Automated vehicles with a high degree of autonomy are a highly relevant topic in the fields of passenger and freight transport, agriculture, forestry, warehouse automation, as well as rescue and exploration operations. A key aspect of autonomous systems is the vehicle's motion control and its close integration with planning algorithms, particularly in situations where the vehicle encounters its traction limits. This lecture will present the concept of vehicle motion control, which builds on functions known from automotive industry assistance systems and fully integrates these functions into a unified control architecture. The concept is extended with functionality for tracking the vehicle's reference trajectory determined by its movement – hence, vehicle motion control. By unifying the vehicle's response across a wide range of driving surfaces and their traction properties, assumptions for the operation of planning algorithms are ensured and simplified.
Assoc. Prof. Ing. Tomáš Haniš, Ph.D. graduated from the Faculty of Electrical Engineering, Czech Technical University in Prague in 2008 and completed his Ph.D. in Control Engineering and Robotics in 2012. Between 2013 and 2015, he held a postdoctoral position at the Technical University of Denmark. He worked in the research-commercial sector (Porsche Engineering Services, Rolls-Royce Deutschland), and in 2018, he returned to the Department of Control Engineering at CTU. In 2019, he founded the research center Smart Driving Solutions, dedicated to innovative autonomous driving systems, and in 2021, he was habilitated (appointed associate professor).
Assoc. Prof. Haniš systematically develops control algorithms for vehicle motion optimization and their subsystems in autonomous driving, actively publishes in top journals (7 articles with AIS above the field median, 6 in Q1, 2 in D1), and is co-author of 16 conference papers and 5 international patents. He supervises Master's and PhD theses, introduced the course "Car Control Systems" for the Master's program in Cybernetics and Robotics, and his students received significant awards in autonomous mobility competitions (American Control Conference Self-Driving Car Student Competition, 1st place 2024, 2nd place 2025).
