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Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Driving

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arXiv 2023年

作者： Li, Yueyuan Yuan, Wei Zhang, Songan Yan, Weihao Shen, Qiyuan Wang, Chunxiang Yang, Ming The Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The Innovation Center of Intelligent Connected Vehicles Global Institute of Future Technology Shanghai Jiao Tong University Shanghai200240 China The Global Institute of Future Technology Shanghai Jiao Tong University Shanghai200240 China

Simulators play a crucial role in autonomous driving, offering significant time, cost, and labor savings. Over the past few years, the number of simulators for autonomous driving has grown substantially. However, there is a growing concern about the validity of algorithms developed and evaluated in simulators, indicating a need for a thorough analysis of the development status of the simulators. To bridge the gap in research, this paper analyzes the evolution of simulators and explains how the functionalities and utilities have developed. Then, the existing simulators are categorized based on their task applicability, providing researchers with a taxonomy to swiftly assess a simulator’s suitability for specific tasks. Recommendations for select simulators are presented, considering factors such as accessibility, maintenance status, and quality. Recognizing potential hazards in simulators that could impact the confidence of simulation experiments, the paper dedicates substantial effort to identifying and justifying critical issues in actively maintained open-source simulators. Moreover, the paper reviews potential solutions to address these issues, serving as a guide for enhancing the credibility of simulators. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

A Method for Precise Positioning and Rapid Correction of Blue License Plate 15th

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A Method for Precise Positioning and Rapid Correction of Blu...

15th International Conference on intelligent information Hiding and Multimedia Signal processing, IIH-MSP 2019, held in conjunction with the 12th International Conference on Frontiers of information Technology, Applications and Tools, FITAT 2019

作者： Wu, Jiawei Yu, Zhaochai Zhang, Zuchang Li, Zuoyong Liu, Weina Yu, Jiale College of Computer and Control Engineering Minjiang University Fuzhou350121 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Department of Computer Engineering Fujian Polytechnic of Information Technology Fuzhou350003 China

ISBN: (纸本)9789811397097

To alleviate the problems of slow speed and weak correction ability of existing license plate correction methods under complex conditions, this paper presents a faster license plate positioning method based on the color component combination and color region fusion and develops a more accurate correction algorithm of blue license plate using probabilistic Hough transform and perspective transform. The proposed methods utilize the characteristics of white characters on the blue background of the Chinese license plate. Color component combination in HSV and RGB color spaces and image thresholding are first performed to obtain the background region of the blue license plate and its character region. Then, both regions are fused to obtain complete and accurate license plate region. And finally, edge detection, probabilistic Hough transform, and perspective transform are performed to achieve rapid license plate correction. Experimental results show that average correction time of blue license plate obtained by the proposed method is 0.023 s, and the average correction rate is 95.0%. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Hough transforms

Attacking End-to-End Visual Navigation Model: How Weak Existing Learning-Based Approaches Can Be?

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Attacking End-to-End Visual Navigation Model: How Weak Exist...

IEEE International Conference on Robotics and Biomimetics

作者： Hongye Wang Kefan Jin Hesheng Wang Shanghai Jiao Tong University China MOE Key Laboratory of Marine Intelligent Equipment and System State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665405362

Learning-based self-driving techniques and vehicle navigation approaches are the most hot topics in recent years. However, existing approaches typically assume the attack-free sensor data, the safety issue under large disturbance or external attack have not been well-solved. In this article, we build a simple FGSM-based attack method designed by minimizing the maximum value of the extracted visual features in order to greatly decrease the performance of the popular learning model for vehicle navigation and even make it totally fail. The proposed min-max operation based feature space attack method solves the problems of branch activation uncertainties and the lack of labels. Furthermore, we also provide a general adversarial training framework which can be used to overcome the proposed feature space attack. Simulational experiments in CARLA platform demonstrate the effectiveness and practical applicability of our attacking approach and defence strategy.

关键词： Training Space vehicles Visualization Uncertainty Navigation Feature extraction Robustness

Independent dimensional phase transition on a two-dimensional Kuramoto model with matrix coupling

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arXiv 2021年

作者： Wang, Chongzhi Shao, Haibin Li, Dewei Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

The high-dimensional generalization of the one-dimensional Kuramoto paradigm has been an essential step in bringing about a more faithful depiction of the dynamics of real-world systems. Despite the multi-dimensional nature of the oscillators in these generalized models, the interacting schemes so far have been dominated by a scalar factor unanimously between any pair of oscillators that leads eventually to synchronization on all dimensions. As a natural extension of the scalar coupling befitting for the one-dimensional case, we take a tentative step in studying numerically and theoretically the coupling mechanism of 2 × 2 real matrices on two-dimensional Kuramoto oscillators. One of the features stemmed from this new mechanism is that the matrix coupling enables the two dimensions of the oscillators to separate their transitions to either synchronization or desynchronization which has not been seen in other high-dimensional generalizations. Under various matrix configurations, the synchronization and desynchronization of the two dimensions combine into four qualitatively distinct modes of position and motion of the system. We demonstrate that as one matrix is morphed into another in a specific manner, the system mode also switches correspondingly either through continuous or explosive transitions of the order parameters, thus mimicking a range of behaviors in information science and biology. Copyright © 2021, The Authors. All rights reserved.

关键词： Synchronization

Tracking Performance of Networked Systems with Limited Bandwidth and Colored Noise

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Tracking Performance of Networked Systems with Limited Bandw...

Chinese Automation Congress (CAC)

作者： Bin Zhang Xiaowei Jiang Li Sun Xianhe Zhang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China School of Statistics and Mathematics Zhongnan University of Economics and Law Wuhan China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

This study investigated the optimal tracking performance (OTP) of multi-input multi-output (MIMO), discrete- time networked control systems (NCSs). The limits of tracking performance (TP) under the influences of bandwidth, encoding- decoding, and additive coloured Gaussian noise (ACGN) are derived using the techniques of coprime decomposition and all-pass decomposition. The results reveal the negative impact of non-minimum phase (NMP) zeros and unstable poles of the plant as well as network communication constraints on the TP of NCSs. Finally, a numerical simulation is discussed and verifies our conclusions.

关键词： Networked control systems Gaussian noise Bandwidth Numerical simulation Downlink Decoding Colored noise

Topology Inference for Network Systems: Causality Perspective and Non-asymptotic Performance

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arXiv 2021年

作者： Li, Yushan He, Jianping Chen, Cailian Guan, Xinping Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

Topology inference for network systems (NSs) plays a crucial role in many areas. This paper advocates a causality-based method based on noisy observations from a single trajectory of a NS, which is represented by the state-space model with general directed topology. Specifically, we first prove its close relationships with the ideal Granger estimator for multiple trajectories and the traditional ordinary least squares (OLS) estimator for a single trajectory. Along with this line, we analyze the non-asymptotic inference performance of the proposed method by taking the OLS estimator as a reference, covering both asymptotically and marginally stable systems. The derived convergence rates and accuracy results suggest the proposed method has better performance in addressing potentially correlated observations and achieves zero inference error asymptotically. Besides, an online/recursive version of our method is established for efficient computation or time-varying cases. Extensions on NSs with nonlinear dynamics are also discussed. Comprehensive tests corroborate the theoretical findings and comparisons with other algorithms highlight the superiority of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Trajectories

Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations

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arXiv 2022年

作者： Liu, Qi Yang, Bo Wang, Zhaojian Zhu, Dafeng Wang, Xinyi Ma, Kai Guan, Xinping The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China

Due to the different losses caused by various photovoltaic (PV) array faults, accurate diagnosis of fault types is becoming increasingly important. Compared with a single one, multiple PV stations collect sufficient fault samples, but their data is not allowed to be shared directly due to potential conflicts of interest. Therefore, federated learning can be exploited to train a collaborative fault diagnosis model. However, the modeling efficiency is seriously affected by the model update mechanism since each PV station has a different computing capability and amount of data. Moreover, for the safe and stable operation of the PV system, the robustness of collaborative modeling must be guaranteed rather than simply being processed on a central server. To address these challenges, a novel asynchronous decentralized federated learning (ADFL) framework is proposed. Each PV station not only trains its local model but also participates in collaborative fault diagnosis by exchanging model parameters to improve the generalization without losing accuracy. The global model is aggregated distributedly to avoid central node failure. By designing the asynchronous update scheme, the communication overhead and training time are greatly reduced. Both the experiments and numerical simulations are carried out to verify the effectiveness of the proposed method. © 2022, CC BY.

关键词： Failure analysis

Distributed Stabilization of Signed Networks via Self-loop Compensation

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arXiv 2021年

作者： Shao, Haibin Pan, Lulu The Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

This paper examines the stability and distributed stabilization of signed multi-agent networks. Here, positive semidefiniteness is not inherent for signed Laplacians, which renders the stability and consensus of this category of networks intricate. First, we examine the stability of signed networks by introducing a novel graph-theoretic objective negative cut set, which implies that manipulating negative edge weights cannot change a unstable network into a stable one. Then, inspired by the diagonal dominance and stability of matrices, a local state damping mechanism is introduced using self-loop compensation. The self-loop compensation is only active for those agents who are incident to negative edges and can stabilize signed networks in a fully distributed manner. Quantitative connections between selfloop compensation and the stability of the compensated signed network are established for a tradeoff between compensation efforts and network stability. Necessary and/or sufficient conditions for predictable cluster consensus of compensated signed networks are provided. The optimality of self-loop compensation is discussed. Furthermore, we extend our results to directed signed networks where the symmetry of signed Laplacian is not free. The correlation between the stability of the compensated dynamics obtained by self-loop compensation and eventually positivity is further discussed. Novel insights into the stability of multi-agent systems on signed networks in terms of self-loop compensation are offered. Simulation examples are provided to demonstrate the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Feedback

Student Behavior Recognition in Remote Video Classrooms 16th

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Student Behavior Recognition in Remote Video Classrooms

16th International Conference on intelligent information Hiding and Multimedia Signal processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of information Technology, Applications and Tools, FITAT 2020

作者： Wang, Rongrong Zhang, Guanglong Zhang, Fuquan Dong, Zhiwei Qi, Mingzhu Computer School Beijing Institute of Technology Beijing100081 China Computer School Jilin University Changchun130012 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Botou Vocational College Botou062150 China Shandong Dezhou Experimental Middle School Dezhou253000 China

ISBN: (纸本)9789813367562

With the development of high-definition camera equipment and Internet communication technology, remote video teaching methods have emerged. This new type of teaching method has led to changes in traditional classrooms. On the one hand, remote video teaching has broken the constraints of time and space and effectively improved the inequality of educational resources. On the other hand, in actual video courses, teachers cannot effectively monitor students’ learning actions and states, so they cannot communicate well. In order to solve this problem, this paper proposes an algorithm based on deep learning to monitor the behaviors of students in real time during the learning process, understand the learning status of students, and strengthen the real-time communication between teachers and students. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Students