2014
DOI: 10.1137/130907707
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Can Local Single-Pass Methods Solve Any Stationary Hamilton--Jacobi--Bellman Equation?

Abstract: The use of local single-pass methods (like, e.g., the fast marching method) has become popular in the solution of some Hamilton-Jacobi equations. The prototype of these equations is the eikonal equation, for which the methods can be applied saving CPU time and possibly memory allocation. Then some questions naturally arise: Can local single-pass methods solve any HamiltonJacobi equation? If not, where should the limit be set? This paper tries to answer these questions. In order to give a complete picture, we p… Show more

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Cited by 20 publications
(31 citation statements)
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“…(6) The interaction velocity (5) makes people move away from crowded region and its modulus is inversely proportional to the distance from the others. The sensory region (6) instead is a circular region in front of the pedestrian, assuming that his/her head is aligned with the desired velocity. The size of the sensory region is ruled by the parameter r, while the (small) parameter ε is used to avoid singularities.…”
Section: The Basic Modelmentioning
confidence: 99%
“…(6) The interaction velocity (5) makes people move away from crowded region and its modulus is inversely proportional to the distance from the others. The sensory region (6) instead is a circular region in front of the pedestrian, assuming that his/her head is aligned with the desired velocity. The size of the sensory region is ruled by the parameter r, while the (small) parameter ε is used to avoid singularities.…”
Section: The Basic Modelmentioning
confidence: 99%
“…A second class of methods concerns discontinuous Galerkin method, a direct method was proposed in the work of Cheng and Shu and a scheme for front propagation with obstacles in the work of Bokanowski et al Then, we can also consider semi‐Lagrangian schemes, which are based on the discretization of the dynamic programming principle as developed in the works of Falcone and Ferretti() and Carlini et al, for instance. A brief review of different efficient techniques that have been proposed can also be found in the work of Cacace et al…”
Section: Numerical Resolutionmentioning
confidence: 99%
“…A second class of methods concerns discontinuous Galerkin method, a direct method was proposed in the work of Cheng and Shu 31 and a scheme for front propagation with obstacles in the work of Bokanowski et al 32 Then, we can also consider semi-Lagrangian schemes, which are based on the discretization of the dynamic programming principle as developed in the works of Falcone and Ferretti 33,34 and Carlini et al, 35 for instance. A brief review of different efficient techniques that have been proposed can also be found in the work of Cacace et al 36 In this paper, we use the Ultra-Bee scheme (a finite difference type scheme) to solve the HJB equations (12)- (13). First developed for advection equations with constant velocity, 24,25 a generalization to velocity with changing sign velocities is done in the work of Bokanowski and Zidani 37 for HJB equations.…”
Section: Ultra-bee Scheme For Hjb Resolutionmentioning
confidence: 99%
“…For each pair h n , X n , we solve the discrete Isaacs equation (11) with boundary conditions (12) and call W n its solution. Then, we define for x ∈ Ω the viscosity semi-limits…”
Section: Example 1 Consider the Convex-concave Eikonal Equation In R mentioning
confidence: 99%
“…Our motivation comes from the so-called fast Marching methods (briefly, FMM) for Hamilton-Jacobi equations with convex Hamiltonian arising in deterministic control and front propagation problems, introduced in [34] and [29] and developed by Sethian [30], Sethian and Vladimirsky [31], Cristiani [15], Andrews and Vladimirsky [2], see also the references therein and Cacace et al [12] for some recent improvements. These numerical methods approximate time-optimal control in continuous time and space with a fully discrete Bellman equation on a grid and then rely on the classical Dijkstra algorithm for an efficient solution of the discrete approximation.…”
Section: Introductionmentioning
confidence: 99%