Webinar • Siemens Industry Software: Digital Manufacturing • Industria y Fabricación

Verification and validation of autonomous vehiclesAgéndalo en tu calendario habitual ¡en tu horario!

Jueves, 31 de marzo de 2022, de 05.00 a 06.00 hs Horario de Virginia (US)
Webinar en inglés
Find the right balance between safety, comfort, and efficiency for AVs
 
Several challenges have arisen as the automotive industry introduces autonomous vehicles (AVs). In addition to the technological capabilities, a key challenge is meeting the requirements and constraints of the developing legal framework by governments and regulatory agencies. Their increasingly active involvement is logical given the initial results of on-street testing, with providers of autonomous vehicles needing to find the right balance between safety, comfort, and efficiency. This webinar addresses the various solutions available today to address the pain points experienced.
 
Develop safe and comfortable autonomous vehicles systems
 
The introduction of autonomous vehicles has continuously been pushed back over the last eight years, with the roll-out in everyday situations proving much more complex than initially estimated. For the technology to be operating safely and comfortably, massive testing of AV systems is required. Where strides have been made regarding operations in specific areas, particularly in favorable (weather) conditions, deployment of autonomous vehicles anywhere at any time requires more development and much more testing.
 
The requirement to deliver tangible results and visible deployments leads to a shift from uncontrolled to semi-controlled environments and completely automated to driver assistance.
 
AV development benefits from advanced driver assistance systems
 
In a push to deliver autonomous applications today, the focus is shifting towards fixed-route deployments featuring a reduced number of variables and thus scenarios to consider. The robo-taxi use case takes a back seat to deploy autonomous trucks on the major arteries between cities. Autonomous trucks operating mainly on highways feature shorter deployment and a currently financially viable business case.
 
In addition, car manufacturers are pushing hard towards improving safety today by including the latest functionalities of advanced driver assistance systems in their vehicles. With humans remaining in control, technology plays a supporting role in becoming a better driver. The various onboard sensor systems collect valuable data in this status, helping develop and deploy completely automated vehicles.
 
Legislations and regulations driving AV verification
 
Legislations and regulations will only be changed or introduced when technological developments and public opinion push their boundaries. This happens once the technology has proven safer — objectively and subjectively. Standards such as UNEC and NCAP are progressive, including requirements regarding driver assistance features, in preparation for autonomous vehicles.
 
Virtual world testing, the Digital Twin, will contribute to testing; it also comes with its own set of regulations. Without verifying that the Digital Twin is a reliable copy of the real world, there is no way to determine whether the results can be viewed as trustworthy. ISO26262 certification of the simulation tool is only a first step in this regard, as certification of the tool does not mean that sufficient and appropriate scenarios are being tested. Discover how to find unknown-unsafe scenarios in this webinar.
 
Discover an integrated tool suite for AV safety engineering
 
Siemens’ software solutions address the different phases of the product lifecycle to accelerate the development of autonomous vehicle technology with the world's most comprehensive automotive and transportation software portfolio. Featuring the required flexibility and interfacing to allow developers to select the tools of their preference for each phase, this integrated tool suite with the associated services supports:
 
- Capture data: autonomous vehicle development is very much a data-driven process where massive amounts of data are being used for machine learning and statistical analysis.
- Analyze and diagnose: the collected data is analyzed to extract the relevant content, allowing it to be prepared and serve as the basis for the data-driven design and performance evaluation.
- Design and explore: the data captured is used for design exploration and generative design optimization.
- Verification and validation: proving the autonomous vehicle are both safe and comfortable enough to be deployed in the real world with members of the public on board.
 
Ponentes:
 
Gwen van Vugt:Senior Director Autonomous Vehicles, Siemens Digital Industries Software
 
Gwen Van Vugt leads the Autonomous Vehicle business segment within Siemens Digital Industries Software - Simulation and Test Solutions. His team of researchers, engineers, testers, software developers, and business developers serve the automotive industry with software and hardware products, knowledge, and experience to design and validate ADAS and AV systems for optimal safety and comfort.
 
 
Robbert Lohmann:Business Development Director AV, Siemens Digital Industries Software
 
Robbert Lohmann, MSc is Business Develop Director for the Segment ADAS/AV, supporting the market approach and project engagements. He has been in the automated transit industry since 1999, introducing autonomous vehicles to ports, theme parks, and public transit. At 2getthere, he was responsible for, among others, the introduction of autonomous shuttles at Masdar City (Abu Dhabi), Business Park Rivium (the Netherlands), and Brussels Airport (Belgium). Robbert graduated with a master’s degree from Nyenrode Business University in the Netherlands.
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