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Recent work has shown that the introduction of autonomous vehicles (AVs) in traffic could help reduce traffic jams.
Density estimation for statistics and data analysis , volume 26
Bernard W Silverman · 1986
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Traffic jams without bottlenecks - experimental evidence for the physical mechanism of the formation of a jam
Yuki Sugiyama, Minoru Fukui, Macoto Kikuchi, Katsuya Hasebe, Akihiro Nakayama, Katsuhiro Nishinari, Shin-ichi Tadaki, and Satoshi Yukawa · 2008
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Learning a mahalanobis distance metric for data clustering and classification
Shiming Xiang, Feiping Nie, and Changshui Zhang · 2008
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A stochastic model of traffic flow: Theoretical foundations
Saif Eddin Jabari and Henry X Liu · 2012
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Recent development and applications of sumo-simulation of urban mobility
Daniel Krajzewicz, Jakob Erdmann, Michael Behrisch, and Laura Bieker · 2012
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The arcade learning environment: An evaluation platform for general agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Concentration inequalities: A nonasymptotic theory of independence
Stéphane Boucheron, Gábor Lugosi, and Pascal Massart · 2013
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A stochastic model of traffic flow: Gaussian approximation and estimation
Saif Eddin Jabari and Henry X Liu · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Traffic flow dynamics
Martin Treiber and Arne Kesting · 2013
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Online anomaly detection for hard disk drives based on mahalanobis distance
Yu Wang, Qiang Miao, Eden WM Ma, Kwok-Leung Tsui, and Michael G Pecht · 2013
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Detecting an anomalous traffic attack area based on entropy distribution and mahalanobis distance
Dolgormaa Bayarjargal and Gihwan Cho · 2014
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A probabilistic stationary speed–density relation based on Newell’s simplified car-following model
Saif Eddin Jabari, Jianfeng Zheng, and Henry X Liu · 2014
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Mahalanobis distance learning for person re-identification
Peter M Roth, Martin Hirzer, Martin Köstinger, Csaba Beleznai, and Horst Bischof · 2014
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Understanding machine learning: From theory to algorithms
Shai Shalev-Shwartz and Shai Ben-David · 2014
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Continuous control with deep reinforcement learning
Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2015
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Influence of connected and autonomous vehicles on traffic flow stability and throughput
Alireza Talebpour and Hani S Mahmassani · 2016
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Vulnerability of deep reinforcement learning to policy induction attacks
Vahid Behzadan and Arslan Munir · 2017
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Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
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Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2017
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Adversarial attacks on neural network policies
Sandy Huang, Nicolas Papernot, Ian Goodfellow, Yan Duan, and Pieter Abbeel · 2017
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Tactics of adversarial attack on deep reinforcement learning agents
Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, and Min Sun · 2017
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Neural trojans
Y. Liu, Y. Xie, and A. Srivastava · 2017
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Deep reinforcement learning framework for autonomous driving
Ahmad EL Sallab, Mohammed Abdou, Etienne Perot, and Senthil Yogamani · 2017
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Urban traffic signal control with connected and automated vehicles: A survey
Qiangqiang Guo, Li Li, and Xuegang Jeff Ban · 2019
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Learning traffic flow dynamics using random fields
Saif Eddin Jabari, Deepthi Mary Dilip, Dianchao Lin, and Bilal Thonnam Thodi · 2019
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Trojdrl: Trojan attacks on deep reinforcement learning agents, 2019
Panagiota Kiourti, Kacper Wardega, Susmit Jha, and Wenchao Li · 2019
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Abs: Scanning neural networks for back-doors by artificial brain stimulation
Yingqi Liu, Wen-Chuan Lee, Guanhong Tao, Shiqing Ma, Yousra Aafer, and Xiangyu Zhang · 2019
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Hidden trigger backdoor attacks, 2019
Aniruddha Saha, Akshayvarun Subramanya, and Hamed Pirsiavash · 2019
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Bypassing backdoor detection algorithms in deep learning, 2019
Te Juin Lester Tan and Reza Shokri · 2019
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Flow: Architecture and benchmarking for reinforcement learning in traffic control
Cathy Wu, Aboudy Kreidieh, Kanaad Parvate, Eugene Vinitsky, and Alexandre M Bayen · 2017
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Detecting backdoor attacks on deep neural networks by activation clustering, 2018
Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian Molloy, and Biplav Srivastava · 2018
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Backdoor attacks on neural network operations
Joseph Clements and Yingjie Lao · 2018
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Backdooring convolutional neural networks via targeted weight perturbations, 2018
Jacob Dumford and Walter Scheirer · 2018
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Stochastic Lagrangian modeling of traffic dynamics
Saif Eddin Jabari, Fangfang Zheng, H Liu, and Monika Filipovska · 2018
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Flow: Deep reinforcement learning for control in sumo
Nishant Kheterpal, Kanaad Parvate, Cathy Wu, Aboudy Kreidieh, Eugene Vinitsky, and Alexandre Bayen · 2018
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
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Neural cleanse: Identifying and mitigating backdoor attacks in neural networks
Bolun Wang, Yuanshun Yao, Shawn Shan, Huiying Li, Bimal Viswanath, Haitao Zheng, and Ben Y. Zhao · 2019
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Latent backdoor attacks on deep neural networks
Yuanshun Yao, Huiying Li, Haitao Zheng, and Ben Y. Zhao · 2019
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Blind backdoors in deep learning models
Eugene Bagdasaryan and Vitaly Shmatikov · 2020
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Backdooring and poisoning neural networks with image-scaling attacks
Erwin Quiring and Konrad Rieck · 2020
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Traffic flow with multiple quenched disorders
A Sai Venkata Ramana and Saif Eddin Jabari · 2020
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Dynamic backdoor attacks against machine learning models, 2020
Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, and Yang Zhang · 2020
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Backdoor suppression in neural networks using input fuzzing and majority voting
Esha Sarkar, Yousif Alkindi, and Michail Maniatakos · 2020
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Noticeability versus impact in traffic signal tampering
Bilal Thonnam Thodi, Timothy Mulumba, and Saif Eddin Jabari · 2020
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Flow: A deep reinforcement learning framework for mixed autonomy traffic
UC Berkeley Mobile Sensing Lab · 2020
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Detecting ai trojans using meta neural analysis, 2020
Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, and Bo Li · 2020
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Analyzing the impact of automated vehicles on uncertainty and stability of the mixed traffic flow
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Power-laws and phase transitions in heterogeneous car following with reaction times
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