Trucks transport the most goods worldwide: In Europe, they account for around 70% of freight traffic. However, 44% of long-distance drivers would not choose their profession again and 94% of logistics companies are currently struggling with driver shortages. In addition, around 90% of truck accidents are caused by human error. Autonomous trucks are the answer to many major challenges facing the modern trucking industry: Increasing truck uptime, driver productivity, driver shortages, safety, and environmental friendliness.A major obstacle towards this promising future is to guarantee in a mathematically provable way that the automated system always works correctly in diverse environments with varying road and weather conditions and a varying degree of collaboration of traffic participants. This endeavor is especially challenging since each traffic situation is different and thus automated driving cannot be verified beforehand, requiring that the vehicle verifies itself periodically given the current traffic situation.We address the important requirement to guarantee safe, correct, and coordinated motion of automated truck by establishing a framework, which integrates the consideration of traffic rules, maneuver and trajectory planning, and formal verification in a unique framework to provide intrinsic correctness. We will specify traffic rules and further specifications with temporal logics. These specifications will be checked using reachability analysis.

Excellent Masters degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics).Fluency in spoken and written English is required.Good programming skills in at least one programming language, e.g. MATLAB, C/C++, Python.