Final Weeks to Reserve your Place

The implementation of autonomous technology is at the forefront of OEM vehicle development within applications such as passenger cars, commercial vehicles and public transportation. Making the vision of mainstream autonomous driving a reality will require overcoming some significant technological, safety and regulatory barriers. This summit will address the latest technological advancements in intelligent transportation, it will also explore how developers will overcome the various safety and regulatory hurdles on the path to implementation. Don’t miss this opportunity to hear from OEMs, commercial/academic R&D developers, insurers as well as government regulatory agencies on how autonomous driving is positioned to significantly change the landscape of transportation as we know it today.

Final Agenda

Tuesday, February 13, 2018

Autonomous R&D Applications

1:40 pm Chairperson’s Opening Remarks

Sai Yagnyamurthy, Director Global Strategy for Automotive Mobility Services, AI, Telematics, Autonomous Driving, Ford Motor Company

1:45 OPENING KEYNOTE PRESENTATION: Artificial Intelligence in Autonomous Vehicles

Gaurav Agarwal, DriveWorks Product Management, Autonomous Vehicle, NVIDIA

Building a self-driving technology which can understand the nuances of the world and drive in all the scenarios is a hard problem. Driving in bad weather conditions e.g. snow when there is no lane markings, complex urban streets, construction zones etc are some examples. Artificial intelligence can help solve some of these issues. In this talk, the latest trends and challenges in Autonomous driving will be presented. Then the talk with discuss the role of Artificial intelligence/deep learning to enable this technology.

2:15 Autonomous Driving - Trends, Challenges and Path through Machine Learning

Liang Heng, Ph.D., Cofounder & CTO,

Autonomous driving has gained enormous attention and momentum over the past years, due to its potentially huge benefit to our transportation systems. This talk will summarize the current trends and on-going efforts of autonomous cars. Then the talk will highlight the technical challenges and share some insights in how machine learning leads us to the path.

2:45 Self Driving Machines

Sam_KheratSam Kherat, Ph.D., Adjunct Professor, Mechanical Engineering Department, Bradley University

The adoption of robotics and automation technologies has been and will continue to be an evolutionary process. This past decade has seen a huge leap in autonomous vehicle technologies. On the other hand, the off-road implementation has been intricate. The mining and construction industries have been facing fewer skilled operators, increased scrutiny on hazardous or dangerous operations and environmental impacts like operator sound and vibration limits. In this presentation, Dr. Sam Kherat will overview the adoption of robotics, automation, and operator assist programs to improve safety in on-road as well as off-road applications.

3:15 Localization for the Next Generation of Autonomous Vehicles

Rob_HranacRob Hranac, Chief Operating Officer, Swift Navigation

The next generation of vehicles offering advanced driver assistance or fully autonomous operation will demand increasingly accurate position information, available in all driving conditions and with 100% availability. No single sensor can meet these requirements alone and therefore it is necessary to use a combined sensor suite solution incorporating several different kinds of sensors working together. As the only source of absolute position, velocity and time, GNSS play a critical role, however the next levels of autonomy (levels 3 - 5) require a GNSS system with lane-level positioning or centimeter-level accuracy (10 cm). Swift Navigation’s discussion will provide a data-supported look at how RTK GNSS—augmented with local inertial measurements through accelerometers and gyroscopes—provides the accuracy required to gather useful information like vehicle heading, as well as increasing the frequency, smoothness and robustness of position information.

3:45 Refreshment Break with Exhibit and Poster Viewing

4:15 KEYNOTE PANEL DISCUSSION: Integrating Transportation into the IoT – Smart Cities and the Logistics Ecosystem

Sai_YagnyamurthyModerator: Sai Yagnyamurthy, Director Global Strategy for Automotive Mobility Services, AI, Telematics, Autonomous Driving, Ford Motor Company


Gaurav Agarwal, DriveWorks Product Management, Autonomous Vehicle, NVIDIA

Anand Gopalan, Ph.D., CTO, Velodyne LiDAR

Jonathan Riehl, Ph.D., Transportation Systems Engineer, Traffic Operations and Safety Laboratory - Civil and Environmental Engineering, University of Wisconsin-Madison

One of the key components that will lead to widespread consumer adoption of autonomous vehicles is the integration of smart transportation infrastructure. Examining the potential of the IoT in both private and public applications in addressing critical transportation issues such as traffic congestion, minimization of environmental impacts and improvement in overall quality of life. This panel discussion will explore how smart cities and the logistics ecosystem will propel autonomous vehicles into the mainstream and what the future holds for smart transportation.

5:15 Close of Day One

Wednesday, February 14, 2018

Advancements in LIDAR and RADAR

8:00 am Morning Coffee

8:35 Chairperson’s Opening Remarks

Sam Kherat, Ph.D., Adjunct Professor, Mechanical Engineering Department, Bradley University

8:40 KEYNOTE PRESENTATION: Smart 3-D LiDAR – Computing on the Autonomous Edge

Anand_GopalanAnand Gopalan, Ph.D., Chief Technology Officer, Velodyne LiDAR

Today, LIDAR sensors are becoming an essential element of the AV system, due to their rich data content, robustness to a variety of environmental conditions and coverage of the largest number of corner cases. The next few years will see the roll out of several AV fleets thereby proving out the case for a driverless car. A crucial bottleneck to mass commercialization will then be cost and power optimization of the autonomous driver system. One key enabler for this will be a smart LIDAR that not only generates a rich point cloud data set but also utilizes its first-hand knowledge of the dataset to carry out perception tasks at the sensor edge. As with other edge computing paradigms, this will result in a much more cost and power efficient compute system.

9:10 Photonic Technologies for LIDAR Sensors in Autonomous and ADAS Applications

Jake_LiJake Li, Engineer, Hamamatsu Photonics

From fleets to commercial vehicles, there are a growing number of new and existing technologies that are important for the development of a fully autonomous vehicle. Aside from traditional sensors such as cameras, ultrasonic, and radar, LIDAR technologies are becoming the key enabler in the fusion of sensors needed to achieve higher levels of autonomous control (levels 4/5). Today, there are already multiple designs of LIDAR systems whose key components are photonic devices such as light sources, photodetectors, and MEMS mirrors. This presentation will provide an overview of the tradeoffs for LIDAR vs. competing sensor technologies (camera, radar, and ultrasonic) that re-enforce the need for sensor fusion, as well as summarize and compare various mechanical and solid state LIDAR designs. Guidelines for selecting photonic components such as photodetectors, light sources, and MEMS mirrors will also be discussed.

Autonomous Investment

9:40 Autonomous Vehicles – Infrastructure and Key Investment Trends

Fred_TanadaFred Tanada, Co-Investor, Chestnut Street Ventures

Some key questions to be addressed in this presentation will be what infrastructure investments have been made to improve AVs? What are key trends in making investments with AVs? What’s next?

10:10 Coffee Break with Exhibit and Poster Viewing

Autonomous Safety & Liability

10:35 Chairperson’s Opening Remarks

Sam Kherat, Ph.D., Adjunct Professor, Mechanical Engineering Department, Bradley University

10:40 Safe ADAS Evaluation at the Wisconsin AV Proving Grounds

Jonathan_RiehlJonathan Riehl, Ph.D., Transportation Systems Engineer, Traffic Operations and Safety Laboratory - Civil and Environmental Engineering, University of Wisconsin-Madison

The Wisconsin Automated Vehicle (AV) Proving Grounds was created to allow OEMs and integrators opportunities to test and improve upon their advanced driver-assistance systems (ADAS) at various stages of development. The MGA research facility in Burlington, WI offers closed-course, private testing for early state development. The Road America race track and access roads allow for public-facing marketing of ADAS. The UW-Madison and Epic campuses offer semi-open course testing in a controlled environment and the City of Madison roads and state highways offer final testing in an open environment. This presentation will outline the resources available through the Wisconsin AV Proving Grounds as well as offer a summary of the first year of rapidly-expanding activities of the proving grounds.

11:10 Can These Vehicles Be Trusted, What Might the Future Look Like with Them on Our Roads and What Are the Implications for the UK Regulatory Environment?

Lisa_CollingwoodLisa Collingwood, Ph.D., Senior Lecturer, Law, Kingston University, United Kingdom

Testing and Regulatory Procedures will need to be amended to accommodate AVs on public roads. This proposal will evaluate the regulatory changes muted to date and evaluate the likely impact they will have in the UK.

11:40 A Driver’s License Test for Driverless Vehicles: AV Software Verification and Safety Certification

Rahul_MangharamRahul Mangharam, Ph.D., Professor, Electrical and Systems Engineering, University of Pennsylvania

Autonomous vehicles (AVs) have driven millions of miles on public roads, but even the simplest scenarios, such as a lane change maneuver, have not been certified for safety. As there is no systematic method to bound and minimize the risk of decisions made by the vehicle’s decision controller, the insurance liability of autonomous vehicles currently is entirely on the manufacturer. I will describe APEX, a tool for autonomous vehicle plan verification and execution across a variety of driving scenarios. We will see the use of synthetic environments such as computer gaming to train and evaluate machine learning and decision control algorithms in future AVs.

12:10 pm Training to Become a Self-Driving Car Engineer

David_SilverDavid Silver, Self-Driving Car Team Lead, Udacity

Learn how Udacity trains engineers to work on autonomous vehicles! Topics include deep learning, computer vision, sensor fusion, localization, control, path planning, and system integration. You’ll cover the technical challenges and trends of self-driving cars and the autonomous vehicle industry. Review examples of the projects that Udacity students build to learn and showcase their autonomous vehicle skills.

12:40 Luncheon Presentation (Sponsorship Opportunity Available)

Autonomous Safety & Liability

2:05 Chairperson’s Opening Remarks

Fred Tanada, Co-Investor, Chestnut Street Ventures

2:10 Interior Cocoon as Prerequisite for a Safe, Autonomous Mobility

Moritz_vonGrotthussMoritz von Grotthuss, Chief Executive Officer, Gestigon GmbH, a Valeo company

Most discussions about autonomous mobility cover the navigation of the car. But how will the passengers be able to use the additional time in the car and how can today’s safety standards be transformed into the new epoch of mobility? Understanding passenger behavior, recognizing objects and creating an Interior Cocoon can be (part of) the solution.

2:40 A History of Automobile Sensor Algorithms

Tony_GioutsosTony Gioutsos, Director, TASS International

A history of Automobile Sensor Algorithms is presented with all the pitfalls and testing techniques to overview the ill-posed nature of the problem. Yesterday’s approaches can help today’s AI technology. Providing the necessary “due care” to reach acceptable safety levels is also described.

3:10 Refreshment Break with Exhibit and Poster Viewing

3:40 Sue My Car Not Me: A Discussion of Civil Liability for Autonomous Vehicle Accidents

Jeffrey_GurneyJeffrey Gurney, Attorney, Thomas, Fisher, Sinclair & Edwards, P.A.

This presentation will discuss the alternatives for imposing liability for harm and damage caused by autonomous vehicles. The presentation will analyze accidents from a civil liability and an ethical standpoint, and will argue that traditional drivers should not bear the responsibility to compensate persons injured or property damaged by autonomous vehicles. Instead, manufacturers of autonomous vehicles should bear primary liability for accidents caused by their autonomous technology. The presenter welcomes a general discussion on the topic and open participation by audience members.

4:10 PANEL DISCUSSION: Autonomous Vehicles – Maximizing Opportunities and Minimizing Risks

System interoperability is critical to the safe and efficient operation of autonomous drive vehicles in real world traffic situaitons. Integration of sensors, hardware and software are essential and have zero failure tolerance. This panel will discuss the latest advancements in systems and safety in developing autonomous vehicles that will be widely adopted by consumers.

Moderator: Sam Kherat, Ph.D., Adjunct Professor, Mechanical Engineering Department, Bradley University


Uwe Higgen, Managing Director, BMW iVentures

Youna Yang, Product Strategy & Design, Youna Yang Consulting, Carnegie Mellon University

5:10 Close of Conference

For more details on the conference, please contact:
Craig Wohlers
Executive Director, Conferences
Cambridge EnerTech
Phone: 781-247-6260

For partnering and sponsorship information, please contact:
Sherry Johnson
Manager, Business Development
Cambridge EnerTech
Phone: 781-972-1359


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