Technical program

Workshop 1 Cognitively Inspired Intelligent Vehicles
Organizers Serge Thill, University of Skövde
Date/time June 11, 2017 (full-day, 9:00 am – 5:00 pm)
Abstract In the development of autonomous systems, the initial focus is often on algorithms designed from a pure engineering perspective. This is apparent in autonomous vehicle development and other fields, such as robotics. In fields that have been in existence for longer than autonomous vehicle research, for example robotics, such methods are eventually supplemented with inspiration from the cognitive sciences. A primary reason for this is the need to increase the autonomy of a system, to ensure its ability to deal with events that are not foreseeable at design time, and sometimes even to ensure behaviour that is intuitively understandable by humans that interact with these systems (in the sense that the autonomous system’s actions are predictable). The converse of the latter is also a motivator: an autonomous vehicle will necessarily have to interact with other vehicles as well as humans such as pedestrians and other vulnerable road users; it must therefore also be able to understand and predict the actions of others. Such approaches are now well established in robotics, both at the control level and where interaction with human users are concerned, but are only beginning to emerge in intelligent vehicle development.   The purpose of the present workshop is therefore to attract researchers who either apply cognitive approaches to intelligent vehicles or have made major contributions to robotics in this manner. The content of this workshop is thus relevant to anyone interested in one of the major under-researched areas in the field of intelligent vehicles, now ripe for exploitation. As such, it is highly appropriate to the participants of the Intelligent Vehicle Symposium 2017.
Keywords Self-Driving Vehicles; Vehicle Control; Situation Analysis and Planning
Proposed speakers Tom Ziemke, University of Sk¨ovde and Link¨oping University, Sweden.
Yiannis Demiris, Imperial College London, UK
Alex Blenkinsop, University of Sheffield, UK.
Azra Habibovic, RISE Viktoria, Sweden.
Mauro da Lio, University of Trento, Italy.
Henrik Svensson, University of Sk¨ovde, Sweden.
Fabio Tango, Centro Ricerce Fiat, Italy.
Tim Tiedemann, Hochschule fr Angewandte Wissenschaften Hamburg , Germany.
David Windridge, Middlesex University, UK.
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Workshop 2 Automotive Cybersecurity 2017 (AutoCyS-17)
Organizers Madhusudan Singh and Shiho Kim, Yonsei University
Date/time June 11, 2017 (half-day, 1:30 pm – 5:30 pm)
Abstract Nowadays intelligent vehicle is an emerging research topic going on around us. The researcher is working on to make intelligent and autonomous vehicles, and transportation system. The more our vehicles become intelligent, the more we need to work on safety and security for vehicles technology. The workshop aims to foster discussion on automotive cybersecurity related problem and solutions and security standardization for not only intelligent vehicles but also discuss security for Infrastructure of Intelligent transportation system. We need to know what type of security requirements needed during design and development of intelligent vehicles. Therefore it’s aimed to investigate security, standardization, security method and process for vehicle communication. The primary objective of this proposed workshop will also discuss vehicle-communication security for the vehicle to vehicle (V2V) communication and Vehicle to Infrastructure (V2X) to work with intelligent vehicles and intelligent transportation environment and concentrate on research work for, Cryptography, Embedded security, hardware security for intelligent vehicles. The topics of interest of this workshop cover, but is not limited to, the following scope:  Automotive Security threats to cyber-physical systems  Security architecture, design, implementation, and management of intelligent vehicles  Security Techniques and protocols for cooperative vehicles  Data communication security in networked embedded systems  Automotive collision prediction and avoidance in cyber world  Security mechanism for automotive motion planning in dynamic environments  Practical security experiences and testbeds related with intelligent vehicles  Automotive Industrial expe
Keywords Autonomous / Intelligent Robotic Vehicles; Intelligent Vehicle Software Infrastructure; Smart Infrastructure
Proposed speakers Dhananjay Singh, Yonsei University, Korea
Gaurav Tripathi, Bharat Electronics Limited, India
B. Balaji Naik, National Institute of Technology (NIT) Sikkim, India
Antonio Jesus Zara, HES-SO Valais, Switzerland
Workshop 3 Workshop on machine vision and interfaces in data fusion platforms for automated driving
Organizers Michael Schilling, HELLA KGaA Hueck & Co.

Cristobal Curio, Reutlingen University

Date/time June 11, 2017 (full-day, 9:00 am – 5:00 pm)
Abstract While the path to series production of automated driving cars still faces many challenges we will focus in this workshop on two topics. One main challenge in building automated driving cars today is the huge variety of interfaces to the environmental fusion system. The current diversity in technologies (e.g. lidar/radar/camera sensors, V2X, maps) and suppliers, spawn a myriad of interfaces which does not allow a quick or easy integration into any data fusion platform. Furthermore, the deployed interfaces of the environmental fusion systems for a specific driving function (e.g. from intersection assist to valet parking) are also not standardized in any way today. When we look at the next step by implementing distributed data fusion in order to get redundancy and enhanced fusion algorithms, the interface challenges will become even more complex. The second topic our workshop will focus on, are the challenges in using high resolution cameras. Human drivers base most of their decision solely on their visual system. Current infrastructure offers rich visual cues to guarantee safe and flexible driving. It seems that today’s semantic vision in combination with high resolution cameras can interprete the richness of the environment very much like the human visual system does and thus will play a big role in future automated driving vehicles. Yet todays systems still face challenges, ranging from adverse weather conditions over pedestrian movement estimation for enhanced predictions to implementing high data stream interfaces to a central fusion platform. Further, high resolution image data also offers the opportunity to produce highly sophisticated simulations, useful e.g. for function optimization and testing purposes.
Keywords Sensor and Data Fusion; Vision Sensing and Perception; Automated Vehicles
Proposed speakers Daniel Clarke, Cranfield University
Thomas Dammeier, Hella Aglaia
Christian Görick, Honda Research Institute
Rolf Johansson, SPE
Mohsen Sefati, RWTH Aachen
Paul Michael Newman, University of Oxford
more invited people to be confirmed
Workshop 4 Deep Learning for Vehicle Perception
Organizers José M. Alvarez,; Uwe Franke,; Trevor Darrell, NICTA
Date/time To be announced
Abstract Deep learning, and in particular Convolutional Neural Networks, has become the main component of many intelligent vehicle algorithms. Jointly with the explosive growth in the available amount of driving data these data-driven algorithms have certainly enabled the next generation of platforms for reliable autonomous driving as evidenced by the algorithms used by a large number of companies like MobilEye, AutoX, Zoox, Toyota Research, General Motors, Volkswagen, and Daimler among many others. The goal of this workshop on deep learning for vehicle perception (as a second edition of the Deep-Driving workshop held in conjunction with IV2016, follow textit{http://iv2016.berkeleyvision.org/} for further information) is to foster discussion and to accelerate the study of deep architectures in autonomous driving problems with a focus on the efficiency of the algorithms.
Keywords Autonomous / Intelligent Robotic Vehicles; Cooperative Systems (V2X); Self-Driving Vehicles
Proposed speakers To be announced
Workshop 5 Multi-Sensor Fusion and Extended Object Tracking
Organizers Stephan Reuter, Karl Granstrom, Marcus Baum, University of Ulm
Date/time June 11, 2017 (full-day, 9:00 am – 5:00 pm)
Abstract The aim of this workshop is to provide an overview of recent approaches for environment perception based on occupancy grid maps and multi-object tracking and to foster discussions about multi-sensor fusion approaches as well as the reliability of environment perception. Further, the audience is introduced to extended object tracking, with a focus on both the underlying theory and relevant real world applications. The modelling of object shapes and measurements in extended object tracking algorithms are introduced in detail and the integration in multi-object tracking algorithms is outlined. Additionally, several applications of extended object tracking and the multi-sensor fusion approaches are presented by the organizers and invited presenters
Keywords Sensor and Data Fusion; Information Fusion; Vehicle Environment Perception
Proposed speakers
  • Stephan Reuter, Daimler Research Institute for Vehicle Environment Perception (driveU) / Ulm University, Ulm, Germany
  • Karl Granström, Chalmers University, Gothenborg, Sweden
  • Marcus Baum, Georg-August-University Göttingen, Göttingen, Germany
Workshop 6 The 4th Workshop on Naturalistic Driving Data Analytics
Organizers Takashi Bando, DENSO International America, Inc.
Chiyomi Miyajima, Nagoya University
Pujitha Gunaratne,Toyota Motor Engineering and Mnf. North America
Date/time June 11, 2017 (full-day, 9:00 am – 5:00 pm)
Abstract This workshop on Naturalistic Driving Data Analytics is proposed for the fourth time now, to be collocated at IEEE Intelligent Vehicles Symposium (IV) in 2017. The purpose is two folds, to foster discussions on challenges related to developing and using the right methods to make meaningful inferences and interpretations from large scale unlabeled naturalistic driving data to and to exchange ideas on how to optimally use naturalistic driving data for different purposes, such as driver behavior analysis, further development of ITS technologies, as well as for automated driving.

Topics of Interest are

  • Data Collection
    • Naturalistic driving data collection & sharing
    • Robust data compression, reduction, and annotation for large-scale data
  • Data Analytics
    • Driver behavior analysis
    • Image processing methods for naturalistic driving videos
    • Machine learning methods for naturalistic driving data
  • NDD applications
    • Human Machine Interface / Interaction
    • Advanced Driver Assistance Systems / Automated Driving
    • Fuel efficiency
    • Traffic Management Systems
Keywords Driver State and Intent Recognition; Situation Analysis and Planning; Human Factors and Human Machine Interaction
Proposed speakers To be announced
Tutorial Dedicated Short Range Vehicular Communications: Overview, Technical Challenges, and Applications
Organizers Gaurav Bansal and Dr. John Kenney, Toyota InfoTechnology Center, USA
Data/time June 11, 2017 (half-day, 9:00 am – 12:00 noon)
Abstract In this tutorial we cover the most important aspects of Dedicated Short Range Communications (DSRC), also known as Cooperative ITS. This technology is in the early stages of deployment in North America, Europe, and other regions. The US DOT plans to require DSRC in new vehicles in the coming years. DSRC is used to communicate vehicle-to-vehicle (V2V) and vehicle-to/from-infrastructure (V2I), enabling a set of compelling safety, mobility, automated driving, and environmental applications. This tutorial focuses on the safety and automated driving use cases. We explain the DSRC protocol stack, collision avoidance applications, and technical challenges for deployment. We discuss large-scale field tests and early deployment projects in the US, Europe, and Japan, e.g. the US Safety Pilot and the Rotterdam-Vienna Corridor Project. After presenting DSRC basics, we focus on a specific research problem that is currently of great interest: DSRC Channel Congestion. We discuss the merits of various approaches to address congestion, including avoidance and active control, as well as control modalities (message rate, transmit power, etc.). As a case study we present our specific research on adaptive message rate control, which is under consideration for standardization in the US and Europe. We end the tutorial with a discussion of the role DSRC can play in support of automated vehicles, including a framework for communicating dynamic road conditions to nearby vehicles. The primary goal of the tutorial is to empower the attendee to participate in this important emerging technology, whether as a researcher, a developer, or a planner.

The objectives of the tutorial are:

  1. Master the fundamentals of a critical emerging VTC technology, DSRC
  2. Design collision avoidance applications based on V2V communication
  3. Evaluate the impact of strategic investment on DSRC deployment
  4. Join the DSRC research community, contributing to solutions for congestion control and other technical challenges
  5. Incorporate DSRC in automated vehicle development
Keywords Cooperative Systems (V2X); V2X Communication; Automated Vehicles
The syllabus of the tutorial
  1. DSRC Technology  (15 minutes)
  2. Vehicular Safety Communications  (20 minutes)
  3. Overview of DSRC Protocols (20 minutes)
  4. Technical and Policy challenges for deployment (20 minutes)
  5. Field tests and early deployments (20 minutes)
  6. DSRC channel congestion control (40 minutes)
  7. DSRC in support of automated vehicles (45 minutes)
Presenters Gaurav Bansal and John Kenney, Toyota InfoTechnology Center, USA
Workshop 7 VIVA-Surround: Vision for Intelligent Vehicles and Application-Surround 2017, Workshop & Challenges
Organizers Akshay Rangesh, UC San Diego,

Jacob Dueholm, UC San Diego and Aalborg University

Miklas Kristoffersen, UC San Diego and Aalborg University

Rakesh Rajaram, UC San Diego

Eshed Ohn-Bar, UC San Diego

Ravi Satzoda, UC San Diego

Mohan Trivedi, UC San Diego

Date/time June 11, 2017 (half-day, 1:30 pm – 5:30 pm)
Abstract The workshop will cover topics relevant to vision-based analysis of surround vehicles from RGB video. Specifically, an extensive U.S. highway dataset collected with 4 perspectives for complete panoramic surround will be presented and made public for the scientific community with complete annotations of vehicle location, ID, state, calibration data, and semantic trajectory labels.

We will discuss the following specific challenges, to which motivation, challenges, benchmark, results, and metrics will be presented:

1) Multi-perspective vehicle detection

2) Multi-perspective vehicle tracking (image plane)

3) Multi-perspective vehicle tracking (3D)

4) Multi-perspective trajectory behavior classification and prediction.

Keywords Image, Radar, Lidar Signal Processing; Situation Analysis and Planning; Vehicle Environment Perception
Proposed speakers To be announced
Workshop 8 CPSS Based Parallel Driving
Organizers Fei-Yue Wang, Institute of Automation, Chinese Academy of Sciences, China

Nanning Zheng,Xi’an Jiaotong University, China

Li Li, Tsinghua University, China

Lingxi Li, Indiana University-Purdue University Indianapolis, USA

Dongpu Cao, Cranfield University, U.K.

Date/time June 11, 2017 (half-day, 8:00 am – 12:00 noon)
Abstract Along with ACP-based parallel management and control and its wide real-world applications in the past decade, cyber-physical-social systems (CPSS)-based parallel driving has been steadily developed. This is also greatly correlated with the emerging development in connected and automated vehicles. This workshop aims to compile the latest research and development advances in parallel driving, and present and highlight the emerging new technologies in Connected and Automated Vehicles in China.

The topics of this Workshop include, but are not limited to:

  • Theories of ACP-based parallel management and control for parallel driving
  • Development of artificial transportation systems in parallel driving • V2V, V2I and V2S (vehicle to service) communications and control for parallel driving
  • Parallel transportation systems for mixed-level automated vehicles • Driver-vehicle interaction and collaboration between physical and artificial driving systems
  • Testing, demonstration and assessment of parallel vehicles
  • Parallel testing approaches for automated vehicles
  • All the latest advances and emerging new techniques in Connected and Automated Vehicles in China
Keywords Automated Vehicles, Connected Vehicle, CPSS, Parallel Driving
Proposed speakers To be announced