181 research outputs found
A Lagrangian discretization multiagent approach for large-scale multimodal dynamic assignment
No full textThis 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
No full textThis 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
Public Transport Priority for Multimodal Urban Traffic Control
No full textIn order to improve the travel time of surface public transport vehicles (bus, tramway, etc.), several cities use Urban Traffic Control (UTC) systems enabling to give priority to public transport. This paper reviews these systems. Further on after a debate on their insufficiencies in the global regulation of the urban traffic on a whole network, the paper proposes intermodal regulation strategies, operating on intersection traffic lights to regulate the traffic, favouring the public transport. All these strategies are based on the Linear Quadratic (LQ) optimal control theory, but they are different in their ways of taking into account the public transport in the optimization problem. The simulation tests are carried out in a network of eight intersections and two public transport lines.Fil: Bhouri, Neila. Université Paris Est; FranciaFil: Mayorano, Fernando Javier. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lotito, Pablo Andres. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Haj Salem, Habib. Université Paris Est; FranciaFil: Lebacque, Jean Patrick. Université Paris Est; Franci
Upper Bounds for the Travel Time on Traffic Systems
No full textAbstractA key measure of performance and comfort in a road traffic network is the travel time that the users of the network experience to complete their journeys. Travel times on road traffic networks are stochastic, highly variable, and dependent on several parameters. It is, therefore, necessary to have good indicators and measures of their variations. In this article, we extend a recent approach for the derivation of deterministic bounds on the travel time in a road traffic network (Farhi, Haj-Salem and Lebacque 2013). The approach consists in using an algebraic formulation of the cell-transmission traffic model on a ring road, where the car-dynamics is seen as a linear min-plus system. The impulse response of the system is derived analytically, and is interpreted as what is called a service curve in the network calculus theory (where the road is seen as a server). The basic results of the latter theory are then used to derive an upper bound for the travel time through the ring road.We consider in this article open systems rather than closed ones. We define a set of elementary traffic systems and an operator for the concatenation of such systems. We show that the traffic system of any road itinerary can be built by concatenating a number of elementary traffic systems. The concatenation of systems consists in giving a service guarantee of the resulting system in function of service guarantees of the composed systems. We illustrate this approach with a numerical example, where we compute an upper bound for the travel time on a given route in a urban network
Upper bounds for the travel time on traffic systems
No full textEWGT2014 - 17th Meeting of the EURO Working Group on Transportation, SEVILLE, ESPAGNE, 02-/07/2014 - 04/07/2014A key measure of performance and comfort in a road traffic network is the travel time that the users of the network experience to complete their journeys. Travel times on road traffic networks are stochastic, highly variable, and dependent on several parameters. It is, therefore, necessary to have good indicators and measures of their variations. In this article, we extend a recent approach for the derivation of deterministic bounds on the travel time in a road traffic network (Farhi, Haj-Salem and Lebacque 2013). The approach consists in using an algebraic formulation of the cell-transmission traffic model on a ring road, where the car-dynamics is seen as a linear min-plus system. The impulse response of the system is derived analytically, and is interpreted as what is called a service curve in the network calculus theory (where the road is seen as a server). The basic results of the latter theory are then used to derive an upper bound for the travel time through the ring road.We consider in this article open systems rather than closed ones. We define a set of elementary traffic systems and an operator for the concatenation of such systems. We show that the traffic system of any road itinerary can be built by concatenating a number of elementary traffic systems. The concatenation of systems consists in giving a service guarantee of the resulting system in function of service guarantees of the composed systems. We illustrate this approach with a numerical example, where we compute an upper bound for the travel time on a given route in a urban network
Modeling of multimodal transportation systems of large networks
No full textL’objectif de ce travail consiste en la modélisation des flux de véhicules d’un grand et dense réseau de transport multimodal. Le travail s’organise en deux parties: un aspect théorique et un aspect développement. L’étude théorique met l’accent sur la façon dont un réseau multimodal peut être modélisé et comment sa performance en termes d’offre peut être optimisée. Pour ce faire, trois études principales sont réalisées: la prévision et la régulation des flux de trafic sur les grands réseaux de surface, la multimodalité véhiculaire dans les grands réseaux de surface prenant en compte les nouvelles formes de mobilité, et enfin l’impact de l’information sur le coût des itinéraires. La partie développement consiste en la conception d’un simulateur de flux de trafic pour réguler le trafic multimodal véhiculaire. Le simulateur développé devrait aider les opérateurs de transport et les collectivités territoriales dans leurs stratégies de gestion des flux de traficThe objective of this work consists on the modeling of traffic flow of a large multimodaltransportation network. The work is organized in two parts: a theoretical study part anda development part. The theoretical study emphasizes on how a multimodal network canbe model and how its performance in terms of supply can be optimized. To do so, threemain studies are discussed: the traffic flow prediction and regulation on large surface net-works, the vehicular multimodality in big surface networks taking into account new forms ofmobility, and finally the impact of the information on the cost of the itineraries. The devel-opment part consists on the conception of a traffic flow simulator to regulate the vehicularmultimodal traffic. The developed simulator should assist transport operators and territorialcommunities in their traffic flow management strategie
Breadth-First Search-Based Remaining Range Estimation and Representation for Electric Vehicle
No full textSAE World Congress and Exhibition, DETROIT, ETATS-UNIS, 08-/04/2014 - 10/04/2014This paper presents a new extension of the well-known Breadth-First Search (BFS) algorithm for remaining range estimation and representation in electric vehicle (EV) driving range indicators. To build up the EV remaining range graph the proposed algorithm is coupled with a simple electric energy consumption model. Road data as well as weather conditions are taken into account when calculating the electric energy consumption. The BFS-based Indicator System is modeled in Matlab/ Simulink. Simulation results are compared with different manufacturer specifications for range under various route and driving conditions. The results are shown in the form of a graph of road segments all starting from the initial EV position and ending at the farthest achievable road nodes
Discussion about traffic junction modelling: conservation laws vs Hamilton-jacobi equations
No full textIn this paper, we consider a numerical scheme to solve first order Hamilton-Jacobi (HJ) equations posed on a junction. The main mathematical properties of the scheme are first recalled and then we give a traffic flow interpretation of the key elements. The scheme formulation is also adapted to compute the vehicles densities on a junction. The equivalent scheme for densities recovers the well-known Godunov scheme outside the junction point. We give two numerical illustrations for a merge and a diverge which are the two main types of traffic junctions. Some extensions to the junction model are finally discussed
Bidimensional traffic flow models.
No full textParallel sessionInternational audience1. Motivation 2. Static assignment 3. Pedestrian models 4. Macroscopic fundamental diagrams 5. Anisotropic model
Algorithms for optimal guidance of users in road networks
No full textNous nous intéressons dans ce travail au guidage optimal des usagers dans un réseau routier. Plus précisément, nous nous focalisons sur les stratégies adaptatives de guidage avec des garanties en termes de fiabilité des temps de parcours, et en termes de robustesse de ces stratégies. Nous nous basons sur une approche stochastique où des distributions de probabilités sont associées aux temps de parcours sur les liens du réseau. Le guidage est adaptatif et individuel. L'objectif de ce travail de recherche est le développement de stratégies « robustes » de guidage des usagers dans un réseau de transport routier. Une stratégie de guidage d’un nœud origine vers un nœud destination est dite robuste, ici, si elle minimise la détérioration de sa valeur maximale calculée au départ de l’origine, contre d’éventuelles reconfigurations du réseau dues à des coupures de liens (accidents, travaux, etc.) La valeur de la stratégie de guidage est maximisée par rapport à la moyenne et à la fiabilité des temps de parcours associées à la stratégie. Deux principales parties sont distinguées dans ce travail. Nous commençons par l’aspect statique du guidage, où la dynamique du trafic n’est pas prise en compte. Nous proposons une extension d’une approche existante de guidage, pour tenir compte de la robustesse des itinéraires calculés. Dans une deuxième étape, nous combinons notre nouvel algorithme avec un modèle microscopique du trafic pour avoir l’effet de la dynamique du trafic sur le calcul d’itinéraires robustesIn this work, we are interested in the optimal guidance of users on road networks. More precisely, we are focused on the adaptive strategies of guidance with guarantees in terms of the travel time reliability and in terms of the robustness of the strategies. We base here on a stochastic approach, where probability distributions are associated to travel times on the links of the network. The guidance is adaptive and user-based. The objective of this work is the development of "robust" strategies for user guidance in a road network. A guidance strategy is said to be robust, here, if it minimizes the deterioration of its maximum value calculated at the origin, against eventual reconfigurations of the network due to link failures (accidents, works, etc.) The value of a guidance strategy is maximized with respect to the mean travel time and its reliability. Two main parts are distinguished in this work. We start with the static aspect of the guidance, where the traffic dynamics are not taken into account. We propose an extension of an existing guidance approach, to take into account the robustness of the calculated itineraries. In a second step, we combine our new guidance algorithm with a microscopic traffic model in order to have the effect of the traffic dynamics on the robust route calculatio
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