EP2012289B1 - Estimation of traffic in a road network - Google Patents

Estimation of traffic in a road network Download PDF

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Publication number
EP2012289B1
EP2012289B1 EP08104579A EP08104579A EP2012289B1 EP 2012289 B1 EP2012289 B1 EP 2012289B1 EP 08104579 A EP08104579 A EP 08104579A EP 08104579 A EP08104579 A EP 08104579A EP 2012289 B1 EP2012289 B1 EP 2012289B1
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EP
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Prior art keywords
graph
sub
triplet
arcs
traffic
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EP08104579A
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German (de)
French (fr)
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EP2012289A1 (en
Inventor
Léo Liberti
Gilles Barbier
Philippe Baptiste
Daniel Krob
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Ecole Polytechnique
Mediamobile SA
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Ecole Polytechnique
Mediamobile SA
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    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/0104Measuring and analyzing of parameters relative to traffic conditions

Definitions

  • the present invention relates to a partial estimate of traffic in a road network based on partial dynamic traffic information in the road network.
  • the aim of the invention is to assign up-to-date traffic information to sections of the road network not covered by measurements of measuring equipment on the road network, using the available traffic information for the sections of the road network covered by readings.
  • the invention relates to a computer program capable of being implemented in a computing device and intended to estimate the traffic in a road network represented by a graph of arcs corresponding to sections of the road network and bounded by intersection nodes, the graph comprising a sub-graph of arcs corresponding to sections of the road network whose traffic information is measured.
  • the program includes instructions which, when the program is executed in said device, perform the steps of the method according to the invention.
  • a traffic estimation device DET for processing the traffic of a road network RR comprises a central processing unit UC, a road traffic modeler by MTR oriented graph, a propagation probability determination module DPP, a PT traffic propagation module, an IC communication interface and a BD database.
  • the central processing unit UC controls the execution of the method and is connected to or integrates the aforementioned components into the device.
  • the device for estimating traffic DET according to the invention is for example included in a personal computer or a server.
  • the functional blocks of the DET device represented in figure 1 provide functions related to the invention and may correspond to software and / or hardware modules.
  • the DET device is included in or connected to a server periodically broadcasting in real time updated road traffic information to road navigation systems for example on board vehicles or included in portable radiocommunication terminals, such as communicating personal digital assistants. PDA (smartphones), to determine routes.
  • the broadcast traffic information is updated according to traffic information measured by EMT traffic measuring equipment.
  • the DET device is included in or connected to a road navigation system which periodically receives traffic information recorded by measuring equipment.
  • the database BD is linked to the device DET, that is to say it is either integrated in the device DET, or incorporated into a database management server and connected to the device DET by a local or remote link.
  • the database BD includes information necessary for the operation of the device DET of the invention such as map data and traffic network RR characterizing a graph of oriented arcs G1 representing the road network and a second graph of oriented arcs G2 representing a part of the road network RR, the graphs being defined hereinafter.
  • the communication interface IC is capable of communicating with EMT traffic measuring equipment such as vehicle counting stations, speed sensors and traffic surveillance cameras, some of which are temporarily or permanently fixed on and over. above roadways and for some mobiles in specialized vehicles, such as taxis.
  • EMT traffic measuring equipment such as vehicle counting stations, speed sensors and traffic surveillance cameras, some of which are temporarily or permanently fixed on and over. above roadways and for some mobiles in specialized vehicles, such as taxis.
  • the IC interface and the EMT equipment are connected through secure links of a telecommunications network RT which can include the Internet and a professional terrestrial radiocommunication network.
  • the device DET periodically processes traffic information measured and transmitted by the EMT equipment, for example with a period of update and measurement of traffic information from one to five minutes.
  • the RR road network comprises a multitude of road sections.
  • the road network RR is formally represented for its processing in the traffic estimation device DET in the form of a valued oriented graph G1 composed of an A1 set of arcs oriented a1.
  • An arc oriented a1 represents a direction of movement on a respective road section extending between two intersections.
  • a node represents an intersection at the junction of two or more sections. Intersections of roads and streets such as intersections, interchanges and junctions are represented by nodes.
  • Each road section is delimited at its ends by two nodes.
  • a one-way road section of traffic from a first naked node to a second node nv is thus represented by an arc oriented a1 (nu, nv) of predetermined length.
  • a two-way road section between a naked node and a node nv is represented by two opposite oriented arcs a1 (nu, nv) and a1 (nv, naked).
  • each arc a1 (nu, nv) of the graph G1 is associated traffic information which may be variable and which is for example the travel time required for a vehicle to travel the section represented by the arc, or alternatively any other variable depending on the travel time as a vehicle flow or the speed of movement on the section, which is deduced from the ratio of the travel time and the length of the section.
  • the road network RR is defined by two graphs G1 (N1, A1) and G2 (N2, A2) shown in FIGS. Figures 2 and 3 .
  • N1 and A1 denote the set of nodes n1 and the set of arcs a1 of the graph G1.
  • N2 and A2 denote the set of nodes n2 and the set of arcs a2 of the graph G2.
  • an arc designated by the letter "a” not followed by the number 1 or 2 belongs indifferently to one or other of the graphs G1 and G2; at least one of the two nodes designated by the letter "n” followed by a lowercase letter between parentheses succeeding "a1", "a2" belongs to the graph G1, G2 to which the arc belongs.
  • the graph G1 represents the exhaustive road network RR, that is to say all the sections of the road network are represented.
  • all the streets in which vehicles are allowed to circulate at a given instant are represented in the graph G1 and are divided into sections represented by arcs a1 each bounded by two intersections represented respectively by nodes n1.
  • the particular case of an impasse bounded by a blind end and an intersection can also be represented by an arc a1 with two nodes n1.
  • the road network RR is that of a country, all the movable roads are contained in the graph G1.
  • each arc a1 (nu, nv) is associated with one and only one mean travel time ⁇ uv , expressed in the same unit of time for all the arcs, as the second.
  • the travel time ⁇ uv is a mean estimate and is static. It does not evolve according to the actual traffic conditions at a given moment in the corresponding road section.
  • the database BD has prememorated in association with an identifier designating an arc a1, in addition to the average travel time ⁇ uv , other information characterizing the arc, including a capacity C uv , a length and a number of traffic lanes. on the road section corresponding to arc a1 (nu, nv) and its meaning.
  • the graph G2 is a subgraph of the graph G1 representing a sub-network of the road network RR.
  • arc a2 of the subgraph G2 corresponds a respective arc a1 of the graph G1.
  • the arcs a2 contained in subgraph G2 correspond exclusively to road sections respective ones on which traffic information is periodically read by at least one EMT traffic measuring equipment which transmits it to the DET device.
  • arches a2 correspond to urban sections as high traffic axes such as peripheral boulevards, avenues, boulevards and one-way streets in a city, and highways, national roads and other major roads for a country .
  • the subgraph G2 at the figure 2 represents all the sections of the main Parisian traffic arteries.
  • a measured traffic information such as a traffic flow f uv , a travel time ⁇ uv or the average speed of passage of a vehicle having crossed the road section corresponding to the arc a2.
  • the measured traffic information changes over time and is periodically recorded on the corresponding road section by at least one EMT traffic measuring equipment.
  • the measured traffic information is periodically transmitted by the EMT equipment to the traffic estimation device DET and stored in the database BD.
  • the MTR traffic modeler models traffic in the RR road network based on the following definitions and rules.
  • the traffic flow f of an arc a is equal to the number of vehicles traveling on the arc per unit of time.
  • an outgoing flow of a node nv corresponding to an intersection of the road network RR is defined as equal to the sum of the flows on so-called outgoing arc arches aO1, ... aOm, ... aOM having first ends connected to the node nv and corresponding to sections of the road network RR whose vehicles leave the intersection, with 1 ⁇ m ⁇ M.
  • a flow entering the node nv is defined as equal to the sum of the flows on arcs called incoming arcs aI1, ... aIk, ... aIK having second ends connected to the node nv and corresponding to sections of the road network RR whose vehicles enter the intersection corresponding to node nv, with 1 ⁇ k ⁇ K.
  • traffic flow f is maintained at each intersection of the road network.
  • the outgoing flow of a node nv distributed in the outgoing arcs aO1 to aOM is always equal to the flow entering the node nv coming from the incoming arcs aI1 to aIK.
  • the current flow of an arc a1 (nu, nv) is a priori inversely proportional to the mean travel time ⁇ uv of the arc by a vehicle since the number of vehicles crossing the arc per unit of time is high, the faster the vehicles are on the bow.
  • the ratio of the current flow f uv of the arc to the current instant on the cuval capacity of the arc equal to the maximum flux of the arc is proportional to the ratio of the mean static travel time ⁇ uv according to a static estimate on the current travel time ⁇ vw evaluated dynamically by at least one piece of equipment for measuring traffic on the road section corresponding to the arc.
  • the cuvet capacity of the arc can be estimated as equal to the product of arc length by the number of channels in the same arc direction, divided by the average length of a vehicle.
  • the capacitance C uv and the mean static travel time ⁇ uv of each section of the road network RR are prerecorded in association with the characteristics of the arc corresponding to 1 in the database BD.
  • f uv vs uv ⁇ ⁇ uv / ⁇ uv
  • the traffic information available on the subgraph G2 is propagated to the graph G1, each update of the traffic information on the subgraph G2 measured by the equipment. EMT.
  • the invention applies the principle that if the traffic is slowed down on a given section of road, there is strong presumption that it is also on sections of road immediately following the given section of road. Partial traffic information in the subgraph G2 is then supplemented by traffic information calculated for at most the complementary part to the subgraph G2 in the graph G1.
  • the traffic estimation device DET works on the graph G1 based on arcs a2 present in the subgraph G2 for which the device has a measured dynamic information, and calculates a dynamic information estimated on adjacent arcs.
  • the device assigns estimated information to the following arcs, and so on recursively, until satisfying a stop criterion CA defined below.
  • a stop criterion CA defined below.
  • an arc a20 of the subgraph G2 is followed by two arcs a10 and a11 of the graph G1 which themselves are respectively followed by arcs a100 and a101 of the graph G1 and an arc a110 of the graph G1.
  • the arcs of the graph G1 carry static traffic information and the arc a20 of the subgraph G2 carries a measured dynamic traffic information actually.
  • the dynamic information measured on the arc a20 is used by the device DET to estimate dynamic information on arcs a10 and a11 succeeding immediately at the arc a2, that is to say adjacent downstream of the arc a20.
  • the DET device uses the dynamic information measured on the arc a10 to estimate dynamic traffic information on adjacent arcs a100 and a101 downstream, and the dynamic information measured on arc a11 for estimating dynamic traffic information on adjacent arc a110 downstream.
  • Estimate step passes may be repeated for subsequent arcs downstream of the graph G1 based respectively on previously estimated traffic information on arcs a100, a101 and a110, and so on.
  • the estimation of the dynamic traffic information to be assigned to an arc a1 is done by applying a heuristic model based on the preceding rules.
  • This heuristic model uses flow conservation in particular, which concretely means that the quantity of vehicles arriving at a network intersection is entirely distributed on the road sections whose vehicles leave this intersection.
  • the distribution of the flow is determined in the following manner. For a node nv whose outgoing arcs are (nv, nw 1 ), (nv, nw 2 ), ... (nv, nw m ), ... (nv, nw M ) as shown in FIG.
  • the device DET determines the proportion of the flux entering the node nv which is directed towards each outgoing arc (nv, nw m ), with 1 ⁇ m ⁇ M, by calculating for each intersection of the road network such as at node nv, the probability p (aI k , aO m ) for a vehicle to take an outgoing road section corresponding to the arc aO m according to the road section from where the vehicle corresponding to arc aI k .
  • the probability calculation is based on the fastest path selection rule, assigning higher probabilities to the intersections that are part of the most used paths of the vehicles. This confers a set of propagation probabilities that are used for the distribution of the flow through the graph G1 of the road network.
  • the road traffic estimation method is based on the above definitions and rules and comprises a first step E1 relating to a pre-processing executed once and for all on the graph G1 (N1, A1) of the complete road network and a second step E2 relating to a processing of the arcs a1 * of the graph G1 which do not belong to the subgraph G2 (N2, A2) and executed at each update of the measured traffic information of the arcs a2 of the subgraph G2 .
  • the step E1 comprises steps E11 and E12 executed by the DPP propagation probability determination module in order to previously determine propagation probabilities on all the nodes of the graph G1 by applying the rule of the choice of the fastest path.
  • the DPP module counts for each triplet (nu, nv, nw) composed of three nodes successive directly connected by arcs in this order ( figure 6 ), the fastest paths between any two nodes of the graph G1 that pass through this triplet and the database BD stores the number of fastest routes.
  • the fastest paths are counted using the well-known Floyd-Warshall algorithm that calculates the shortest distances between any two nodes (vertices) of a graph.
  • the number of fastest paths between any two nodes of the graph G1 is limited by a predetermined maximum. Since it is prohibitive to carry out the counting step E11 in one go on the whole of the graph G1, the DPP module implements the counting step E11 only in a predetermined neighborhood around the central intersection node n.sub.n of each triplet (nu, nv, nw).
  • the neighborhood is predetermined as being the N closest nodes in travel time of the central node nv considered, including the naked end nodes and nw of the triplet, N being an integer at least equal to 2.
  • the DPP module calculates this neighborhood by implementing the known algorithm of EW Dijkstra which gives the shortest paths between a node (vertex) source of the neighborhood and each node of the neighborhood which is a subgraph of the graph G1.
  • the neighborhood has a predetermined depth expressed as the number of nodes closest to the central node of the triplet.
  • the database BD has for each triplet (nu, nv, nw) of the graph G1 the number of fastest paths that take it from among all the possible paths between any two nodes among the most nodes. close in time of the journey of the central node nv in the neighborhood of the node nv.
  • the number of fastest paths is called "propagation frequency" fp.
  • step E12 the DPP module transforms these propagation frequencies fp into propagation probabilities p, by applying the traffic flow conservation rule for each node n1 of the graph G1: for each node nv, the sum of all the probabilities relating to triplets (nu, nv, nw) for a vehicle coming from a knot and heading towards a node nw to cross node nv is equal to 1 according to relation (2).
  • the propagation probability p uvw associated with the triplet (nu, nv, nw) is equal to the ratio of the propagation frequency fp uvw of the triplet (nu, nv, nw) on the total sum of the propagation frequencies of all the triplets (n , nv, nx) having the node as the starting node and the node nv as the central node.
  • the step E2 comprises estimation steps E21 to E23 executed by the PT traffic propagation module at each update of the measured dynamic traffic information constituting the weights of the arcs a2 of the subgraph G2 so as to propagate these traffic information.
  • the PT module is based on the list of arcs a2 subgraph G2 filled with dynamic traffic information, such as traffic flows expressed in the number of vehicles per unit of time, transmitted to the device DET by the EMT traffic measuring equipment on the sections of the RR road network corresponding to the arcs of sub-graph G2 following a new measurement and stored in a queue of the database BD.
  • dynamic traffic information such as traffic flows expressed in the number of vehicles per unit of time
  • Steps E21 and E22 are then repeated recursively, as indicated in step E23, taking as starting arcs in step E21 of a second iteration the newly updated arcs a1 * (nv, nw) of the list of incoming arcs read in the queue instead of the list of arcs a2 of subgraph G2 populated by dynamic measured traffic information at the beginning of the first iteration described above.
  • the second iteration estimates the traffic information f, ⁇ of another series of arcs of the graph G1 not belonging to the subgraph G2, nor to the set of arcs a1 * newly updated, and each connected to a node for which at least one newly refreshed arc is an incoming arc.
  • the traffic information of the arcs a10 and a11 are estimated based on at least the measured traffic information of the arc a20 during the first iteration
  • the traffic information of the arcs a100 and a101 are estimated according to the less than the estimated traffic information of the arc a10 and the traffic information of the arc a110 is estimated based at least on the estimated traffic information of the arc a10 during the second iteration.
  • Repetition of the iterative steps E21 to E23 in the PT traffic propagation module is stopped when a CA stop criterion is satisfied to ensure that the propagation does not extend to the whole graph G1 of the entire road network RR.
  • the more road sections are separated from the dynamically indicated sections of the road axes corresponding to the arcs of the subgraph G2, the more dynamic information to propagate in the graph G1 arcs not dynamically indicated or by estimation according to the invention loses its relevance and must decrease.
  • the AC stop criterion may be of different natures, depending on the constraints and objectives imposed on the DET traffic estimation device.
  • the stopping criterion is for example one of the following criteria CA1, CA2 and CA3, or a combination of at least two of these criteria.
  • the first criterion CA1 is based on a maximum predetermined execution time of the iterations of the steps E21 to E23, still less than the period of measurement and update of the traffic information transmitted by the EMT equipment and on which the variables f depend.
  • the maximum execution time is thus chosen according to the performance constraints of the DET device such as the propagation time, that is to say as a function of the duration of a pass of the steps E21 to E23 relative to the measurement and update frequency of dynamic traffic information of subgraph G2.
  • the second criterion CA2 is based on an iteration number of the steps E21 to E23 set empirically.
  • the number of iterations characterizes the depth of the neighborhoods used, that is to say the extent of the influence of the dynamic arcs a2 on the adjacent arcs A1 traffic information initially static in the graph G1.
  • the third criterion CA3 is based, for a given arc, on the absolute difference
  • the PT traffic propagation module stops the propagation to this arc since the contribution of the dynamic information f, ⁇ for subsequent adjacent static arcs a1 becomes negligible compared with the static information c, ⁇ .
  • step E23 When the stop criterion CA is satisfied in step E23, the recursive steps E21 to E23 are again reiterated to the transmission period of the updated traffic information measured by the EMT equipment, as indicated in E3 in FIG. figure 7 , for determinations and corrections of routes in the real-time RR road network.
  • the invention described here relates to a method and a device for estimating road network traffic.
  • the steps of the method of the invention are determined by the instructions of a computer program incorporated into a computing device such as the traffic estimation device DET.
  • the program comprises program instructions which, when said program is executed in a processor of the device whose operation is then controlled by the execution of the program, carry out the steps of the method according to the invention.
  • the invention also applies to a computer program, in particular a computer program recorded on or in a computer readable information medium and any data processing device, adapted to implement the computer program. 'invention.
  • This program can use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code such as in a partially compiled form, or in any other form desirable to implement the method according to the invention.
  • the information carrier may be any entity or device capable of storing the program.
  • the medium may comprise storage means or recording medium on which is recorded the computer program according to the invention, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a USB key, or a magnetic recording medium, for example a diskette (floppy disc) or a hard disk.

Abstract

The method involves determining propagation probability for a triplet of consecutive nodes of a graph, where the probability is proportional with respect to propagation frequency of the triplet on total sum of propagation frequencies of the triplet. Traffic information is estimated for arcs of the graph, which are connected to a node of a sub-graph, where the arcs does not belong to the sub-graph and exits the node of the sub graph. The information is estimated according to propagation and information probability of the traffic. Independent claims are also included for the following: (1) a device for estimating traffic in a road network (2) a computer program to be implemented in the device for estimating traffic in a road network.

Description

La présente invention concerne une estimation partielle du trafic dans un réseau routier reposant sur une information de trafic dynamique partielle dans le réseau routier.The present invention relates to a partial estimate of traffic in a road network based on partial dynamic traffic information in the road network.

Avec le développement des systèmes d'informations routiers, on est aujourd'hui capable d'obtenir et de diffuser en temps réel des données concernant la fluidité du trafic sur un réseau routier.
Cette information de trafic, exprimée en vitesses de circulation ou de temps de parcours, est relevée en permanence en temps réel sur le terrain par différents équipements de mesure tels que des capteurs fixes sur les chaussées et des capteurs mobiles dans des véhicules. Cependant, ces équipements de mesure sont peu nombreux comparativement à l'étendue du réseau routier et produisent des relevés d'information de trafic ne couvrant qu'une partie minime du réseau routier.
Concrètement, une information de trafic n'est disponible à un instant donné que sur un sous-ensemble très réduit de tronçons du réseau routier. Sur les très nombreux tronçons restants du réseau routier, non couverts pas les relevés d'information de trafic sur le terrain, on ne dispose au mieux que de valeurs estimées statiques, qui peuvent être complètement séparées et très éloignées de la réalité du trafic à l'instant donné.
Dans cette situation, il est impossible de diffuser une information de trafic variable liée aux tronçons restants, et de considérer l'information statique qu'ils portent comme fiable par exemple dans un système de détermination d'itinéraire routier le plus rapide qui dépendrait de l'état actuel du trafic.
With the development of road information systems, we are now able to obtain and disseminate in real time data concerning the fluidity of traffic on a road network.
This traffic information, expressed in traffic speeds or travel time, is continuously recorded in real time in the field by different measuring equipment such as fixed sensors on the roadways and mobile sensors in vehicles. However, these measurement devices are few in number compared to the extent of the road network and produce traffic information records covering only a small part of the road network.
Specifically, traffic information is only available at a given moment on a very small subset of sections of the road network. Of the very large number of remaining sections of the road network, not covered by field traffic information, only static estimated values are available at best, which can be completely separated and far removed from the reality of traffic on the road. given moment.
In this situation, it is impossible to broadcast variable traffic information related to the remaining sections, and to consider the static information they carry as reliable for example in a system for determining the fastest road route that would depend on the current state of the traffic.

L'invention a pour objectif d'attribuer une information de trafic actualisée à des tronçons du réseau routier non couverts par les relevés des équipements de mesure sur le réseau routier, en utilisant l'information de trafic disponible pour les tronçons du réseau routier couverts par les relevés.The aim of the invention is to assign up-to-date traffic information to sections of the road network not covered by measurements of measuring equipment on the road network, using the available traffic information for the sections of the road network covered by readings.

Pour atteindre cet objectif, un procédé pour estimer le trafic dans un réseau routier représenté par un graphe d'arcs correspondant à des tronçons du réseau routier et bornés par des noeuds d'intersection, le graphe comprenant un sous-graphe d'arcs correspondant à des tronçons du réseau routier dont une information de trafic est mesurée, est caractérisé en ce qu'il comprend:

  • pour chaque triplet de noeuds consécutifs du graphe, une détermination d'une probabilité de propagation proportionnelle au rapport d'une fréquence de propagation du triplet sur la somme totale des fréquences de propagation des triplets ayant les mêmes noeuds de départ et central que le triplet, la fréquence de propagation du triplet étant un nombre de chemins les plus rapides qui empruntent le triplet, et
  • une estimation des informations de trafic pour des arcs du graphe n'appartenant pas au sous-graphe et reliés chacun à un noeud du sous-graphe, l'information de trafic d'un arc n'appartenant pas au sous-graphe et sortant d'un noeud du sous-graphe étant estimée en fonction de probabilité de propagation et d'information de trafic mesurée relatives à l'ensemble d'arc du sous-graphe entrant dans ledit noeud.
L'estimation des informations de trafic pour des arcs du graphe n'appartenant pas au sous-graphe reflète une propagation des informations de trafic dynamique, relevées physiquement sur des tronçons du réseau routier correspondant aux arcs du sous-graphe, vers des arcs correspondant à des tronçons pour lesquels aucune information de trafic n'est mesurée. Ainsi de proche en proche, par au moins une itération de l'estimation en prenant les arcs dont les informations de trafic viennent d'être estimées et donc actualisées comme arcs du sous-graphe, et plus généralement par plusieurs itérations successives de l'estimation, les informations de trafic d'arcs dans le voisinage des arcs du sous-graphe sont estimées. L'invention permet de proposer en temps réel des itinéraires dans le réseau routier en fonction d'informations de trafic estimées reflétant le trafic routier réel sur des tronçons pour lesquels le trafic n'est pas mesuré.
L'information de trafic disponible sur le sous-graphe dont les informations de trafic sont mesurées est propagée progressivement itération par itération dans le graphe, par pas d'arc, pour chaque actualisation des informations de trafic mesurées. Ceci résulte de l'influence de la vitesse moyenne des véhicules dans un tronçon de route donné sur la vitesse moyenne des véhicules sur des tronçons de route adjacents au tronçon de route donné suivant son sens de circulation.
Des itérations de l'estimation peuvent être arrêtées lorsqu'un temps prédéterminé d'exécution des itérations inférieur à une période de mesure des informations de trafic est atteint, et/ou le nombre d'itérations de l'estimation peut être limité à la profondeur de voisinages des noeuds du sous-graphe, et/ou des itérations de l'estimation peuvent être arrêtées pour un arc donné lorsque l'information de trafic estimée avoisine une constante prédéterminée à un paramètre de tolérance près.
Préalablement à l'estimation des informations de trafic, la probabilité de propagation d'un triplet de trois noeuds du graphe est déterminée définitivement et peut comprendre un dénombrement des chemins les plus rapides qui empruntent le triplet parmi tous les chemins possibles entre deux noeuds quelconques du graphe. Afin de limiter le temps de détermination des probabilités de propagation et l'intérêt de celles-ci à des arcs du graphe voisins du sous-graphe, le dénombrement des chemins les plus rapides qui empruntent le triplet peut être mis en oeuvre dans un voisinage de profondeur prédéterminée exprimée en nombre de noeuds les plus proches du noeud central du triplet.
Selon une réalisation, l'information de trafic mesurée d'un arc du sous-graphe dépend du flux de trafic dans un tronçon correspondant du réseau routier, et l'information de trafic d'un arc n'appartenant pas au sous-graphe et sortant d'un noeud du sous-graphe est proportionnelle au produit de la probabilité de propagation et de l'information de trafic relatives à au moins un arc du sous-graphe entrant dans ledit noeud.To achieve this objective, a method for estimating the traffic in a road network represented by a graph of arcs corresponding to sections of the road network and bounded by intersection nodes, the graph comprising a sub-graph of arcs corresponding to sections of the road network for which traffic information is measured, is characterized in that it comprises:
  • for each triplet of consecutive nodes of the graph, a determination of a propagation probability proportional to the ratio of a propagation frequency of the triplet to the total sum of the propagation frequencies of the triplets having the same starting and central nodes as the triplet, the frequency of propagation of the triplet being a number of the fastest paths that take the triplet, and
  • an estimation of the traffic information for arcs of the graph not belonging to the sub-graph and each connected to a node of the sub-graph, the traffic information of an arc which does not belong to the sub-graph and outgoing a node of the sub-graph being estimated as a function of propagation probability and measured traffic information relating to the arc set of the sub-graph entering said node.
The estimation of the traffic information for arcs of the graph not belonging to the sub-graph reflects a propagation of the dynamic traffic information, physically recorded on sections of the road network corresponding to the arcs of the sub-graph, to arcs corresponding to sections for which no traffic information is measured. Thus, step by step, by at least one iteration of the estimate by taking the arcs whose traffic information has just been estimated and thus updated as arcs of the subgraph, and more generally by several successive iterations of the estimate. , the traffic information of arcs in the vicinity of the arcs of the sub-graph are estimated. The invention makes it possible to propose in real time routes in the road network according to estimated traffic information reflecting real road traffic on sections for which the traffic is not measured.
The traffic information available on the sub-graph whose traffic information is measured is progressively propagated iteratively by iteration in the graph, by arc step, for each update of the measured traffic information. This results from the influence of the average speed of the vehicles in a given section of road on the average speed of the vehicles on sections of road adjacent to the given section of road according to its direction of circulation.
Iterations of the estimate can be stopped when a predetermined time of execution of the iterations less than a measurement period of the traffic information is reached, and / or the number iterations of the estimate may be limited to the neighborhood depth of the nodes of the subgraph, and / or iterations of the estimate may be stopped for a given arc when the estimated traffic information approximates a predetermined constant to a tolerance setting close.
Prior to estimating the traffic information, the probability of propagation of a triplet of three nodes of the graph is definitively determined and may include a count of the fastest paths that take the triplet among all the possible paths between any two nodes of the graph. graph. In order to limit the time of determination of the probabilities of propagation and the interest of these to arcs of the graph adjacent to the subgraph, the enumeration of the fastest paths that take the triple can be implemented in a neighborhood of predetermined depth expressed in the number of nodes closest to the central node of the triplet.
According to one embodiment, the measured traffic information of an arc of the sub-graph depends on the traffic flow in a corresponding section of the road network, and the traffic information of an arc that does not belong to the sub-graph and leaving a node of the sub-graph is proportional to the product of the propagation probability and the traffic information relating to at least one arc of the sub-graph entering said node.

L'invention a aussi pour objet un dispositif pour estimer le trafic dans un réseau routier représenté par un graphe d'arcs correspondant à des tronçons du réseau routier et bornés par des noeuds d'intersection, le graphe comprenant un sous-graphe d'arcs correspondant à des tronçons du réseau routier dont une information de trafic est mesurée. Le dispositif est caractérisé en ce qu'il comprend:

  • pour chaque triplet de noeuds consécutifs du graphe, un moyen pour déterminer une probabilité de propagation proportionnelle au rapport d'une fréquence de propagation du triplet sur la somme totale des fréquences de propagation des triplets ayant les mêmes noeuds de départ et central que le triplet, la fréquence de propagation du triplet étant un nombre de chemins les plus rapides qui empruntent le triplet, et
  • un moyen pour estimer des informations de trafic pour des arcs du graphe n'appartenant pas au sous-graphe et reliés chacun à un noeud du sous-graphe, l'information de trafic d'un arc n'appartenant pas au sous-graphe et sortant d'un noeud du sous-graphe étant estimée en fonction de probabilité de propagation et d'information de trafic mesurée relatives à l'ensemble d'arc du sous-graphe entrant dans ledit noeud.
The invention also relates to a device for estimating the traffic in a road network represented by a graph of arcs corresponding to sections of the road network and bounded by intersection nodes, the graph comprising a sub-graph. arcs corresponding to sections of the road network whose traffic information is measured. The device is characterized in that it comprises:
  • for each triplet of consecutive nodes of the graph, a means for determining a propagation probability proportional to the ratio of a propagation frequency of the triplet to the total sum of the propagation frequencies of the triplets having the same starting and central nodes as the triplet, the frequency of propagation of the triplet being a number of the fastest paths that take the triplet, and
  • means for estimating traffic information for arcs of the graph not belonging to the sub-graph and each connected to a node of the sub-graph, the traffic information of an arc not belonging to the sub-graph and out of a node of the sub-graph being estimated as a function of propagation probability and measured traffic information relating to the arc set of the sub-graph entering said node.

Enfin, l'invention se rapporte à un programme d'ordinateur apte à être mis en oeuvre dans un dispositif informatique et destiné à estimer le trafic dans un réseau routier représenté par un graphe d'arcs correspondant à des tronçons du réseau routier et bornés par des noeuds d'intersection, le graphe comprenant un sous-graphe d'arcs correspondant à des tronçons du réseau routier dont une information de trafic est mesurée. Le programme comporte des instructions qui, lorsque le programme est exécuté dans ledit dispositif, réalisent les étapes du procédé selon l'invention.Finally, the invention relates to a computer program capable of being implemented in a computing device and intended to estimate the traffic in a road network represented by a graph of arcs corresponding to sections of the road network and bounded by intersection nodes, the graph comprising a sub-graph of arcs corresponding to sections of the road network whose traffic information is measured. The program includes instructions which, when the program is executed in said device, perform the steps of the method according to the invention.

D'autres caractéristiques et avantages de la présente invention apparaîtront plus clairement à la lecture de la description suivante de plusieurs réalisations de l'invention données à titre d'exemples non limitatifs, en référence aux dessins annexés correspondants dans lesquels :

  • la figure 1 est un bloc-diagramme schématique d'un dispositif d'estimation de trafic routier selon l'invention ;
  • la figure 2 est un premier graphe d'arcs respectivement associés aux tronçons d'un réseau routier ;
  • la figure 3 est un deuxième graphe comprenant des arcs renseignés dynamiquement et associés à des tronçons du réseau routier munis d'équipements de mesure de trafic ;
  • la figure 4 est un schéma d'arcs entrants et d'arcs sortants autour d'un noeud du premier graphe ;
  • la figure 5 est un schéma d'arcs du premier graphe à renseigner par propagation d'information de trafic depuis un arc renseigné dynamiquement du deuxième graphe selon l'invention ; et
  • la figure 6 est un algorithme d'un procédé d'estimation de trafic routier selon l'invention.
Other characteristics and advantages of the present invention will emerge more clearly on reading the following description of several embodiments of the invention given by way of non-limiting examples, with reference to the corresponding appended drawings in which:
  • the figure 1 is a schematic block diagram of a road traffic estimation device according to the invention;
  • the figure 2 is a first graph of arcs respectively associated with the sections of a road network;
  • the figure 3 is a second graph comprising dynamically populated arcs associated with sections of the road network equipped with traffic measurement equipment;
  • the figure 4 is a schema of incoming arcs and outgoing arcs around a node of the first graph;
  • the figure 5 is a diagram of arcs of the first graph to be informed by propagation of traffic information from a dynamically indicated arc of the second graph according to the invention; and
  • the figure 6 is an algorithm of a road traffic estimation method according to the invention.

Comme montré à la figure 1, un dispositif d'estimation de trafic routier DET pour traiter le trafic d'un réseau routier RR selon l'invention comprend une unité centrale de traitement UC, un modélisateur de trafic routier par graphe orienté MTR, un module de détermination de probabilité de propagation DPP, un module de propagation de trafic PT, une interface de communication IC et une base de données BD.As shown in figure 1 , a traffic estimation device DET for processing the traffic of a road network RR according to the invention comprises a central processing unit UC, a road traffic modeler by MTR oriented graph, a propagation probability determination module DPP, a PT traffic propagation module, an IC communication interface and a BD database.

L'unité centrale de traitement UC, telle qu'un processeur, contrôle l'exécution du procédé et est reliée aux ou intègrent les composants précités dans le dispositif.
Le dispositif d'estimation de trafic DET selon l'invention est par exemple inclus dans un ordinateur personnel ou un serveur. Les blocs fonctionnels du dispositif DET représentés à figure 1 assurent des fonctions ayant un lien avec l'invention et peuvent correspondre à des modules logiciels et/ou matériels.
Selon la réalisation illustrée à la figure 1, le dispositif DET est inclus dans ou relié à un serveur diffusant périodiquement en temps réel des informations de trafic routier actualisées vers des systèmes de navigation routière par exemple à bord de véhicules ou inclus dans des terminaux de radiocommunication portables, comme des assistants numériques personnels communicants PDA (smartphones), pour déterminer des itinéraires. Les informations de trafic routier diffusées sont actualisées en fonction d'informations de trafic mesurées par des équipements de mesure de trafic EMT.
Selon une autre réalisation, le dispositif DET est inclus dans ou relié à un système de navigation routière qui reçoit périodiquement des informations de trafic relevées par des équipements de mesure.
La base de données BD est liée au dispositif DET, c'est-à-dire elle est soit intégrée dans le dispositif DET, soit incorporée dans un serveur de gestion de base de données et reliée au dispositif DET par une liaison locale ou distante. La base de données BD comprend notamment des informations nécessaires au fonctionnement du dispositif DET de l'invention telles que des données cartographiques et de trafic du réseau routier RR caractérisant un graphe d'arcs orientés G1 représentant le réseau routier et un deuxième graphe d'arcs orientés G2 représentant une partie du réseau routier RR, les graphes étant définis ci-après.
L'interface de communication IC est apte à communiquer avec des équipements de mesure de trafic EMT tels que des postes de comptage de véhicule, capteurs de vitesse et caméras de surveillance de trafic, qui sont pour certains fixés temporairement ou en permanence sur et au-dessus des chaussées et pour certains mobiles dans des véhicules spécialisés, tels que des taxis. Par exemple, l'interface IC et les équipements EMT sont connectés à travers des liaisons sécurisées d'un réseau de télécommunications RT pouvant comprendre l'internet et un réseau de radiocommunication terrestre professionnel. Le dispositif DET traite périodiquement des informations de trafic mesurées et transmises par les équipements EMT, par exemple avec une période d'actualisation et de mesure des informations de trafic d'une à cinq minutes environ.
The central processing unit UC, such as a processor, controls the execution of the method and is connected to or integrates the aforementioned components into the device.
The device for estimating traffic DET according to the invention is for example included in a personal computer or a server. The functional blocks of the DET device represented in figure 1 provide functions related to the invention and may correspond to software and / or hardware modules.
According to the realization illustrated in figure 1 , the DET device is included in or connected to a server periodically broadcasting in real time updated road traffic information to road navigation systems for example on board vehicles or included in portable radiocommunication terminals, such as communicating personal digital assistants. PDA (smartphones), to determine routes. The broadcast traffic information is updated according to traffic information measured by EMT traffic measuring equipment.
In another embodiment, the DET device is included in or connected to a road navigation system which periodically receives traffic information recorded by measuring equipment.
The database BD is linked to the device DET, that is to say it is either integrated in the device DET, or incorporated into a database management server and connected to the device DET by a local or remote link. The database BD includes information necessary for the operation of the device DET of the invention such as map data and traffic network RR characterizing a graph of oriented arcs G1 representing the road network and a second graph of oriented arcs G2 representing a part of the road network RR, the graphs being defined hereinafter.
The communication interface IC is capable of communicating with EMT traffic measuring equipment such as vehicle counting stations, speed sensors and traffic surveillance cameras, some of which are temporarily or permanently fixed on and over. above roadways and for some mobiles in specialized vehicles, such as taxis. For example, the IC interface and the EMT equipment are connected through secure links of a telecommunications network RT which can include the Internet and a professional terrestrial radiocommunication network. The device DET periodically processes traffic information measured and transmitted by the EMT equipment, for example with a period of update and measurement of traffic information from one to five minutes.

Comme montré aux figures 2 et 3, le réseau routier RR comprend une multitude de tronçons routiers. Le réseau routier RR est représenté formellement pour son traitement dans le dispositif d'estimation de trafic routier DET sous la forme d'un graphe orienté valué G1 composé d'un ensemble A1 d'arcs orientés a1. Un arc orienté a1 représente un sens de circulation sur un tronçon routier respectif s'étendant entre deux intersections.
Un noeud représente une intersection à la jonction de deux ou plusieurs tronçons. Les intersections de routes et de rues telles que carrefours, échangeurs et bifurcations sont représentées par des noeuds. Chaque tronçon routier est délimité à ses extrémités par deux noeuds. Un tronçon routier à sens unique de circulation depuis un premier noeud nu vers un deuxième noeud nv est ainsi représenté par un arc orienté a1 (nu, nv) de longueur prédéterminée. Un tronçon routier à double sens de circulation entre un noeud nu et un noeud nv est représenté par deux arcs orientés opposés a1(nu, nv) et a1(nv, nu).
A chaque arc a1 (nu, nv) du graphe G1 est associée une information de trafic qui peut être variable et qui est par exemple le temps de parcours nécessaire à un véhicule pour parcourir le tronçon représenté par l'arc, ou en variante toute autre variable dépendant du temps de parcours comme un flux de véhicule ou la vitesse de circulation sur le tronçon, laquelle est déduite du rapport du temps de parcours et de la longueur du tronçon.
As shown in Figures 2 and 3 , the RR road network comprises a multitude of road sections. The road network RR is formally represented for its processing in the traffic estimation device DET in the form of a valued oriented graph G1 composed of an A1 set of arcs oriented a1. An arc oriented a1 represents a direction of movement on a respective road section extending between two intersections.
A node represents an intersection at the junction of two or more sections. Intersections of roads and streets such as intersections, interchanges and junctions are represented by nodes. Each road section is delimited at its ends by two nodes. A one-way road section of traffic from a first naked node to a second node nv is thus represented by an arc oriented a1 (nu, nv) of predetermined length. A two-way road section between a naked node and a node nv is represented by two opposite oriented arcs a1 (nu, nv) and a1 (nv, naked).
At each arc a1 (nu, nv) of the graph G1 is associated traffic information which may be variable and which is for example the travel time required for a vehicle to travel the section represented by the arc, or alternatively any other variable depending on the travel time as a vehicle flow or the speed of movement on the section, which is deduced from the ratio of the travel time and the length of the section.

Le réseau routier RR est défini par deux graphes G1(N1, A1) et G2(N2, A2) montrés aux figures 2 et 3. N1 et A1 désignent l'ensemble des noeuds n1 et l'ensemble des arcs a1 du graphe G1. N2 et A2 désignent l'ensemble des noeuds n2 et l'ensemble des arcs a2 du graphe G2. Dans la suite de la description, un arc désigné par la lettre "a" non suivie du chiffre 1 ou 2 appartient indifféremment à l'un ou l'autre des graphes G1 et G2 ; au moins l'un des deux noeuds désigné par la lettre "n" suivie d'une lettre minuscule entre des parenthèses succédant à "a1", "a2" appartient au graphe G1, G2 auquel l'arc appartient.The road network RR is defined by two graphs G1 (N1, A1) and G2 (N2, A2) shown in FIGS. Figures 2 and 3 . N1 and A1 denote the set of nodes n1 and the set of arcs a1 of the graph G1. N2 and A2 denote the set of nodes n2 and the set of arcs a2 of the graph G2. In the remainder of the description, an arc designated by the letter "a" not followed by the number 1 or 2 belongs indifferently to one or other of the graphs G1 and G2; at least one of the two nodes designated by the letter "n" followed by a lowercase letter between parentheses succeeding "a1", "a2" belongs to the graph G1, G2 to which the arc belongs.

Le graphe G1 représente le réseau routier exhaustif RR, c'est-à-dire tous les tronçons du réseau routier considéré y sont représentés. Selon un exemple montré à la figure 2 relatif à une ville comme Paris et sa proximité immédiate, toutes les rues dans lesquelles des véhicules sont autorisés à circuler à un instant donné sont représentées dans le graphe G1 et sont divisées en des tronçons représentés par des arcs a1 bornés chacun par deux intersections représentées respectivement par des noeuds n1. Le cas particulier d'une impasse bornée par une extrémité borgne et une intersection peut être également représenté par un arc a1 avec deux noeuds n1. Selon un autre exemple, si le réseau routier RR est celui d'un pays, toutes les routes circulables sont contenues dans le graphe G1.
À chaque arc a1(nu, nv) est associé un et un seul temps de parcours moyen σuv, exprimé dans la même unité de temps pour tous les arcs, comme la seconde. Le temps de parcours σuv est une estimation moyenne et est statique. Il n'évolue pas en fonction des conditions réelles du trafic à un instant donné dans le tronçon routier correspondant.
La base de données BD a prémémorisé en association à un identificateur désignant un arc a1, outre le temps de parcours moyen σuv, d'autres informations caractérisant l'arc, notamment une capacité Cuv, une longueur et un nombre de voies de circulation sur le tronçon routier correspondant à l'arc a1(nu, nv) et à son sens.
The graph G1 represents the exhaustive road network RR, that is to say all the sections of the road network are represented. According to an example shown in figure 2 relating to a city like Paris and its immediate proximity, all the streets in which vehicles are allowed to circulate at a given instant are represented in the graph G1 and are divided into sections represented by arcs a1 each bounded by two intersections represented respectively by nodes n1. The particular case of an impasse bounded by a blind end and an intersection can also be represented by an arc a1 with two nodes n1. According to another example, if the road network RR is that of a country, all the movable roads are contained in the graph G1.
At each arc a1 (nu, nv) is associated with one and only one mean travel time σ uv , expressed in the same unit of time for all the arcs, as the second. The travel time σ uv is a mean estimate and is static. It does not evolve according to the actual traffic conditions at a given moment in the corresponding road section.
The database BD has prememorated in association with an identifier designating an arc a1, in addition to the average travel time σ uv , other information characterizing the arc, including a capacity C uv , a length and a number of traffic lanes. on the road section corresponding to arc a1 (nu, nv) and its meaning.

Le graphe G2 est un sous-graphe du graphe G1 représentant un sous-réseau du réseau routier RR. A tout arc a2 du sous-graphe G2 correspond un arc respectif a1 du graphe G1.
Les arcs a2 contenus dans le sous-graphe G2 correspondent exclusivement à des tronçons routiers respectifs sur chacun desquels une information de trafic est relevée périodiquement par au moins un équipement de mesure de trafic EMT qui la transmet au dispositif DET. Le plus souvent, les arcs a2 correspondent aux tronçons urbains comme des axes à trafic élevé tels que des boulevards périphériques, avenues, boulevards et rues à sens unique dans une ville, et des autoroutes, routes nationales et autres grands axes de circulation pour un pays. Comparativement à la figure 1, le sous-graphe G2 à la figure 2 représente l'ensemble des tronçons des grandes artères de circulation parisiennes.
À chaque arc a2(nu, nv) est associée une information de trafic mesurée, telle qu'un flux de trafic fuv, un temps de parcours τuv ou la vitesse de passage moyenne d'un véhicule ayant traversé le tronçon routier correspondant à l'arc a2. L'information de trafic mesurée évolue au cours du temps et est relevée périodiquement sur le tronçon routier correspondant par au moins un équipement de mesure de trafic EMT. Les informations de trafic mesurées sont périodiquement transmises par les équipements EMT au dispositif d'estimation de trafic routier DET et mémorisées dans la base de données BD.
The graph G2 is a subgraph of the graph G1 representing a sub-network of the road network RR. At any arc a2 of the subgraph G2 corresponds a respective arc a1 of the graph G1.
The arcs a2 contained in subgraph G2 correspond exclusively to road sections respective ones on which traffic information is periodically read by at least one EMT traffic measuring equipment which transmits it to the DET device. Most often, arches a2 correspond to urban sections as high traffic axes such as peripheral boulevards, avenues, boulevards and one-way streets in a city, and highways, national roads and other major roads for a country . Compared to the figure 1 , the subgraph G2 at the figure 2 represents all the sections of the main Parisian traffic arteries.
At each arc a2 (nu, nv) is associated a measured traffic information, such as a traffic flow f uv , a travel time τ uv or the average speed of passage of a vehicle having crossed the road section corresponding to the arc a2. The measured traffic information changes over time and is periodically recorded on the corresponding road section by at least one EMT traffic measuring equipment. The measured traffic information is periodically transmitted by the EMT equipment to the traffic estimation device DET and stored in the database BD.

Le modélisateur de trafic routier MTR modélise le trafic dans le réseau routier RR sur la base des quelques définitions et règles suivantes.
Le flux de trafic f d'un arc a, c'est-à-dire en réalité du tronçon routier correspondant, est égal au nombre de véhicules circulant sur l'arc par unité de temps.
En référence à la figure 4, un flux sortant d'un noeud nv correspondant à une intersection du réseau routier RR est défini comme égal à la somme des flux sur des arcs dits arcs sortants aO1, ... aOm, ... aOM ayant des premières extrémités reliées au noeud nv et correspondant à des tronçons du réseau routier RR dont les véhicules sortent de l'intersection, avec 1 ≤ m ≤ M. Un flux entrant dans le noeud nv est défini comme égal à la somme des flux sur des arcs dits arcs entrants aI1,... aIk,... aIK ayant des deuxièmes extrémités reliées au noeud nv et correspondant à des tronçons du réseau routier RR dont les véhicules entrent dans l'intersection correspondant au noeud nv, avec 1 ≤ k ≤ K.
D'après les caractéristiques d'un réseau routier complet, le flux de trafic f est conservé à chaque intersection du réseau routier. En d'autres termes comme montré à la figure 4, le flux sortant d'un noeud nv réparti dans les arcs sortants aO1 à aOM est toujours égal au flux entrant dans le noeud nv provenant des arcs entrants aI1 à aIK. Cette conservation des flux est exprimée par l'égalité suivante: k = 1 k = K f aI k = m = 1 m = M f aO m .

Figure imgb0001
The MTR traffic modeler models traffic in the RR road network based on the following definitions and rules.
The traffic flow f of an arc a, that is to say in reality of the corresponding road section, is equal to the number of vehicles traveling on the arc per unit of time.
With reference to the figure 4 , an outgoing flow of a node nv corresponding to an intersection of the road network RR is defined as equal to the sum of the flows on so-called outgoing arc arches aO1, ... aOm, ... aOM having first ends connected to the node nv and corresponding to sections of the road network RR whose vehicles leave the intersection, with 1 ≤ m ≤ M. A flow entering the node nv is defined as equal to the sum of the flows on arcs called incoming arcs aI1, ... aIk, ... aIK having second ends connected to the node nv and corresponding to sections of the road network RR whose vehicles enter the intersection corresponding to node nv, with 1 ≤ k ≤ K.
Based on the characteristics of a complete road network, traffic flow f is maintained at each intersection of the road network. In other words as shown in figure 4 the outgoing flow of a node nv distributed in the outgoing arcs aO1 to aOM is always equal to the flow entering the node nv coming from the incoming arcs aI1 to aIK. This flow conservation is expressed by the following equality: Σ k = 1 k = K f have k = Σ m = 1 m = M f aO m .
Figure imgb0001

Dans le réseau routier réel, la conservation des flux n'est vérifiée qu'approximativement. En effet dans un tronçon routier ou à une intersection, des véhicules peuvent s'arrêter notamment pour stationner et donc quitter le flux de circulation, ou commencer à circuler et donc entrer dans le flux de circulation. Sachant que le nombre de véhicules s'arrêtant et/ou commençant à circuler est négligeable comparativement au trafic qui traverse le tronçon routier ou l'intersection, la conservation des flux est une approximation suffisante du comportement du réseau routier observé à un instant courant.
A un instant courant de trafic sur un arc, le flux courant d'un arc a1(nu, nv) est a priori inversement proportionnel au temps de parcours moyen τuv de l'arc par un véhicule puisque plus le nombre de véhicules traversant l'arc par unité de temps est élevé, plus les véhicules sont rapides sur l'arc. Le rapport du flux courant fuv de l'arc à l'instant courant sur la capacité cuv de l'arc égale au flux maximum de l'arc est proportionnel au rapport du temps de parcours statique moyen σuv selon une estimation statique sur le temps de parcours courant τvw évalué dynamiquement par au moins un équipement de mesure de trafic EMT sur le tronçon routier correspondant à l'arc. La capacité cuv de l'arc peut être estimée comme égale au produit de la longueur de l'arc par le nombre de voies d'un même sens de l'arc, divisé par la longueur moyenne d'un véhicule. La capacité Cuv et le temps de parcours statique moyen σuv de chaque tronçon du réseau routier RR sont préenregistrés en association avec les caractéristiques de l'arc correspondant a1 dans la base de données BD. Ainsi pour chaque arc est établi un flux de trafic respectif : f uv = c uv σ uv / τ uv

Figure imgb0002
In the real road network, flow conservation is checked only approximately. Indeed, in a road section or at an intersection, vehicles may stop, in particular to park and therefore leave the flow of traffic, or begin to circulate and thus enter the flow of traffic. Knowing that the number of vehicles stopping and / or starting to circulate is negligible compared to the traffic that crosses the road section or the intersection, the conservation of flows is a sufficient approximation of the road network behavior observed at a current time.
At a current moment of traffic on an arc, the current flow of an arc a1 (nu, nv) is a priori inversely proportional to the mean travel time τ uv of the arc by a vehicle since the number of vehicles crossing the arc per unit of time is high, the faster the vehicles are on the bow. The ratio of the current flow f uv of the arc to the current instant on the cuval capacity of the arc equal to the maximum flux of the arc is proportional to the ratio of the mean static travel time σ uv according to a static estimate on the current travel time τ vw evaluated dynamically by at least one piece of equipment for measuring traffic on the road section corresponding to the arc. The cuvet capacity of the arc can be estimated as equal to the product of arc length by the number of channels in the same arc direction, divided by the average length of a vehicle. The capacitance C uv and the mean static travel time σ uv of each section of the road network RR are prerecorded in association with the characteristics of the arc corresponding to 1 in the database BD. Thus for each arc is established a respective traffic flow: f uv = vs uv σ uv / τ uv
Figure imgb0002

Enfin on suppose que les véhicules circulant d'un point P1 à un point P2 choisissent naturellement le chemin le plus rapide entre ces deux points.Finally, it is assumed that vehicles traveling from a point P1 to a point P2 naturally choose the fastest path between these two points.

Selon le procédé d'estimation de trafic routier de l'invention, l'information de trafic disponible sur le sous-graphe G2 est propagée vers le graphe G1, à chaque actualisation des informations de trafic sur le sous-graphe G2 mesurées par les équipements EMT. L'invention applique le principe selon lequel si le trafic est ralenti sur un tronçon de route donné, il y a de fortes présomptions pour qu'il le soit aussi sur des tronçons de route succédant immédiatement au tronçon de route donné.
Une information de trafic partielle dans le sous-graphe G2 est alors complétée par une information de trafic calculée pour au plus la partie complémentaire au sous-graphe G2 dans le graphe G1. Le dispositif d'estimation de trafic routier DET travaille sur le graphe G1 en se basant sur des arcs a2 présents dans le sous-graphe G2 pour lesquels le dispositif dispose d'une information dynamique mesurée, et calcule une information dynamique estimée sur des arcs adjacents qui sont chacun situés en aval d'un arc a2 vers un point de destination et qui n'appartiennent pas au sous-graphe G2 et appartiennent au graphe G1. En partant de ces arcs du graphe G1 nouvellement actualisés, le dispositif attribue ensuite une information estimée aux arcs suivants, et ainsi de suite récursivement, jusqu'à satisfaire un critère d'arrêt CA défini plus loin.
A titre d'exemple montré à la figure 5, un arc a20 du sous-graphe G2 est suivi de deux arcs a10 et a11 du graphe G1 qui eux-mêmes sont respectivement suivis par des arcs a100 et a101 du graphe G1 et un arc a110 du graphe G1. Initialement les arcs du graphe G1 portent des informations de trafic statiques et l'arc a20 du sous-graphe G2 porte une information de trafic dynamique mesurée réellement.
A une première passe récursive d'étapes d'estimation selon l'invention, l'information dynamique mesurée sur l'arc a20 est utilisée par le dispositif DET pour estimer des informations dynamiques sur les arcs a10 et a11 succédant immédiatement à l'arc a2, c'est-à-dire adjacents en aval de l'arc a20.
Puis à une deuxième passe d'étapes d'estimation, le dispositif DET utilise l'information dynamique mesurée sur l'arc a10 pour estimer des informations de trafic dynamiques sur les arcs a100 et a101 adjacents en aval, et l'information dynamique mesurée sur l'arc a11 pour estimer une information de trafic dynamique sur l'arc a110 adjacent en aval.
Des passes d'étapes d'estimation peuvent être répétées pour des arcs suivants en aval du graphe G1 sur la base respectivement des informations de trafic antérieurement estimées sur les arcs a100, a101 et a110, et ainsi de suite.
According to the road traffic estimation method of the invention, the traffic information available on the subgraph G2 is propagated to the graph G1, each update of the traffic information on the subgraph G2 measured by the equipment. EMT. The invention applies the principle that if the traffic is slowed down on a given section of road, there is strong presumption that it is also on sections of road immediately following the given section of road.
Partial traffic information in the subgraph G2 is then supplemented by traffic information calculated for at most the complementary part to the subgraph G2 in the graph G1. The traffic estimation device DET works on the graph G1 based on arcs a2 present in the subgraph G2 for which the device has a measured dynamic information, and calculates a dynamic information estimated on adjacent arcs. which are each located downstream of an arc a2 towards a destination point and which do not belong to the subgraph G2 and belong to the graph G1. Starting from these newly updated arcs of the graph G1, the device then assigns estimated information to the following arcs, and so on recursively, until satisfying a stop criterion CA defined below.
As an example shown in figure 5 an arc a20 of the subgraph G2 is followed by two arcs a10 and a11 of the graph G1 which themselves are respectively followed by arcs a100 and a101 of the graph G1 and an arc a110 of the graph G1. Initially, the arcs of the graph G1 carry static traffic information and the arc a20 of the subgraph G2 carries a measured dynamic traffic information actually.
At a first recursive pass of estimation steps according to the invention, the dynamic information measured on the arc a20 is used by the device DET to estimate dynamic information on arcs a10 and a11 succeeding immediately at the arc a2, that is to say adjacent downstream of the arc a20.
Then at a second pass of estimation steps, the DET device uses the dynamic information measured on the arc a10 to estimate dynamic traffic information on adjacent arcs a100 and a101 downstream, and the dynamic information measured on arc a11 for estimating dynamic traffic information on adjacent arc a110 downstream.
Estimate step passes may be repeated for subsequent arcs downstream of the graph G1 based respectively on previously estimated traffic information on arcs a100, a101 and a110, and so on.

L'estimation de l'information de trafic dynamique à affecter à un arc a1 (nu, nv) se fait en appliquant un modèle heuristique basée sur les règles précédentes.
Ce modèle heuristique recourt en particulier à la conservation des flux qui signifie concrètement que la quantité de véhicules parvenant à une intersection du réseau est intégralement distribuée sur les tronçons routiers dont les véhicules quittent cette intersection. Pour pouvoir propager les temps de parcours dynamiques estimés de proche en proche dans le graphe G1, la distribution du flux est déterminée de la manière suivante. Pour un noeud nv dont les arcs sortants sont (nv, nw1), (nv, nw2) ,... (nv, nwm),... (nv, nwM) comme montré à la figure 6, le dispositif DET détermine la proportion du flux entrant dans le noeud nv qui est dirigée vers chaque arc sortant (nv, nwm), avec 1 ≤ m ≤ M, en calculant pour chaque intersection du réseau routier telle qu'au noeud nv, la probabilité p (aIk, aOm) pour un véhicule d'emprunter un tronçon routier sortant correspondant à l'arc aOm en fonction du tronçon routier de provenance du véhicule correspondant à l'arc aIk. De telles probabilités à chaque noeud nv sont liées par la relation suivante : m = 1 m = M p aI k aO m = 1

Figure imgb0003
The estimation of the dynamic traffic information to be assigned to an arc a1 (nu, nv) is done by applying a heuristic model based on the preceding rules.
This heuristic model uses flow conservation in particular, which concretely means that the quantity of vehicles arriving at a network intersection is entirely distributed on the road sections whose vehicles leave this intersection. To be able to propagate the estimated dynamic travel times gradually in the graph G1, the distribution of the flow is determined in the following manner. For a node nv whose outgoing arcs are (nv, nw 1 ), (nv, nw 2 ), ... (nv, nw m ), ... (nv, nw M ) as shown in FIG. figure 6 the device DET determines the proportion of the flux entering the node nv which is directed towards each outgoing arc (nv, nw m ), with 1 ≤ m ≤ M, by calculating for each intersection of the road network such as at node nv, the probability p (aI k , aO m ) for a vehicle to take an outgoing road section corresponding to the arc aO m according to the road section from where the vehicle corresponding to arc aI k . Such probabilities at each node nv are related by the following relation: Σ m = 1 m = M p have k aO m = 1
Figure imgb0003

Le calcul de probabilité est basé sur la règle du choix du chemin le plus rapide, en attribuant des probabilités plus élevées aux intersections qui font partie des chemins les plus empruntés par les véhicules. Ceci confère un ensemble de probabilités de propagation qui sont utilisées pour la répartition du flux à travers le graphe G1 du réseau routier.The probability calculation is based on the fastest path selection rule, assigning higher probabilities to the intersections that are part of the most used paths of the vehicles. This confers a set of propagation probabilities that are used for the distribution of the flow through the graph G1 of the road network.

En se référant à la figure 7, le procédé d'estimation de trafic routier conforme à l'invention est fondé sur les définitions et règles précédentes et comprend une première étape E1 relative à un prétraitement exécuté une fois pour toutes sur le graphe G1(N1, A1) du réseau routier complet, et une deuxième étape E2 relative à un traitement des arcs a1* du graphe G1 qui n'appartiennent pas au sous-graphe G2(N2, A2) et exécutée à chaque actualisation des informations de trafic mesurées des arcs a2 du sous-graphe G2.Referring to the figure 7 , the road traffic estimation method according to the invention is based on the above definitions and rules and comprises a first step E1 relating to a pre-processing executed once and for all on the graph G1 (N1, A1) of the complete road network and a second step E2 relating to a processing of the arcs a1 * of the graph G1 which do not belong to the subgraph G2 (N2, A2) and executed at each update of the measured traffic information of the arcs a2 of the subgraph G2 .

L'étape E1 comprend des étapes E11 et E12 exécutées par le module de détermination de probabilité de propagation DPP pour déterminer préalablement des probabilités de propagation sur tous les noeuds du graphe G1 en appliquant la règle du choix du chemin le plus rapide.
A l'étape E11, le module DPP dénombre pour chaque triplet (nu, nv, nw) composé de trois noeuds successifs directement reliés par des arcs dans cet ordre (figure 6), les chemins les plus rapides entre deux noeuds quelconques du graphe G1 qui passent par ce triplet et la base de données BD mémorise le nombre d'itinéraires les plus rapides. Les chemins les plus rapides sont dénombrés en exploitant l'algorithme connu de Floyd-Warshall qui permet de calculer les plus courtes distances entre deux noeuds (sommets) quelconques d'un graphe. Le nombre de chemins les plus rapides entre deux noeuds quelconques du graphe G1 est limité par un maximum prédéterminé.
Comme il est prohibitif de réaliser l'étape de dénombrement E11 d'un seul coup sur l'ensemble du graphe G1, le module DPP met en oeuvre l'étape de dénombrement E11 seulement dans un voisinage prédéterminé autour du noeud d'intersection central nv de chaque triplet (nu, nv, nw). Le voisinage est prédéterminé comme étant les N noeuds les plus proches en temps de parcours du noeud central nv considéré, y compris les noeuds d'extrémité nu et nw du triplet, N étant un entier au moins égal à 2. Le module DPP calcule ce voisinage en implémentant l'algorithme connu de E. W. Dijkstra qui donne les plus courts chemins entre un noeud (sommet) source du voisinage et chacun des noeuds du voisinage qui est un sous-graphe du graphe G1. Le voisinage présente une profondeur prédéterminée exprimée en nombre de noeuds les plus proches du noeud central du triplet.
Après l'étape E11, la base de données BD possède pour chaque triplet (nu, nv, nw) du graphe G1 le nombre de chemins les plus rapides qui l'empruntent parmi tous les chemins possibles entre deux noeuds quelconques parmi les noeuds les plus proches en temps de parcours du noeud central nv dans le voisinage du noeud nv. Le nombre de chemins les plus rapides est appelé "fréquence de propagation" fp.
A l'étape E12, le module DPP transforme ces fréquences de propagation fp en probabilités de propagation p, par application de la règle de conservation de flux de trafic pour chaque noeud n1 du graphe G1: pour chaque noeud nv, la somme de toutes les probabilités relatives aux triplets (nu, nv, nw) pour qu'un véhicule en provenance d'un noeud nu et se dirigeant vers un noeud nw traverse le noeud nv est égale à 1 selon la relation (2). La probabilité de propagation puvw associée au triplet (nu, nv, nw) est égale au rapport de la fréquence de propagation fpuvw du triplet (nu, nv, nw) sur la somme totale des fréquences de propagation de tous les triplets (nu, nv, nx) ayant comme noeud de départ le noeud nu et comme noeud central le noeud nv.
The step E1 comprises steps E11 and E12 executed by the DPP propagation probability determination module in order to previously determine propagation probabilities on all the nodes of the graph G1 by applying the rule of the choice of the fastest path.
In step E11, the DPP module counts for each triplet (nu, nv, nw) composed of three nodes successive directly connected by arcs in this order ( figure 6 ), the fastest paths between any two nodes of the graph G1 that pass through this triplet and the database BD stores the number of fastest routes. The fastest paths are counted using the well-known Floyd-Warshall algorithm that calculates the shortest distances between any two nodes (vertices) of a graph. The number of fastest paths between any two nodes of the graph G1 is limited by a predetermined maximum.
Since it is prohibitive to carry out the counting step E11 in one go on the whole of the graph G1, the DPP module implements the counting step E11 only in a predetermined neighborhood around the central intersection node n.sub.n of each triplet (nu, nv, nw). The neighborhood is predetermined as being the N closest nodes in travel time of the central node nv considered, including the naked end nodes and nw of the triplet, N being an integer at least equal to 2. The DPP module calculates this neighborhood by implementing the known algorithm of EW Dijkstra which gives the shortest paths between a node (vertex) source of the neighborhood and each node of the neighborhood which is a subgraph of the graph G1. The neighborhood has a predetermined depth expressed as the number of nodes closest to the central node of the triplet.
After the step E11, the database BD has for each triplet (nu, nv, nw) of the graph G1 the number of fastest paths that take it from among all the possible paths between any two nodes among the most nodes. close in time of the journey of the central node nv in the neighborhood of the node nv. The number of fastest paths is called "propagation frequency" fp.
In step E12, the DPP module transforms these propagation frequencies fp into propagation probabilities p, by applying the traffic flow conservation rule for each node n1 of the graph G1: for each node nv, the sum of all the probabilities relating to triplets (nu, nv, nw) for a vehicle coming from a knot and heading towards a node nw to cross node nv is equal to 1 according to relation (2). The propagation probability p uvw associated with the triplet (nu, nv, nw) is equal to the ratio of the propagation frequency fp uvw of the triplet (nu, nv, nw) on the total sum of the propagation frequencies of all the triplets (n , nv, nx) having the node as the starting node and the node nv as the central node.

L'étape E2 comprend des étapes d'estimation E21 à E23 exécutées par le module de propagation de trafic PT à chaque actualisation des informations de trafic dynamiques mesurées constituant les poids des arcs a2 du sous-graphe G2 de manière à propager ces informations de trafic dynamiques sur les autres arcs a1* du graphe G1 et ainsi à estimer les informations de trafic de ces autres arcs n'appartenant pas au sous-graphe G2.
A l'étape E21, le module PT se base sur la liste des arcs a2 du sous-graphe G2 renseignés par des informations de trafic dynamiques, telles que les flux de trafic exprimés en nombre de véhicule par unité de temps, transmises au dispositif DET par les équipements de mesure de trafic EMT sur les tronçons du réseau routier RR correspondant aux arcs du sous-graphe G2 à la suite d'une nouvelle mesure et mémorisées dans une file d'attente de la base données BD. Pour chaque noeud nv tel qu'il existe au moins un arc entrant renseigné a2(nu, nv) appartenant au sous-graphe G2, le module PT estime le flux résultant fvw sur l'arc a1 (nv, nw) sortant du noeud nv et n'appartenant pas au sous-graphe G2. Pour cette estimation, le module PT applique d'une part la probabilité de propagation puvw associée au triplet (nu, nv, nw) au flux de trafic fuv mesuré sur l'arc a2(nu, nv), ou plus généralement les probabilités de propagation aux flux de trafic mesurés de l'ensemble δ-(v) de tous les arcs renseignés entrants du noeud nv, selon la relation : f vw = u v δ - v p uvw f uv .

Figure imgb0004
D'autre part, le module PT applique la conservation du flux provenant d'un arc entrant a2(nu, nv) dans l'arc sortant a1*(nv, nw), ou plus généralement de l'ensemble δ+(v) de tous les arcs sortants du noeud d'intersection nv, soit: v w δ + v p uvw = 1.
Figure imgb0005
The step E2 comprises estimation steps E21 to E23 executed by the PT traffic propagation module at each update of the measured dynamic traffic information constituting the weights of the arcs a2 of the subgraph G2 so as to propagate these traffic information. dynamic on the other arcs a1 * of the graph G1 and thus to estimate the traffic information of these other arcs not belonging to subgraph G2.
In step E21, the PT module is based on the list of arcs a2 subgraph G2 filled with dynamic traffic information, such as traffic flows expressed in the number of vehicles per unit of time, transmitted to the device DET by the EMT traffic measuring equipment on the sections of the RR road network corresponding to the arcs of sub-graph G2 following a new measurement and stored in a queue of the database BD. For each node nv such that there exists at least one entered incoming arc a2 (nu, nv) belonging to the subgraph G2, the module PT estimates the resulting flow f vw on the arc a1 (nv, nw) coming out of the node nv and not belonging to subgraph G2. For this estimation, the PT module applies on the one hand the propagation probability p uvw associated with the triplet (nu, nv, nw) to the traffic flow f uv measured on the arc a2 (nu, nv), or more generally the probabilities of propagation to the measured traffic flows of the set δ - (v) of all the incoming informed arcs of the node nv, according to the relation: f vw = Σ u v δ - v p uvw f uv .
Figure imgb0004
On the other hand, the module PT applies the conservation of the flux coming from an incoming arc a2 (nu, nv) in the outgoing arc a1 * (nv, nw), or more generally of the set δ + (v) of all the outgoing arcs of the intersection node nv, that is: Σ v w δ + v p uvw = 1.
Figure imgb0005

A l'étape E22, le module PT recourt à la relation (1) entre le flux de trafic et le temps de parcours dynamique courant, et en déduit le temps de parcours dynamique courant τvm estimé sur l'arc a1* (nv, nw) : τ VW = C VW σ VW / f VW .

Figure imgb0006
In step E22, the module PT uses the relation (1) between the traffic flow and the current dynamic travel time, and deduces therefrom the current dynamic travel time τ vm estimated on the arc a1 * (nv, nw): τ VW = VS VW σ VW / f VW .
Figure imgb0006

Les temps de parcours estimés τVW, et/ou en variante les flux estimés fVW, en tant qu'informations de trafic estimées des arcs nouvellement actualisés a1*(nv, nw) sont mémorisés respectivement en association avec les identificateurs de ces arcs dans une liste d'arcs entrants dans la file d'attente de la base de données BD.
Les étapes E21 et E22 sont ensuite répétées récursivement, comme indiqué à l'étape E23, en prenant comme arcs de début à l'étape E21 d'une deuxième itération les arcs a1*(nv, nw) nouvellement actualisés de la liste d'arcs entrants lue dans la file d'attente à la place de la liste des arcs a2 du sous-graphe G2 renseignés par des informations de trafic mesurées dynamiques au début de la première itération décrite ci-dessus. La deuxième itération estime les informations de trafic f, τ d'une autre série d'arcs du graphe G1 n'appartenant pas au sous-graphe G2, ni à l'ensemble des arcs a1* nouvellement actualisés, et reliés chacun à un noeud pour lequel au moins un arc nouvellement actualisé est un arc entrant. Par exemple en référence à la figure 5, les informations de trafic des arcs a10 et a11 sont estimées en fonction au moins de l'information de trafic mesurée de l'arc a20 au cours de la première itération, puis les informations de trafic des arcs a100 et a101 sont estimées en fonction au moins de l'information de trafic estimée de l'arc a10 et l'information de trafic de l'arc a110 est estimée en fonction au moins de l'information de trafic estimée de l'arc a10 au cours de la deuxième itération.
Ceci revient à chaque itération des étapes E21 et E22 à enrichir le sous-graphe G2 avec les arcs dont les informations de trafic sont nouvellement estimées et donc actualisées pour des déterminations et corrections d'itinéraires dans le réseau routier RR en temps réel.
The estimated travel times τ VW , and / or alternatively the estimated flows f VW , as estimated traffic information of the newly updated arcs a1 * (nv, nw) are stored respectively in association with the identifiers of these arcs in a list of arcs incoming in the queue of the database BD.
Steps E21 and E22 are then repeated recursively, as indicated in step E23, taking as starting arcs in step E21 of a second iteration the newly updated arcs a1 * (nv, nw) of the list of incoming arcs read in the queue instead of the list of arcs a2 of subgraph G2 populated by dynamic measured traffic information at the beginning of the first iteration described above. The second iteration estimates the traffic information f, τ of another series of arcs of the graph G1 not belonging to the subgraph G2, nor to the set of arcs a1 * newly updated, and each connected to a node for which at least one newly refreshed arc is an incoming arc. For example with reference to the figure 5 the traffic information of the arcs a10 and a11 are estimated based on at least the measured traffic information of the arc a20 during the first iteration, and the traffic information of the arcs a100 and a101 are estimated according to the less than the estimated traffic information of the arc a10 and the traffic information of the arc a110 is estimated based at least on the estimated traffic information of the arc a10 during the second iteration.
This amounts to each iteration of the steps E21 and E22 to enrich the subgraph G2 with the arcs whose traffic information is newly estimated and thus updated for determinations and corrections of routes in the RR road network in real time.

La répétition des étapes itératives E21 à E23 dans le module de propagation de trafic PT est arrêtée lorsqu'un critère d'arrêt CA est satisfait afin d'assurer que la propagation ne s'étend pas à tout le graphe G1 du réseau routier entier RR.
En effet, plus des tronçons routiers sont éloignés des tronçons des axes routiers dynamiquement renseignés correspondant aux arcs du sous-graphe G2, plus l'information dynamique à propager dans le graphe G1 des arcs non renseignés dynamiquement ou par estimation selon l'invention perd de sa pertinence et doit décroître. Il serait irréaliste et coûteux en temps de calcul d'estimer l'information de trafic sur le graphe G1 en entier correspondant à tout le réseau routier RR en fonction du faible nombre d'arcs renseignés dynamiquement a2 comparativement au nombre élevé d'arcs a1 du graphe G1
L'invention fait décroître le poids de l'information de trafic estimée par rapport à celui de l'information de trafic statique jusqu'à arrêter complètement la propagation de l'information au bout d'un certain nombre d'itérations. De ce fait, des arcs a1 du graphe G1 en nombre limité sont renseignés par une information de trafic estimée dépendant d'une information de trafic mesurée, ce qui confère un ensemble d'arcs renseignés beaucoup plus important que celui des seuls arcs a2 disposant d'une information de trafic mesurée réellement.
Repetition of the iterative steps E21 to E23 in the PT traffic propagation module is stopped when a CA stop criterion is satisfied to ensure that the propagation does not extend to the whole graph G1 of the entire road network RR.
In fact, the more road sections are separated from the dynamically indicated sections of the road axes corresponding to the arcs of the subgraph G2, the more dynamic information to propagate in the graph G1 arcs not dynamically indicated or by estimation according to the invention loses its relevance and must decrease. It would be unrealistic and expensive in terms of calculation time to estimate the traffic information on the graph G1 as a whole corresponding to the entire road network RR as a function of the small number of arcs dynamically indicated a2 compared to the high number of arcs a1 of graph G1
The invention decreases the weight of the estimated traffic information relative to that of the static traffic information to completely stop the propagation of the information after a certain number of iterations. As a result, arcs a1 of the graph G1 in limited number are indicated by an estimated traffic information dependent on a measured traffic information, which confers a much larger set of arcs than the arcs a2 with a measured traffic information actually.

Le critère d'arrêt CA peut être de différentes natures, en fonction de contraintes et objectifs imposés au dispositif d'estimation de trafic routier DET. Le critère d'arrêt est par exemple l'un des critères suivants CA1, CA2 et CA3, ou une combinaison d'au moins deux de ces critères.The AC stop criterion may be of different natures, depending on the constraints and objectives imposed on the DET traffic estimation device. The stopping criterion is for example one of the following criteria CA1, CA2 and CA3, or a combination of at least two of these criteria.

Le premier critère CA1 est basé sur un temps d'exécution prédéterminé maximum des itérations des étapes E21 à E23, toujours inférieur à la période de mesure et d'actualisation des informations de trafic transmises par les équipements EMT et dont dépendent les variables f. Le temps d'exécution maximum est ainsi choisi en fonction de contraintes de performance du dispositif DET telles que le temps de propagation, c'est-à-dire en fonction de la durée d'une passe des étapes E21 à E23 par rapport à la fréquence de mesure et d'actualisation des informations de trafic dynamiques du sous-graphe G2.
Le deuxième critère CA2 est basé sur un nombre d'itérations des étapes E21 à E23 fixé empiriquement. Le nombre d'itérations caractérise la profondeur des voisinages utilisés, c'est-à-dire l'étendue de l'influence des arcs dynamiques a2 sur les arcs a1 voisins à information de trafic initialement statiques dans le graphe G1.
Le troisième critère CA3 est basé, pour un arc donné, sur la différence absolue | f - c | entre le flux de trafic dynamique courant estimé f et la capacité c, ou en variante sur la différence absolue |τ - σ| entre le temps de parcours dynamique courant estimé τ et le temps de parcours statique moyen σ. Si la différence absolue |f - c| ou |τ - σ| est inférieure à un paramètre de tolérance prédéterminé ε, c'est-à-dire si l'information de trafic estimée f, τ avoisine une constante prédéterminée à un paramètre de tolérance ε près, le module de propagation de trafic PT arrête la propagation à cet arc puisque l'apport de l'information dynamique f, τ pour des arcs statiques voisins suivants a1 devient négligeable par rapport à l'information statique c, σ.
The first criterion CA1 is based on a maximum predetermined execution time of the iterations of the steps E21 to E23, still less than the period of measurement and update of the traffic information transmitted by the EMT equipment and on which the variables f depend. The maximum execution time is thus chosen according to the performance constraints of the DET device such as the propagation time, that is to say as a function of the duration of a pass of the steps E21 to E23 relative to the measurement and update frequency of dynamic traffic information of subgraph G2.
The second criterion CA2 is based on an iteration number of the steps E21 to E23 set empirically. The number of iterations characterizes the depth of the neighborhoods used, that is to say the extent of the influence of the dynamic arcs a2 on the adjacent arcs A1 traffic information initially static in the graph G1.
The third criterion CA3 is based, for a given arc, on the absolute difference | f - c | between the estimated current dynamic traffic flow f and the capacity c, or alternatively the absolute difference | τ - σ | between the estimated current dynamic travel time τ and the average static travel time σ. If the absolute difference | f - c | or | τ - σ | is less than a predetermined tolerance parameter ε, i.e. if the estimated traffic information f, τ is close to a predetermined constant at a tolerance parameter ε, the PT traffic propagation module stops the propagation to this arc since the contribution of the dynamic information f, τ for subsequent adjacent static arcs a1 becomes negligible compared with the static information c, σ.

Lorsque le critère d'arrêt CA est satisfait à l'étape E23, les étapes récursives E21 à E23 sont à nouveau réitérées à la période de transmission des informations de trafic actualisées mesurées par les équipements EMT, comme indiqué en E3 dans la figure 7, pour des déterminations et corrections d'itinéraires dans le réseau routier RR en temps réel.When the stop criterion CA is satisfied in step E23, the recursive steps E21 to E23 are again reiterated to the transmission period of the updated traffic information measured by the EMT equipment, as indicated in E3 in FIG. figure 7 , for determinations and corrections of routes in the real-time RR road network.

L'invention décrite ici concerne un procédé et un dispositif d'estimation de trafic de réseau routier. Selon une implémentation, les étapes du procédé de l'invention sont déterminées par les instructions d'un programme d'ordinateur incorporé dans un dispositif informatique tel que le dispositif d'estimation de trafic DET. Le programme comporte des instructions de programme qui, lorsque ledit programme est exécuté dans un processeur du dispositif dont le fonctionnement est alors commandé par l'exécution du programme, réalisent les étapes du procédé selon l'invention.
En conséquence, l'invention s'applique également à un programme d'ordinateur, notamment un programme d'ordinateur enregistré sur ou dans un support d'informations lisible par un ordinateur et tout dispositif de traitement de données, adapté à mettre en oeuvre l'invention. Ce programme peut utiliser n'importe quel langage de programmation, et être sous la forme de code source, code objet, ou de code intermédiaire entre code source et code objet tel que dans une forme partiellement compilée, ou dans n'importe quelle autre forme souhaitable pour implémenter le procédé selon l'invention.
The invention described here relates to a method and a device for estimating road network traffic. According to one implementation, the steps of the method of the invention are determined by the instructions of a computer program incorporated into a computing device such as the traffic estimation device DET. The program comprises program instructions which, when said program is executed in a processor of the device whose operation is then controlled by the execution of the program, carry out the steps of the method according to the invention.
Accordingly, the invention also applies to a computer program, in particular a computer program recorded on or in a computer readable information medium and any data processing device, adapted to implement the computer program. 'invention. This program can use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code such as in a partially compiled form, or in any other form desirable to implement the method according to the invention.

Le support d'informations peut être n'importe quelle entité ou dispositif capable de stocker le programme. Par exemple, le support peut comporter un moyen de stockage ou support d'enregistrement sur lequel est enregistré le programme d'ordinateur selon l'invention, tel qu'une ROM, par exemple un CD ROM ou une ROM de circuit microélectronique, ou encore une clé USB, ou un moyen d'enregistrement magnétique, par exemple une disquette (floppy disc) ou un disque dur.The information carrier may be any entity or device capable of storing the program. For example, the medium may comprise storage means or recording medium on which is recorded the computer program according to the invention, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a USB key, or a magnetic recording medium, for example a diskette (floppy disc) or a hard disk.

Claims (10)

  1. A method for estimating the traffic in a road network (RR) illustrated by a graph (G1) of arcs (a1) corresponding to road network sections and restricted by intersection nodes (n1), the graph comprising a sub-graph (G2) of arcs (a2) corresponding to road network sections, a piece of traffic information of which is measured, characterized in that it comprises :
    for each triplet of consecutive nodes (nu, nv, nw) of the graph (G1), a determination (E1) of a probability of propagation (Puvw) proportional to the ratio of a triplet (nu, nv, nw) propagation frequency on the total sum of the triplet propagation frequency with the same starting and central nodes (nu, nv) as the triplet, the triplet propagation frequency being a number of the fastest paths that follow the triplet, and
    an estimation (E2) of the traffic information for arcs (a1(nu, nw)) of the graph (G1) not belonging to the sub-graph (G2) and each one linked to a sub-graph node, the traffic information of an arc (a1(nu, nw)) not belonging to the sub-graph (G2) and leaving a node (nv) of the sub-graph (G2) being estimated versus traffic propagation and information probability being measured concerning the whole arc of the sub-graph entering said node (nv).
  2. A method according to claim 1, wherein the determination (E1) of a propagation probability for a three node triplet (nu, nv, nw) of the graph (G1) comprises a count (E11) of the fastest paths following all the possible paths between two any nodes of the graph (G1).
  3. A method according to claim 2, wherein the count of the fastest paths following the triplet (nu, nv, nw) is implemented in a predetermined depth proximity expressed in number of nodes being the closest to the triplet central node (nv).
  4. A method according to any of claims 1 to 3, comprising at least one iteration (E23) of the estimation (E2) by taking the arcs, the traffic information of which has just been estimated as arcs of the sub-graph.
  5. A method according to claim 4, wherein iterations (E23) of the estimation (E2) are stopped when a predetermined execution time of the iterations being less than a traffic information measuring time is reached.
  6. A method according to claim 4 or 5, wherein the number of iterations (E23) of the estimation (E2) is restricted to the proximity depth of the sub-graph (G2) nodes.
  7. A method according to any of claims 4 to 6, wherein the iterations (E23) of the estimation (E2) are stopped for a given arc when the estimated traffic information is near a predetermined constant except for one tolerance parameter.
  8. A method according to any of claims 1 to 7, wherein the measured traffic information of an arc (a2(nu, nv)) of the sub-graph (G2) depends on the traffic flow (fuv) in a corresponding section of the road network (RR), and the traffic information (fuv) of an arc (a1(nv, nw)) not belonging to the sub-graph (G2) and leaving a node (nv) of the sub-graph (G2) is proportional to the product of the traffic propagation and information probability (fuv) concerning at least one arc (a2(nu, nv)) of the sub-graph entering said node (nv).
  9. A device (DET) adapted to estimate the traffic in a road network (RR) illustrated by a graph (G1) of arcs (a1) corresponding to road network sections and restricted by intersection nodes (n1), the graph comprising a sub-graph (G2) of arcs (a2) corresponding to road network sections, a piece of traffic information of which is measured, characterized in that it comprises:
    - for each triplet of consecutive nodes (nu, nv, nw) of the graph (G1), a means (DPP) adapted to determine a propagation probability (puvw) proportional to the ratio of a triplet (nu, nv, nw) propagation frequency on the total sum of the triplet propagation frequencies with the same starting and central nodes (nu, nv) as the triplet, the triplet propagation frequency being a number of the fastest paths following the triplet, and
    - a means (PT) adapted to estimate the traffic information for arcs (a1(nu, nw)) of the graph (G1) not belonging to the sub-graph (G2) and each one linked to a node of the sub-graph, the traffic information of an arc (a1(nu, nw)) not belonging to the sub-graph (G2) and leaving a node (nv) of the sub-graph (G2) being estimated in accordance with the traffic propagation and information probability being measured concerning the whole arc of the sub-graph entering said node (nv).
  10. A computer program able to be provided in a computing device (DET) and intended for estimating the traffic in a road network (RR) illustrated by a graph (G1) of arcs (a1) corresponding to road network sections and restricted by intersection nodes (n1), the graph comprising a sub-graph (G2) of arcs (a2) corresponding to road network sections, a piece of traffic information of which is measured, said program being characterized in that it comprises instructions which, when the program is executed in said device, perform :
    for each triplet of consecutive nodes (nu, nv, nw) of
    the graph (G1), a determination (E1) of a propagation probability (Puvw) proportional to the ratio of the triplet (nu, nv, nw) propagation frequency to the total sum of the triplet propagation frequencies with the same starting and central nodes (nu, nv) as the triplet, the triplet propagation frequency being a number of the fastest paths following the triplet, and
    an estimation (E2) of the traffic information for arcs (a1(nu, nw)) of the graph (G1) not belonging to the sub-graph (G2) and each one linked to a sub-graph node, the traffic information of an arc (a1(nu, nw)) not belonging to a sub-graph (G2) and leaving a node (nv) of the sub-graph (G2) being estimated in accordance with probability propagation and traffic information being measured in accordance with the whole arc of the sub-graph entering said node (nv).
EP08104579A 2007-07-02 2008-06-27 Estimation of traffic in a road network Not-in-force EP2012289B1 (en)

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FR0756224A FR2918495B1 (en) 2007-07-02 2007-07-02 ESTIMATION OF TRAFFIC IN A ROAD NETWORK

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Cited By (2)

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US8818380B2 (en) 2004-07-09 2014-08-26 Israel Feldman System and method for geographically locating a cellular phone
US9552725B2 (en) 2000-08-28 2017-01-24 Inrix Global Services Limited Method and system for modeling and processing vehicular traffic data and information and applying thereof

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Publication number Priority date Publication date Assignee Title
GB2492369B (en) 2011-06-29 2014-04-02 Itis Holdings Plc Method and system for collecting traffic data
DE102011083375A1 (en) * 2011-09-26 2013-03-28 Robert Bosch Gmbh Method for transmitting route data for traffic telematics
CN116303835B (en) * 2023-05-24 2023-07-21 北京建筑大学 Mapping data management method for road planning

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SE470367B (en) * 1992-11-19 1994-01-31 Kjell Olsson Ways to predict traffic parameters
US6587781B2 (en) * 2000-08-28 2003-07-01 Estimotion, Inc. Method and system for modeling and processing vehicular traffic data and information and applying thereof
US7894980B2 (en) * 2005-02-07 2011-02-22 International Business Machines Corporation Method and apparatus for estimating real-time travel times over a transportation network based on limited real-time data

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9552725B2 (en) 2000-08-28 2017-01-24 Inrix Global Services Limited Method and system for modeling and processing vehicular traffic data and information and applying thereof
US8818380B2 (en) 2004-07-09 2014-08-26 Israel Feldman System and method for geographically locating a cellular phone

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EP2012289A1 (en) 2009-01-07
FR2918495A1 (en) 2009-01-09
DE602008003158D1 (en) 2010-12-09
ATE486344T1 (en) 2010-11-15

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