Participants will shed some light on whether the vehicle manufacturers approach to ADAS evolution or the ICT sector’s aspiration to leapfrogging autonomous transportation is more feasible.

The automotive industry is in transition. The entire eco-system is under strain. ICT drives innovations of automotive OEMS. New entrants challenge incumbents. There are tremendous growth opportunities for those who shape the future of the industry. Others will fail to adapt and cease to exist.

All stakeholders benefit from a coordinated evolution of enabling technologies, the value chain, and business models under the umbrella of ideally self-regulated boundary conditions.

IEEE provides platforms for open collaboration to facilitate a smooth transition of the automotive eco-system. Standards related activities including setting of standards are the means to this end. Standards ensure interoperable solutions and significantly reduce risks and costs for individual companies while building trust in new technologies among customers and in public.

Autonomous Vehicles will generate and consume an ever-increasing abundance of data.  Exchanging and sharing data is the basis to leverage intelligence hidden in data. New business models can be implemented by monetizing data. An e2e data infrastructure will integrate vehicle platforms and platform businesses.

Huge amounts of data need to be managed and governed during the operation of an autonomous vehicle and as the foundation of key engineering processes. ADAS development and validation of safety are two challenging data intensive engineering processes, in particular in the presence of data-based learning techniques.

The workshops will address these challenges of data driven engineering and operation, all evolving around three key themes, which may result in distinct standardization work programs:

• Achieving Data Interoperability among actors in the mobility eco-system
• ADAS Engineering including AI for automated driving of Autonomous Vehicles
• Test solutions and validation methods for safety in the presence of AI in Autonomous Vehicles

The workshop covers two parts:

Part 1: Inform about the IEEE standardization pipeline for road transportation

Examples include:

• Automotive Ethernet (IEEE 802.3, 802.1)
• Automotive Image Quality and Performance Testing (P2020)
• Automated Vehicle Decision Making (P2846)
• Certificate Management Interfaces for End-Entities (P1609.2.1)
• … and more

Part 2: Identify standardization gaps to facilitate data driven engineering for autonomous vehicle

Topics to be addressed include:

• Vehicle platform evolution
• E2e data interoperability: on-board, off-board, from vehicle to fog to cloud
• Interoperable engineering tools: for automotive AI, ultimately for safety
• ADAS engineering
• Test solutions and validation of safety in the presence of AI for autonomous vehicles