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We study the design of learning architectures for behavioural planning in a dense traffic setting.
Dynamic programming and lagrange multipliers
Richard Bellman · 1956
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Alvinn: An autonomous land vehicle in a neural network
Dean a Pomerleau · 1989
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Q-learning
Christopher J. C. H. Watkins and Peter Dayan · 1992
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Congested traffic states in empirical observations and microscopic simulations
Martin Treiber, Ansgar Hennecke, and Dirk Helbing · 2000
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Evolving competitive car controllers for racing games with neuroevolution
Luigi Cardamone, Daniele Loiacono, and Pier Luca Lanzi · 2009
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Learning for autonomous navigation
James Bagnell, David Bradley, David Silver, Boris Sofman, and Anthony Stentz · 2010
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Unfreezing the robot: Navigation in dense, interacting crowds
Peter Trautman and Andreas Krause · 2010
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A reduction of imitation learning and structured prediction to no-regret online learning
Stephane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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Intention-aware online pomdp planning for autonomous driving in a crowd
Haoyu Bai, Shaojun Cai, Nan Ye, David Hsu, and Wee Lee · 2015
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Learning driver behavior models from traffic observations for decision making and planning
Tobias Gindele, Sebastian Brechtel, and Rudiger Dillmann · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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End to End Learning for Self-Driving Cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, and Karol Zieba · 2016
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A Review of Motion Planning Techniques for Automated Vehicles
David González, Joshué Pérez, Vicente Milanés, and Fawzi Nashashibi · 2016
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A survey of motion planning and control techniques for self-driving urban vehicles
Brian Paden, Michal Čáp, Sze Zheng Yong, Dmitry Yershov, and Emilio Frazzoli · 2016
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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Charles R. Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas · 2016
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Intention-Aware Autonomous Driving Decision-Making in an Uncontrolled Intersection
Weilong Song, Guangming Xiong, and Huiyan Chen · 2016
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End-to-end Learning of Driving Models from Large-scale Video Datasets
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell · 2016
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Socially aware motion planning with deep reinforcement learning
Yu Fan Chen, Michael Everett, Miao Liu, and Jonathan P. How · 2017
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End-to-End Deep Learning for Steering Autonomous Vehicles Considering Temporal Dependencies
Hesham M. Eraqi, Mohamed N. Moustafa, and Jens Honer · 2017
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Recurrent world models facilitate policy evolution
David Ha and Jürgen Schmidhuber · 2018
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Navigating occluded intersections with autonomous vehicles using deep reinforcement learning
David Isele, Reza Rahimi, Akansel Cosgun, Kaushik Subramanian, and Kikuo Fujimura · 2018
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An environment for autonomous driving decision-making
Edouard Leurent · 2018
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Elements of Effective Deep Reinforcement Learning towards Tactical Driving Decision Making
Jingchu Liu, Pengfei Hou, Lisen Mu, Yinan Yu, and Chang Huang · 2018
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Pedestrian Prediction by Planning Using Deep Neural Networks
Eike Rehder, Florian Wirth, Martin Lauer, and Christoph Stiller · 2018
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Reg-gan: Semi-supervised learning based on generative adversarial networks for regression
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Multipolicy decision-making for autonomous driving via changepoint-based behavior prediction: Theory and experiment
Enric Galceran, Alexander G. Cunningham, Ryan M. Eustice, and Edwin Olson · 2017
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Tactical decision making for lane changing with deep reinforcement learning
Mustafa Mukadam, Akansel Cosgun, Alireza Nakhaei, and Kikuo Fujimura · 2017
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Combining neural networks and tree search for task and motion planning in challenging environments
Chris Paxton, Vasumathi Raman, Gregory Hager, and Marin Kobilarov · 2017
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Driving Like a Human: Imitation Learning for Path Planning using Convolutional Neural Networks
Eike Rehder, Jannik Quehl, and Christoph Stiller · 2017
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The value of inferring the internal state of traffic participants for autonomous freeway driving
Zachary N. Sunberg, Christopher J. Ho, and Mykel J. Kochenderfer · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst, 2018
Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale · 2018
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M. Rezagholiradeh and M. A. Haidar · 2018
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Deep imitative models for flexible inference, planning, and control
Nicholas Rhinehart, Rowan McAllister, and Sergey Levine · 2018
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Car-net: Clairvoyant attentive recurrent network
Amir Sadeghian, Ferdinand Legros, Maxime Voisin, Ricky Vesel, Alexandre Alahi, and Silvio Savarese · 2018
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Social attention: Modeling attention in human crowds
Anirudh Vemula, Katharina Muelling, and Jean Oh · 2018
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Learning to drive in a day
Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, and Amar Shah · 2019
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Non-local Social Pooling for Vehicle Trajectory Prediction
Kaouther Messaoud, Itheri Yahiaoui, Anne Verroust-Blondet, and Fawzi Nashashibi · 2019
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PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings
Nicholas Rhinehart, Rowan McAllister, Kris Kitani, and Sergey Levine · 2019
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Sophie: An attentive gan for predicting paths compliant to social and physical constraints
Amir Sadeghian, Vineet Kosaraju, Ali Sadeghian, Noriaki Hirose, Hamid Rezatofighi, and Silvio Savarese · 2019
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