Interview with AustriaTech on automated trucks

Automotive IQ sat down with Martin Böhm, Head of Technologies and Services for Mobility from AustriaTech, and discussed the latest developments within automated commercial vehicles ahead of the upcoming conference Automated Trucks where Mr. Böhm will be presenting.

1) What are the major technical issues in creating multi-brand platoons and how do we overcome it?

The problem is not a technical one. The platooning challenge has shown, that technically platooning is possible. It is more an organizational problem including the willingness for cooperation. The word of the future will be copetition – a combination of cooperation and competition. Here we need to find the right balance between cooperation and competition to ensure better services – including platooning – where the business model is based on copetition. Without cooperation we will fail bringing such services to market.

2) What are the challenges and benefits in the area of C-ITS for platooning and automated driving systems?

The major challenges are currently with data and service security, privacy issues and harmonized interfaces to exchange data and services. We need to ensure that we are deploying harmonized and interoperable services serving first travelers and later on automated vehicles. We are now forming the ground for the future road system, which will be safer, more efficient and hopefully as well more environmental friendly. But to achieve such a cooperative connected automated road system it is crucial that all stakeholders work together for the benefit of the European citizens.

3) How far are we in platooning regulations and the legal framework, and what can/needs be done to be done for a connected Europe/USA?

The legal framework to enable platooning in Europe is not existing at all. The platooning challenge showed that even for demonstration issues the achievement of an permission is difficult, as the national road traffic acts need to be adapted. But before doing that, responsibilities in case of incidents and accidents need to be defined and agreed. I am quite sure that here input from insurance companies would be highly welcomed to work together on a sustainable legal framework.

4) How can interoperability, data analysis & processing be used for better path planning and control?

Planning a route from A to B is no challenge with good road and perfect weather conditions. But in case of incidents, accidents, unexpected weather events, traffic jams, etc. additional data will help us to provide an improved journey plan. This goes with routing recommendations as well as with speed advices based on the current traffic and weather situation. At the end we will achieve better route plans for a safer, more efficient and hopefully as well more relaxed journey from A to B.

5) How machine and deep learning can be used to improve control behavior for highly automated driving?

Machine learning will become one central element to make cooperative connected automated vehicles (CCAV) reality. Real life is much more complex than any technical environment. Therefore not every situation and every critical situation can be coded in all details beforehand, but general attitudes will be embedded into the CCAV. And then the machine needs to learn based on real life experiences, taking into account different driving styles and environments all over the globe.

6) What are the challenges in developing simulations, platform testing and related methods for automated driving?

The biggest challenge I see currently is with the non-comparability of the learnings. Everywhere in Europe we are starting with test trials, simulations, etc. But all tests are based on different methods as well as on different test and validation procedures. We get results which are hardly comparable, access to results and data is difficult and at the end we are delaying the process of making cooperative connected automated driving a reality in the near future. In fact we should join forces of all stakeholders (including OEMs, infrastructure operators, telecom operators, etc.) to work together.