Vdata

In modern vehicles, the continuous generation of large amounts of data, particularly through automated driving functions (ADFs), has become a significant aspect of vehicle technology. This data is often processed immediately but, in many cases, also stored for later use, or even shared with other vehicles. Examples include storing vehicle data in an event data recorder, broadcasting hazard alerts to other vehicles in the vicinity, or transmitting data from a vehicle to the cloud for preventive diagnostics.

The ability to collect and exchange data enables new functionalities, such as enhancing driving assistance systems, early detection of sensor failures or even inform the automated driving functions in advance of ODD (Operational Design Domain) gaps, so they can react early and potentially take appropriate action to stay within their ODD. However, managing and utilizing this data presents challenges, including ensuring data quality, long-term availability, and traceability of its origin.

The handling of data traces and large data collections is a continuous process that requires maintaining data integrity and protecting against data loss. Long-term readability and processability of the data are also crucial. Understanding the origin and circumstances of data collection is vital for supporting the development of automated driving functions. This involves documenting relevant metadata to ensure traceability.

Connectivity technologies like V2X, including V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure), can increase personal data collection, essential for ADF development. It's important to ensure lawful data recording, respecting user privacy, and making users aware of potential data sharing. In this context, regulations such as the General Data Protection Regulation (GDPR) and the EU Data Act play a critical role. The GDPR establishes strict guidelines for the collection and processing of personal data, ensuring that individuals' privacy rights are protected. It mandates that data can only be collected with explicit consent and must be processed transparently. The EU Data Act complements this by focusing on data sharing and access rights, promoting the use of data while safeguarding privacy and security.

Standards like ISO 24748 contribute to data management in automated driving. This standard provides guidelines for the lifecycle management of automated driving systems, ensuring that data is handled consistently and securely throughout its lifecycle. The Event Data Recorder (EDR) and Data Storage System for Automated Driving (DSSAD) are two specific systems designed to manage vehicle data. The EDR captures critical data during a vehicle incident, such as speed and braking patterns, which can be used for accident analysis. In contrast, the DSSAD is focused on storing a broader range of data necessary for the ongoing operation and improvement of automated driving functions. While both systems aim to enhance safety and performance, they differ in their scope and purpose: the EDR is primarily concerned with post-incident data retrieval, whereas the DSSAD is designed for continuous data collection and analysis to support real-time decision-making and system improvements. In summary, the interplay between data collection, regulatory frameworks like GDPR and the EU Data Act, and standards such as ISO 24748 is essential for the responsible management of vehicle data. The distinctions between systems like EDR and DSSAD highlight the diverse approaches to data handling in the context of automated driving, each serving unique functions within the broader landscape of vehicle technology.