Bibliography about Autonomous Driving.md · xiangdangY/phd

# Bibliography about autonomous driving

# Table of contents

* [Survey](#survey)
* [Course](#course)
* [End-to-end method](#end-to-end-method)
* [Traditional method](#traditional-method)
  * [Perception](#perception)
  * [Planning](#planning)
  * [Control](#control)

# Survey

* [Planning and Decision-Making for Autonomous Vehicles](https://www.annualreviews.org/doi/pdf/10.1146/annurev-control-060117-105157), 2018.
* [A survey of motion planning and control techniques for self-driving urban vehicles](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7490340), 2016
* [A Review of Motion Planning Techniques for Automated Vehicles](https://ieeexplore.ieee.org/iel7/6979/4358928/07339478.pdf), 2016
* [Automated driving and autonomous functions on road vehicles](https://www.tandfonline.com/doi/pdf/10.1080/00423114.2015.1037774?needAccess=true) 2016
* [Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions](https://www.sciencedirect.com/science/article/pii/S0968090X15003447)

# Course

* [MIT Course：Deep Learning for Self-Driving Cars](http://selfdrivingcars.mit.edu/)
* [CMU Deep Reinforcement Learning and Control](https://katefvision.github.io/)
* [ICRA tutorials: Motion Planning for Dynamic Environments](http://msl.cs.uiuc.edu/~lavalle/icra12/)
* [The DARPA Urban Challenge]()
* [Probabilistic-Robotics]()
* [Planning Algorithm]()
* [Principles of robot motion theory algorithms and implementations]()

# End-to-end Method

* [End to End Learning for Self-Driving Cars](https://arxiv.org/abs/1604.07316), 2016
* [CARMA: A Deep Reinforcement Learning Approach to Autonomous Driving](),2016
* [Learning to navigate in complex environments](https://arxiv.org/abs/1611.03673), 2016
* [Learning to Navigate in Cities Without a Map](https://arxiv.org/abs/1804.00168), 2016
* [End-to-end Learning of Driving Models from Large-scale Video Datasets](https://arxiv.org/abs/1612.01079), 2016
* [Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving](https://arxiv.org/abs/1610.03295), 2016
* [DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving](https://www.cv-foundation.org/openaccess/content_iccv_2015/html/Chen_DeepDriving_Learning_Affordance_ICCV_2015_paper.html), 2015
* [From Perception to Decision A Data-driven Approach to End-to-end Motion Planning for Autonomous Ground Robots](https://ieeexplore.ieee.org/abstract/document/7989182/), 2015
* [Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning](https://ieeexplore.ieee.org/abstract/document/7989381/), 2017
* [Cognitive Mapping and Planning for Visual Navigation](http://openaccess.thecvf.com/content_cvpr_2017/papers/Gupta_Cognitive_Mapping_and_CVPR_2017_paper.pdf), 2017
* [Towards cognitive exploration through deep reinforcement learning for mobile robots](https://arxiv.org/abs/1610.01733), 2016

# Traditional Method

## Perception
* [Perception for autonomous driving in urban road environment](https://scholarbank.nus.edu.sg/handle/10635/119269), 2014
* [In-car positioning and navigation technologies—A survey](https://ieeexplore.ieee.org/abstract/document/4770175/), 2009
* [Simultaneous localization and mapping: A survey of current trends in autonomous driving](https://ieeexplore.ieee.org/iel7/7274857/7448921/08025618.pdf), 2017
* [Towards 3D object recognition via classification of arbitrary object tracks](https://ieeexplore.ieee.org/abstract/document/5979636/), 2011
* [Multi-modal semantic place classification](https://journals.sagepub.com/doi/abs/10.1177/0278364909356483), 2010

## Planning
* [Autonomous driving in urban environments: Boss and the urban challenge](http://www.frc.ri.cmu.edu/users/alonzo/pubs/papers/JFR_08_Boss.pdf), 2008
* [Route Planning in Transportation Networks](https://link.springer.com/chapter/10.1007/978-3-319-49487-6_2), 2015
* [Hierarchical route planning based on taxi GPS-trajectories](https://ieeexplore.ieee.org/abstract/document/5293532/), 2009
* [Automated Driving in Uncertain Environments Planning With Interaction and Uncertain Maneuver Prediction](https://ieeexplore.ieee.org/abstract/document/8248668/), 2018
* [Adaptive Behavior Generation for Autonomous Driving using Deep Reinforcement Learning with Compact Semantic States](https://ieeexplore.ieee.org/abstract/document/8500427/). 2018
* [Combining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environments](https://arxiv.org/abs/1703.07887), 2017
* [Probabilistic Decision-Making under Uncertainty for Autonomous Driving Using Continuous POMDPs](https://ieeexplore.ieee.org/abstract/document/6957722/), 2014
* [Towards tactical behaviour planning under uncertainties for automated vehicles in urban scenarios](https://ieeexplore.ieee.org/abstract/document/8317819), 2017 
* [Probabilistic online POMDP decision making for lane changes in fully automated driving](https://ieeexplore.ieee.org/abstract/document/6728533/), 2013
* [Spatiotemporal state lattices for fast trajectory planning in dynamic on-road driving scenarios](https://ieeexplore.ieee.org/abstract/document/5354448/), 2009
* [Optimal Motion Planning with the Half-Car Dynamical Model for Autonomous High-Speed Driving](https://ieeexplore.ieee.org/abstract/document/6579835/), 2013
* [Continuous curvature planning with obstacle avoidance capabilities in urban scenarios](https://hal.inria.fr/hal-01086888/), 2014
* [Trajectory planning for Bertha — A local, continuous method](https://ieeexplore.ieee.org/abstract/document/6856581/), 2014

## Control
* Overview [Automated driving: The role of forecasts and uncertainty—A control perspective](https://www.sciencedirect.com/science/article/pii/S094735801500062X), 2015 
* MPC [Design and evaluation of a model predictive vehicle control algorithm for automated driving using a vehicle traffic simulator](https://www.sciencedirect.com/science/article/pii/S0967066116300570), 2016
* MPC [Model Predictive Control for Autonomous Driving considering Actuator Dynamics](https://arxiv.org/abs/1803.03478), 2018 
* LQR
* PID

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