Agenda

Over the past few years, stakeholders across the mobility ecosystem have pushed back their ambitious timelines for Level 5 autonomous vehicle (AV) development and deployment. While some companies, such as Elon Musk’s Tesla, still believe a breakthrough is just around the corner, most now accept that mass deployment is more than a decade away.

• What is the likely adoption timeline for all levels of autonomous driving (L1-L5)?
• What are the main technological challenges to achieving Level 5, and what is the industry doing to overcome them?
• How must the regulatory landscape evolve to enable the widespread adoption of AVs?
• What are the potential regional differences in the adoption of AVs?

The mobility sector has, in recent years, achieved rapid development in advanced driver assistance systems (ADAS), resulting in much wider adoption. This trend is on track to continue, with the North American ADAS market expected to more than double to around US$23bn by the end of this decade as automakers strive to deliver enhanced driving safety, comfort, and efficiency to their customers.

• What is the long-term vision for the role of ADAS in shaping the future of mobility?
• Which technological innovations are most likely to influence the future of ADAS?
• What are the main obstacles companies face in developing secure, dependable, and scalable next-generation ADAS functionality?
• Will ADAS adoption eventually become widespread across all regions and vehicle segments, and if so, what is the timeframe?

Ralph Tritsch, Senior Manager, Eraneos

Sensor fusion techniques, which combine data from cameras, radars, Lidars, and ultrasonic sensors to help the vehicle perceive its surroundings and make decisions, will play a critical role in the evolution of autonomous vehicles. Our panel of experts discuss how they approach the complex task of achieving sensor fusion in the quest for Level 5 autonomous driving.

• What is sensor fusion, and what role does it play in enabling autonomous driving?
• What are the main challenges to achieving sensor fusion?, and how can they be overcome?
• How will sensor fusion evolve as we move towards Level 5 autonomous driving?
• How might sensor technology and artificial intelligence advancements impact the future of sensor fusion?