Proceedings of the IEEE最新文献_第2页

Special Issue on Technologies for Automated Vehicles 自动驾驶汽车技术特刊

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2026-08-20 DOI: 10.1109/JPROC.2026.3714949

Christoph Stiller;Ljubo Vlacic;Matthew Barth

引用次数: 0

Proceedings of the IEEE: Stay Informed. Become Inspired. IEEE会刊：保持信息灵通。成为灵感。

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2026-08-20 DOI: 10.1109/JPROC.2026.3714973

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Cooperative Perception for Automated Driving: A Survey of Algorithms, Applications, and Future Directions 自动驾驶的协同感知：算法、应用和未来方向综述

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2025-10-01 DOI: 10.1109/JPROC.2025.3608874

Chuheng Wei;Guoyuan Wu;Matthew J. Barth

{"title":"Cooperative Perception for Automated Driving: A Survey of Algorithms, Applications, and Future Directions","authors":"Chuheng Wei;Guoyuan Wu;Matthew J. Barth","doi":"10.1109/JPROC.2025.3608874","DOIUrl":"10.1109/JPROC.2025.3608874","url":null,"abstract":"Cooperative perception (CP) has emerged as an important research topic in connected and automated transportation systems, significantly enhancing situational awareness in challenging conditions such as limited communication bandwidth, harsh weather, and poor lighting. By sharing and aggregating data from multiple sources—including vehicles, roadside units (RSUs), and other infrastructure—CP addresses critical issues like occlusion and long-range perception in complex environments. This article provides a comprehensive review of existing CP methodologies, evaluating their effectiveness across diverse scenarios and fusion layers. We investigate approaches ranging from early to late collaboration strategies, highlighting how multimodal sensing at the network level can improve detection accuracy, system robustness, and adaptability. Additionally, we review publicly available datasets, identifying key gaps in their coverage of heterogeneous sensors, adverse conditions, and large-scale spatial scenarios. Finally, we propose actionable future research directions, including advanced algorithms for adverse environments, adaptive fusion strategies for heterogeneous sensors, and the integration of emerging technologies such as high-definition (HD) maps, large language models (LLMs), and end-to-end frameworks. These advancements aim to ensure reliability, interoperability, and scalability for real-world connected and automated vehicle (CAV) applications.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"114 4","pages":"523-549"},"PeriodicalIF":30.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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IEEE Member Discounts Program IEEE会员折扣计划

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2026-08-20 DOI: 10.1109/JPROC.2026.3714971

引用次数: 0

LLM4AD: Large Language Models for Autonomous Driving—Concept, Review, Benchmark, Experiments, and Future Trends LLM4AD：用于自动驾驶的大型语言模型——概念、回顾、基准、实验和未来趋势

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2026-04-08 DOI: 10.1109/JPROC.2026.3678829

Can Cui;Yunsheng Ma;Sung-Yeon Park;Zichong Yang;Yupeng Zhou;Peiran Liu;Juanwu Lu;Juntong Peng;Jiaru Zhang;Ruqi Zhang;Lingxi Li;Yaobin Chen;Jitesh H. Panchal;Amr Abdelraouf;Rohit Gupta;Kyungtae Han;Ziran Wang

{"title":"LLM4AD: Large Language Models for Autonomous Driving—Concept, Review, Benchmark, Experiments, and Future Trends","authors":"Can Cui;Yunsheng Ma;Sung-Yeon Park;Zichong Yang;Yupeng Zhou;Peiran Liu;Juanwu Lu;Juntong Peng;Jiaru Zhang;Ruqi Zhang;Lingxi Li;Yaobin Chen;Jitesh H. Panchal;Amr Abdelraouf;Rohit Gupta;Kyungtae Han;Ziran Wang","doi":"10.1109/JPROC.2026.3678829","DOIUrl":"10.1109/JPROC.2026.3678829","url":null,"abstract":"With the broader adoption and highly successful development of large language models (LLMs), there has been growing interest and demand for applying LLMs to autonomous driving technology. Driven by their natural language (NL) understanding and reasoning capabilities, LLMs have the potential to enhance various aspects of autonomous driving systems, from perception and scene understanding to interactive decision-making. This article first introduces the novel concept of designing LLMs for autonomous driving (LLM4AD), followed by a review of existing LLM4AD studies. Then, a comprehensive benchmark is proposed for evaluating the instruction-following and reasoning abilities of LLM4AD systems, which includes LaMPilot-Bench, CARLA Leaderboard 1.0 Benchmark in simulation and NuPlanQA for multiview visual question answering (VQA). Furthermore, extensive real-world experiments are conducted on autonomous vehicle platforms, examining both on-cloud and on-edge LLM deployment for personalized decision-making and motion control. Next, the future trends of integrating language diffusion models into autonomous driving are explored, exemplified by the proposed vision-language diffusion (ViLaD) framework. Finally, the main challenges of LLM4AD are discussed, including latency, deployment, security and privacy, safety, trust and transparency, and personalization.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"114 4","pages":"573-608"},"PeriodicalIF":30.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147664365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Day-to-Day Traffic Flow Dynamics With Mixed Autonomy Considering Link-Level Penetration Rate Evolution of Autonomous Vehicles 考虑链路级渗透率演化的混合自主日常交通流动力学

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2025-07-10 DOI: 10.1109/JPROC.2025.3562946

Zelin Wang;Zhiyuan Liu;Yuqian Lin;Yicheng Zhang;Qixiu Cheng

{"title":"Day-to-Day Traffic Flow Dynamics With Mixed Autonomy Considering Link-Level Penetration Rate Evolution of Autonomous Vehicles","authors":"Zelin Wang;Zhiyuan Liu;Yuqian Lin;Yicheng Zhang;Qixiu Cheng","doi":"10.1109/JPROC.2025.3562946","DOIUrl":"10.1109/JPROC.2025.3562946","url":null,"abstract":"The imminent integration of autonomous vehicles (AVs) with human-driven vehicles (HVs) presents a significant transport paradigm shift, making it imperative to understand traffic flow dynamics in a mixed autonomy scenario for effective traffic management and harnessing the benefits of AVs. This study focuses on investigating the mixed autonomy of day-to-day traffic flow dynamics, leveraging its unique advantages to capture the mixed traffic flow evolution over multiple days, considering individual travelers’ route choices based on past experiences and current conditions. Although some studies have explored the day-to-day dynamics with mixed autonomy, the evolutionary process of the link-level AV penetration rate is usually ignored in the existing literature. In this study, we investigate the mixed autonomy of day-to-day dynamics considering the link-level penetration rate evolution of AVs. In our proposed approach, HV-based travelers use predictions from the advanced traveler information system (ATIS) along with their past route travel time (RTT) data to make route predictions for the current day and subsequently select their routes. Conversely, AV-based travelers employ advanced communication and coordination techniques to predict HV-based travelers’ route choices when ATIS broadcasts its prediction, and then make system-optimal route choices. We develop an optimization model and design a customized Armijo rule-based improved gradient projection (IGP) algorithm to obtain the optimal AV flows. Through numerical experiments, we validate the effectiveness of our approach. The systematic analysis of day-to-day dynamics in mixed traffic environments enhances our understanding of the intricate interactions between AVs and HVs, especially for long-term transport systems planning and management with day-to-day dynamics.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"114 4","pages":"658-677"},"PeriodicalIF":30.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144602882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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No More Traffic Tickets: A Tutorial to Ensure Traffic-Rule Compliance of Automated Vehicles 不再有交通罚单：确保自动驾驶汽车遵守交通规则的教程

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2025-06-11 DOI: 10.1109/JPROC.2025.3570483

Matthias Althoff;Sebastian Maierhofer;Gerald Würsching;Yuanfei Lin;Florian Lercher;Roland Stolz

{"title":"No More Traffic Tickets: A Tutorial to Ensure Traffic-Rule Compliance of Automated Vehicles","authors":"Matthias Althoff;Sebastian Maierhofer;Gerald Würsching;Yuanfei Lin;Florian Lercher;Roland Stolz","doi":"10.1109/JPROC.2025.3570483","DOIUrl":"10.1109/JPROC.2025.3570483","url":null,"abstract":"Imagine an automated vehicle violating a traffic rule and, by that, causing an accident. This would not only be devastating for a responsible operator, but more importantly, each such incident would erode the trust of the public in automated vehicles. Fortunately, compliance with traffic rules can be fully controlled, unless other traffic participants breach them—this causality obviously makes it possible for responsible operators to avoid liability claims. Traffic rules can be seen as guardrails for automated driving and should take center stage. Unfortunately, this is currently not the case. Many traffic rules are typically implicitly embedded in various fragments of the software stack of automated vehicles. Instead, the considered traffic rules should be explicitly and centrally provided. Adherence to traffic rules should also be ensured by formal methods to gain the trust needed in the public. This article provides all the steps required to achieve this goal. Due to the interdisciplinary nature of this topic (law, engineering, and computer science), we aim to address a broad audience by focusing on the governing principles of the presented methods, and we refer to more technical works for details.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"114 4","pages":"628-657"},"PeriodicalIF":30.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11030935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144268680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Future Special Issues/Special Sections of the Proceedings 未来的特刊/会议记录的特别部分

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2026-08-20 DOI: 10.1109/JPROC.2026.3714969

引用次数: 0

Toward Intelligent Automated Driving Functionalities for Multipurpose Vehicles in UNICARagil UNICARagil中多用途车辆的智能自动驾驶功能

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2026-08-05 DOI: 10.1109/JPROC.2026.3714578

Timo Woopen;Michael Buchholz;Matti Henning;Charlotte Hermann;Alexandru Kampmann;Christian Kinzig;Bastian Lampe;Martin Lauer;Markus Schön;Raphael van Kempen;Lingguang Wang;Klaus Dietmayer;Lutz Eckstein;Stefan Kowalewski;Christoph Stiller

{"title":"Toward Intelligent Automated Driving Functionalities for Multipurpose Vehicles in UNICARagil","authors":"Timo Woopen;Michael Buchholz;Matti Henning;Charlotte Hermann;Alexandru Kampmann;Christian Kinzig;Bastian Lampe;Martin Lauer;Markus Schön;Raphael van Kempen;Lingguang Wang;Klaus Dietmayer;Lutz Eckstein;Stefan Kowalewski;Christoph Stiller","doi":"10.1109/JPROC.2026.3714578","DOIUrl":"https://doi.org/10.1109/JPROC.2026.3714578","url":null,"abstract":"This article provides an overview of the automated driving (AD) stack developments contributed to the UNICAR<italic>agil</i> research project. It focuses on the novelties in software design tailored to the redundant and fail-safe architectures developed in the project. We focus on the implementation of four mechatronically independent sensor modules and their respective perception, tracking, and fusion algorithms, as well as on the fully redundant planning architecture incorporating the over-actuated four-wheel 90° steer-by-wire drivetrain. Intelligent cloud applications support the on-board AD stack with collective environment modeling, behavior planning, and continuous learning. UNICAR<italic>agil</i> presented novel architectures for electrics and electronics (E/E) as well as a service-oriented software architecture (SOA) for fully automated and driverless operation of special-purpose software-defined vehicles (SDVs). We demonstrated the vehicles’ capabilities in driverless operations, without safety drivers onboard, in challenging mixed traffic scenarios. The results pave the way for the design of future vehicle architectures dedicated to AD and have already been widely adopted.","PeriodicalId":20556,"journal":{"name":"Proceedings of the IEEE","volume":"114 4","pages":"678-707"},"PeriodicalIF":30.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148781728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Proceedings of the IEEE Publication Information IEEE出版信息学报

IF 30.9 1区计算机科学

Proceedings of the IEEE Pub Date : 2026-04-01 Epub Date: 2026-08-20 DOI: 10.1109/JPROC.2026.3714965

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