How cloud-based systems and machine-driven big data can contribute to the development of autonomous vehicles

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1 How cloud-based systems and machine-driven big data can contribute to the development of autonomous vehicles David Fidalgo- Altran Senior Business Manager

2 CONTENTS I. Altran Group/ Intelligence Systems II. Key Challenges for Addressing Autonomous Vehicles III. How we can use virtual testing to validate Autonomous Features IV. How Cloud Base Applications could help in the development of Autonomous vehicles V. Potential Benefits of using Cloud base applications and virtual testing

3 Intelligent Systems / Altran THE GLOBAL INTEGRATOR OF INTELLIGENT SYSTEMS TECHNOLOGY Complexity Systems integration Safety and security USAGE Desirable and efficient Seamless experience PROFITABILITY Cost-effective Sustainable New business models

4 Intelligent Systems / Altran Service Lines Product Engineering Services World-in-the-Loop Virtual Engineering Hardware-in-the-Loop Synthetic Environment Simulation Turnkey Development Integration Partner Low/Medium Rate Production Connected World VueForge TM Connected X Network Technology Network Management Human Systems Integration User Experience Human Factors Ergonomics & Design Safe & Secure World Safety-Critical Systems Cybersecurity Safecurity Certification

5 Key Challenges for Addressing Autonomous Vehicles Complexity Highly Critical environments New Technologies Costumer Demand Pace of Change New Entrants/Business Models New Lifecycles Consumer Impact Security & Safety Regulations & Standards Safety Constraints Cyber-Security Validation and Verification New Synthetic environments ( HIL, SIL) Virtual Engineering Testing

6 Key Challenges for Addressing Autonomous Vehicles Complexity Highly Critical environments New Technologies Costumer Demand Develop, Validate and Verify mixed integrity applications with real-time requirements The need for shared services and resources to take accurate decisions Integration of these technologies in the actual vehicles architectures Vehicle Network Communications and Infrastructure How we can influence the driver to take the right decision..

7 Key Challenges for Addressing Autonomous Vehicles Reduce Time to Market Faster Autonomous Feature Development Market Penetration Reduce Vehicle Insurance Pace of Change New Entrants/Business Models New Lifecycles Consumer Impact Security and Safety Levels Systems Resilience Safety Standards

8 Challenges of Testing Autonomous Vehicles Features Validation and Verification New Synthetic environments ( HIL, SIL) Virtual Engineering Testing Autonomous features are increasingly more complex and in-vehicle tests will no longer be sufficient. In-vehicle tests create constraints to repeatability and comparability, as well as large costs and time. Vast amounts of data are needed to be stored and used during development. The need of data fusion to ensure accurate situation recognition and interpretation increases complexity of test environment.

9 How we can use virtual testing to validate Autonomous Features The solution lies on testing and evaluating Autonomous features using virtual test driving with realistic behaviour and traffic environment. The approach has the capability of integrating cameras in addition to environment sensors (Radar, Lidar, Ultrasonic) for functional testing of algorithms. + Full Dynamic Vehicle HIL with Autonomous Sensor and Actuators Camera HiL Test Bench

10 How Cloud Base Applications could help in the development of Autonomous vehicles ADAS Sensors Business Close Loop Machines Data Storage+ Open Loop Testing Storage+ Open Loop Testing Data Actuators Users Open Loop Testing 10

11 Potential Benefits of using Cloud base applications and virtual testing The integration of the HiL test rig with the Cloud Base applications will allows the enhancement of the simulation environment: Provide storage for static data (i.e. navigation, driver preferences, simulation models) and measurement data (in-vehicle tests and HiL). Worldwide availability for constant development. Through a web based and flexible GUI, it will be possible to configure different tests and conditions for Autonomous features. The cloud base systems will then load all the relevant data to execute the specific test. Measurement data from in-vehicle test will be available to used in the rigs in open-loop. At the same time, data from HiL test will be instantly available to test drivers to improve real world test results. Use of multiple test rigs validating different Autonomous features using the same data. Test are fully reproducible everywhere, reducing considerably development costs and time.

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