashmatullah Sadid, Constantinos Antoniou","doi":"10.1049/itr2.12537","DOIUrl":"10.1049/itr2.12537","url":null,"abstract":"The behavioural differences between autonomous vehicles (AVs) and human-driven vehicles (HDVs) can significantly impact traffic efficiency, safety, and emissions. Simulation-based impact assessments using microscopic traffic models often modify car-following (CF) and lane-changing (LC) configurations to differentiate AVs from HDVs. Typically, researchers adjust CF model parameters to replicate AV driving behaviour, but these assumptions can lead to varying conclusions on AV impacts. The scope of each study (e.g., freeways, highways, urban links, intersections) also influences the outcomes. This research conducts an impact assessment utilizing optimized AV driving behavior rather than assumptions on a city network level (Munich) using a simulation-based platform. The particle swarm optimization (PSO) algorithm is used to calibrate the base model and run simulation experiments under various penetration rates (PRs) and demand scenarios. Results show significant safety improvements throughout the network under higher PRs, while lower PRs might lead to deteriorating safety. At 100% AV PR, the total number of conflicts decreased by around 25% compared to a fully HDV environment. Considering AVs' sensing capabilities, additional safety improvements are found in almost any AV PR. However, AVs might not improve traffic efficiency; in some cases, they may slightly increase average network travel time, though this change is minimal.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814795","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

Low-light visibility enhancement for improving visual surveillance in intelligent waterborne transportation systems 提高低照度能见度，改善智能水运系统中的视觉监控

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-16 DOI: 10.1049/itr2.12534

Ryan Wen Liu, Chu Han, Yanhong Huang

{"title":"Low-light visibility enhancement for improving visual surveillance in intelligent waterborne transportation systems","authors":"Ryan Wen Liu, Chu Han, Yanhong Huang","doi":"10.1049/itr2.12534","DOIUrl":"10.1049/itr2.12534","url":null,"abstract":"Under low-light imaging conditions, visual scenes captured by intelligent waterborne transportation systems often suffer from low-intensity illumination and noise corruption. The visual quality degradation would lead to negative effects in maritime surveillance, e.g., vessel detection, positioning and tracking, etc. To restore the low-light images, we develop an effective visibility enhancement method, which contains a coarse-to-fine framework of spatially-smooth illumination estimation. In particular, the refined illumination is effectively generated by optimizing a novel structure-preserving variational model on the coarse version, estimated through the Max-RGB method. The proposed variational model has the capacity of suppressing the textural details while preserving the main structures in the refined illumination map. To further boost imaging performance, the refined illumination is adjusted through the Gamma correction to increase brightness in dark regions. We then estimate the refined reflection map by implementing the joint denoising and detail boosting strategies on the original reflection. In this work, the original reflection is yielded by dividing the input image using the refined illumination. We finally produce the enhanced image by multiplying the adjusted illumination and the refined reflection. Experiments on synthetic and realistic datasets illustrate that our method can achieve comparable results to the state-of-the-art techniques under different imaging conditions.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12534","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141641101","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 two-stage optimization method of power supply scheme of on-board supercapacitor-powered tram 车载超级电容器供电电车供电方案的两阶段优化方法

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-13 DOI: 10.1049/itr2.12536

Huazhi Zhang, Chengcheng Fu, Qingyuan Wang, Pengfei Sun, Xiaoyun Feng, Bin He

引用次数: 0