We change the transport of goods with our Hub-to-Hub solution: Our highly automated driverless system takes over long distances on highways.
On these routes, logistics costs are drastically reduced by cutting driver costs and eliminating legally required rest periods. Our solution saves 50% of operating costs for Hub-to-Hub logistics.
driveblocks offers the only solution in the market that accounts for European road network, traffic rules, vehicles, certifications and weather conditions.
Our software uses a local planning approach, operating exclusively with in-vehicle sensors. No HD maps are required, enabling our solution to work in unknown and unstructured environments.
We don't rely on good weather conditions: Our solution uses robust perception models, enabling automated driving functions even in adverse weather conditions and at night.
With years of experience in the validation of artificial intelligence and complex systems, we have taken legal approval into account from the very start and develop according to norms such as ISO26262 and ISO PAS 21448.
Our highly modular software structure enables high development speed, innovation and scalability.
We use open standards and open architetcture models - utilizing and contributing to the power of inspiration and innovation.
driveblocks is founded and operated by the 2021 winners of Indy Autonomous Challenge. Our world-class team of researchers and developers has many years of experience in artificial intelligence and autonomous driving software.
With our proven track record in bringing autonomous driving to the road, we create a cutting-edge solution for the logistics sector.
Chief Technical Officer
Alexander was the team leader and system architect of the winning Indy Autonomous Challenge team of the Technical University of Munich. In addition, he developed vehicle motion control systems of varying complexity during his time as a research assistant and has a strong background in control engineering and numerical optimization.
Chief Executive Officer
After his PHD on vehicle concept optimisation at the TU Munich, Stephan founded his first company together with Prof. Dr. Markus Lienkamp and Dr. Peter Burda. He also worked as a system engineer, project manager and team leader for a well known Tier-1 automotive supplier. His seven years of industry and leadership experience complete our diverse expertise.
Environment Model Lead
During his time as a research associate at the TU Munich, Tim was member of the Indy Autonomous Challenge winning race team. Tim has been involved in programming automated systems for over 10 years and focused on lidar localization, trajectory planning, and safety during his PhD. The technical know-how is complemented by more than five years of industrial experience.
As a research associate at TU Munich, Felix was responsible for the computer vision and perception pipeline of the winning Indy Autonomous Challenge team. His research revolved around sensor fusion and robust perception for autonomous vehicles. Prior to this, he strenghtened his knowledge through studies and working experience at UC Berkeley, TU Munich, UP Valencia and BMW.
During his time as a research associate at the TU Munich, Leonhard was member of the Indy Autonomous Challenge winning race team. Leonhard was responsible for vehicle dynamics simulation, HiL simulator development, and online analysis of performance relevant vehicle data. Next to his technical expertise, he brings work experience in automotive industry and motorsports, as well as a strong network through his membership at the Bavarian Elite-Academy.
Motion Planning Lead
Thomas was the deputy team leader of the Indy Autonomous Challenge winning team. During his time as a research associate at the Technical University of Munich and the Eindhoven University of Technology, he focused on real-time embedded motion planning and energy strategy optimization algorithms for autonomous vehicles.
Do you want to learn more about our cutting-edge solution for autonomous driving? We're happy to hear from you.