Photo Credit: Uber

The National Transportation and Safety Board (NTSB) held a board meeting yesterday to discuss its investigation of the March 18, 2018, fatal car accident in Tempe, Arizona, involving an automated test vehicle, a 2017 Volvo XC90, modified and operated by the Advanced Technologies Group of Uber Technologies, Inc. (Uber ATG).  A more detailed summary of the full report will be posted once it is released, however an abstract, summarizing the NTSB’s findings, probable cause and recommendations, was published on the NTSB’s website following the conclusion of the meeting.  All findings, probable cause and recommendations were adopted by the NTSB without amendment.

Summary of Accident

The SUV was completing the second loop on an established test route when it approached the collision site in the right lane at a speed of 45 mph.  About that time, a pedestrian began walking across the roadway where there was no crosswalk.  The ADS detected the pedestrian and continued to track the pedestrian until the crash, however it never accurately classified her as a pedestrian or predicted her path. By the time the ADS determined that a collision was imminent, the situation exceeded the response specifications of the ADS braking system.  Video from the SUV’s inward-facing camera shows that the operator of the test vehicle was glancing away from the road for an extended period while the vehicle was approaching the pedestrian.  The operator redirected her gaze to the road ahead about one second before impact.  The pedestrian died in the crash. The vehicle operator was not injured.

Findings

NTSB provided 19 findings as a result of the investigation.  Significantly, the NTSB found:

  • Uber ATG did not adequately manage the anticipated safety risk of its automated driving system’s functional limitations.
  • The safety risks associated with testing automated driving systems on public roads where increased by:
    • the aspect of the automated driving system’s design that precluded braking in emergency situations only when a crash was unavoidable;
    • the removal of the second vehicle operator; and
    • the deactivation of the Volvo forward collision warning and automatic emergency braking systems.
  • Had the vehicle operator been attentive, she would likely have had sufficient time to detect and react to the crossing pedestrian to avoid the crash or mitigate the impact.
  • Uber ATG did not adequately recognize the risk of automation complacency and develop effective countermeasures to control the risk of vehicle operator disengagement contributed to the crash.
  • Uber ATG’s inadequate safety culture created conditions that contributed to the circumstances of the crash and specifically to the vehicle operator’s extended distraction during the crash trip.
  • Mandatory submission of safety self-assessment reports—which are currently voluntary—and their evaluation by the National Highway Traffic Safety Administration (NHTSA) would provide a uniform, minimal level of assessment that could aid states with legislation pertaining to the testing of automated vehicles.
  • Arizona’s lack of a safety-focused application-approval process for ADS testing at the time of the crash, and its inaction in developing such a process since the crash, demonstrate the state’s shortcomings in improving the safety of ADS testing and safeguarding the public.
  • Considering the lack of federal safety standards and assessment protocols for automated driving systems, as well as the National Highway Traffic Safety Administration’s inadequate safety self-assessment process, states that have no, or only minimal, requirements related to automated vehicle testing can improve the safety of such testing by implementing a thorough application and review process before granting testing permits.

Probable Causes of Accident

NTSB determined that probable cause of the accident was the failure of the vehicle operator to monitor the driving environment and the operation of the automated driving system because she was visually distracted throughout the trip by her personal cell phone.  It was also found that Uber ATG’s inadequate safety culture, including s (1) inadequate safety risk assessment procedures, (2) ineffective oversight of vehicle operators, and (3) lack of adequate mechanisms for addressing operators’ automation complacency, was a contributing cause to the accident.  Finally, other contributing factors to the accident included the impaired pedestrian’s crossing of roadway outside a crosswalk, and Arizona’s Department of Transportation’s insufficient oversight of automated vehicle testing.

Recommendations

The NTSB made six recommendations: two to NHTSA, two to the State of Arizona, one to the American Association of Motor Vehicle Administrators and one to Uber ATG.

To NHTSA

  • Require safety self-assessment reports (which are currently voluntary) to be submitted to NHTSA by entities who are testing or who intend to test a developmental automated driving system on public roads.
  • Establish a process for the ongoing evaluation of the safety self-assessment reports and determine whether the plans include appropriate safeguards for testing a developmental automated driving system on public roads, including adequate monitoring of vehicle operator engagement, if applicable.

To State of Arizona

  • Require applications for testing ADS equipped vehicles that, at a minimum, details a plan to manage the risk associated with crashes and operator inattentiveness and establishes countermeasures to prevent crashes or mitigate crash severity within the ADS testing parameters.
  • Establish a task group of experts to evaluate applications for testing vehicles equipped with ADS before granting a testing permit.

To the American Association of Motor Vehicle Administrators

  • Inform states about the circumstances of the Tempe crash, encouraging states to (1) require an application for testing ADS equipped vehicles that, at a minimum, details a plan to manage the risks associated with crashes and operator inattentiveness and establishes countermeasures to prevent crashes or mitigate crash severity within the ADS testing parameters, and (2) establish a task group of experts to evaluate the application before granting a testing permit.

To Uber ATG

  • Complete the implementation of a Safety Management System for ADS testing that, at a minimum, includes safety policy, safety risk management, safety assurance, and safety promotion.

Copies of presentations discussed at the meeting can be found here.

NTSB Chair Robert L Sumwalt, will be testifying about this meeting at today’s hearing of the U.S. Senate’s Committee on Commerce, Science and Transportation will hold a hearing on highly automated vehicles, titled “Highly Automated Vehicles: Federal Perspectives on the Deployment of Safety Technology.”  The hearing will examine the U.S. Department of Transportation and the NTSB’s perspectives on the safe testing and deployment of highly automated vehicles, otherwise referred to as autonomous vehicles (AVs), self-driving vehicles, or driverless vehicles.

Continue following this blog for future posts regarding the final release of the NTSB report and the U.S. Senate Committee hearing.

The October 2019 Update of the Autonomous Vehicle Legislative Survey has been released. It’s been a busy several months for actions at the national and state level related to connected and automated vehicles. The updates, some of which are highlighted below, include updates at the national, state and city levels.

National

• The Federal Highway Administration (FHWA) presented awards for a Phase 1 Truck Platooning Early Deployment Assessment in March 2019. The project is being conducted to understand how truck platoons will operate in a realistic, operational environment. FHWA hopes that the project will provide insight into actual truck platooning operations that can be used to inform state and local stakeholders that are making decisions related to truck platooning regulations.

• In April 2019, USDOT announced the creation of a new council to help further the advancement of AVs, among other technologies. The Non-Traditional and Emerging Transportation Technology Council (NETT) was created to identify and resolve jurisdictional and regulatory gaps that may impede the deployment of new technology, such as tunneling, hyperloop, AVs and other innovations.

• On May 9, 2019, Congresswoman Suzan DelBene (D-WA), Senator Maria Cantwell (D-WA), and Congressman Ben Ray Luján (D-NM) reintroduced the Smart Cities and Communities Act to the U.S. Senate. The bill would authorize $200 million for smart city investments over five years.

• In May 2019, the National Highway Traffic Safety Administration (NHTSA) and Federal Motor Carrier Safety Administration (FMCSA) filed Advanced Notices of Proposed Rulemaking (ANPRM). NHTSA sought seeking comments on the proposed testing and verification rules for automated driving system-dedicated vehicles with Federal Motor Vehicle Safety Standards (FMVSS). (See 84 FR 24433) FMCSA filed an ANPRM regarding amendments to its rules to account for significant differences between human operators and ADS.

• On August 9, 2019, the U.S. Chambers of Congress’ Technology Engagement Center released its Automated Vehicle Policy Principles. The Principles are meant to prioritize safety while ensuring that the United States remains a global leader in AV innovation. Representing a whole-of-industry perspective, the Principles provide policymakers with an innovation-focused national framework to safely develop, test, and deploy AVs.

• In September 2019, USDOT announced $60 million in Federal grant funding to seven recipients for the Automated Driving Systems (ADS) Demonstration Grant. Recipients include: Texas A&M Engineering Experiment Station; University of Iowa; Virginia Tech Transportation Institute (two grants); Ohio Department of Transportation; Pennsylvania Department of Transportation; City of Detroit; and Contra Costa Transportation Authority (CCTA).

States

Alabama legislature passed SJR 21 and re-established the AV Committee “to study all aspects of self-driving vehicles, including specifically, the issues of public safety and state and local economic impact regarding such vehicles.” The Legislature also passed SB 47 which authorizes certain autonomous commercial vehicles to be operated by an automated driving systems (ADS).

Arkansas Legislature enacted Act 468 authorizing the operation of AVs under an AV pilot program. Also enacted, Act 1052 governs the operation of AVs at railroad crossings.

• On April 12, 2019, the California DMV published proposed AV regulations that allow the testing and deployment of autonomous motor trucks (delivery vehicles) weighing less than 10,001 pounds on California’s public roads.

Colorado’s Governor signed SB 19-239 which requires Colorado’s Department of Transportation to convene and engage in robust consultation with a stakeholder group comprised of representatives of specified industries, workers, governmental entities, planning organizations, and interest groups that will potentially be affected by the adoption of new and emerging transportation technologies and business models, including AVs.

• In June, with passage of HB No. 311, Florida became one of the few states to allow a fully AV to operate without a person present in the vehicle. The Bill provides that the automated driving system, rather than a person, is deemed the operator of an AV when operating with the ADS engaged.

House Concurrent Resolution 220 (along with companion resolution House Resolution No. 195) was adopted in 2019, requesting that the Attorney General convene an AV Legal Preparation Task Force (Task Force) to prepare Hawaii with laws and regulations required for AVs.

Senate File 302 was signed into law by Iowa’s Governor, Adam Gregg. It outlines the parameters for operation of AVs in Iowa.

• On June 11, 2019, the Governor of Louisiana, John Bel Edwards, signed HB 455 (Act 232) authorizing autonomous commercial vehicles, which are those used for the purposes of compensation, employment or trade, to operate in the state without a conventional driver physically present in the vehicle, if the vehicle meets all of the requisite criteria relating to safety and insurance.

Massachusetts’ AV Working Group released its Report in February 2019, recommending: establishment of a CAV Committee; engagement of first responders and law enforcement in CAV development; movement from an Executive Order to regulations; and establishment of CAV legislation.

Michigan Council on Future Mobility’s 2019 Report was published on March 15, 2019. The Report provided a list of issues the Council would review throughout 2019 in order to provide future recommendations to the legislature.

LEGISLATION UPDATE: Minnesota’s House File No 242, has been referred to and remains in the House Transportation Finance and Policy Committees.

• On April 1, 2019, Minnesota’s Governor Tim Walz signed Executive Order 19-18, rescinding Governor Dayton’s AV Executive Order 18-04, and establishing a Governor’s Council on Connected and Automated Vehicles. The Council is directed to study, assess and prepare for the opportunities and challenges associated with widespread adoption of AVs. House File No. 6 was also passed to allow for platooning of commercial vehicles.

• LEGISLATION UPDATE: Senate Bill No. 186, was referred to and remains with Missouri’s Transportation, Infrastructure and Public Safety Committee.

• LEGISLATION UPDATE: Legislative Bill No. 521 was referred to and remains with Nebraska’s Transportation/Telecommunications Committee.

• In August 2019, Act No. 2019-310 was enacted to establish an AV testing pilot program. The Act provides that a testing entity seeking to test ADS-equipped vehicles must provide notice to the New Hampshire DMV, upon forms furnished by the department.

• LEGISLATION UPDATE: Assembly Joint Resolution 164 was signed by New Jersey Governor Phil Murphy to establish the New Jersey Advanced Autonomous Vehicle Task Force, the purpose of which would be to conduct a study of AVs and make recommendations on laws that New Jersey may enact to safely integrate AVs on the State’s roads.

• LEGISLATION UPDATE: Senate Bill No. 332 which was introduced to authorize the use of AVs and platooning in New Mexico, was recommended by the Corporation and Transportation Committee; however the Bill is listed as being “postponed indefinitely.”

• LEGISLATION UPDATE: All bills introduced to the New York’s legislature in January 2019 regarding AVs, have been referred to and remain with Committees.

• LEGISLATION UPDATE: North Dakota’s House Bill No. 1418 was enacted to allow AVs to operate in the state without a human driver present. House Bill No. 1197, regarding ownership of data, failed to pass.

HB No. 1199 was enacted in North Dakota to create an exception to the follow-too-closely law for platooning vehicles.

• LEGISLATION UPDATE: Oklahoma’s lawmakers passed legislation regarding AVs with SB 365. The Bill created the Oklahoma Driving Automation System Uniformity Act, which preempts local laws and asserts that only the State may enact laws or regulations regarding the use of motor vehicles equipped with driving automation systems in Oklahoma.

SB 189 was also enacted in Oklahoma exempting platoons, defined as a group of individual motor vehicles traveling in a unified manner at electronically coordinated speeds, from spacing requirements on state highways.

HB 1068 was signed by South Dakota’s Governor in March 2019 regarding platooning within the state. The Bill provides that the Transportation Commission shall promulgate rules to authorize the testing and operation of groups of individual motor vehicles traveling in a unified manner at electronically coordinated speeds and distance intervals that are closer than otherwise allowed under State law.

• LEGISLATION UPDATE: Neither House Bill 119, regarding liability of manufacturers in the event of a crash involving an automated vehicle, nor House Bill 113, regarding requiring providers to equip AVs with a failure alert system and the latest software, were enacted by the Texas legislature.

HB 101 was enacted amending provisions regarding traffic laws, licensing, and titling requirements to add provision regarding the operation of AVs in Utah. The Bill, among other things, allows the operation of AVs within the State.

Vermont’s legislature passed SB No. 149 adding a new chapter to codified law providing the Traffic Committee with the responsibility of approving testing of AVs on public highways, directs the Agency of Transportation to identify the municipalities that want to preapprove AV testing and for the Agency to prepare an AV Testing Guide by January 1, 2021.

Cities

• In March 2019, Pittsburgh’s Mayor Peduto issued an Executive Order (Pittsburgh Principles) outlining the objectives and expectations from the city for testing AVs.

Regular updates to the Survey will be released quarterly. Subscribe to this the blog to stay update to date on developments on the AV landscape in the United States and for notification when the next update is released.

Please join me next week at the Pennsylvania Automated Vehicle Summit.  This is the premier AV event in Pennsylvania and is the largest dedicated Automated Vehicle conference in the Northeast region, bringing together both public and private industries. The conference’s subject matter experts and diverse group of attendees come together to discuss and engage with the broad range of issues related to these emerging technologies.

I will be part of an esteemed panel featuring:

Our panel is scheduled for Thursday, September 5, 2019 at 2:30 p.m. discussing Autonomous Vehicle from the state and federal perspectives.

For more information and to learn how to register, check out the Summit Website.

In what can be seen as a huge step forward in the arena of autonomous vehicle technology, Lyft has announced that it will share with the public its level 5 dataset from its autonomous vehicle data. The dataset is described as a “comprehensive, large-scale dataset featuring the raw sensor camera and LiDAR inputs as perceived by a fleet of multiple, high-end, autonomous vehicles in a bounded geographic area.”  The Lyft Level 5 Dataset includes:

  • Over 55,000 human-labeled 3D annotated frames;
  • Data from seven cameras and up to three LiDARs;
  • A drivable surface map; and
  • An underlying HD spatial semantic map (including lanes, crosswalks, etc.)

In addition, Lyft is also launching a competition for individuals to train on the algorithms on the dataset, including completing testing on 3D object detection over the semantic maps. Although specific details about the competition have yet to be released,  Lyft has indicated there will be $25,000 in prizes, and they will fly the top researchers to the NeurIPS Conference in December, as well as allow the winners to interview with Lyft for a position within the company.

So, what does all this really mean for the advancement of autonomous vehicles? One of the biggest issues in the autonomous vehicle arena right now is cooperation among the manufacturers and developers. This is not to say that these entities are not creating consortium groups or teaming up on manufacturing ventures, but this cooperation remains very segmented. The sharing of data within the entire industry is not common place, so it is very exciting to see such an extensive dataset being shared so openly by Lyft. Sharing knowledge of this kind is crucial if autonomous vehicles are to become a reality on the roadways, as these vehicles are going to need to work in cooperation with not only each other but the infrastructure of the areas in which these vehicles operate.

It also seems, on the surface, that this dataset is being shared not only among manufacturers and technology developers, but with the entire public. While this is technically true, as anyone can download the dataset, unless you are capable of reading the data, there is no way for the average person to understand what it is that has been collected or what it really all means with respect to autonomous vehicles. I downloaded the available dataset (there is additional information being released within the coming weeks) and while it is very impressive, it doesn’t enhance my knowledge of this technology in anyway.

It’s obvious that Lyft is partially using the release of this data, in conjunction with a competition, as a way in which the company can find new talent to add to its autonomous vehicle team, and maybe even acquire some free research out of it by the submissions received in the competition. Though not a criticism of Lyft, this is an observation that this data release is really not to the public at large, but to a select group of individuals who have the capability of reading and interpreting the data.

As the public’s understanding of and trust in this technology is also a crucial factor in the acceptance of autonomous vehicles on our roadways, there needs to a way to help relay this type of information to the general public so they can continue to learn, along with the manufacturers and developers, about how the technology works, its safety and improvements being made as issues arise. While this dataset may not be capable of such relatability and dissemination, this is a reminder to all involved that no amount of technology with be worth much, without the public’s trust in and use of autonomous vehicles.

Subscribe to the AI blog to receive updates on this dataset and Lyft’s competition. Also follow our AI Blog Calendar, where you can find extensive information regarding just about every AI event coming up, worldwide, including the NeurIPS Conference discussed above.

In what appears to be a first, the city of Yuma, Arizona, has announced that it will host a free seminar on TV and over the internet regarding autonomous vehicles, Autonomous Vehicles 101: Education for Yuma and Surrounding Communities. The seminar is being sponsored by the city, Yuma County, Greater Yuma Economic Development Corporation, and the Yuma Metropolitan Planning Organization. National, state, and local experts will discuss key aspects of the autonomous vehicles economy, as well as policy and infrastructure preparations that communities can make today to prepare for the arrival of self-driving technologies.

Topics for discussion will include:

  • The Changing Nature of Transportation — Shared, Electric, Connected and Autonomous
  • The AV Situation in Arizona: The View From ADOT and the Governor’s Office
  • The Implications of the AV Economy for Yuma City and Towns in Yuma County
  • How the Siemens-anyCOMM project (the City of Yuma has dual agreements with Siemens and anyCOMM to provide infrastructure for autonomous vehicle to this region) can underpin an Autonomous Vehicle-Supportive Infrastructure

With autonomous vehicles reality on the rise, this type of educational event is not only beneficial, but absolutely mandatory for autonomous vehicles to become part of the “real world.” One of the main barriers for autonomous vehicles, beyond things such as the lack of federal regulation, is the lack of trust and acceptance of these vehicles by the public. Currently there are countless misconceptions about autonomous technology by the public, which has led to distrust and lack of willingness to use or even try the technology. By providing educational events for the public relating accurate information will go a long way to breakdown the barrier of public mistrust of autonomous vehicles, helping to smooth the path to autonomous vehicles on our roadways.

More information on this seminar and other valuable autonomous vehicle events can be found on the AI Blog Calendar. Subscribe to the calendar for updates as more events are added.

As reported yesterday, National Institute of Standards and Technology’s Request for Comments was published today and comments will be accepted until 5 p.m. Eastern time on May 31, 2019, and may be submitted via email to ai_standards@nist.gov, or by mail to the National Institute of Standards and Technology, 100 Bureau Drive, Stop 2000, Gaithersburg, MD 20899. Comments will be made publicly available without redaction.

In addition, NIST announced a workshop, Federal Engagement in Artificial Intelligence Standards Workshop, to promote discussions in support of a federal plan for engagement in AI technical standards development, on May 30, 2019, at its Gaithersburg, Maryland, campus and via webcast.  Further information can be found on our Calendar.

Tomorrow, May 1, 2019, the National Institute of Standards and Technology (NIST) will officially publish in the Federal Register a Request for Information (Docket Number: 190312229-9229-01) seeking comments on development of Artificial Intelligence (AI) Standards.  Pursuant to the Executive Order on Maintaining American Leadership in Artificial Intelligence (signed on February 11, 2019), NIST was directed to create a plan for “federal engagement in the development of technical standards and related tools in support of reliable, robust, and trustworthy systems that use AI technologies.” In order to fulfill this directive, NIST seeks to consult with will consult with federal agencies, the private sector, academia, non-governmental entities, and other stakeholders with interest in and expertise relating to AI.

Specifically, NIST seeks to understand the:

  1. Current status and plans regarding the availability, use, and development of AI technical standards and tools in support of reliable, robust, and trustworthy systems that use AI technologies;
  2. Needs and challenges regarding the existence, availability, use, and development of AI standards and tools; and
  3. The current and potential future role of federal agencies regarding the existence, availability, use, and development of AI technical standards and tools in order to meet the nation’s needs.

NIST also lists three specific categories with subtopics in the notice covering the major areas on which the department is seeking information; however, these categories are not intended to limit the topics addressed by those who submit comments to the notice.

AI Technical Standards and Related Tools Development: Status and Plans

  1. AI technical standards and tools that have been developed, and the developing organization, including the aspects of AI these standards and tools address, and whether they address sector-specific needs or are cross-sector in nature;
  2. Reliable sources of information about the availability and use of AI technical standards and tools;
  3. The needs for AI technical standards and related tools. How those needs should be determined, and challenges in identifying and developing those standards and tools;
  4. AI technical standards and related tools that are being developed, and the developing organization, including the aspects of AI these standards and tools address, and whether they address sector-specific needs or are cross sector in nature;
  5. Any supporting roadmaps or similar documents about plans for developing AI technical standards and tools;
  6. Whether the need for AI technical standards and related tools is being met in a timely way by organizations;
  7. Whether sector-specific AI technical standards needs are being addressed by sector-specific organizations, or whether those who need AI standards will rely on cross-sector standards which are intended to be useful across multiple sectors; Technical standards and guidance that are needed to establish and advance trustworthy aspects (e.g., accuracy, transparency, security, privacy, and robustness) of AI technologies.

Defining and Achieving U.S. AI Technical Standards Leadership

  1. The urgency of the U.S. need for AI technical standards and related tools, and what U.S. effectiveness and leadership in AI technical standards development should look like;
  2. Where the U.S. currently is effective and/or leads in AI technical standards development, and where it is lagging;
  3. Specific opportunities for, and challenges to, U.S. effectiveness and leadership in standardization related to AI technologies; and
  4. How the U.S. can achieve and maintain effectiveness and leadership in AI technical standards development.

Prioritizing Federal Government Engagement in AI Standardization

  1. The unique needs of the federal government and individual agencies for AI technical standards and related tools, and whether they are important for broader portions of the U.S. economy and society, or strictly for federal applications;
  2. The type and degree of federal agencies’ current and needed involvement in AI technical standards to address the needs of the federal government;
  3. How the federal government should prioritize its engagement in the development of AI technical standards and tools that have broad, cross-sectoral application versus sector- or application-specific standards and tools;
  4. The adequacy of the federal government’s current approach for government engagement in standards development, which emphasizes private sector leadership, and, more specifically, the appropriate role and activities for the federal government to ensure the desired and timely development of AI standards for federal and non-governmental uses;
  5. Examples of federal involvement in the standards arena (e.g., via its role in communications, participation, and use) that could serve as models for the Plan, and why they are appropriate approaches; and
  6. What actions, if any, the federal government should take to help ensure that desired AI technical standards are useful and incorporated into practice.

The deadlines for the submission of comments will be released tomorrow, with the official publication of the notice.

The blog is now maintaining a Google Calendar featuring upcoming notable artificial intelligence events. (If you would like to submit an event for inclusion, please contact Jodi Oley at joley@eckertseamans.com.)

The calendar will be updated on an ongoing basis, so check back or sync with your own calendar to stay in the loop. Here’s a quick preview of notable events happening in the next week:

PLM ReInvented MeetUp: Connected and Automated Vehicles – End-to-End Design, Traceability and Security

Tuesday, April 30, 6:00 to 8:30 p.m.

Microsoft Technology Center, 1 Campus Martius, Detroit, MI 48226, USA

Join us to discuss managing key functions of the product lifecycle for connected and automated vehicles (CAV). This event will focus on current strategies and solutions for CAV’s with an emphasis on solutioning trusted-platforms, connected services, and traceability of data generated necessary to build these vehicles. Hear Richard Doak, Chief Strategist for Automotive MFG at Microsoft, and Bill Bone, CTO for Automotive at Aras, present their views on business/technical challenges and solution opportunities for these vehicles in a casual environment.

Building Trust in Autonomy – Driving at the Limits of Handling and Interacting with Pedestrians

Wednesday, May 1, 12:30 to 2:30 p.m.

Francois-Xavier Bagnoud Building, 1012 FXB, University of Michigan

The first half of this talk focuses on one aspect of this challenge, developing a mathematical model for a pedestrian’s behavior and studying its interaction with an automated vehicle at a mid-block, unsignalized intersection. By modeling pedestrian behavior through the concept of gap acceptance, we show that a hybrid controller with just four distinct modes allows an autonomous vehicle to successfully interact with a pedestrian across a continuous spectrum of possible crosswalk entry behaviors. The controller is validated through extensive simulation and compared to an alternate POMDP solution, with experimental results provided on a Hyundai research vehicle for a virtual pedestrian. The second half of this talk will focus on another contribution related to automated driving – a feedback-feedforward steering algorithm that enables an autonomous vehicle to accurately follow a specified trajectory at the friction limits while preserving robust stability margins. Experimental data collected from an Audi TTS driving at the handling limits (0.95 g) on a full length race circuit will demonstrate the performance of the controller design.

Sligo Engineering & Technology Expo 2019

Thursday, May 2, 10:00 a.m. to 6:00 p.m.

Knocknarea Arena, Ash Ln, Ballytivnan, Sligo, F91 YW50, Ireland

This year’s Expo will concentrate on the exciting new developments facing industries in the coming decade. Labelled as Industry 4.0, businesses across the globe are having to adapt to new technology quicker than ever if they wish to thrive and even survive. Robotics, Artificial Intelligence, Internet of Things and Automation are all key buzzwords doing the rounds at the moment, but what do they mean and how will they affect industry and society in the near future?

AAA Autonomous Vehicles Summit 2019

Friday, May 3,⋅9:30 a.m. to 1:30 p.m.

Mohawk Valley Community College, Utica, NY 13501, USA

AAA New York State will host an Autonomous Vehicle Summit that will offer perspective on the future of self driving vehicles. Entitled “Navigating Our Transportation Future: Preparing New York for Autonomous Vehicles” the summit will bring together municipal planners, transportation professionals, business leaders, and lawmakers to discuss how autonomous vehicles will transform the state’s economy and transportation infrastructure and how New York’s policymakers should facilitate this new technology.

Machine Learning, AI, and Digital Health Panel at FDLI Annual Meeting

Friday, May 3, 10:40 to 11:30 a.m.

Ronald Reagan Building and International Trade Center, 1300 Pennsylvania Ave NW, Washington, D.C., 20004, USA

Mark Levy, one of the co-editors of the AI blog, will be on a panel discussing “Machine Learning, AI, and Digital Health” as part of the Food and Drug Law Institute’s Annual Conference in Washington, D.C., on May 2-3.

The panel will focus on digital health technologies, which are rapidly integrating into healthcare and life sciences – from wearables in clinical trials to digital tools for disease management and clinical decision support. Many of these technologies are and will deploy machine learning and artificial intelligence. This panel will discuss how these new technologies are being integrated and how FDA’s role in regulation will continue to evolve. FDA’s recent discussion paper on AI devices, as well as the challenges of AI regulation generally, such as liability, quality assurance, and approval pathways for a product that continually evolves will also be discussed.

Mark Levy, one of the co-editors of this blog, will be on a panel discussing “Machine Learning, AI, and Digital Health” as part of the Food and Drug Law Institute’s Annual Conference in Washington, D.C., on May 2-3.

The panel will focus on digital health technologies, which are rapidly integrating into healthcare and life sciences – from wearables in clinical trials to digital tools for disease management and clinical decision support. Many of these technologies are and will deploy machine learning and artificial intelligence. This panel will discuss how these new technologies are being integrated and how FDA’s role in regulation will continue to evolve. FDA’s recent discussion paper on AI devices, as well as the challenges of AI regulation generally, such as liability, quality assurance, and approval pathways for a product that continually evolves will also be discussed.

Sign up with the discount code annual15 for a 15% discount on registration, and learn more at fdli.org/annual.


The FDA recently issued the discussion paper “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD)” and a request for comments.

Commissioner Scott Gottlieb issued a statement at the time of the paper’s release lauding artificial intelligence and machine learning as having “the potential to fundamentally transform the delivery of health care.” He stated that the “ability of artificial intelligence and machine learning software to learn from real-world feedback and improve its performance is spurring innovation and leading to the development of novel medical devices.” However, he recognized the inadequacy of traditional regulatory pathways to foster the growth of this technology, saying the FDA was “announcing steps to consider a new regulatory framework specifically tailored to promote the development of safe and effective medical devices that use advanced artificial intelligence algorithms.”

FDA employs a risk-based approach to determine whether a new premarket submission is required each time a manufacturer makes substantial, iterative changes through a software update or makes other changes that would significantly affect the device’s performance. But, this approach is not a match for review of AI and machine learning-based algorithms, medical devices that may continuously update themselves in response to real-world feedback.

Gottlieb noted as an example, “an algorithm that detects breast cancer lesions on mammograms could learn to improve the confidence with which it identifies lesions as cancerous or may learn to identify specific sub-types of breast cancer by continually learning from real-world use and feedback.” The agency concluded that it had to change its approach to foster software that evolves over time to improve care, while still guaranteeing safety and effectiveness. As a first step, the FDA released the paper exploring a new proposed framework that it believes will encourage development and may allow some modifications without review—“[I]t would be a more tailored fit than our existing regulatory paradigm for software as a medical device.”

Under the proposed framework, AI/ML-based SaMD would require a premarket submission when a software change or modification “significantly affects device performance or safety and effectiveness; the modification is to the device’s intended use; or the modification introduces a major change to the SaMD algorithm.” This approach was developed based on harmonized SaMD risk categorization principles that were established via the International Medical Devices Regulators Forum, FDA’s benefit-risk framework, risk management principles in FDA’s 2017 guidance on submitting new 510(k)s for software changes to existing devices, Software Pre-certification Pilot Program’s organizational-based total product life cycle approach, as well as the 510(k), De Novo classification request, and premarket application pathways.

So, where it is anticipated that the software will evolve over time and not remain static, the “evolution” will be described at the time of submission along with specific plans for post-market surveillance and modification of intended use where appropriate.

FDA will accept comments through June 3, 2019, via its website. This will be an important part of evolving the proposal into something that better fits the needs of this growing technology