On Tuesday 16th March at 10:00am, Mr. Charles Philippe will publicly support his doctoral thesis entitled:
"Reliable and safe control and navigation for autonomous vehicles in dynamic urban environments"
Place: Amphi Recherche du pôle Physique, Campus des Cézeaux, 63178 AUBIERE
ABSTRACT
In this thesis is presented an algorithmic architecture for systematic risk evaluation, mitigation
and management intended for autonomous transportation vehicles. The methods
presented span low level control, trajectory tracking and multi-vehicle coordination. A
task separation between low level steering control and trajectory tracking has been implemented
to spread the design eort across two functional blocks. A robust low level
controller has been designed, and a comfortable and flexible Model Predictive Controller
(MPC) has been implemented for trajectory tracking. This controller has been associated
with a supervision mechanism that monitors its performance in real time to evaluate the
probability to underperform. When such a risk is identified, the speed of the system is
adapted. The multi-vehicle coordination block fulfils the planning task. It is a decentralized,
probabilistic optimization algorithm that is naturally risk-adverse. It is based on the
Probability Collectives (PC) algorithm and operates a multi-stage negociation between
vehicles. It has been made compatible with mixed-trac scenarios with human drivers on
the road. Results show that risks are monitored and managed across the whole architecture.
Furthermore, easy to understand risk metrics are outputted to make the algorithms
decisions understandable by the users and engineers working on the system. The work in
this thesis thus proposes systematic risk management techniques transposable to all autonomous
vehicles systems. It has been tested in simulations and on the autonomous test
vehicles available at the Institut Pascal.