Workshop on AI for autonomous driving
Anna Choromanska · Larry Jackel · Li Erran Li · Juan Carlos Niebles · Adrien Gaidon · Wei-Lun Chao · Herbert Ingmar Posner · Wei-Lun (Harry) Chao

Sat Jun 15th 08:30 AM -- 06:00 PM @ 101
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A diverse set of methods have been devised to develop autonomous driving platforms. They range from modular systems, systems that perform manual decomposition of the problem, systems where the components are optimized independently, and a large number of rules are programmed manually, to end-to-end deep-learning frameworks. Today’s systems rely on a subset of the following: camera images, HD maps, inertial measurement units, wheel encoders, and active 3D sensors (LIDAR, radar). There is a general agreement that much of the self-driving software stack will continue to incorporate some form of machine learning in any of the above mentioned systems in the future.

Self-driving cars present one of today’s greatest challenges and opportunities for Artificial Intelligence (AI). Despite substantial investments, existing methods for building autonomous vehicles have not yet succeeded, i.e., there are no driverless cars on public roads today without human safety drivers. Nevertheless, a few groups have started working on extending the idea of learned tasks to larger functions of autonomous driving. Initial results on learned road following are very promising.

The goal of this workshop is to explore ways to create a framework that is capable of learning autonomous driving capabilities beyond road following, towards fully driverless cars. The workshop will consider the current state of learning applied to autonomous vehicles and will explore how learning may be used in future systems. The workshop will span both theoretical frameworks and practical issues especially in the area of deep learning.

09:00 AM Opening Remarks (Talk)
09:15 AM Sven Kreiss: "Compositionality, Confidence and Crowd Modeling for Self-Driving Cars" (Talk) Sven Kreiss, Alexandre Alahi
09:40 AM Mayank Bansal: "ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst" (Talk) Mayank Bansal
10:05 AM Chelsea Finn: "A Practical View on Generalization and Autonomy in the Real World" (Talk) Chelsea Finn
10:50 AM Sergey Levine: "Imitation, Prediction, and Model-Based Reinforcement Learning for Autonomous Driving" (Talk) Sergey Levine
11:15 AM Wolfram Burgard (Talk) Wolfram Burgard
11:40 AM Dorsa Sadigh: "Influencing Interactive Mixed-Autonomy Systems" (Talk) Dorsa Sadigh
01:30 PM Poster Session Heejin Jeong, Jonah Philion
02:30 PM Alexander Amini: "Learning to Drive with Purpose" (Talk) Alexander Amini
02:55 PM Fisher Yu: "Motion and Prediction for Autonomous Driving" (Talk) Fisher Yu, Prof. Darrell
03:20 PM Alfredo Canziani: "Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic " (Talk) Alfredo Canziani
04:05 PM Jianxiong Xiao: "Self-driving Car: What we can achieve today?" (Talk) Jianxiong Xiao
04:30 PM German Ros: "Fostering Autonomous Driving Research with CARLA" (Talk) German Ros
04:55 PM Venkatraman Narayanan: "The Promise and Challenge of ML in Self-Driving" (Talk) Venkatraman Narayanan, Drew Bagnell
05:20 PM Best Paper Award and Panel Discussion (Panel Discussion)

Author Information

Anna Choromanska (NYU Tandon School of Engineering)
Larry Jackel (North-C Technologies)
Li Erran Li (Scale AI)
Juan Carlos Niebles (Stanford)
Adrien Gaidon (Toyota Research Institute)
Wei-Lun Chao (Cornell)
Ingmar Posner (University of Oxford)
Wei-Lun (Harry) Chao (Ohio State University Cornell University)

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