Use this URL to cite or link to this record in EThOS:
Title: Optimal motion cueing for race-car simulators
Author: Salisbury, Ingrid Gael
ISNI:       0000 0004 6497 9246
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
This thesis is a study of motion cueing algorithms in race-car simulators. Motion cues are accelerations that are used by a driver to infer particular vehicle behaviours. Motion cueing algorithms use vehicle accelerations to generate simulator accelerations. Typically, these algorithms aim to produce motion cues that indicate the vehicle accleration and behaviour, without reproducing exactly the vehicle motion. The cueing algorithms also prevent the simulator motions from hitting the hardware kinematic and dynamic limits. Existing simulator platforms and cueing algorithms, most of which have been developed for passenger car simulators, are discussed to determine how these can be applied to race-cars. In the process, the distinguishing features of the race-car application are identified. The large accelerations and high-frequency motions are a challenging combination to render in a power and workspace limited simulator. Furthermore, the driver is required to operate the vehicle on the performance limit, which is a difficult control task requiring particular vehicle information. The study of fundamental vehicle stability and handling across the range of operating conditions is conducted to understand better the vehicle motion cues required by the simulator driver to perform the race-driving task. With a knowledge of the driver cueing requirements, passenger car cueing strategies are modified and implemented in a Formula 1 simulator. Alternative cueing methods are also developed that address the racing cueing problem. Tests are conducted and on the basis of the driver feedback the algorithms are retuned to develop a cueing system that enables the drivers to execute their tasks successfully. The implemented cueing algorithms do not consider explicitly the optimal usage of simulator workspace. The final element of this thesis is the use of numerical optimal control to determine the optimal platform workspace exploitation, while minimising cueing acceleration and velocity errors. The solutions of open-loop optimal control calculations are used as a baseline against which to compare the tested cueing techniques. The limitations of, and areas in which to improve the implemented methods are identified.
Supervisor: Limebeer, David Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available