BDVA Task Forces


Automtive Big Data Artificial Intelligence

Focus and activities

Aim: this Task Force focuses on Big Data and Artificial Intelligence applications applied to the Automotive sector.

Nowadays, five main pillars drive innovation in the automotive sector. In each of these pillars, big data is acting as a cross-cutting enabler:

  1. Electrification: With the introduction of e-mobility (hybrid, pure electric vehicle) to optimize or even completely remove the internal combustion engine, finally reducing the resulting local pollutant emissions during vehicle operation. Big data are essential to assess state of health, charging strategy and infrastructure, ageing behaviour of batteries, as well as real driving emissions.
  2. Advanced Driver Assistance Systems and Autonomous Driving: With the purpose of providing more comprehensive information to the driver for better context awareness, up to taking over specific driving manoeuvres – finally reducing the demands on the driver and lowering number and impact of possible accidents. Big data feeds the data driven artificial Intelligence systems responsible for vehicle autonomy. It also supports the validation and verification of the exploding number of driving scenarios.
  3. Connected & cooperative vehicle: Enabling optimization of vehicle’s operation or the emergence of new services while relying on external information, e.g., exploiting data from other vehicles or from the infrastructure. These tasks require reliable and scalable big data management and security.
  4. Smart Mobility: Targeting the efficient movement of people and goods with respect to different factors such that time, energy consumption, or ecological footprint. Big Data enables a new mobility service architecture and, on top of that, a new, much more flexible ecosystem of mobility offers, which will reshape the road transport in the future years.
  5. Vehicle Technology Development & Lifecycle: All above mentioned trends will have an impact on the lifecycle of the vehicle (design, production, maintenance). For example, big data plays a crucial role in virtualization of vehicle engineering and in the optimization of production and vehicle maintenance.

The Automotive Task Force will create a common understanding between members of the BDVA interested in Big Data and Artificial Intelligence applications applied to the Automotive sector with special emphasis on Connected Cooperative Automated and Electric domains. It will also answer, among others, the needs to create meaningful strategic insights as input for policy makers as well as strengthening a critical European automotive industry during its shift towards digitalisation.

The outcomes of the Automotive Task Force will be of relevance for their application and industrial deployment, spanning data-driven product and process design, and innovative business models.


Bernard Peischl
Task Force Co-Lead
AVL List GmbH
Oihana Otaegui
Task Force Co-Lead
Vicomtech Foundation