Longitudinal control of self-driving heavy-duty vehicles: a robust Markovian approach

• Published in: 2022 IEEE 61st Conference on Decision and Control (CDC) pp. 6966 - 6972
• Main Authors: Marcos, Lucas B., Bueno, Jose Nuno A. D., Rocha, Kaio D. T., Terra, Marco H.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06-12-2022
• Subjects: Markov processes; Regulators; Robust control; Robustness; Tracking; Trajectory; Uncertainty
• ISSN: 2576-2370
• DOI: 10.1109/CDC51059.2022.9992855

The past few years have seen a massive improvement in self-driving vehicle technology. However, many challenges remain ahead. For example, the robust autonomous control of heavy-duty vehicles is still an issue. Furthermore, gear shifting in the driveline affects state estimation and autonomous control, as it abruptly changes powertrain dynamics. This paper proposes a robust recursive discrete-time Markov jump linear system technique for achieving autonomous driveline control. The algorithm is tested for a truck bodywork. Experiments show that the proposed recursive controller outperforms its LMI-based counterpart in terms of tracking error and can complete the test track in scenarios where the nominal LMI-based version cannot.