Priority-based intersection management with kinodynamic constraints

We consider the problem of coordinating a collection of robots at an intersection area taking into account dynamical constraints due to actuator limitations. We adopt the coordination space approach, which is standard in multiple robot motion planning. Assuming the priorities between robots are assigned in advance and the existence of a collision-free trajectory respecting those priorities, we propose a provably safe trajectory planner satisfying kinodynamic constraints. The algorithm is shown to run in real time and to return safe (collision-free) trajectories. Simulation results on synthetic data illustrate the benefits of the approach.Comment: to be presented at ECC2014; 6 page

Time-optimal Coordination of Mobile Robots along Specified Paths

In this paper, we address the problem of time-optimal coordination of mobile robots under kinodynamic constraints along specified paths. We propose a novel approach based on time discretization that leads to a mixed-integer linear programming (MILP) formulation. This problem can be solved using general-purpose MILP solvers in a reasonable time, resulting in a resolution-optimal solution. Moreover, unlike previous work found in the literature, our formulation allows an exact linear modeling (up to the discretization resolution) of second-order dynamic constraints. Extensive simulations are performed to demonstrate the effectiveness of our approach.Comment: Published in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS

Large deviation principale for Markov chains in continuous time

Related research report available at http://hal.inria.fr/docs/00/07/27/76/PDF/RR-3877.pdfInternational audienceLet Y t be a homogeneous nonexplosive Markov process with generator R defined on a denumerable state space E (not necessarily ergodic). We introduce the empirical generator G t of Y t and prove the Ruelle-Lanford property, which implies the weak LDP. In a fairly broad setting, we show how to perform almost all classical operations (e.g., contraction) on the weak LDP under suitable assumptions, whence Sanov's theorem follows

Coordination of automated vehicles at intersections: decision, efficiency and control

International audienceThis papers studies the kind of control that is needed to efficiently coordinate multiple automated vehicles. An intersection is chosen in order to present the main concept but consequences of this work also hold for other areas of cooperation, such as lane changes or maneuvers in parking lots. We chose the classical framework for multi-robots systems: the coordination space i.e. we assume the future paths are known and fixed. The problem is to coordinate the speeds of the vehicles. We first prove a theorem stating that a smooth feedback control cannot always avoid gridlocks: for more than 2 vehicles, there are always starting states ending into gridlocks. The paper then proposes some ways to avoid this drawback, leading to a better conceptual way to take decision in such a cooperative system, in order to have provable efficient decision and control

Back-pressure traffic signal control with unknown routing rates

The control of a network of signalized intersections is considered. Previous works proposed a feedback control belonging to the family of the so-called back-pressure controls that ensures provably maximum stability given pre-specified routing probabilities. However, this optimal back-pressure controller (BP*) requires routing rates and a measure of the number of vehicles queuing at a node for each possible routing decision. It is an idealistic assumption for our application since vehicles (going straight, turning left/right) are all gathered in the same lane apart from the proximity of the intersection and cameras can only give estimations of the aggregated queue length. In this paper, we present a back-pressure traffic signal controller (BP) that does not require routing rates, it requires only aggregated queue lengths estimation (without direction information) and loop detectors at the stop line for each possible direction. A theoretical result on the Lyapunov drift in heavy load conditions under BP control is provided and tends to indicate that BP should have good stability properties. Simulations confirm this and show that BP stabilizes the queuing network in a significant part of the capacity region.Comment: accepted for presentation at IFAC 2014, 6 pages. arXiv admin note: text overlap with arXiv:1309.648

A Distributed Model Predictive Control Framework for Road-Following Formation Control of Car-like Vehicles (Extended Version)

This work presents a novel framework for the formation control of multiple autonomous ground vehicles in an on-road environment. Unique challenges of this problem lie in 1) the design of collision avoidance strategies with obstacles and with other vehicles in a highly structured environment, 2) dynamic reconfiguration of the formation to handle different task specifications. In this paper, we design a local MPC-based tracking controller for each individual vehicle to follow a reference trajectory while satisfying various constraints (kinematics and dynamics, collision avoidance, \textit{etc.}). The reference trajectory of a vehicle is computed from its leader's trajectory, based on a pre-defined formation tree. We use logic rules to organize the collision avoidance behaviors of member vehicles. Moreover, we propose a methodology to safely reconfigure the formation on-the-fly. The proposed framework has been validated using high-fidelity simulations.Comment: Extended version of the conference paper submission on ICARCV'1

Discrete events model for dual mode transport system simulation and evaluation

Full text also available at http://www.mech.kuleuven.be/MT-ITS2011/downloads/Abstracts/042,%20A.%20de%20La%20Fortelle%20et%20al.,%20Discrete%20Events%20Model%20for%20Dual%20Mode%20Transport%20System%20Simulation%20and%20Evaluation.pdfInternational audienceThe European project CATS --- City Alternative Transport System --- is developing and evaluating a new vehicle system using a single type of vehicle for two different usages: individual use or collective transport. Real experiments will necessarily take place with a limited number of vehicles and stations. Hence there is a need for evaluation using simulations. INRIA is developing a discrete events simulator for that purpose, based on a previous work done for collective taxis. We present in this paper the model we use for the CATS project. This model rely on an adapted events/decision graph that extends previous graphs. The new feature of this model is the way we deal with two modes that can be extended to many other modes. This work therefore shows on a concrete example a method to efficiently merge multiple modes into one model