IEEE Open Journal of Vehicular Technology最新文献_第5页

Enhancing AAV-to-Ground Communication Security With the Proceed-Hover-Return (PHR) Approach 利用 "继续-悬停-返回"（PHR）方法提高无人飞行器与地面通信的安全性

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-11-08 DOI: 10.1109/OJVT.2024.3494740

Yulin Zhou;Aziz Altaf Khuwaja;Hua Yan

{"title":"Enhancing AAV-to-Ground Communication Security With the Proceed-Hover-Return (PHR) Approach","authors":"Yulin Zhou;Aziz Altaf Khuwaja;Hua Yan","doi":"10.1109/OJVT.2024.3494740","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3494740","url":null,"abstract":"Downlink communications with multiple ground targets using autonomous aerial vehicles (AAVs) as a base station is critical across various fields. However, the presence of potential eavesdroppers introduces significant challenges that must be addressed to ensure the effectiveness and security of these operations. In this work, we investigate the AAV-to-ground communications in the presence of an eavesdropper, focusing on enhancing physical layer security by maximizing the secrecy rate. We propose a Proceed-Hover-Return (PHR) approach, which optimizes the AAV's trajectory, flight time, speed, and hovering duration to achieve the highest possible secrecy rate during communication with ground users. Our numerical results demonstrate the effectiveness of the PHR scheme, which consistently outperforms the fixed-time baseline approach, with particularly significant improvements for users located farther from the eavesdropper. This work provides essential insights into designing secure and efficient AAV communication systems in scenarios involving multiple ground users and potential eavesdroppers.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1746-1755"},"PeriodicalIF":5.3,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10748360","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Performance and Radiation Regulation Compliance for a Small Sub-Array Based Ka Band Antenna 一种小型子阵Ka波段天线的性能与辐射调节符合性分析

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-11-07 DOI: 10.1109/OJVT.2024.3494040

Aparna P. T. Adithyababu;Stefano Caizzone;Ramon Martinez Rodríguez-Osorio

引用次数: 0

OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing OptiFlow：利用改进的集群路由优化智能交通系统中的交通流

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-30 DOI: 10.1109/OJVT.2024.3488084

Roopa Tirumalasetti;Sunil Kumar Singh

{"title":"OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing","authors":"Roopa Tirumalasetti;Sunil Kumar Singh","doi":"10.1109/OJVT.2024.3488084","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3488084","url":null,"abstract":"Intelligent Transport Systems (ITS) rely heavily on Vehicular Ad hoc Networks (VANET) to facilitate effective communication, especially Vehicle-to-Everything (V2X) communication. However, current research has identified challenges in node management, security, and routing within VANET, calling for bespoke solutions to address these issues. This study introduces an innovative cluster-based routing strategy using Enhanced Slap Swarm Optimization (ESSO) and Evaluation with Mixed Data Multi-criteria Decision-Making (EVAmix MCDM) Method tailored to optimize routing in V2X communication. Unlike existing meta-heuristic methods, which often face slow convergence, premature convergence, and local optima stability, the proposed approach demonstrates striking results. Notably, it enhances throughput by 6278 kbps, elevates the Packet Delivery Ratio (PDR) by 95.77\u0000<inline-formula><tex-math>$%$</tex-math></inline-formula>\u0000, and reduces end-to-end delay by 1856ms in the 300th iteration, outperforming existing cluster routing methodologies. Our findings suggest a substantial leap toward surmounting the existing challenges in V2X communication. This innovative solution advances the field and sets a course for real-time applications. This approach allows vehicles to continually monitor, adjust their position, and control their speed on highways, enhancing safety and traffic control.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1727-1745"},"PeriodicalIF":5.3,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10738438","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Modeling of Interest Forwarding in Information Centric Vehicular Networks 以信息为中心的车载网络中兴趣转发的高效建模

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-28 DOI: 10.1109/OJVT.2024.3487245

Surya Samantha Beri;Nitul Dutta

{"title":"Efficient Modeling of Interest Forwarding in Information Centric Vehicular Networks","authors":"Surya Samantha Beri;Nitul Dutta","doi":"10.1109/OJVT.2024.3487245","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3487245","url":null,"abstract":"Vehicular networks (V-Nets) of the current era is widely used for information sharing and entertainment. Considering the popularity and demand for faster data communications, V-Nets are evolving towards an information-centric approach, namely the Information Centric Vehicular Networks (ICVN). In ICVN, nodes such as vehicles, roadside units, pedestrian devices, and sensors, generate interest packets and forward them to appropriate cache stores to retrieve desired data. Hence, an efficient interest forwarding algorithm in ICVN considerably enhances the content retrieval performance and make supports road safety, traffic management, environmental monitoring in real-vehicular environment. However, designing such efficient scheme is critical due to the involvement of various communication scenarios like vehicle-to-vehicle (V2V), vehicle-to-roadside unit (V2R), vehicle-to-in-vehicle sensors (V2S), vehicle-to-mobile infrastructure (V2I), and vehicle-to-personal device (V2P) and it demands a comprehensive and connected vehicular network. In this paper, we propose an interest forwarding scheme for ICVN with the above said realistic scenario. The interest forwarding process is governed by the Secretary Selection Problem (SSP) which guides a vehicular node to select the next level forwarder for locating the desired content. The goal is to select the best neighboring vehicle as the next forwarder thereby maximizing the chances of obtaining the requested data. The proposed scheme, named as Selection Based Interest Forwarding (SBIF) which uses Secretary Selection Problem (SSP) for governing the forward process to select the next level forwarder for locating the desired content. This scheme is analyzed mathematically and implemented in \u0000<inline-formula><tex-math>$ndn$</tex-math></inline-formula>\u0000 simulator. Performance is compared with existing state of the art schemes and observation shows that SBIF outperforms existing approaches considered for comparison.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1680-1691"},"PeriodicalIF":5.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10737109","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Agent Deep Reinforcement Learning Based Optimizing Joint 3D Trajectories and Phase Shifts in RIS-Assisted UAV-Enabled Wireless Communications 基于多代理深度强化学习优化 RIS 辅助无人机无线通信中的联合 3D 轨迹和相位偏移

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-24 DOI: 10.1109/OJVT.2024.3486197

Belayneh Abebe Tesfaw;Rong-Terng Juang;Hsin-Piao Lin;Getaneh Berie Tarekegn;Wendenda Nathanael Kabore

{"title":"Multi-Agent Deep Reinforcement Learning Based Optimizing Joint 3D Trajectories and Phase Shifts in RIS-Assisted UAV-Enabled Wireless Communications","authors":"Belayneh Abebe Tesfaw;Rong-Terng Juang;Hsin-Piao Lin;Getaneh Berie Tarekegn;Wendenda Nathanael Kabore","doi":"10.1109/OJVT.2024.3486197","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3486197","url":null,"abstract":"Unmanned aerial vehicles (UAVs) serve as airborne access points or base stations, delivering network services to the Internet of Things devices (IoTDs) in areas with compromised or absent infrastructure. However, urban obstacles like trees and high buildings can obstruct the connection between UAVs and IoTDs, leading to degraded communication performance. High altitudes can also result in significant path losses. To address these challenges, this paper introduces the deployment of reconfigurable intelligent surfaces (RISs) that smartly reflect signals to improve communication quality. It proposes a method to jointly optimize the 3D trajectory of the UAV and the phase shifts of the RIS to maximize communication coverage and ensure satisfactory average achievable data rates for RIS-assisted UAV-enabled wireless communications by considering mobile multi-user scenarios. In this paper, a multi-agent double-deep \u0000<italic>Q</i>\u0000-network (MADDQN) algorithm is presented, which each agent dynamically adjusts either the positioning of the UAV or the phase shifts of the RIS. Agents learn to collaborate with each other by sharing the same reward to achieve a common goal. In the simulation, results demonstrate that the proposed method significantly outperforms baseline strategies in terms of improving communication coverage and average achievable data rates. The proposed method achieves 98.6% of a communication coverage score, while IoTDs are guaranteed to have acceptable achievable data rates.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1712-1726"},"PeriodicalIF":5.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10734161","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Twin-Empowered Green Mobility Management in Next-Gen Transportation Networks 下一代交通网络中由数字孪生驱动的绿色交通管理

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-22 DOI: 10.1109/OJVT.2024.3484956

Kubra Duran;Lal Verda Cakir;Achille Fonzone;Trung Q. Duong;Berk Canberk

{"title":"Digital Twin-Empowered Green Mobility Management in Next-Gen Transportation Networks","authors":"Kubra Duran;Lal Verda Cakir;Achille Fonzone;Trung Q. Duong;Berk Canberk","doi":"10.1109/OJVT.2024.3484956","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3484956","url":null,"abstract":"Evolving transportation networks need seamless integration and effective infrastructure utilisation to form the next-generation transportation networks. Also, they should be capable of capturing the traffic flow data at the right time and promptly applying sustainable actions toward emission reduction. However, traditional transportation networks cannot handle right-time updates and act upon the requirements in dynamic conditions. Here, Digital Twin (DT) enables the development of enhanced transportation management via robust modelling and intelligence capabilities. Therefore, we propose a DT-empowered Eco-Regulation (DTER) framework with a novel twinning approach. We define a transport-specific twin sampling rate to catch right-time data in a transportation network. Besides, we perform emission prediction using Multi-Layer Perceptron (MLP), Bidirectional Long Short-Term Memory (Bi-LSTM), and BANE embeddings. We perform Laplacian matrix analysis to cluster the risk zones regarding the emissions. Thereafter, we recommend actions by setting the number of vehicle limits of junctions for high-emission areas according to the outputs of Q-learning. In summary, DTER takes control of the emission with its transport-specific twin sampling rate and automated management of transportation actions by considering the emission predictions. We note DTER achieves 19% more successful right-time data capturing, with 30% reduced query time. Moreover, our hybrid implementation of intelligent algorithms for emission prediction resulted in higher accuracy when compared to baselines. Lastly, the autonomous recommendations of DTER achieved \u0000<inline-formula><tex-math>$sim$</tex-math></inline-formula>\u0000 20% decrease in emissions by presenting an effective carbon tracing framework.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1650-1662"},"PeriodicalIF":5.3,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10726797","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fairness-Aware Utility Maximization for Multi-UAV-Aided Terrestrial Networks 多无人机辅助地面网络的公平意识效用最大化

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-21 DOI: 10.1109/OJVT.2024.3477268

Nishant Gupta;Satyam Agarwal;Aymen Fakhreddine

{"title":"Fairness-Aware Utility Maximization for Multi-UAV-Aided Terrestrial Networks","authors":"Nishant Gupta;Satyam Agarwal;Aymen Fakhreddine","doi":"10.1109/OJVT.2024.3477268","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3477268","url":null,"abstract":"Integrating unmanned aerial vehicles (UAVs) with terrestrial networks can enable high-speed communication in various applications. UAVs can serve as aerial base stations (ABSs), offering several benefits to the existing terrestrial networks, such as enhanced coverage, increased capacity, rapid deployment, and mobile communication support. However, this integration presents various technical challenges, including coordination, interference management, and dynamic allocation of resources. To address these key challenges, in this paper, we maximize the network utility by jointly optimizing the scheduling and cell association, transmit power of all base stations, and ABS deployment locations in the presence of co-channel interference. A two-stage approach is proposed to obtain a solution. In the first stage, we propose a heuristic solution by using the clustering algorithm to determine the initial ABS locations and user scheduling while ignoring the co-channel interference. In the second stage, we utilize the solution obtained in the first part and develop an interference-aware iterative scheme to jointly optimize user scheduling, resource allocation, and ABS placement. Given the non-convex nature of this problem, we employ the successive convex approximation technique to approximate the non-convex objectives and constraints. Numerical results show the proposed approach's insights and effectiveness over other schemes. Specifically, our proposed approach provides an average of 25% improvement over the benchmark schemes.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1611-1624"},"PeriodicalIF":5.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10726751","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LiFi for Industry 4.0: Main Features, Implementation and Initial Testing of IEEE Std 802.15.13 工业 4.0 的 LiFi：IEEE 802.15.13 标准的主要功能、实施和初步测试

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-16 DOI: 10.1109/OJVT.2024.3481884

Kai Lennert Bober;Anselm Ebmeyer;Falko Dressler;Ronald Freund;Volker Jungnickel

{"title":"LiFi for Industry 4.0: Main Features, Implementation and Initial Testing of IEEE Std 802.15.13","authors":"Kai Lennert Bober;Anselm Ebmeyer;Falko Dressler;Ronald Freund;Volker Jungnickel","doi":"10.1109/OJVT.2024.3481884","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3481884","url":null,"abstract":"As industrial communication continues to evolve to increase flexibility through wireless communication, networked optical wireless communication (OWC), also known as LiFi, has emerged as a promising candidate technology due to its unlicensed spectrum and relatively deterministic propagation. The inherent containment of light improves security, enables dense cellular networks with spatial reuse, and results in reduced sporadic interference while providing high-capacity short range communication links to mobile end devices. This paper outlines the features of the new IEEE Std 802.15.13-2013, suitable for industrial OWC, and presents details of our prototype implementation along with initial experiments. The standard specifies deterministic medium access control (MAC), based on dynamic time division multiple access (TDMA), as well as two physical layers (PHYs) for extended range and robustness, and for spectral efficiency, respectively. Our prototype includes a central coordinator, implemented entirely in software, running on commodity server hardware. It connects to distributed ceiling-mounted optical wireless frontends via a packet-switched network (Ethernet) and is capable of forming them into adaptive virtual cells on a per-user basis. This approach enhances reliability through multiple-input multiple-output (MIMO) transmission and allows for smooth mobility. We implemented the Pulsed Modulation PHY (PM-PHY) on a commercially available field programmable gate array (FPGA) evaluation board. Initial test results indicate that the PM-PHY supports typical distances of up to 6 m between the ceiling and the mobile device. The MAC achieves deterministic latency values below 4 ms.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1625-1636"},"PeriodicalIF":5.3,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720513","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Partial Learning-Based Iterative Detection of MIMO Systems 基于部分学习的多输入多输出系统迭代检测

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-16 DOI: 10.1109/OJVT.2024.3482008

Abdulaziz Babulghum;Chao Xu;Soon Xin Ng;Mohammed El-Hajjar

{"title":"Partial Learning-Based Iterative Detection of MIMO Systems","authors":"Abdulaziz Babulghum;Chao Xu;Soon Xin Ng;Mohammed El-Hajjar","doi":"10.1109/OJVT.2024.3482008","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3482008","url":null,"abstract":"One of the major challenges in multiple input multiple output (MIMO) system design is the salient trade-off between performance and computational complexity. For instance, the maximum likelihood (Max-L) detection is capable of achieving optimal performance based on exhaustive search, but its exponential computational complexity renders it impractical. By contrast, zero-forcing detection has low computational complexity, while having significantly worse performance compared to that of the Max-L. The recent developments in deep learning (DL) based detection techniques relying on back propagation neural networks (BPNN) constitute promising candidates for the open challenge of the MIMO detection performance versus complexity trade-off. Against this background, in this paper, we propose a novel partial learning (PL) model for MIMO detection with soft-bit decisions that can be incorporated into channel-coded communication systems. More explicitly, the proposed PL model consists of two parts: first, a subset of the transmitted MIMO symbols is detected by the data-driven DL technique and then the detected symbols are removed from the received MIMO signals for the sake of interference cancellation. Afterwards, the classic model-based zero-forcing detector is invoked to detect the remaining symbols at a linear complexity. As a result, near-optimal MIMO performance can be achieved with substantially reduced computational complexity compared to Max-L and BPNN. The proposed solution is adapted to both accept and produce soft information, so that iterative detection can be performed, where the iteration gain is analyzed by extrinsic information transfer (EXIT) charts. Our simulation results demonstrate that the proposed partial learning-based iterative detection is capable of attaining near-Max-L performance while attaining a flexible performance versus complexity trade-off.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1600-1610"},"PeriodicalIF":5.3,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720516","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decentralized and Asymmetric Multi-Agent Learning in Construction Sites 建筑工地上的分散和非对称多代理学习

IF 5.3

IEEE Open Journal of Vehicular Technology Pub Date : 2024-10-14 DOI: 10.1109/OJVT.2024.3479927

Yakov Miron;Dan Navon;Yuval Goldfracht;Dotan Di Castro;Itzik Klein

{"title":"Decentralized and Asymmetric Multi-Agent Learning in Construction Sites","authors":"Yakov Miron;Dan Navon;Yuval Goldfracht;Dotan Di Castro;Itzik Klein","doi":"10.1109/OJVT.2024.3479927","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3479927","url":null,"abstract":"Multi-agent collaboration involves multiple participants working together in a shared environment to achieve a common goal. These agents share information, divide tasks, and synchronize their actions. Key aspects of multi-agent collaboration include coordination, communication, task allocation, cooperation, adaptation, and decentralization. On construction sites, surface grading is the process of leveling sand piles to increase a specific area's height. There, a bulldozer grades while a dumper allocates sand piles. Our work aims to utilize a multi-agent approach to enable these vehicles to collaborate effectively. To this end, we propose a decentralized and asymmetric multi-agent learning approach for construction sites (DAMALCS). We formulate DAMALCS to reduce expected collisions for operating vehicles. Therefore, we develop two heuristic experts capable of achieving their joint goal optimally, by applying an innovative prioritization method. In this approach, the bulldozer's movements take precedence over the dumper's operations. This enables the dozer to clear the path for the dumper and ensure continuous operation of both vehicles. As heuristics alone are insufficient in real-world scenarios, we utilize them to train AI agents, which proves to be highly effective. We simultaneously train dozer and dumper agents to operate within the same environment, aiming to avoid collisions and optimizing performance in terms of time efficiency and sand volume handling. Our trained agents and heuristics are evaluated in both simulation and real-world lab experiments, testing them under various conditions such as visual noise and localization errors. The results demonstrate that our approach significantly reduces collision rates for these vehicles.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"1587-1599"},"PeriodicalIF":5.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10715664","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0