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Article
Engineering, Civil
Kaiwen Liu et al.
Summary: In this paper, the problem of autonomous vehicle control for forced merge scenarios is addressed. A novel game-theoretic controller called the Leader-Follower Game Controller (LFGC) is proposed, which models the interactions between the autonomous ego vehicle and other vehicles with uncertain driving intentions as a partially observable leader-follower game. The LFGC estimates the other vehicles' intentions online, predicts their future trajectories, and plans the ego vehicle's trajectory using Model Predictive Control (MPC) to achieve both probabilistically guaranteed safety and merging objectives. The LFGC demonstrates a high success rate of 97.5% in merging based on simulations and NGSIM data.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Robotics
Christopher Diehl et al.
Summary: This work proposes a novel approach for learning decision-making from offline data in automated driving. By training a learning-based dynamics model, the effectiveness and state-of-the-art performance of the proposed approach are demonstrated in challenging AD simulations and using a real-world public dataset.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Automation & Control Systems
Qinghai Miao et al.
Summary: This paper summarizes the virtual-to-real paradigm, which trains models on virtual data and then applies them to real-world problems, attracting increasing attention for solving the data shortage problem in machine learning. It proposes an extended parallel learning framework covering main domains and designs a multi-dimensional taxonomy to organize literature. It analyzes and compares virtual-to-real works based on the principles of parallel learning, and discusses key issues and future research directions.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Review
Engineering, Civil
Sajjad Mozaffari et al.
Summary: This article provides a comprehensive review of deep learning-based approaches for vehicle behavior prediction. It discusses the challenges and issues in behavior prediction and categorizes and reviews the most recent solutions based on input representation, output type, and prediction method. The article also evaluates the performance of several solutions and outlines potential future research directions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Xiaoshuang Li et al.
Summary: This paper proposes a data augmented deep behavioral cloning (DADBC) method to imitate the problem-solving skills of traffic engineers, which utilizes a parallel learning (PL) framework that combines machine learning techniques to solve decision-making problems in traffic signal control. The method can learn traffic engineers' control schemes using the deep behavioral cloning (DBC) model, and has shown promising results in improving traffic efficiency in urban areas through real-world data validation from Hangzhou, China.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Li Li et al.
Summary: This study focuses on improving driving safety of autonomous vehicles by setting up a set of decision rules. Three essential design principles are summarized, and a nine-step communication-decision model is established. The decision rules aim to be ambiguity-free and readily computable to facilitate understanding between human drivers and autonomous vehicles.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Chen Zhao et al.
Summary: This article provides an overview of parallel transportation management and control, discussing its principles, applications, challenges, and emerging opportunities. Additionally, it proposes a transportation foundation model based on parallel learning and federated intelligence as a potential path for future development.
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
(2022)
Article
Computer Science, Information Systems
Peijun Ye et al.
Summary: Traditional cognitive science methods have limitations in the application in cyber-physical-social systems (CPSSs) due to the severe heterogeneity and dynamics caused by the large number of human users. To reduce decision-making conflicts between humans and machines, a new research paradigm called parallel cognition is proposed, which investigates cognitive activities and functionals using intelligent techniques in three stages: descriptive cognition, predictive cognition, and prescriptive cognition. A hybrid learning method based on psychological models and user behavioral data is further introduced to adaptively learn individual cognitive knowledge. Preliminary experiments indicate the effectiveness and feasibility of parallel cognition learning for human behavioral prescription, facilitating human-machine cooperation in complex engineering and social systems.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Fangyin Tian et al.
IEEE Transactions on Intelligent Vehicles
(2022)
Article
Engineering, Civil
Zeyu Zhu et al.
Summary: This paper provides a comprehensive survey on the use of deep reinforcement learning (DRL) and deep imitation learning (DIL) techniques for deriving driving policies in autonomous driving (AD) systems. The research covers integration modes, model formulations for AD tasks, and addressing critical issues such as driving safety, interaction with other traffic participants, and environmental uncertainty. The findings may lead to further investigation and advancements in this field.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Xianglei Zhu et al.
Summary: This study proposes a cut-in prediction and risk assessment method that considers the interactions of multiple traffic participants, using a combination of support vector machine and Gaussian mixture model to predict cut-in behavior and trajectory. It introduces two risk measurements to evaluate the comprehensive interaction risk based on the predicted trajectory and responsive actions of the autonomous vehicles.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Automation & Control Systems
Hong Mo et al.
Summary: This paper proposes a new vehicle-following control strategy, which effectively addresses traffic congestion and improves road traffic safety by integrating different control models and methods.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Computer Science, Artificial Intelligence
Xiao Wang et al.
Summary: This article reviews the development and changes in the field of cyber-physical-social systems (CPSS) over the past decade since 2010. It focuses on the comparison between digital twins in CPS and parallel intelligence in CPSS, and discusses their relationship with blockchain intelligence, smart contracts, metaverses, DAO, Web3, and decentralized science. The concept of DeMetaverses is introduced as a decentralized autonomous metaverse based on DAO. The characteristics, mechanism, and impact of DeMetaverses are explored, envisioning an integrated human, artificial, natural, and organizational intelligence in 6S societies.
IEEE INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Jiangong Wang et al.
Summary: The long-tail effect is a common phenomenon in vision-related problems, and accurately perceiving long-tail scenarios remains challenging for vision systems. This paper introduces the theoretical framework of LoTR and the practical implementation of PVAS to address this issue by regularizing long-tail scenarios and generating large-scale driving scenarios.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2022)
Article
Computer Science, Artificial Intelligence
Kaouther Messaoud et al.
Summary: This paper focuses on vehicle trajectory prediction by modeling vehicle interactions, utilizing an attention mechanism to highlight neighboring vehicles' future states, and considering multiple potential futures based on different goals and driving behaviors, leading to outperforming the state-of-the-art performances on highway datasets through a combination of global and partial attention.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2021)
Article
Computer Science, Information Systems
Guo Xie et al.
SCIENCE CHINA-INFORMATION SCIENCES
(2020)
Article
Automation & Control Systems
Jingwei Lu et al.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2020)
Article
Ergonomics
Yasir Ali et al.
ACCIDENT ANALYSIS AND PREVENTION
(2020)
Article
Engineering, Civil
Anshuman Sharma et al.
TRANSPORTATION RESEARCH RECORD
(2019)
Article
Engineering, Electrical & Electronic
Yang Xing et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2019)
Article
Transportation Science & Technology
Guoqing Ren et al.
INTERNATIONAL JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS RESEARCH
(2019)
Proceedings Paper
Automation & Control Systems
Wenchao Ding et al.
2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
(2019)
Article
Engineering, Civil
Clara Marina Martinez et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2018)
Review
Automation & Control Systems
Yang Xing et al.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2018)
Review
Automation & Control Systems
Li Li et al.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2017)
Article
Transportation Science & Technology
Ekaterina Gilman et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2015)
Article
Mathematics, Applied
C. Guardiola et al.
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS
(2014)
Article
Environmental Studies
Abhisek Mudgal et al.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2014)
Article
Automation & Control Systems
Z. Constantinescu et al.
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL
(2010)
Article
Engineering, Mechanical
A. Augustynowicz
INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY
(2009)
