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Anomaly Detection in Multi-Agent Trajectories for Automated Driving [article]

Julian Wiederer, Arij Bouazizi, Marco Troina, Ulrich Kressel, Vasileios Belagiannis
2021 arXiv   pre-print
Due to the lack of multi-agent trajectory datasets for anomaly detection in automated driving, we introduce our dataset using a driving simulator for normal and abnormal manoeuvres.  ...  To perform anomaly detection, we first estimate a density function of the learned trajectory feature representation and then detect anomalies in low-density regions.  ...  The authors would like to thank the consortium for the successful cooperation.  ... 
arXiv:2110.07922v2 fatcat:zphumc7hqjau5enq2czelaucee

Scanning the Issue

Azim Eskandarian
2022 IEEE transactions on intelligent transportation systems (Print)  
The authors take into account the integration of blockchain and federated learning in vehicular networks as a direction for future research.  ...  This article first presents the state-of-the-art communication technologies, standards, and protocols in vehicular networks (either inter-vehicle networking or in-vehicle networking) along with several  ...  Vehicle Trajectory Prediction and Cut-In Collision Warning Model in a Connected Decentralized Multi-Agent Path Finding for UAV Traffic Management F. Ho, R. Geraldes, A. Gonçalves, B. Rigault, B.  ... 
doi:10.1109/tits.2022.3141513 fatcat:gvywr655cvgolg7rfjrqmt33b4

Learning Models of Plant Behavior for Anomaly Detection and Condition Monitoring

A. J. Brown, V. M. Catterson, M. Fox, D. Long, S. D. J. McArthur
2007 2007 International Conference on Intelligent Systems Applications to Power Systems  
This paper proposes the integration of a newly developed anomaly detection technique with an existing diagnosis system.  ...  In dealing with the large volumes of data involved, it is possible that faults may not be noticed until serious damage has occurred.  ...  Agents have previously been used for power engineering applications such as feeder automation [1] , substation automation [2] , and microgrid control [3] .  ... 
doi:10.1109/isap.2007.4441620 fatcat:digdtknttfdrdf7rimpx7menta

Multi-rover testbed for teleconducted and autonomous surveillance, reconnaissance, and exploration

Wolfgang Fink, Mark A. Tarbell, Wolfgang Fink
2009 Space Exploration Technologies II  
It enables the implementation, field-testing, and validation of algorithms/software and strategies for navigation, exploration, feature extraction, anomaly detection, and target prioritization with applications  ...  in planetary exploration, security surveillance, reconnaissance of disaster areas, military reconnaissance, and delivery of lethal force such as explosives for urban warfare.  ...  It enables the implementation, field-testing, and validation of algorithms/software and strategies for navigation, exploration, feature extraction, anomaly detection, and target prioritization with applications  ... 
doi:10.1117/12.819991 fatcat:skiyujkc6fdsfcsuly3kxtvxz4

2019 Index IEEE Transactions on Intelligent Transportation Systems Vol. 20

2019 IEEE transactions on intelligent transportation systems (Print)  
., +, TITS Oct. 2019 3688-3699 Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Pro- cesses.  ...  ., +, TITS March 2019 1052-1068 Aircraft Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes.  ... 
doi:10.1109/tits.2020.2966388 fatcat:xkvww7uabzhlzgfz3yiecyb75y

Papertitles

2019 2019 International Conference on Control, Automation and Information Sciences (ICCAIS)  
for Anomaly Detection in Real Surveillance VideosSpatio-Temporal Correlation based Anomaly Detection and Identification Method for IoT Sensors Stabilizing Control for Cyber-Physical Systems against Energy-Constrained  ...  Data The research of energy control strategy of four-wheel drive Vehicle with Series-Parallel hybrid power system Trajectory Tracking Control of a Large Six-DOF Platform Based on Integral-Type Terminal  ... 
doi:10.1109/iccais46528.2019.9074559 fatcat:srkln5llk5czjgcksdtuhlgwdy

IEEE Access Special Section Editorial: Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems

Edith Ngai, Chao Chen, Amr M. Tolba, Mohammad S. Obaidat, Fanzhao Wang
2021 IEEE Access  
In the article "nLSALog: An anomaly detection framework for log sequence in security management," by Yang et al., a general anomaly detection framework is proposed.  ...  In the article "A distributed network intrusion detection system for distributed denial of service attacks in vehicular 69492 This work is licensed under a Creative Commons Attribution 4.0 License.  ...  He has published over 100 articles, including 20 in IEEE TRANSACTIONS. His work on taxi trajectory data mining was featured in IEEE SPECTRUM in 2011 , 2016 , and 2020.  ... 
doi:10.1109/access.2021.3074996 fatcat:dfyrghfswff6vmdlpa55jxtkjm

A Flexible System Architecture for Acquisition and Storage of Naturalistic Driving Data

Asher Bender, James R. Ward, Stewart Worrall, Marcelo L. Moreyra, Santiago Gerling Konrad, Favio Masson, Eduardo M. Nebot
2016 IEEE transactions on intelligent transportation systems (Print)  
Anomaly Detection in Driving Behaviour by Road Profiling. 2013 IEEE Intelligent Vehicles Symposium Workshop, Gold Coast, Queensland, Australia: IEEE.  ...  The Warrigal dataset: Multi-vehicle trajectories and V2V communications. IEEE Intelligent Transportation Systems Magazine, 6(3), 109-117.  ... 
doi:10.1109/tits.2016.2524523 fatcat:ycuisqnduzcp5h27sw2vmdlhbm

Deep Reinforcement Learning for Autonomous Driving: A Survey [article]

B Ravi Kiran, Ibrahim Sobh, Victor Talpaert, Patrick Mannion, Ahmad A. Al Sallab, Senthil Yogamani, Patrick Pérez
2021 arXiv   pre-print
in real world deployment of autonomous driving agents.  ...  The role of simulators in training agents, methods to validate, test and robustify existing solutions in RL are discussed.  ...  During his 6 years in academic research, he has worked on DNNs for video anomaly detection, online time series anomaly detection, hyperspectral image processing for tumor detection.  ... 
arXiv:2002.00444v2 fatcat:axj3ohhjwzdrxp6dgpfqvctv2i

A Multi-Agent Approach for Designing Next Generation of Air Traffic Systems [chapter]

Jos Miguel, Juan Besada, Jos Manuel, Jess Garc
2012 Advances in Air Navigation Services  
In addition, an ATC with the role of a central agent should drive air ground negotiation processes in order to provide free of conflict trajectories.  ...  One of them drives processes of trajectories negotiation.  ... 
doi:10.5772/50284 fatcat:fkecjp67nngwnch6lnxn4p52gy

Guest Editorial Introduction to the Special Issue on Deep Learning Models for Safe and Secure Intelligent Transportation Systems

Alireza Jolfaei, Neeraj Kumar, Min Chen, Krishna Kant
2021 IEEE transactions on intelligent transportation systems (Print)  
He served in industry for 18 years at Intel, Bellcore, and Bell Labs, and ten years in academia at Penn State and Northwestern University.  ...  named science, engineering and education for sustainability (SEES).  ...  In the article entitled "Anomaly detection in automated vehicles using multistage attention-based convolutional neural network," Javed et al. propose a combination of a multi-stage attention mechanism  ... 
doi:10.1109/tits.2021.3090721 fatcat:c2o2vno6bjbnxdn6y4zm7ztmvq

Table of Contents

2021 IEEE Robotics and Automation Letters  
(Contents Continued on Page ix) (Contents Continued from Page viii) Circular Fields and Predictive Multi-Agents for Online Global Trajectory Planning . , and T.  ...  Arai 2978 A Minimally Supervised Approach Based on Variational Autoencoders for Anomaly Detection in Autonomous Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/lra.2021.3072707 fatcat:qyphyzqxfrgg7dxdol4qamrdqu

Compromised ACC vehicles can degrade current mixed-autonomy traffic performance while remaining stealthy against detection [article]

George Gunter, Huichen Li, Avesta Hojjati, Matthew Nice, Matthew Bunting, Carl A. Gunter, Bo Li, Jonathan Sprinkle, Daniel Work
2021 arXiv   pre-print
We also develop an anomaly detection technique that uses GPS traces on vehicles to identify malicious/compromised vehicles.  ...  That is, these attacks are stealthy to detection.  ...  automated driving systems.  ... 
arXiv:2112.11986v1 fatcat:lghy5cceqjhknjf7gmfxsv7fhi

Towards Modeling the Behavior of Autonomous Systems and Humans for Trusted Operations [chapter]

Gavin Taylor, Ranjeev Mittu, Ciara Sibley, Joseph Coyne
2016 Robust Intelligence and Trust in Autonomous Systems  
For example, flexible autonomous platforms deployed in a range of environments place a burden on humans to understand evolving behaviors.  ...  This paradigm can benefit from novel and intuitive techniques that isolate and predict anomalous situations or state trajectories within complex autonomous systems in terms of mission context to allow  ...  Furthermore, anomaly detection is difficult in large, multi-dimensional datasets and is affected by the "curse of dimensionality."  ... 
doi:10.1007/978-1-4899-7668-0_2 fatcat:t42fhspaqverlb63bollcmriva

Ieee Access Special Section Editorial: Human-Driven Edge Computing

Rongbo Zhu, Lu Liu, Ashq Anjum, Maode Ma, Shiwen Mao
2021 IEEE Access  
In the article ''An improved AlexNet for power edge transmission line anomaly detection,'' by Guo et al., proposes an improved AlexNet model for anomaly detection, which extracts the characteristics of  ...  The article ''Wearable computing for defence automation: Opportunities and challenges in 5G network,'' by Sharma et al., conducts a study to identify the role of wearable computing for the defense automation  ... 
doi:10.1109/access.2021.3092476 fatcat:wirzxkbrkfg7jmsk2vl67a7gnu
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