ATSSA New England Chapter Meeting Autonomous and Connected Vehicles ATSSA New England Chapter Meeting November 2, 2016 Cathie Curtis, Director Vehicle Programs, AAMVA

We’ll discuss: AAMVA Classification of Automated Vehicles (AV) Connected Vehicles AV Working Group NHTSA AV Policy

AAMVA Mission and Vision American Association of Motor Vehicle Administrators (AAMVA) was founded in 1933 All 69 of the states, provinces and territories of the U.S. and Canada are AAMVA members Charge: uniformity and reciprocity among the jurisdictions

AAMVA Community Every State & Provincial Driver and Vehicle Licensing Agency; Every Provincial & State Police or State Highway Patrol Agency

Automated Vehicle Classification Terms As adopted by SAE, International: Level 0 – No Automation Level 1 – Driver Assistance Level 2 – Partial Automation Level 3 – Conditional Automation Level 4 – High Automation Level 5 – Full Automation

Automated Vehicle Classification Terms In vehicles available today: The human driver does everything An automated system on the vehicle can sometimes assist the human driver conduct some parts of the driving task. An automated system on the vehicle can actually conduct some parts of the driving task, while the human continues to monitor the driving environment and performs the rest of the driving tasks. In vehicles on the road today. Level 0 example - no technology Level 1 example – cruise control Level 2 example – adaptive cruise control, lane departure warning, lane keep and automatic braking all working to conduct parts of the driving but the human monitors the road.

Adaptive Cruise Control Lane Departure Warning Lane Keeping Assistance Forward Collision Warning Collision Avoidance Braking Parking Assistance Systems

Forward Collision Warning Collision Avoidance Braking Parking Assistance Systems

Automated Vehicle Classification Terms In testing and development today also called HAVs An automated system can both actually conduct some parts of the driving task and monitor the driving environment in some instances, but the human driver must be ready to take back control when the automated system requests. An automated system can conduct the driving task and monitor the driving environment, and the human need not take back control, but the automated system can operate only in certain environments and under certain conditions. The automated system can perform all driving tasks, under all conditions that a human driver could perform them. In testing and development today Level 3 describe the Audi we rode in, on highway could drive itself, could pass by it self but driver had to perform exiting the highway. If driver doesn’t take over, the car cannot make a decision to do something else such as pull over. Level 4 can be partially or fully autonomous but has limitations such as low speed or can not function in bad weather. If the driver needs to take over but doesn’t, the vehicle can make a decision to get to a safe place and stop. Level 5 early stages of development, fully autonomous and does not have any, no restrictions, can go in rain, snow etc.

LIDAR Laser Illuminating Detection and Ranging – or LIDAR – is used to build a 3D map and allow the car to “see” potential hazards by bouncing a laser beam off of surfaces surrounding the car in order to accurately determine the distance and the profile of that object. The Google Car uses a Velodyne 64-beam laser in order to give the on-board processor a 360-degree view by mounting the LIDAR unit to the top of the car (for unobstructed viewing) and allowing it to rotate on a custom-built base.

Radar LIDAR accurately mapping surroundings, it can not accurately monitor speed of surrounding vehicles in real time. Bumper-mounted radar units allow the car to avoid impact by sending a signal to the on-board processor to apply the brakes, or move out of the way when applicable. This technology works in conjunction with other features on the car such as inertial measurement units, gyroscopes, and a wheel encoder in order to send accurate signals to the processing unit (the brain) of the vehicle in order to better make decisions on how to avoid potential accidents.

High-Powered Cameras The actual camera technology and setup on cars varies, but one prototype uses cameras mounted to the exterior with slight separation in order to give an overlapping view of the car’s surroundings. This technology is not unlike the human eye which provides overlapping images to the brain before determining things like depth of field, peripheral movement, and dimensionality of objects.

Sonar Vehicles are slightly different, but some of those tested have featured advanced sonar technology. The limitations of sonar are its narrow field of view and its relatively short effective range (about 6 meters). However, the inclusion provides yet another redundant system that allows the car to effectively cross-reference data from other systems in real time to apply the brakes, pre-tension seat belts for impact, or swerve to avoid obstacles.

Positioning Their own mapping systems and/or GPS satellites Positioning Their own mapping systems and/or GPS satellites. The system works alongside the on- board cameras to process real-world information as well as GPS data, and driving speed to accurately determine the precise position of each vehicle.

Sophisticated Software The software processes all of the data in real- time as well as modeling behavioral dynamics of other drivers, pedestrians, and objects around the vehicle. While some data is hard-coded into the car, such as stopping at red lights, other responses are learned based on previous driving experiences. Every mile driven on each car is logged, and this data is processed in an attempt to find solutions to every applicable situation. While some data is hard-coded into the car, such as stopping at red lights, other responses are learned based on previous driving experiences. Every mile driven on each car is logged, and this data is processed in an attempt to find solutions to every applicable situation. The learning algorithm processes the data of not just the car you’re riding in, but that of others in order to find an appropriate response to each possible problem. Behavioral dynamics are also mapped and this data is used to help recognize situations before they happen, much like a human driver. For example, the cars are smart enough to recognize – and adapt to – situations such as: A slow-moving vehicle in the right line suggests a higher probability that the car following it will attempt to pass. A pot hole or foreign item in the street shows a higher probability of a driver swerving to avoid it. Congestion in the left lane means that drivers are more likely to attempt to enter the right lane.

Connected Vehicles Advanced, wireless communication is supported by dedicated short-range communications (DSRC) as well as through the 4G LTE (Long Term Evolution) cellular telecommunication technology Vehicles could serve as data collectors and anonymously transmit traffic and road condition information from every major road within the transportation network.

Connected Vehicles

Connected Vehicles

Connected Vehicles Connected Vehicles: Vehicle to Vehicle (V2V)

Connected Vehicles V2V

Connected Vehicles Platooning

Automated Vehicles Among AAMVA’s top priorities is helping our members prepare for new technologies such as automated vehicles. Potential safety advancements. That we all need to support safer roadways but need to do so in a thoughtful manner. Find a balanced approach to regulation. Support innovation but balance it with a safe and proven deployment. Industry wants a consistent national approach to regulations. Insert death stats here

AAMVA - Automated Vehicle Initiatives AAMVA Autonomous Vehicle Information Sharing Group and Library; and AAMVA Autonomous Vehicle Working Group - To help our members prepare for the impact of vehicle automation. Discuss Information Sharing Group on this slide Started 2014 Share information, hear from experts Jurisdictions, industry and research groups Developed library Meets via conference call on a regular basis Met with many vehicle manufactures and tier 1 supplies over in August and sept

Autonomous Vehicle Working Group The AVWG has three sub-groups focusing on issues impacting: Driver Licensing & Testing; Vehicle Titling & Registration; and Law Enforcement

Autonomous Vehicle Working Group The AAMVA Autonomous Vehicle Working Group (NHTSA funded working group): Provided input for NHTSAs Model State Policy – NHTSA Published September 20, 2016 The working group will complete guidelines for the regulation of Highly Automated Vehicles a final piece of its work for NHTSA in support of  the Model State Policy Established 2014 NHTSA funded 16 us jurisdictions and 2 Canadian NHTSA involved 2 deliverables To assist jurisdictions with the regulation of Avs.

Federal Automated Vehicles Policy Four sections Section 1 Vehicle Performance for manufactures Section 2 Model State policy Section 3 and 4 NHTSA’s authority Section 2 Administration Testing Vehicles on Public Roadways Jurisdictional Permission to Test (Permitting Process) Testing by Manufacturers Deployed Vehicles, Driver Training & Examination Considerations Deployed Vehicles, Registration and Title Considerations Deployed Vehicles, Law Enforcement Considerations Considered New Tools • Variable Test Procedures: Expand vehicle testing methods to create test environments more representative of real-world environments. • Functional and System Safety: Make mandatory the 15-point Safety Assessment envisioned in the Vehicle Performance Guidance for Automated Vehicles. • Regular Reviews: Regular reviews of standards and testing protocols to keep current with the development of technology. • Additional Recordkeeping and Reporting: Require additional reporting about HAV testing and deployment. • Enhanced Data Collection: Enhance data recorders and greater reporting requirements about the performance of HAVs. Network of Experts: Establish a network of experts to broaden the NHTSA’s existing expertise and knowledge. • Special Hiring Tools: Special hiring tools—including direct hiring authority, term appointments, and greater compensation flexibility—to hire qualified applicants with specialized skills.

Contacts For More Information, Contact: Cathie Curtis, Director of Vehicle Programs ccurtis@aamva.org