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Back Issues Online
Back Issues Online

by Erwin Schoitsch (AIT)

Highly automated and autonomous systems are currently a key issue in many application domains: automotive, transport in general (railways, metro-lines, aircraft, space, ships), industrial automation, health care, cooperating mobile robots and related machines (e.g., fork lifts, off-road construction engines, smart farming, mining, all kind of drones and robots for surveillance, rescue, emergency services, maintenance). Highly automated and autonomous systems play an important role in the ‘digital transformation’ - the strategic and disruptive evolution towards a ‘digital society’, which is the key focus of European Research in Horizon 2020. This is depicted in Figure 1, which is taken from an official presentation of DG CONNECT at various events.

Figure 1: Technologies driving the digital transformation  (source: European Commission, DG CONNECT, W. Steinhögl).
Figure 1: Technologies driving the digital transformation (source: European Commission, DG CONNECT, W. Steinhögl).

At a European level, research initiatives in Horizon 2020 include smart mobility and related applications for highly automated vehicles, such as those used in smart farming, marine, construction, logistics, manufacturing, smart cities and even health care (elderly care homes, hospital environments). This comprises general ICT research as well as domain-related programmes. Some relevant programs are:

  • ECSEL (Electronic Components and Systems for European Leadership, a joint undertaking between the EC, national member states and private partners from the industrial associations ARTEMIS, AENEAS and EPoSS),
  • SPARC (robotics research, a PPP between EC and euRobotics) and the
  • ‘Large Scale Pilot’ Programmes (e.g., in Smart Farming and Mobility), which are closely connected to the ‘Internet of Things’ Innovation Initiative (AIoTI and the EC).  

At a national level in many European countries, substantial research is being conducted on autonomous vehicles and in particular (highly) automated driving. These efforts are not restricted to large countries like Germany and France - for example, the Austrian Federal Ministry for Transport, Innovation, and Technology (BMVIT) has launched a call to set up and run a public test region for automated vehicles, the ‘Austrian Light-vehicle Proving Ground’ (ALP.Lab) starting in 2017. For another example see ‘RECAR: Hungarian REsearch Center for Autonomous Road vehicles is on the way’.
There are many challenges to consider:

  • Safety and security, privacy, dependability in general (see articles under ‘Generic Challenges’)
  • Sensors and actuators
  • Software development, life cycle issues
  • System integration
  • Connected vehicles, V2X connectivity
  • Cooperative driving and transport systems, systems-of-systems aspects
  • New mobility (multi-modality enabled by highly automated/autonomous vehicles)
  • Imulation and control
  • Verification and validation
  • Standardisation
  • Situation understanding, cognition, decision making
  • Path planning, (precision) maps, localisation and navigation
  • Environmental awareness, self-learning,
  • Human interaction and (public) acceptance, and
  • Societal, ethical and legal aspects.

This includes impact from other sciences such as big data, IoT, artificial intelligence, communications and cloud, mechatronics and semiconductors, which contribute to meet these challenges. Connected cooperative autonomous vehicles are adaptive systems-of-systems. In this context, we have to consider several levels of system autonomy:

  • the vehicle (robot) as such (level 1, local autonomy, self-dependence),
  • the fleet/swarm/ad-hoc group of connected vehicles (level 2, increased amount and chances for information and adaptation of control), and
  • the regional/global level 3 (throughput, environmental friendly operation, saving of resources), which needs to be considered  for traffic or logistics optimisation or multi-modal transport, for instance.

There is a big difference between development and use in specialised fields of application, where trained operators and/or structured environments are involved (like construction, manufacturing, on-site operations, railways/metros, aircraft and space) and where the general public and public spaces set the requirements (road transport, smart cities/buildings/homes and care). ‘Mixed traffic’ of autonomous and traditional vehicles is the most demanding scenario, and in urban environments the ‘vulnerable road users’ (people, bicycles etc.) will still remain as partners (see also ‘Hello human, can you read my mind?’). Therefore, the Roadmaps for automated driving foresee five levels of ‘take over’ from the driver, the highest one being urban traffic. Similar levels are defined for other transport systems like railways and aircraft (see article on ‘Cross-Domain Fertilisation in the Evolution towards Autonomous Vehicles’ and the key note).

For many businesses, ‘Digital Transformation’ will be disruptive – some will vanish, some will change, but also new challenges and chances will arise and roles change. One example may be that for fully autonomous cars, insurance and liability will become the OEM/manufacturer’s responsibility and no longer be with the driver, the driver’s licence will become a vehicle licence. With reduced individual car ownership, OEMs may shift from pure selling to fleet management and maintenance of autonomous car fleets, because vehicles are then used mainly on demand (see also ‘How the Digital Business Model can Transform and Boost the Car Industry’).

This issue of ERCIM News covers many diverse aspects of the Special Theme, without being able to claim completeness.

The first group of contributions discusses rather generic challenges, like dependability of autonomous controls, safety and security co-engineering (addressing connected, intelligent automated vehicles) and the chances for disruptive innovations in advanced robotics by adaptive autonomy.

The largest block of articles is about automotive topics, ranging from the importance of new digital business models for the car industry to particular applications, specific development and technology paradigms and national research initiatives, including considerations for cooperative systems, connected vehicles and human factors and models for traffic safety and optimisation.

Several articles address cross-domain or very particular challenges and technologies, including agriculture, railways, ships and underwater robots, UAVs, machines, issues of swarm and fleet management in context of off-road and road vehicles, to name just a few.

[1] ARTEMIS Strategic Research Agenda 2016, ARTEMIS Industrial Association, March 2016
(SRA 2016: )
[2] MASRIA 2017 – Multi-Annual Strategic Research and Innovation Agenda for ECSEL Joint Undertaking (AENEAS, ARTEMIS, EPoSS)     
[3] Position Paper Safetrans Working Group “Highly automated Systems: Test, Safety, and Development Processes” (2016) (cited in: D. Watzenig, M. Horn (Eds.): “Automated Driving”, Springer 2016, ISBN 978-3-319-31895-0)

Please contact:
Erwin Schoitsch, AIT Austrian Institute of Technology
This email address is being protected from spambots. You need JavaScript enabled to view it.

Next issue: January 2024
Special theme:
Large Language Models
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