IET Intelligent Transport Systems最新文献_第7页

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":"18 9","pages":"1697-1715"},"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":"18 9","pages":"1677-1696"},"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":"18 9","pages":"1632-1651"},"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

Evaluation of comfort zone boundary based automated emergency braking algorithms for car-to-powered-two-wheeler crashes in China 基于舒适区边界的自动紧急制动算法对中国汽车与电动两轮车碰撞事故的评估

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-13 DOI: 10.1049/itr2.12532

Xiaomi Yang, Nils Lubbe, Jonas Bärgman

{"title":"Evaluation of comfort zone boundary based automated emergency braking algorithms for car-to-powered-two-wheeler crashes in China","authors":"Xiaomi Yang, Nils Lubbe, Jonas Bärgman","doi":"10.1049/itr2.12532","DOIUrl":"10.1049/itr2.12532","url":null,"abstract":"Crashes between cars and powered two-wheelers (PTWs: motorcycles, scooters, and e-bikes) are a safety concern; as a result, developing car safety systems that protect PTW riders is essential. While the pre-crash protection system automated emergency braking (AEB) has been shown to avoid and mitigate injuries for car-to-car, car-to-cyclist, and car-to-pedestrian crashes, much is still unknown about its effectiveness in car-to-PTW crashes. Further, the characteristics of the crashes that remain after the introduction of such systems in traffic are also largely unknown. This study estimates the crash avoidance and injury risk reduction performance of six different PTW-AEB algorithms that were virtually applied to reconstructed car-to-PTW pre-crash kinematics extracted from a Chinese in-depth crash database. Five of the algorithms include combinations of drivers’ and PTW riders’ comfort zone boundaries for braking and steering, while the sixth is a traditional AEB. Results show that the average safety performance of the algorithms using only the driver's comfort zone boundaries is higher than that of the traditional AEB algorithm. All algorithms resulted in similar distributions of impact speed and impact locations, which means that in-crash protection systems likely can be made less complex, not having to consider differences in AEB algorithm design among car manufacturers.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 9","pages":"1599-1615"},"PeriodicalIF":2.3,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12532","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141651277","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

Gap setting control strategy for connected and automated vehicles in freeway lane-drop bottlenecks 互联和自动驾驶车辆在高速公路车道下降瓶颈中的间隙设置控制策略

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-11 DOI: 10.1049/itr2.12538

Sungyong Chung, Dongju Ka, Yongju Kim, Chungwon Lee

{"title":"Gap setting control strategy for connected and automated vehicles in freeway lane-drop bottlenecks","authors":"Sungyong Chung, Dongju Ka, Yongju Kim, Chungwon Lee","doi":"10.1049/itr2.12538","DOIUrl":"10.1049/itr2.12538","url":null,"abstract":"Commercial automated vehicles equipped with adaptive cruise control (ACC) systems offer multiple gap settings that determine their longitudinal behaviour. This study introduces two novel strategies—inflow control and combined control—that leverage the distinct driving behaviours associated with different gap settings in connected and automated vehicles. These strategies aim to enhance traffic efficiency in freeway lane-drop bottlenecks, where capacity drops are common, by maintaining bottleneck occupancy at the target level using a proportional-integral-derivative controller. Simulation experiments were conducted using VISSIM to validate the proposed strategies. The results from a hypothetical lane-drop bottleneck indicate that the proposed strategies enhanced both efficiency and safety across all simulated demand levels, with the combined control outperforming inflow control by redistributing the relative positions of vehicles before the mandatory lane changes using a new gap setting. Moreover, the proposed strategies were effective under all the simulated market penetration rates (MPRs), where better performances were demonstrated at higher MPRs. An evaluation of a calibrated real-world network further demonstrated the potential of recommending gap settings to drivers of ACC-equipped vehicles using variable message signs to enhance freeway efficiency in the near future.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 12","pages":"2641-2659"},"PeriodicalIF":2.3,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141658201","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

Modelling the fundamental diagram of traffic flow mixed with connected vehicles based on the risk potential field 基于风险潜势场的互联车辆混合交通流基本图建模

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-11 DOI: 10.1049/itr2.12533

Jiacheng Yin, Peng Cao, Zongping Li, Linheng Li, Zhao Li, Duo Li

{"title":"Modelling the fundamental diagram of traffic flow mixed with connected vehicles based on the risk potential field","authors":"Jiacheng Yin, Peng Cao, Zongping Li, Linheng Li, Zhao Li, Duo Li","doi":"10.1049/itr2.12533","DOIUrl":"10.1049/itr2.12533","url":null,"abstract":"The fundamental diagram (FD) of traffic flow can effectively characterize the macroscopic characteristics of traffic flow and provide a theoretical foundation for traffic planning and control. The rapid development of connected vehicles (CVs) has led to changes in traffic flow characteristics. However, research on the FD of traffic flow involving CVs and non-connected vehicles (NCVs) is still in its early stages. Most FDs do not well characterize the motion behaviour of different vehicles, nor do they study the interaction between mixed vehicles. Therefore, in this study, the FD of mixed traffic flows (i.e. with CVs and NCVs) was constructed within a unified framework. First, the car-following behaviours of CVs and NCVs were modelled based on risk potential field theory. Subsequently, the FD of mixed traffic flows was derived based on the relationship between car-following behaviour and the macroscopic traffic flow under steady-state conditions. To validate the model, rigorous verifications were conducted via numerical experiments using the Monte Carlo method. The results indicate significant agreement between the scatter plots obtained from the experiments and the theoretical curves for different penetration rates. The proposed FD has a unified framework and a more rigorous mathematical structure.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 9","pages":"1616-1631"},"PeriodicalIF":2.3,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12533","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657066","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 reinforcement learning and ant colony optimization supporting multi-UGV path planning and task assignment in 3D environments 深度强化学习和蚁群优化支持三维环境中的多 UGV 路径规划和任务分配

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-10 DOI: 10.1049/itr2.12535

Binghui Jin, Yang Sun, Wenjun Wu, Qiang Gao, Pengbo Si

{"title":"Deep reinforcement learning and ant colony optimization supporting multi-UGV path planning and task assignment in 3D environments","authors":"Binghui Jin, Yang Sun, Wenjun Wu, Qiang Gao, Pengbo Si","doi":"10.1049/itr2.12535","DOIUrl":"10.1049/itr2.12535","url":null,"abstract":"With the development of artificial intelligence, the application of unmanned ground vehicles (UGV) in outdoor hazardous scenarios has received more attention. However, the terrains in these environments are often complex and undulating, which also pose higher challenges to the multi-UGV path planning and task assignment (MUPPTA) optimization. To efficiently improve the multi-UGV collaboration in 3D environments, a MUPPTA method is proposed based on double deep Q learning network (DDQN) and ant colony optimization (ACO) to jointly optimize the path planning and task assignment decisions of multiple UGVs. The authors first comprehensively consider the characteristics of the 3D environments, and model the MUPPTA problem as a combinatorial optimization problem. To tackle it, the original problem is decomposed into the multi-UGV path planning sub-problem and task assignment sub-problem, and solve them separately. First, the path planning sub-problem in the 3D environments is transformed into a Markov decision process (MDP) model, and a multi-UGV path planning algorithm based on DDQN (MUPP-DDQN) is proposed to obtain the optimal paths and actual path costs between tasks through extensive offline learning and training. Based on this, a multi-UGV task assignment algorithm is further proposed based on ACO (MUTA-ACO) to solve the task assignment sub-problem and achieve the optimal task assignment solution. Simulation results show that the proposed method is more cost-effective and time-saving compared to other comparison algorithms.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 9","pages":"1652-1664"},"PeriodicalIF":2.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12535","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141660605","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

Energy-efficient adaptive dependent task scheduling in cooperative vehicle-infrastructure system 车辆-基础设施合作系统中的高能效自适应任务调度

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-07-01 DOI: 10.1049/itr2.12516

Beipo Su, Liang Dai, Yongfeng Ju

{"title":"Energy-efficient adaptive dependent task scheduling in cooperative vehicle-infrastructure system","authors":"Beipo Su, Liang Dai, Yongfeng Ju","doi":"10.1049/itr2.12516","DOIUrl":"10.1049/itr2.12516","url":null,"abstract":"In the cooperative vehicle-infrastructure system (CVIS), due to its computation limitation, vehicles are difficult to handle computing-intensive delay-sensitive tasks, so offload tasks to roadside unit (RSU) become popular. Due to the complexity of vehicles’ tasks and tasks generated by different vehicles have different delay constraints, minimize energy consumption of RSUs under task dependence and delay constraints is challenging. This paper defines the task priority queuing criterion for the task priority division problem, proposes a task scheduling strategy for energy-packet queue length tradeoff (TSET) in CVIS under RSUs distributed task scheduling problem and establishes the vehicle speed state model, task model, data queue model, task computing model and energy consumption model. After Lyapunov optimization theory transformed the optimization model, a knapsack problem was described. The simulation results verify that TSET reduces the average energy consumption of roadside units and ensures the stability of the data queue under task dependence and deadline conditions.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 8","pages":"1545-1557"},"PeriodicalIF":2.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12516","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141697322","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-agent deep reinforcement learning approach for traffic signal coordination 交通信号协调的多代理深度强化学习方法

IF 2.3 4区工程技术

IET Intelligent Transport Systems Pub Date : 2024-06-24 DOI: 10.1049/itr2.12521

Ta-Yin Hu, Zhuo-Yu Li

{"title":"A multi-agent deep reinforcement learning approach for traffic signal coordination","authors":"Ta-Yin Hu, Zhuo-Yu Li","doi":"10.1049/itr2.12521","DOIUrl":"https://doi.org/10.1049/itr2.12521","url":null,"abstract":"The purpose of signal control is to allocate time for competing traffic flows to ensure safety. Artificial intelligence has made transportation researchers more interested in adaptive traffic signal control, and recent literature confirms that deep reinforcement learning (DRL) can be effectively applied to adaptive traffic signal control. Deep neural networks enhance the learning potential of reinforcement learning. This study applies the DRL method, Double Deep Q-Network, to train local agents. Each local agent learns independently to accommodate the regional traffic flows and dynamics. After completing the learning, a global agent is created to integrate and unify the action policies selected by each local agent to achieve the purpose of traffic signal coordination. Traffic flow conditions are simulated through the simulation of urban mobility. The benefits of the proposed approach include improving the efficiency of intersections and minimizing the overall average waiting time of vehicles. The proposed multi-agent reinforcement learning model significantly improves the average vehicle waiting time and queue length compared with the results from PASSER-V and pre-timed signal setting strategies.","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 8","pages":"1428-1444"},"PeriodicalIF":2.3,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12521","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968110","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