Cutting edge Forum on Autonomous Driving, Contributions from Intelligent Robotics, AI and ITS

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2019 IEEE/RSJ International Conference on Intelligent Robots and SystemsCutting edge Forum on Autonomous Driving

Contributions from Intelligent Robotics, AI and ITSMacau, China, November 5th 11:00 12:30, Room LG‐R8

Research Director Christian Laugier, INRIA, CHROMA project,

Christian.Laugier@inrialpes.fr, https://team.inria.fr/chroma/christian-

laugier/

Professor Philippe Martinet, Inria, CHORALE project

Philippe.Martinet@inria.fr,http://www-

sop.inria.fr/members/Philippe.Martinet/

Professor Marcello H. Ang, NUS, mpeangh@nus.edu.sg,,

http://guppy.mpe.nus.edu.sg/~mpeangh/

Professor Christoph Stiller, Karlsruher Institut für Technologie

stiller@kit.edu http://www.mrt.kit.edu/mitarbeiter_stiller.php

Professor M.A. Sotelo, Universityof Alcalà

miguel.sotelo@uah.es, www.invett.es/sotelo

This workshop is organized in the framework of the IEEE Robotics and Automation's Technical Committee on: Autonomous Ground Vehicles and Intelligent Transportation Systems

TC-chairs: P. Martinet, C. Laugier, M.H. Ang, D. Wolf

Cutting edge Forum on Autonomous Driving, Contributions from Intelligent Robotics, AI and ITS

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Christial Laugier, Inria Grenoble Rhône-Alpes, Grenoble, France

Keynote title: Situation Awareness and Decision-making for Autonomous Driving

Abstract: Motion Autonomy and Safety issues in Autonomous Vehicles are strongly dependent upon thecapabilities and performances of both Embedded Perception and Decision-making systems. This talk presentshow it is possible to address these important issues by mixing Bayesian and Machine Learning approaches.The talk will be illustrated using results obtained by INRIA Grenoble Rhône-Alpes (France) in the scope ofseveral R&D projects conducted in collaboration with IRT Nanoelec (French Technological ResearchInstitute) and with several industrial companies such as Toyota or Renault

Keywords: Bayesian Perception, Situation Awareness, Decision-making, Machine Learning,Autonomous Driving

Cutting edge Forum on Autonomous Driving, Contributions from Intelligent Robotics, AI and ITS

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Dinesh Manocha, Department of Computer Science, University of Maryland, USAKeynote title: Autonomous Driving: Simulation and Navigation

Abstract: Autonomous driving has been an active area of research and development over the last decade.Despite considerable progress, there are many open challenges including automated driving in dense andurban scenes. In this talk, we give an overview of our recent work on simulation and navigation technologiesfor autonomous vehicles. This includes development of autonomous driving simulation, that use recentdevelopments in physics-based simulation, robot motion planning, game engines, and behavior modelingalong with data-driven simulation. We describe novel methods for interactive simulation of multiple vehicleswith unique steering or acceleration limits taking into account vehicle dynamics constraints. We also presentnovel multi-agent simulation algorithms using reciprocal velocity obstacles that can model the behavior andtrajectories of different traffic agents in dense scenarios, including cars, buses, bicycles and pedestrians. Wealso present novel methods for extracting trajectories from videos and use them for behavior modeling andsafe navigation.We highlight the performance of our new algorithms in challenging urban driving scenariosand highlight areas for future research.Keywords: dense traffic, urban driving, traffic prediction, collision-free navigation, driver-behavior

Cutting edge Forum on Autonomous Driving, Contributions from Intelligent Robotics, AI and ITS

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Danwei Wang, NTU, SingaporeKeynote title: Security of Autonomous Vehicle under Cyber Attacks

Abstract: Vehicle autonomy is taking human out of decision making process and the driving is based onsome rules set beforehand. Such cyber systems are subject to attacks in various ways. For example, malwaresto allow hijacking of operation of brake, displacement of GPS reading, or distortion of range measurement ofLidar. These are key sensors and components in an autonomous driving vehicle and their malfunctions cancause disastrous consequences. In this research, we study these problems and provide solutions to detectthese malicious attacks. Some successful counter measures are implemented to ensure the continuousautonomous operation of driverless vehicle. Examples and experiments are used to illustrate the effectivenessof proposed solutions.

Keywords: Control, mobile robot

Cutting edge Forum on Autonomous Driving, Contributions from Intelligent Robotics, AI and ITS

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Discussion and questions