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NVIDIA : AI Summit Panel Outlines Autonomous Driving Safety
The autonomous driving industry is shaped by rapid technological advancements and the need for standardization of guidelines to ensure the safety of both autonomous vehicles (AVs) and their interaction with human-driven vehicles. At the NVIDIA AI Summit this week in Washington, D.C., industry experts shared viewpoints on this AV safety landscape from regulatory and technology perspectives. Danny Shapiro, vice president of automotive at NVIDIA, led the wide-ranging conversation with Mark Rosekind, former administrator of the National Highway Traffic Safety Administration, and Marco Pavone, director of AV research at NVIDIA. To frame the discussion, Shapiro kicked off with a sobering comment about the high number of crashes, injuries and fatalities on the world's roadways. Human error remains a serious problem and the primary cause of these incidents. "Improving safety on our roads is critical," Shapiro said, noting that NVIDIA has been working for over two decades with the auto industry, including advanced driver assistance systems and fully autonomous driving technology development. NVIDIA's approach to AV development is centered on the integration of three computers: one for training the AI, one for simulation to test and validate the AI, and one in the vehicle to process sensor data in real time to make safe driving decisions. Together, these systems enable continuous development cycles, always improving the AV software in performance and safety. Rosekind, a highly regarded automotive safety expert, spoke about the patchwork of regulations that exists across the U.S., explaining that federal agencies focus on the vehicle, while the states focus on the operator, including driver education, insurance and licensing. Pavone commented on the emergence of new tools that allow researchers and developers to rethink how AV development is carried out, as a result of the explosion of new technologies related to generative AI and neural rendering, among others. These technologies are enabling new developments in simulation, for example to generate complex scenarios aimed at stress testing vehicles for safety purposes. And they're harnessing foundation models, such as vision language models, to allow developers to build more robust autonomy software, Pavone said. [Link] One of the relevant and timely topics discussed during the panel was an announcement made during the AI Summit by MITRE, a government-sponsored nonprofit research organization. MITRE announced its partnership with Mcity at the University of Michigan to develop a virtual and physical AV validation platform for industry deployment. MITRE will use Mcity's simulation tools and a digital twin of its Mcity Test Facility, a real-world AV test environment in its digital proving ground. The jointly developed platform will deliver physically based sensor simulation enabled by NVIDIA Omniverse Cloud Sensor RTX applications programming interfaces. By combining these simulation capabilities with the MITRE digital proving ground reporting and analysis framework, developers will be able to perform exhaustive testing in a simulated world to safely validate AVs before real-world deployment. [Link] Rosekind commented: The MITRE announcement "represents an opportunity to have a trusted source who's done this in many other areas, especially in aviation, to create an independent, neutral setting to test safety assurance." "One of the most exciting things about this endeavor is that simulation is going to have a key role," added Pavone. "Simulation allows you to test very dangerous conditions in a repeatable and varied way, so you can simulate different cases at scale." "That's the beauty of simulation," said Shapiro. "It's repeatable, it's controllable. We can control the weather in the simulation. We can change the time of day, and then we can control all the scenarios and inject hazards. Once the simulation is created, we can run it over and over, and as the software develops, we can ensure we are solving the problem, and can fine-tune as necessary." The panel wrapped up with a reminder that the key goal of autonomous driving is one that businesses and regulators alike share: to reduce death and injuries on our roadways. Watch areplay of the session. (Registration required.)
[2]
NVIDIA AI Summit Panel Outlines Autonomous Driving Safety
Industry experts gather in D.C. to discuss advances in AI that underscore the need for automotive safety guidelines and regulation. The autonomous driving industry is shaped by rapid technological advancements and the need for standardization of guidelines to ensure the safety of both autonomous vehicles (AVs) and their interaction with human-driven vehicles. At the NVIDIA AI Summit this week in Washington, D.C., industry experts shared viewpoints on this AV safety landscape from regulatory and technology perspectives. Danny Shapiro, vice president of automotive at NVIDIA, led the wide-ranging conversation with Mark Rosekind, former administrator of the National Highway Traffic Safety Administration, and Marco Pavone, director of AV research at NVIDIA. To frame the discussion, Shapiro kicked off with a sobering comment about the high number of crashes, injuries and fatalities on the world's roadways. Human error remains a serious problem and the primary cause of these incidents. "Improving safety on our roads is critical," Shapiro said, noting that NVIDIA has been working for over two decades with the auto industry, including advanced driver assistance systems and fully autonomous driving technology development. NVIDIA's approach to AV development is centered on the integration of three computers: one for training the AI, one for simulation to test and validate the AI, and one in the vehicle to process sensor data in real time to make safe driving decisions. Together, these systems enable continuous development cycles, always improving the AV software in performance and safety. Rosekind, a highly regarded automotive safety expert, spoke about the patchwork of regulations that exists across the U.S., explaining that federal agencies focus on the vehicle, while the states focus on the operator, including driver education, insurance and licensing. Pavone commented on the emergence of new tools that allow researchers and developers to rethink how AV development is carried out, as a result of the explosion of new technologies related to generative AI and neural rendering, among others. These technologies are enabling new developments in simulation, for example to generate complex scenarios aimed at stress testing vehicles for safety purposes. And they're harnessing foundation models, such as vision language models, to allow developers to build more robust autonomy software, Pavone said. One of the relevant and timely topics discussed during the panel was an announcement made during the AI Summit by MITRE, a government-sponsored nonprofit research organization. MITRE announced its partnership with Mcity at the University of Michigan to develop a virtual and physical AV validation platform for industry deployment. MITRE will use Mcity's simulation tools and a digital twin of its Mcity Test Facility, a real-world AV test environment in its digital proving ground. The jointly developed platform will deliver physically based sensor simulation enabled by NVIDIA Omniverse Cloud Sensor RTX applications programming interfaces. By combining these simulation capabilities with the MITRE digital proving ground reporting and analysis framework, developers will be able to perform exhaustive testing in a simulated world to safely validate AVs before real-world deployment. Rosekind commented: The MITRE announcement "represents an opportunity to have a trusted source who's done this in many other areas, especially in aviation, to create an independent, neutral setting to test safety assurance." "One of the most exciting things about this endeavor is that simulation is going to have a key role," added Pavone. "Simulation allows you to test very dangerous conditions in a repeatable and varied way, so you can simulate different cases at scale." "That's the beauty of simulation," said Shapiro. "It's repeatable, it's controllable. We can control the weather in the simulation. We can change the time of day, and then we can control all the scenarios and inject hazards. Once the simulation is created, we can run it over and over, and as the software develops, we can ensure we are solving the problem, and can fine-tune as necessary." The panel wrapped up with a reminder that the key goal of autonomous driving is one that businesses and regulators alike share: to reduce death and injuries on our roadways. Watch a replay of the session. (Registration required.) To learn more about NVIDIA's commitment to bringing safety to our roads, read the NVIDIA Self-Driving Safety Report.
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At the NVIDIA AI Summit in Washington, D.C., industry experts discussed the future of autonomous vehicle safety, emphasizing the role of AI and simulation in improving road safety and the need for standardized guidelines.
The NVIDIA AI Summit in Washington, D.C. brought together industry experts to discuss the critical issue of autonomous vehicle (AV) safety and the role of artificial intelligence in shaping the future of transportation. Danny Shapiro, vice president of automotive at NVIDIA, led a panel discussion with Mark Rosekind, former administrator of the National Highway Traffic Safety Administration, and Marco Pavone, director of AV research at NVIDIA 12.
Shapiro opened the discussion by highlighting the alarming number of crashes, injuries, and fatalities on global roadways, primarily caused by human error. He emphasized NVIDIA's two-decade-long commitment to working with the auto industry on advanced driver assistance systems and fully autonomous driving technology development 12.
NVIDIA's strategy for AV development integrates three key components:
This integrated approach enables continuous development cycles, constantly improving AV software in terms of performance and safety 12.
Rosekind shed light on the complex regulatory environment in the United States, where federal agencies focus on vehicle-related issues while states handle operator-related matters such as driver education, insurance, and licensing 12.
Pavone discussed the impact of emerging technologies, including generative AI and neural rendering, on AV development. These advancements are enabling more sophisticated simulation capabilities for stress-testing vehicles and leveraging foundation models to build robust autonomy software 12.
A significant announcement at the summit came from MITRE, a government-sponsored nonprofit research organization. MITRE revealed its partnership with Mcity at the University of Michigan to develop a virtual and physical AV validation platform for industry deployment 12.
The platform will utilize:
This collaboration aims to provide a comprehensive testing environment for safely validating AVs before real-world deployment 12.
The panel emphasized the crucial role of simulation in AV development and safety assurance. Pavone highlighted that simulation allows for testing dangerous conditions in a repeatable and varied manner, enabling the evaluation of different scenarios at scale 12.
Shapiro elaborated on the advantages of simulation, stating, "It's repeatable, it's controllable. We can control the weather in the simulation. We can change the time of day, and then we can control all the scenarios and inject hazards." This level of control allows for thorough testing and fine-tuning of AV software 12.
The panel concluded by reiterating the primary objective of autonomous driving technology: to reduce deaths and injuries on roadways. This goal aligns the interests of both businesses and regulators in the pursuit of safer transportation systems 12.
As the automotive industry continues to evolve with AI-driven technologies, the insights shared at the NVIDIA AI Summit underscore the importance of collaboration between technology developers, researchers, and regulatory bodies in ensuring the safe deployment of autonomous vehicles on public roads.
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