Abstract:
Automated vehicles are expected to push towards the evolution of transportation systems
and exploit the use of vehicular technologies. This thesis investigates the fundamentals
of motion planning for minimising motion sickness in transportation systems of higher
automation levels. The optimum velocity pro le is sought for a predefined road path
from a specific starting point to a final one within specific and given boundaries and
constraints in order to minimise the motion sickness and the journey time. Motion sick-
ness is minimised by taking the optimum trajectory and velocity profile for any given
road path generated by the motion planner. The trajectory tracking controllers based on
PID control method were able to track the reference trajectory with good performances.
The trade-off between motion sickness and journey time was solved using the application
of multi-objective optimisation by altering the weighting factors to find a compromise
solution. The Pareto front representing the correlation between the two components is
obtained and this front also allows user to select their preference driving style. From the
three case studies, driving styles have a bigger impact on reducing motion sickness and
journey time rather than vehicle speed and the road width. However, the effect of road
width is negligible when travelling on longer road for the reduction of motion sickness
and journey time. This finding is crucial considering the need for automated vehicles to
drive on a fixed road path in respect to road safety and also to allow the employment
of connected and automated vehicles in the future. Finally, an approach combining two
optimisation algorithms, the optimal control problem and the k - є method, is applied
successfully to seek the best trajectory profile that ensures the optimum compromise
between motion comfort and driving behaviour, energy efficiency, vehicle stability, occupant's confidence to ride and journey time.
