Uncertainties in Robust Planning and Control of Autonomous Tractor-Trailer Vehicles
(2022) AVEC'22 The 15th International Symposium on Advanced Vehicle Control- Abstract
- To study the effects of uncertainty in autonomous motion planning and control, an 8-DOF model of a tractor-semitrailer is implemented and analyzed. The implications of uncertainties in the model are then quantified and presented using sensitivity analysis and closed-loop simulations. The study shows that different model parameters are more or less critical depending on the investigated scenario. Using sampling-based closed-loop predictions, uncertainty bounds on state variable trajectories are determined. Our findings suggest the potential for the inclusion of our method within a robust predictive controller or as a driver-assistance system for rollover or lane departure warning.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/a52e553e-3fe9-450b-b12d-f0184c42e20d
- author
- Westny, Theodor ; Olofsson, Björn LU and Frisk, Erik
- organization
- publishing date
- 2022
- type
- Contribution to conference
- publication status
- published
- subject
- conference name
- AVEC'22 The 15th International Symposium on Advanced Vehicle Control
- conference location
- Kanagawa, Japan
- conference dates
- 2022-09-12 - 2022-09-16
- project
- ELLIIT B14: Autonomous Force-Aware Swift Motion Control
- RobotLab LTH
- language
- English
- LU publication?
- yes
- id
- a52e553e-3fe9-450b-b12d-f0184c42e20d
- date added to LUP
- 2023-01-28 20:12:14
- date last changed
- 2023-04-24 21:07:05
@misc{a52e553e-3fe9-450b-b12d-f0184c42e20d, abstract = {{To study the effects of uncertainty in autonomous motion planning and control, an 8-DOF model of a tractor-semitrailer is implemented and analyzed. The implications of uncertainties in the model are then quantified and presented using sensitivity analysis and closed-loop simulations. The study shows that different model parameters are more or less critical depending on the investigated scenario. Using sampling-based closed-loop predictions, uncertainty bounds on state variable trajectories are determined. Our findings suggest the potential for the inclusion of our method within a robust predictive controller or as a driver-assistance system for rollover or lane departure warning.}}, author = {{Westny, Theodor and Olofsson, Björn and Frisk, Erik}}, language = {{eng}}, title = {{Uncertainties in Robust Planning and Control of Autonomous Tractor-Trailer Vehicles}}, year = {{2022}}, }