An Optimal Lateral Trajectory Stabilization of Vehicle using Differential Dynamic Programming

Autor: Mohit Kumar, Sven Kraus, Peter Strauss, Christoph Stiller, Arne-Christoph Hildebrandt, Andreas Zimmermann
Rok vydání: 2020
Předmět:
Zdroj: IV
DOI: 10.1109/iv47402.2020.9304582
Popis: Vehicles nowadays are equipped with several assistance functions for e.g. Cruise Control and Lane Keeping Assist. Classical lateral control approaches such as pure pursuit, Stanley used for lane keeping assist provide good path tracking precision. However the operational domain for these approaches is limited i.e. highway driving. An adaptation of control parameters can increase the operational domain, but its difficult to tune classical approaches for the whole range of automated driving maneuvers. Apart from these classical approaches, optimization approaches are also used for lateral trajectory stabilization. The optimization based approaches have a wider operational domain, but the feasibility and real time execution remain some open issues. In this paper, we combine a classical approach and an optimization method for lateral trajectory stabilization. We present a method to optimize the control input calculated using a classical control approach i.e. pure pursuit based on a performance criteria. The performance criteria weighs the precision and comfort requirements. A non- linear optimization based on Differential Dynamic Programming (DDP) is used to solve the optimization problem. The calculated optimal trajectory is finally evaluated using a line search method to ensure the convergence and to verify the optimization policy. The approach is demonstrated on a full scale automated truck prototype and the experimental results are discussed.
Databáze: OpenAIRE