2 research outputs found
A framework for self-enforced optimal interaction between connected vehicles
This paper proposes a decision-making framework for Connected Autonomous Vehicle interactions. It provides and justifies algorithms for strategic selection of control references for cruising, platooning and overtaking. The algorithm is based on the trade-off between energy consumption and time. The consequent cooperation opportunities originating from agent heterogeneity are captured by a game-theoretic cooperative-competitive solution concept to provide a computationally feasible, self-enforced, cooperative traffic management framework
A self-enforced, connected cooperative traffic framework
This doctoral thesis proposes a novel approach to road traffic de-conflicting. It comes
as a framework consisting of a user-tailored, multi-objective cost function and a negotiation algorithm, in which traffic conflicts are defned within game theoretic formulation, based on side-payment to fairly distribute the benefits, thereby ensuring feasibility within a distributed, intelligent system. The algorithm is then applied to two-agent con-flict resolution in a simulated intersection and platooning/overtake scenarios. Energy consumption and loss of time are compared, indicating a threefold improvement in theoretical efficiency of the framework in relation to a non-cooperative solution. It occurs
when agents are the most heterogeneous. The intersection and platooning algorithms are
then further developed to handle multi-agent scenarios, where complexity is the greatest
challenge. A formulation based on graph theory is proposed, estimating the complexity
to be no smaller than that of complete graph sequence, with time of calculation infeasibly
long above 10 agents, calling for implementation specifc heuristics.
The last chapter of this work considers the framework's future paths of development.
It features extended cost function formulations, incorporating, among others, ancillary
energy use or battery wear. System's sensitivity cheating or market penetration is also
studied, proposing human-in-the-loop architecture as means to ease the adoption process