arXiv subjects
Publications and source records attributed to Paolo Falcone.
We present a mathematical model to predict pedestrian motion over a finite horizon, intended for use in collision avoidance algorithms for autonomous driving. The model is based on a road map structure, and assumes a rational pedestrian behavior. We compare our model with the state-of-the art and discuss its accuracy, and limitations, both in simulations and in comparison to real data.
In this paper we consider the problem of coordinating autonomous vehicles approaching an intersection. We cast the problem in the distributed optimisation framework and propose an algorithm to solve it in real time. We extend previous work on the topic by testing two alternative algorithmic solutions in simulations. Moreover, we test our algorithm in experiments using real cars on a test track. The experimental results demonstrate the applicability and real-time feasibility of the algorithm.
In this paper, we consider a set of agents, which may receive an observation of their state by a central observa- tion post via a shared wireless network. The aim of this work is to design a scheduling mechanism for the central observation post to decide how to allocate the available communication resources. The problem is tackled in two phases: (i) first, the local controllers are designed so as to stabilise the subsystems for the case of perfect communication; (ii) second, the com- munication schedule is decided with the aim of maximising the stability of the subsystems. To this end, we formulate an optimisation problem which explicitly minimises the Lyapunov function increase due to communication limitations. We show how the proposed optimisation can be expressed in terms of Value of Information (VoI), we prove Lyapunov stability in probability and we test our approach in simulations.
Vehicle-to-vehicle communication is a fundamental requirement in cooperative vehicular systems to achieve high performance while keeping high safety standards. Vehicles periodically exchange critical information with nearby vehicles to determine their maneuvers according to the information quality and established strategies. However, wireless communication is prone to failures. Thus, participants can be unaware that other participants have not received the information on time resulting in conflicting trajectories that may not be safe. We present a deterministic solution that allows all participants to use a default strategy when other participants have not received on time the complete information. We base our solution on a timed distributed protocol that adapts its output according to the effect of message omission failures so that the disagreement period occurs for no longer than a constant time (of the order of milliseconds) that only depends on the message delay. We formally show the correctness and perform experiments to corroborate its efficiency. We explain how the proposed solution can be used on vehicular platooning to attain high performance and still guarantee high safety standards despite communication failures. We believe that this work can facilitate the implementation of cooperative driving systems that have to deal with inherent (communication) uncertainties.