Get the latest on imaging and auto sensors, autonomous vehicles, and AI and more.
Roger D. Melen | Senior Advisor of Toyota InfoTechnology Center U.S.A., Inc.
Many future vehicles will have many cameras and radars viewing the roadway providing data to driving assistance systems. These imaging systems are vulnerable to degradation from impacts with roadway bugs and dirt. The vehicle images may monitored and compared with data received from nearby cars using V2X communications. Sensor cleanliness problems noted by a comparison of the images may be reported to on board systems and possibly corrected by automated on-board cleaning equipment and data processing methods
Mahabir Gupta | Solutions & Products Consultant - IoT, Mobility & Data Security of Volvo
Ronald Mueller, Associate Consultant, Smithers Apex
This session will feature presentations from companies that have successfully deployed autonomous vehicles
Steve Vozar | Co-Founder and CTO of May Mobility
Multipolicy Decision Making (MPDM) is a fundamentally different approach for self-driving vehicles to make behavioral decisions. Rather than select from trajectories that pass through anticipated free space, MPDM selects from a relatively small set of closed-loop controllers, or "policies" that are informed by real-time simulation onboard the vehicle, taking interactions between multiple agents into account. The result is an autonomous vehicle with extremely smooth, human-like behavior that reacts to agents in real time with emergent behavior that would not be possible with traditional planning approaches. MPDM has been powering May Mobility's fleet of self-driving shuttles in public road deployments since June of 2018, having carried more than 90,000 passengers in 4 cities as of August 2019. May Mobility CTO and co-founder Dr. Steve Vozar will share the basics of how MPDM works, as well as real world observations from May Mobility's deployments on practical considerations for sensors and behavioral planning.
Romain Clement | Head of Hardware of Lyft, Level 5 Autonomous Vehicle Division
Abstract to come!
Pierre Oliver | Chief Technology Officer of LeddarTech
Join Pierre Olivier – CTO at LeddarTech, and Pierre Lefèvre – CTO at Coast Autonomous as they take a deep dive into a real-world use-case for LiDAR technology deployment in autonomous shuttles. Attendees will walk out of this session with the answers to the following key questions:
This session will also touch base on Pixell: LeddarTech's LiDAR Cocoon product, and how it was developed collaboratively to address a growing market gap.
John B. Rogers, Jr | Co-Founder and Chief Executive Officer of Local Motors
Most automotive companies of today are stuck in the past – they’re inefficient, and don’t readily deliver what consumers want or need. LM Industries’ process, which is founded on local microfactories coupled with the power of co-creation, exceptional safety testing and legislative lobbying, is connecting our outdated mobility industry with the future of autonomy, today. This keynote will explore how an innovative digital OEM is leading the way in bringing autonomous mobility into our daily lives. Jay Rogers, CEO and Co-Founder of LM Industries, will point to use cases to bolster this presentation.
In this session, delegates will hear the latest industry developments and opportunities for automotive image sensors. Where is the market currently, where is it headed?
Phil Amsrud | Senior Principal Analyst, Automotive Electronics & Semiconductor of IHS Markit
Wade Appelman | VP of Sales and Marketing of SensL Technologies
Autonomous transportation requires a fusion of sensors to fulfill the required capabilities and redundancy. ON Semiconductor is already the market share leader for automotive image sensors and is now positioned to deliver the critical components for LiDAR and radar. This ‘triple play’ of sensor modalities is already well proven and is employed in a number of current autonomous transportation applications. This talk will cover the trends for different sensor modalities and their fusion, predications for future performance and an overview of ON Semiconductor’s technology roadmap for addressing these performance challenges.
Ron Mueller | CEO of Vision Markets of Associate Consultant of Smithers Apex
Image sensors with a linear pixel and a typical exposure time provide a limited dynamic range and are not sufficient for the challenging scenarios in automotive imaging, such as alleys in sunlight, frontal sun, or tunnel entries and exits. The human eye can see a much higher contrast. There are a handful of different methods to get the large contrast range in an image. We briefly introduce the technology behind the different methods and provide real image captures from modern image sensors utilizing beforementioned technologies. The presentation provides an overview of the benefits, limitations, and considerations when selecting an HDR image sensor for the next car generations.
John Wheatley | Division Scientist, Display Materials & Systems Division of 3M
Driver monitoring cameras are a critical component to automated vehicle safety systems. However, interference from sunlight can cause significant performance and reliability issues. Presented will be new optical components that, in a thin film, provide both wavelength and angular filtration to reduce interference from noise light and improve system performance. These materials can also reduce overall system thickness in addition to the optical performance advantages. Specific properties of these materials will be discussed as will analytical and experimental analyses.
Dr. Petronel Bigioi | CTO, Imaging and General Manager of FotoNation of Xperi Corporation
The presentation will discuss various aspects of driver monitoring systems dynamics in context of fully autonomous cars transition and proliferation.
Will the driver monitoring systems technology, infrastructure and know-how be lost by fully autonomous cars wide scale adoption?
Dr Alexis Lluis Gomez | Director, Image Quality of ARM
This presentation describes how ISPs can be optimised for automotive ML/CV applications on algorithmic level. Why we need ISP in the first place and what kind of advantages it is going to provide for autonomous driving systems. What exactly is different in processing for human and computer vision, which stages are required and to which level of complexity.
Moderated by Robert Bloomquist, Director Automotive Marketing, Xilinx
Marius Evensen | Head of Automotive Marketing of SONY Electronics
Recently the number of cameras installed automotive is increasing for both sensing and viewing purpose. In addition to the basic image sensor characteristics such as low light performance and wide dynamic range, it is important to take measures against the flicker of LED light sources. (LFM; LED Flicker Mitigation) In this presentation, we will discuss the basic performance and LFM coexistence and consideration of the image sensor structure that realizes it.
Lawrence Vivolo | Sr. Business Development Manager - Automotive & EDA of Dell EMC
After briefly introducing Artificial Intelligence, Machine Learning and Deep Learning, the talk will focus on the common workflow of applying AI to the lifecycle of automotive product development: Data Collection & Acquisition phase, Data annotation phase, Quality checks and finally constructing the network with its test and validation in a last step.
The audience will:
Miguel D. Acosta | Chief Of The Autonomous Vehicles Branch of California Department of Motor Vehicles
The presentation will provide an overview of Autonomous Vehicles regulations in California, including testing and deployment requirements, and the CA DMV’s Autonomous Vehicles Program
Haran Thanigasalam | Senior Architect & Independent Contributor (Intel) Chair of Imaging and Camera Workgroup of MIPI Alliance
Aligned with emerging use cases and applications, discuss the pathway to advancing MIPI imaging conduit targeting multiple product platforms including Mobile, Content Creation, IoT, and Autonomous systems. Provide detailed overview of features and capabilities targeting Machine Awareness and Advanced Driver Assisted Systems.
Boyang Zhang | Senior Camera Engineer of Cruise
Autonomous driving is on its way to completely reshape modern transportation systems. As an industry leader, Cruise is constantly exploring the best vision technology systems for autonomous vehicles. We find that the image sensor technologies on today’s market, which are primarily designed for human vision, do not have optimal performance for the needs of autonomous driving. In this presentation, we will discuss the outlook of future image sensors for fully autonomous vehicles.
Angus Pacala | CEO and Co-Founder of Ouster, Inc.
Silicon has transformed the consumer tech industry over the past few decades by enabling higher performance while lowering tech cost. Ouster has engineered the optimal lidar by using a unique combination of silicon CMOS detectors and SPADs/VCSELs, and custom designing silicon ASICs. These components are on an exponential improvement curve, much like Moore's Law, and are still far from maturity with potential for 10x improvement in just a few years. This talk will dive into the implications of introducing silicon to lidar, expected improvements, and performance roadmap.
Ethan Frantz | Sr Software Engineer of FLIR
Long Wave Infrared (LWIR) Cameras are poised to improve auto safety. As a truly passive sensor, LWIR excels in challenging environments such as high contrast, clutter, driving into the sun, fog, dust and smoke. FLIR has already deployed over 600,000 LWIR cameras in passenger cars, extending the drivers vision at night beyond the range of the headlights.
With the emergence of machine learning, LWIR will improve automotive safety by providing an orthogonal and redundant sensor. This talk will show how LWIR cameras complement the other sensor used in automotive application particularly in challenging conditions.
Bert Fransis | SR. DIRECTOR OF PRODUCT of Arbe
Autonomous driving is no longer just a vision, but a reality already shaping the automotive industry and culture. Arbe is disrupting autonomous driving sensor development by bridging the gap between radar and optics with its proprietary imaging radar solution that provides optic sensor resolution with the reliability and maturity of radar technology for all levels of vehicle autonomy. As the world’s first company to demonstrate ultra-high-resolution 4D imaging radar with post-processing and SLAM (Simultaneous Localization and Mapping), a missing link in technology for level three and higher in vehicle evolution, Arbe's patented radar is changing the future of mobility.
Peter Hodgins | Automotive Product Marketing Director of Optimal Plus
Manufacturing automotive cameras is extremely challenging due to high performance standards and sensitive manufacturing processes where rework is not allowed. In this paper, we will present how you can leverage big data analytics powered by machine learning algorithms to predictively and reactively improve camera performance, quality, and scrap rates. By connecting incoming lenses MTF to CMAT and field data, O+ Big Data analytics solution enables the camera performance prediction by utilizing incoming material characteristics and inline processes, preventing potential unreliable parts from making it into the process flow and optimizing manufacturing yield, efficiency and product reliability
John Stockton | SVP of Operations and Technology Strategy of Aeye
What is the safest, most cost-effective, and most efficient way to design an intelligent perception solution for autonomous vehicles? AEye believes that a truly intelligent perception solution begins with how the data is collected, and that the solution must be software-definable. In this session, AEye SVP of Operations and Tech Strategy John Stockton discusses individual use cases and driving scenarios which are particularly difficult for conventional automotive perception solutions to handle, and how a software-definable perception system can ensure the overall safety and efficiency of autonomous vehicles.