A Lagrangian discretization multiagent approach for large-scale multimodal dynamic assignment

This paper develops a Lagrangian discretization multiagent model for large-scale multimodal simulation and assignment. For road traffic flow modeling, we describe the dynamics of vehicle packets based on a macroscopic model on the basis of a Lagrangian discretization. The metro/tram/train systems are modeled on constant speed on scheduled timetable/frequency over lines of operations. Congestion is modeled as waiting time at stations plus induced discomfort when the capacity of vehicle is achieved. For the bus system, it is modeled similar to cars with different speed settings, either competing for road capacity resources with other vehicles or moving on separated bus lines on the road network. For solving the large-scale multimodal dynamic traffic assignment problem, an effective-path-based cross entropy is proposed to approximate the dynamic user equilibrium. Some numerical simulations have been conducted to demonstrate its ability to describe traffic dynamics on road network.multimodal transportation systems; Lagrangian discretization; traffic assignment; multiagent systems

a cross-entropy based multiagent approach for multiclass activity chain modeling and simulation

This paper attempts to model complex destination-chain, departure time and route choices based on activity plan implementation and proposes an arc-based cross entropy method for solving approximately the dynamic user equilibrium in multiagent-based multiclass network context. A multiagent-based dynamic activity chain model is developed, combining travelers' day-to-day learning process in the presence of both traffic flow and activity supply dynamics. The learning process towards user equilibrium in multiagent systems is based on the framework of Bellman's principle of optimality, and iteratively solved by the cross entropy method. A numerical example is implemented to illustrate the performance of the proposed method on a multiclass queuing network.dynamic traffic assignment, cross entropy method, activity chain, multiagent, Bellman equation

Dynamic Model for Assignment in " Sky-car " Transit System – Spatial Interactions with other Common Transport Modes

International audienceThis chapter provides Lagrangian dynamic fluid model of the traffic of personal rapid maglev transporters or personal rapid transit (PRT). The transport system using these maglev transporters-named sky-cars or sky-podcars-operate in the style of demand-responsive system. The dynamical evolution of sky-podcar travelers' demand is modelled and the problem of relocation of podcars is addressed. In a multimodal transport mobility, we describe assignment in such transit system, and its spatial interactions with other common transportation systems

A kinematic wave theory of capacity drop

Capacity drop at active bottlenecks is one of the most puzzling traffic phenomena, but a thorough understanding is practically important for designing variable speed limit and ramp metering strategies. In this study, we attempt to develop a simple model of capacity drop within the framework of kinematic wave theory based on the observation that capacity drop occurs when an upstream queue forms at an active bottleneck. In addition, we assume that the fundamental diagrams are continuous in steady states. This assumption is consistent with observations and can avoid unrealistic infinite characteristic wave speeds in discontinuous fundamental diagrams. A core component of the new model is an entropy condition defined by a discontinuous boundary flux function. For a lane-drop area, we demonstrate that the model is well-defined, and its Riemann problem can be uniquely solved. We theoretically discuss traffic stability with this model subject to perturbations in density, upstream demand, and downstream supply. We clarify that discontinuous flow-density relations, or so-called "discontinuous" fundamental diagrams, are caused by incomplete observations of traffic states. Theoretical results are consistent with observations in the literature and are verified by numerical simulations and empirical observations. We finally discuss potential applications and future studies.Comment: 29 pages, 10 figure

a cross-entropy based multiagent approach for multiclass activity chain modeling and simulation

This paper attempts to model complex destination-chain, departure time and route choices based on activity plan implementation and proposes an arc-based cross entropy method for solving approximately the dynamic user equilibrium in multiagent-based multiclass network context. A multiagent-based dynamic activity chain model is developed, combining travelers' day-to-day learning process in the presence of both traffic flow and activity supply dynamics. The learning process towards user equilibrium in multiagent systems is based on the framework of Bellman's principle of optimality, and iteratively solved by the cross entropy method. A numerical example is implemented to illustrate the performance of the proposed method on a multiclass queuing network

A Lagrangian discretization multiagent approach for large-scale multimodal dynamic assignment

This paper develops a Lagrangian discretization multiagent model for large-scale multimodal simulation and assignment. For road traffic flow modeling, we describe the dynamics of vehicle packets based on a macroscopic model on the basis of a Lagrangian discretization. The metro/tram/train systems are modeled on constant speed on scheduled timetable/frequency over lines of operations. Congestion is modeled as waiting time at stations plus induced discomfort when the capacity of vehicle is achieved. For the bus system, it is modeled similar to cars with different speed settings, either competing for road capacity resources with other vehicles or moving on separated bus lines on the road network. For solving the large-scale multimodal dynamic traffic assignment problem, an effective-path-based cross entropy is proposed to approximate the dynamic user equilibrium. Some numerical simulations have been conducted to demonstrate its ability to describe traffic dynamics on road network

A convergent scheme for Hamilton-Jacobi equations on a junction: application to traffic

30 pagesInternational audienceIn this paper, we consider first order Hamilton-Jacobi (HJ) equations posed on a "junction", that is to say the union of a finite number of half-lines with a unique common point. For this continuous HJ problem, we propose a finite difference scheme and prove two main results. As a first result, we show bounds on the discrete gradient and time derivative of the numerical solution. Our second result is the convergence (for a subsequence) of the numerical solution towards a viscosity solution of the continuous HJ problem, as the mesh size goes to zero. When the solution of the continuous HJ problem is unique, we recover the full convergence of the numerical solution. We apply this scheme to compute the densities of cars for a traffic model. We recover the well-known Godunov scheme outside the junction point and we give a numerical illustration