List of Strategies & Action plans

This Commission staff working document (SWD) builds on the 2018 Commission Communication On the road to automated mobility: An EU strategy for mobility of the future (1), which provided research, policy and regulatory recommendations at EU level for the development and deployment of connected, cooperative and automated mobility (CCAM). This SWD offers a state of play of CCAM in Europe by taking stock of progress made at operational, technological, societal and economic level since 2018. It also describes 10 main European achievements in this area to date. This document does not present any recommendations for future developments in this area, thus pre-empting the next framework programme for research and innovation and, therefore, does not commit the Commission in relation to potential forthcoming initiatives or decisions on the successor to the current research and innovation framework programme, Horizon Europe.

Automated driving has evolved over nearly a century, from early infrastructure-guided prototypes to today’s vehicle-centric, AI-enabled systems. Each stage in this development has been driven by the pursuit of safe, clean, efficient and accessible mobility yet has also raised fundamental questions about how the safety of automated vehicles (AVs) can be assured, demonstrated and trusted.

This paper, produced by the FISITA Automated Driving Expert Group, traces the historical progression of
automated driving, outlines the current regulatory and standards landscape and explores how data can
underpin credible, evidence-based safety assurance. As automated driving technologies transition from
rule-based architectures to complex, end-to-end deep learning systems, conventional approaches to proving safety through accumulated mileage or human-driver comparisons are no longer sufficient. Instead, the assurance process must shift toward continuous, data-driven evaluation.
AVs generate multiple categories of data that are essential for this process:

• Operational data captures vehicle dynamics, system status and environmental conditions.
• Perception and decision-making data records how the vehicle senses, interprets and responds to its
  surroundings.
• Event data provides detailed context for incidents, disengagements and near misses.
• Training data supports the development and refinement of machine learning algorithms.

Together, these datasets offer a rich source of insight into system performance but their regulatory use is
complicated by the diversity of hardware, software and data architectures among developers. The absence of standardised formats and common interpretive frameworks limits transparency, comparability and effective oversight.

To address these challenges, the British Standards Institution’s (BSI) Digital Commentary Driving (DCD)
framework proposes a standardised method for capturing and communicating how AVs perceive and decide, inspired by the human practice of commentary driving. By defining a consistent structure for explaining system reasoning, DCD provides data that enables examination of AV perceptions, predictions and behaviours to assess safety performance without exposing proprietary code, thereby enabling more transparent regulatory evaluation and public accountability.

This paper concludes that data transparency is both a technical and societal imperative. Building public trust in automated driving will depend on establishing shared frameworks for data collection, interpretation and communication, ensuring that automated vehicles not only operate safely but can be seen to do so. At the same time, consumers may need to accept confidential collection and sharing of data of their use of AVs to support continuous improvement of the safety and performance of such services. Through responsible data use and collaborative safety assurance, the vision of safe, clean, efficient and accessible mobility can move from aspiration to reality.

Autonomous mobility presents a unique and substantial opportunity for public-transport operators and authorities to enact a step-change in their services. By leveraging advanced mobility solutions, public transport can become a truly universal service that enhances connectivity across urban, suburban, and rural areas, reduces reliance on private vehicles, and creates safer and more sustainable communities.

Diverse roadmaps have been released from different countries and regions, led by respective industry organizations as well as governments, playing a crucial role in the alignment among all sectors. To explore the realization path and its corresponding innovation mechanism, starting from exchange and cooperation on these roadmaps, and to lay a solid foundation for further global alignment, the China Society of Automotive Engineers (CSAE) and China Industry Innovation Alliance for Intelligent & Connected Vehicles (CAICV) have established the International Communication and Cooperation Committee of ICV Roadmaps, together with organizations, institutions, and enterprises all around the world, including 5GAA, ACEA, BMW, CAAM, CAERI, CAICT, CATARC, Changan Auto, CICT, DFM, Drive Sweden, ERTICO, ERTRAC & CCAM Partnership, FISITA, GAC Motor, GM, Huawei, KSAE, RIOH, RIRS, SAE International, VDA, Volkswagen, and Zenzic.

This white paper outlines the main contents of these diverse ICV roadmaps, drawing on input from the corresponding committee members, synthesizing the respective characteristics and the best practices of these roadmaps.

Advanced Driver Assistance Systems (ADAS) are systems that assist the driver in carrying out the primary driving task. ADAS observe the environment using sensors and are able to take over control of speed or driving direction, subject to the responsibility of the person at the wheel. Systems of this kind are also able to warn the driver in situations that the system considers dangerous.

Automation in road traffic can help improve road safety, but also engender new road safety risks. On the basis of accident investigations, a literature review and discussions with experts, the Dutch Safety Board has identified a number of types of new risks that are not yet sufficiently recognized or managed.

When they are placed on the market, ADAS are not yet fully mature. This means that following permission for use on public roads, they undergo further development. Together with the lack of knowledge among drivers, situations in which drivers fail to understand why the vehicle responds or indeed fails to respond in a particular way can quickly arise. In addition, drivers in vehicles fitted with ADAS play a different role than drivers in conventional cars, namely the role of operator.

In all its investigations, the Dutch Safety Board operates a reference framework. This framework lays out the standards with which the various stakeholders are expected to comply, in order to manage safety risks in a given field. Essentially, this reference framework is a question of responsible innovation. Based on this framework, the Dutch Safety Board has identified bottlenecks in terms of design, policy, regulation and supervision, data availability and learning capacity. In addition, the Dutch Safety Board provides in total six recommendations to the automotive manufacturers and the OICA and ACEA umbrella organizations (1), to the BOVAG and RAI Association (1), and to the Dutch Minister of Infrastructure and Water Management (4).