4月26日 (火) ―カンファレンス1日目
Salah Hadi | Global R&D Director Vision & Night Vision Systems of Autoliv Vision Systems, Sweden
Dr Bakhtiar Litkouhi | Technical Fellow and the Manager of Automated Driving and Vehicle Control System of General Motors, USA
Dr Massimiliano Lenardi | Laboratory Manager - Senior Researcher of HITACHI, France and Germany
Hitachi’s Automotive Vision targets the supply of reliable components and telematics solutions enabling self-driving vehicles. Insights will be given on technologies and services needed to deploy autonomous driving, in particular on those provided by Hitachi, from total-sensing to control and communication technologies.
- How are customer expectations changing for IS applications in cars?
- What are the latest challenges of integrating all the modules?
- What are the key challenges OEMs want the IS ecosystem to address?
- How should components suppliers approach the auto market – what do they need to consider to industrialise their ideas?
- What is the future of interoperability?
Salah Hadi, Global R&D Director Vision Systems, Autoliv, Sweden
Henrik Lind, Technical Expert, Volvo Car Corporation, Sweden
David Sánchez Fernández, ADAS Technical Specialist, Jaguar Land Rover, UK
Dr Bakhtiar Litkouhi, Technical Fellow. Manager: Automated Driving & Vehicle Control System, General Motors Research & Development, USA
Dr Massimiliano Lenardi, Laboratory Director, Hitachi Europe Ltd
Richard Schram | Technical Manager of Euro NCAP, Belgium
The presentation will show the current developments of test and assessment protocols and will outline Euro NCAP’s vision towards 2020 and beyond.
Srinivasa Narasimhan | Associate Professor Robotics Institute of Carnegie Mellon University, USA
- Gain insign into a new design for a headlight that can be programmed to perform several tasks simultaneously and that can sense, react and adapt quickly to any environment with the goal of increasing safety for all drivers on the road
- Explore the engineering challenges in building this headlight as a high-throughput, low-latency platform for computational imaging and lighting
- Assess experiences with the prototypes developed over the past two years
4月27日 (水) −カンファレンス2日目
Ian Riches | Global Automotive Practice of Strategy Analytics
- Answering the “ultimate” question: When will driverless cars be mainstream?
- ADAS market development
- What functions & features are driving growth?
- How is the role of image sensors evolving?
- The path to autonomous driving
- OEM Evolutionary Path
- “Outsiders” revolutionary Path
- Long-term potential winners & losers
Ralf-Peter Schäfer | Vice President Traffic and Travel Information Product Unit and Fellow of TomTom, Germany
The presentation outlines the technical insights of TomTom’s traffic data analytics portfolio processing billions of probe based speed information day-to-day. With the introduction of TomTom’s historical and real-time traffic technologies IQ Routes and TomTom Traffic in 2007 the portfolio has been implemented in over 45 countries globally.
The backbone of the technology is community data from navigation devices, fleet management solutions as well as GPS based smartphone applications for road users. Today, the entire community of TomTom traffic consists of more than 400 Mio. GPS enabled devices as a basis for big data analytics in mobility, planning, geo-marketing and transport management.
The presentation will give insights into the big traffic data archive, statistical information and examples of how the traffic and digital map database can be used in different areas of traffic analytics as traffic information, traffic planning, traffic management, Geo-Marketing, smart mobility and connected services for road travellers.
- Implementation steps to autonomous driving – what are the main issues that remain to be resolved in order for it to become a reality?
- To what extent will the concept of the car we know today need to change to accommodate new vision technologies?
- Consumers - how will they buy into idea of autonomous car; what lessons are being learned from ADAS take-up?
- Developing advanced decision-making algorithms that will allow autonomous vehicles to make safe driving decisions with and without human input
Ian Riches, Director, Global Automotive Practice, Strategy Analytics, UK
Ralf-Peter Schäfer, Vice President Traffic and Travel Information Product Unit, TomTom, Germany
Allan McAuslin, Product Line Manager, Vision and Automated Drive, NXP Semiconductors
視覚センサーとレーダー、LiDAR (光検出と測距) 、超音波センサー、赤外線センサーを組み合わせたシステム−ADASと自律運転にとって重要なセンサーの種類、低レベルフュージョンと高レベルフュージョン
Mario Brumm | Co-Founder of Ibeo Automotive Systems, Germany
The automotive industry will have to introduce more automation to the vehicle whilst considering human-factors aspects. The aim of the automation has to be a high usability and confidence of the human driver in the automated system as well as the possibility of fluent switching between manual and automatic driving giving the driver full control over the vehicle. This session explores:
- The roadmap from driver assistance to highly-automated driving
- Technological challenges in the functional development
- TriLumina’s solid-state scanning laser system isolates the driver’s face, dynamically illuminating only the area of interest without the inefficiency, heat and red glow of LEDs
- eyeSight's touch-free interface and in-car sensing solution provides safer driving experiences when interacting with automotive systems
- eyeSight’s gesture and head tracking software directs the TriLumina Smart Illuminator to dynamically illuminate only specific areas in the field of view, minimizing power consumption, reducing noise and providing the most robust DMS solution on the market
David Abell, Chief Strategy Officer and Co-Founder, TriLumina Corp., USA
Gideon Shmuel, CEO, eyeSight Mobile Technologies, USA
Pierre-Yves Cattin | Co-founder of Fastree3D SA, Switzerland
Dr Feng Kuo, CTO and Co-Founder, Techpoint Inc, USA
The increasing use of video camera for vision and ADAS application in automobiles has prompted the development of a more robust HD video transport system, the High Definition Transport Video Interface (HD-TVI). It is capable of transmitting HD video (720p/1080p) through low cost coaxial cable/connector or unshielded twisted pair wires over 300m due to the low signal bandwidth used. This HD analogue video transmission system was developed based on the foundation of the widely adopted SD analogue video format for its robustness but without its weakness of video artefacts. The transmission is real-time with minimum latency and also supports the bi-directional data channel over the same cable. With the advantage of low EMI and the resilience against interference, it provides an alternative and low cost solution for HD video transmission in the automotive environment.
Chair: David Sánchez Fernández, ADAS Technical Specialist, Jaguar Land Rover, UK
Winwe Qiu | General Manager of Ningbo Sunny Automotive Optech Co., Ltd
Mario Heid | General Manager OVT Europe of OmniVision
BrightEye™ −先進運転支援システム (ADAS) 対応のビジョンシステム
Dr Ofer David | CEO of BrightWay Vision
Gated imaging has shown great potential in automotive imaging. Raw video imagery by day and night for obstacle detection functionalities will be presented, along with a comparison of gated and passive in harsh weather conditions. Simplified traffic sign localization in 3D will also be discussed.
Take this opportunity to see a demo of this exciting technology.
Andreas Brückner | Head of Microoptical Imaging Systems Group of Fraunhofer IOF, Germany
There is a constant trend for miniaturization of digital cameras which is mainly driven by mobile devices like smartphones but also extremely valuable for applications in automobile and machine vision. It pushes the shrinking of opto-electronic, electronic and optical components. While opto- and micro-electronics have made tremendous progress, the miniaturization of optics still struggles to keep up. The demands for higher image resolution and large aperture of the lens (both driven by smaller pixel size) conflict with the need for a short focal length and a simple, compact design in terms of miniaturization. Array cameras inspired by the smallest known vision systems in Nature – the compound eyes – offer a way out of the dilemma.
The contribution provides an illustration of the fundamental limits of the miniaturization of digital imaging systems. It is shown that these limits can be at least partly overcome by the convergence of microelectronics, microoptics and image processing applied in array cameras. The basics about the wafer-level optics fabrication technology are presented in order to demonstrate its potential for high-precision, parallelized production and thus for reducing the production costs. Finally, the contribution gives examples of realized demonstrators for array imaging sensors and cameras of smallest size that are able to overcome the scaling limits of traditional optics and thus to go where no camera has gone before.
Dr Michael Chiu | Chief Technology Officer of Automation Engineering Incorporated
- Critical attributes of stereo cameras and evolution into the future
- Enabling processes and components for stereo cameras, including image sensors, manufacturing & test processes
Kari Pulli, Senior Principal Engineer, Imaging and Camera Technologies Group, Intel
- Specialized accelerators can be orders of magnitude more efficient than general-purpose hardware, but they can be difficult to program
- Recent standards such as OpenCL and OpenVX can make such accelerators easier to access
Etienne Perot, Vision Research Engineer, Valeo
Mayank Mangla, ADAS Imaging Architect, Texas Instruments
Sascha Klement | Managing Director, CTO of gestigon GmbH
- Features and use cases for gesture control and driver monitoring
- Technical requirements in automotive applications
- KPIs for assessing the quality of such systems
- Testing and quality assurance strategies
- Social challenges in the transition from innovative prototypes to automotive-grade series production
Dr. Bernd Buxbaum | CEO/CTO, Founder of pmdtechnologies
On semi-autonomous and autonomous driving, the driver awareness remains an important safety factor. For safe driver monitoring, ToF (Time-of-Flight) provides unique robustness features on a reasonable cost target.
- Integrated availability recognition: intrinsic amplitude value with each distance including saturation recognition
- Real monitoring of whole sensor chain: reference channel in each measurement cycle
- Long-term availability: robust availability, even on mechanical stress
- Usage of mass market components only – all system components are proven in use
- Moderate calculation effort for accurate distance information
- One camera head for eye lid recognition and distance measurement
Alexandru Drimbarean, Vice President Advanced Research, FotoNation Ireland
Driver and passenger safety is one of the main concern for car makers. Driver’s undivided attention to the traffic is essential to avoid any serious accidents. The National Highway Traffic Safety Administration conservatively estimates that 100,000 police-reported crashes are the direct result of driver fatigue each year. This results in an estimated 1,550 deaths, 71,000 injuries, and $12.5 billion in monetary losses. These figures may be the tip of the iceberg, since it is currently difficult to attribute crashes to sleepiness. Also, distracted driving such as using a cell phone, texting and eating is the cause of 1 out of 5 crashes in the US. In 2012, 3,328 people were killed in crashes involving a distracted driver. Finally, the race toward semi-autonomous and fully-autonomous driving is accelerating the need to have a driver monitoring system is paramount since the vehicle needs to know what the driver state is before it gives back control.
The presentation will begin by detailing the key aspects related to the image acquisition, processing and computer vision technologies with emphasis placed on eye and gaze detection as well as head location and orientation calculation. These are required to continually monitor and assess the driver state in order to detect conditions such as excessive drowsiness or lack of road attentiveness that could potentially lead to accidents. Then a more advanced use case, namely Driver identification implemented using face recognition technology is introduced. This is becoming increasingly relevant for car personalization: seat adjustments, mirror adjustments mirror settings as cars are being used by multiple persons as well as for security particularly important for theft prevention. Finally we address implementation specifics, emphasizing the flexibility that software can offer in terms of where the camera could be located and how hardware acceleration could bring performance and thermal management advantages.