Quantum Computing for Automated Vehicle Trajectory Planning

This work presents an algorithm for solving trajectory planning problem with quantum computing. Trajectory planning is an important problem in the field of automated vehicles, as it makes it possible for the vehicle to traverse in new environments without a preplanned route. It is a computationally expensive task, especially in dynamic environments with lots of moving objects, which is why using quantum computing for the problem is examined in this work. The presented algorithm is designed to scale for arbitrarily complex trajectory planning problems. The algorithm is implemented and tested with a quantum computing simulator and a quantum computer. However, due to limitations in currently available quantum hardware and the high computational cost of quantum computing simulation, the algorithm can only be tested with a simplified version of the problem. Simulation tests show promising results as the algorithm can solve the simplified problem as designed in varying test cases. Tests with a quantum computer show that major improvements in quantum hardware are needed to be able to use the algorithm for real-world applications.