EP3021303A1 - Automatic determination of a speed limit on a road from a navigation system - Google Patents

Abstract

The invention relates to a method for automatically determining a speed limit (SL S) in force on a road taken, or about to be taken, by a motor vehicle, in which it is established, by means of a first system (2), said navigation system including a data receiver (20, 21) of a geographical positioning system embedded on said motor vehicle and mapping data (22), a probable speed limitation (SL NAV). The method is characterized by an extraction step, from at least one attribute (Att) issued by the navigation system (2) and relating to a road context data, a road context in which the vehicle is located; and by a step of determining the speed limit in effect (SL S) on the road considered, from said probable speed limitation (SL NAV) and taking into consideration said road context extracted.

Description

The present invention relates to a method for determining speed limits on a road taken by a motor vehicle, and a system for implementing this method. The main purpose of the invention is to propose a solution for automatically determining information relating to a speed limit that applies to a road taken, or about to be borrowed, by a motor vehicle. The information thus determined is then exploitable in different applications equipping the vehicle in question. In particular, but without limitation, the information relating to a speed limit is used in the context of a driving assistance system by explicitly indicating to the driver what is the maximum speed allowed, for example when this last is in excess of this maximum speed.

• des systèmes dits de vision de nuit pour aider le conducteur à détecter de manière anticipée des obstacles difficilement perceptibles dans des conditions de circulation nocturnes ;
• des systèmes de détection anticipée de virage, pour prévenir au plus tôt le conducteur de la présence prochaine d'un virage ;

The field of the invention is, in general, that of the driver assistance, which proposes a set of assistance systems for the driver, primarily intended to improve the traffic safety conditions. We have recently developed, for example:

• so-called night vision systems to help the driver to early detect obstacles difficult to perceive in night traffic conditions;
• early turn detection systems, to warn the driver of the presence of a turn as soon as possible;

As part of the driver assistance systems, it is also now sought to provide the driver with a warning system of speed limits: such a system must automatically detect a speed limit in force on a borrowed road, or on a road that is about to be taken by a vehicle. In fact, actions concerning excessive speeds are necessary to reduce the number of accidents and the gravity of their consequences. Many drivers do not respect the prescribed speeds: 40% of drivers do not respect them on motorways, 60% on national and departmental roads and 25% exceed the regulatory speed in the city by more than 10 km / h.

Various solutions have been proposed to date to allow a vehicle to automatically determine a speed limit in force on a road.

A first solution lies in the exploitation of information from a navigation system. Navigation systems increasingly equip vehicles for driver guidance from a starting point (corresponding to the current position of the vehicle) to an end point (selected by the driver). With such a navigation system including a data receiver of a geographical positioning system and mapping data, it is known to establish a likely speed limitation.

• La cartographie actuelle est encore très imprécise. Il arrive très souvent qu'à un endroit donné, l'information soit absente. En effet, il existe des zones entières du monde qui ne sont pas couvertes par les bases de données de la cartographie ;
• Il arrive aussi que l'information fournie par le système de navigation soit aberrante. Par exemple, si le conducteur a prévu de se rendre à un lieu B qu'il a mémorisé dans son système de navigation et si, finalement, en cours de route, il est amené à aller vers un lieu C sans suivre les indications données par le système de navigation, alors les informations données par le système de navigation sont incohérentes, voire contradictoires, par rapport aux caractéristiques de la trajectoire réellement suivie par le véhicule ;
• Les changements de configuration de la route dus à des événements ponctuels, par exemple la réalisation de travaux, entrainent une modification des limitations de vitesse en vigueur sur la portion de route considérée ; ces modifications ne sont alors pas connues du système de navigation ;
• Une perte de couverture GPS est également possible, par exemple lors du passage sous un long tunnel.

However, a number of defects inherent in this system limit its effectiveness:

• The current mapping is still very imprecise. It happens very often that in a given place, the information is missing. Indeed, there are entire areas of the world that are not covered by the mapping databases;
• Sometimes the information provided by the navigation system is aberrant. For example, if the driver has planned to go to a place B that he memorized in his navigation system and if, ultimately, en route, he is led to go to a place C without following the instructions given by the navigation system, then the information given by the navigation system is inconsistent or even contradictory, with respect to the characteristics of the trajectory actually followed by the vehicle;
• Changes in the configuration of the road due to one-off events, for example the execution of work, entail a modification of the speed restrictions in force on the portion of the road considered; these modifications are not then known to the navigation system;
• A loss of GPS coverage is also possible, for example when passing under a long tunnel.

Finally, the navigation system is imprecise, the inaccuracy being of the order of ten meters.

• établir, au moyen d'un premier système, dit système de navigation faisant intervenir notamment un récepteur de données d'un système de positionnement géographique et des données de cartographie, une limitation de vitesse vraisemblable associée à un premier indice de confiance ;
• constituer un premier ensemble d'informations comprenant au moins la limitation de vitesse vraisemblable, et le premier indice de confiance;
• établir, au moyen d'un deuxième système, dit système de traitement d'images, faisant intervenir notamment une caméra et des applications de traitement d'images aptes à identifier et interpréter des panneaux de limitation de vitesse disposés au voisinage de la route, une limitation de vitesse probable associée à un deuxième indice de confiance;
• constituer un deuxième ensemble d'informations comprenant au moins la limitation de vitesse probable, et le deuxième indice de confiance; et
• déterminer la limitation de vitesse en vigueur sur la route considérée, à partir du premier ensemble d'informations et du deuxième ensemble d'informations et en prenant en considération le premier indice de confiance et le deuxième indice de confiance.

To overcome at least some of the various disadvantages mentioned above, another solution, described in particular in the document EP 2 017 807 B1 on behalf of the Applicant, consists in combining the data provided, on the one hand, by a navigation system and, on the other hand, by a system associating an on-board camera and image processing applications. More specifically, a method for automatically determining a speed limit in force on a road taken, or about to be borrowed, by a motor vehicle, comprises, according to the teaching of this document, the following steps:

• establishing, by means of a first system, said navigation system including in particular a data receiver of a geographical positioning system and mapping data, a likely speed limitation associated with a first confidence index;
• constituting a first set of information including at least the likely speed limitation, and the first confidence index;
• to establish, by means of a second system, an image processing system, notably involving a camera and image processing applications able to identify and interpret speed limitation panels arranged in the vicinity of the road, a likely speed limitation associated with a second confidence index;
• constituting a second set of information including at least the likely speed limit, and the second confidence index; and
• determine the speed limit in force on the considered route, from the first set of information and the second set of information and taking into account the first confidence index and the second confidence index.

Different calculation methods exist to determine the first confidence index, such as a weighted sum of several criteria that can involve the accuracy of the positioning of the vehicle by the navigation system, the level of information on the road, the functional class of the road, the type of road (highway, main road, secondary road), the environment (city, highway exit ...), the guide mode selected or not by the driver ...

An example of calculation of the second confidence index will involve a weighted sum of different criteria, such as the shadow factor on the image considered, the symmetry index of the image considered, the identity coherence index. speed limit signs from one image to another ...

Advantageously, the information relating to the speed limits provided by each of the two systems is extrapolated to consider other speed limits as being likely to be in force on the road considered; then each of these other speed limits is associated with a weighting coefficient, called mass of belief, involved in the merging of all the information then available relating to the speed likely to be actually in effect, fusion of information ensuring the final determination of the speed limit sought.

In general, the determination of confidence indices, and / or belief masses, and their intervention in the fusion of knowledge from the two systems depend on the merger strategy chosen. Advantageously, various methods extracted from the theory known as beliefs can be used in the data fusion. In particular, one of the methods known as the "conjunctive combination" of Dempster-Shafer, associated with a so-called Dempster-Shafer equation, gives particularly convincing results. Other methods, based on Bayesian theories, or fuzzy logic set theory, can also be used in data fusion.

Once the speed limit in force has been established, it can for example be displayed on a screen.

The confidence indices used for the merger are updated each time new data is provided by the navigation system or by the image processing system 102.

We obtain, with the system described in the document EP 2 017 807 , a determination of the current speed limit much more reliable than with systems that only take into account data from a navigation system, or data from an image processing system. In particular, the risks of confusion due to erroneous information or misinterpretation of this information are avoided. We can also propose a degraded mode of operation, useful in the event of failure of one of the two systems, based on the other system, not defective.

Nevertheless, in practice, the Applicant has found that such a fusion system does not make it possible to satisfactorily manage all the driving situations that a user may be confronted with. In particular, the previous system does not work optimally when the camera on the vehicle detects a sign indicating an end of speed limitation. Indeed, in this case, the fusion system will operate in a degraded mode that only takes into account the data provided by the navigation system. In this case, the problem is related to the inaccuracy of the geographical positioning, of the order of a hundred meters, of the navigation system.

The present invention aims to overcome the above limitations by providing a method for automatically determining a speed limit on a road, from a likely speed limitation provided by an on-board navigation system, which is more reliable and more precise.

• extraire, à partir d'au moins un attribut délivré par le système de navigation et portant sur une donnée de contexte routier, un contexte routier dans lequel le véhicule se trouve ;
• déterminer la limitation de vitesse en vigueur sur la route considérée, à partir de ladite limitation de vitesse vraisemblable et en prenant en considération ledit contexte routier extrait.

More specifically, the subject of the present invention is a method of automatically determining a speed limit in force on a road taken, or about to be taken, by a motor vehicle, in which it is established, by means of a first system, said navigation system including a data receiver of a geographical positioning system embedded on said motor vehicle and mapping data, a speed limit likelihood, the method being characterized in that it comprises the following steps:

• extracting, from at least one attribute issued by the navigation system and relating to a road context data, a road context in which the vehicle is located;
• determine the speed limit in force on the considered route, based on said likely speed limitation and taking into consideration said road context extracted.

• ledit au moins un attribut portant sur une donnée de contexte routier permet de distinguer les contextes routiers dans l'ensemble { ville, autoroute, sortie, autre} ;
• l'étape d'extraction comporte une détermination dudit contexte routier à partir d'un premier attribut relatif au type de route, et d'un deuxième attribut relatif à la situation de conduite, le premier et deuxième attributs étant délivrés par le système de navigation ;
• l'étape de détermination comporte, pour chaque limitation de vitesse possible SLi prise dans un ensemble prédéterminé de limitations de vitesse règlementaires, un calcul d'une probabilité P(SLi) fonction de la combinaison linéaire suivante : $${\mathrm{C}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{C}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$$
  
  
  dans laquelle ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$
  
  est un indice de confiance fonction de chaque limitation de vitesse SLi possible et du contexte extrait ;
  ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$
  
  est un indice de confiance fonction de chaque limitation de vitesse SLi possible et de la limitation de vitesse vraisemblable SL_NAV fournie par le système de navigation; et
  C_CONT et C_NAV sont deux coefficients de pondération prédéfinis liés respectivement au contexte et à la navigation ;
• en variante, le calcul de la probabilité P(SLi) est fonction de la combinaison linéaire suivante : $${\mathrm{C}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{C}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}+{\mathrm{C}}_{\mathrm{TRANS}}{\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$$
  
  
  dans laquelle ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$
  
  est un indice de confiance fonction de chaque limitation de vitesse SLi possible et d'une transition de vitesses possible ; et
  C_TRANS est un coefficient de pondération prédéfini lié à la transition de vitesses possible ;
• l'indice de confiance ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$
  
  est extrait d'une table de transitions établie au préalable, donnant toutes les valeurs d'indice de confiance pour chaque limitation de vitesse possible et pour chaque transition de vitesses possible ;
• l'indice de confiance ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$
  
  est extrait d'une table de contextes établie au préalable, donnant toutes les valeurs d'indice de confiance pour chaque limitation de vitesse possible et pour chaque contexte ;
• la table de contextes est mise à jour par apprentissage ;
• le coefficient de pondération C_CONT associé au contexte a une valeur supérieure à celle du coefficient de pondération C_NAV associé à la navigation.
• le coefficient de pondération C_TRANS associé à la transition de vitesses possible à une valeur comprise entre la valeur du coefficient de pondération C_CONT associé au contexte et la valeur du coefficient de pondération C_NAV associé à la navigation ;
• l'indice de confiance ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$
  
  est fixé à 1 si la limitation de vitesse SLi possible est égale à la limitation de vitesse vraisemblable SL_NAV, et à 0 sinon ;
• la limitation de vitesse en vigueur sur la route considérée déterminée correspond à la limitation de vitesse possible associée à la plus grande probabilité P(SLi).
• l'ensemble prédéterminé de limitations de vitesse règlementaires est fonction du pays.

In addition to the main features which have just been mentioned in the preceding paragraph, the method according to the invention may have one or more additional characteristics among the following:

• said at least one attribute relating to a road context data makes it possible to distinguish the road contexts in the set {city, motorway, exit, other};
• the extraction step comprises a determination of said road context from a first attribute relating to the type of road, and a second attribute relating to the driving situation, the first and second attributes being delivered by the navigation system. ;
• the determination step comprises, for each possible speed limitation SLi taken in a predetermined set of regulatory speed limits, a calculation of a probability P (SLi) according to the following linear combination: $${\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$$
  
  
  in which ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$
  
  is a confidence index function of each possible speed limit SLi and the extracted context;
  ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$
  
  is a confidence index according to each speed limitation SLi possible and the probable speed limitation SL _NAV provided by the navigation system; and
  C _CONT and C _NAV are two predefined weighting coefficients related respectively to context and navigation;
• alternatively, the calculation of the probability P (SLi) is a function of the following linear combination: $${\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{TRANS}}{\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$$
  
  
  in which ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$
  
  is a confidence index according to each speed limitation SLi possible and a possible speed transition; and
  C _TRANS is a predefined weighting coefficient related to the possible speed transition;
• the confidence index ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$
  
  is extracted from a previously established transition table, giving all the confidence index values for each possible speed limit and for each possible speed transition;
• the confidence index ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$
  
  is extracted from a previously established context table, giving all the confidence index values for each possible speed limit and for each context;
• the context table is updated by learning;
• the weighting coefficient C _CONT associated with the context has a value greater than that of the weighting coefficient C _NAV associated with the navigation.
• the weighting coefficient C _TRANS associated with the possible speed transition to a value between the value of the weighting coefficient C _CONT associated with the context and the value of the _NAV weighting coefficient C associated with navigation;
• the confidence index ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$
  
  is set to 1 if the speed limitation SLi possible is equal to the probable speed limitation SL _NAV , and to 0 otherwise;
• the speed limit in effect on the considered road determined corresponds to the possible speed limitation associated with the highest probability P (SLi).
• the predetermined set of regulatory speed limits is country dependent.

• des moyens aptes à extraire, à partir d'au moins un attribut délivré par le système de navigation et portant sur une donnée de contexte routier, un contexte routier dans lequel le véhicule se trouve ;
• des moyens de détermination de la limitation de vitesse en vigueur sur la route considérée, à partir de ladite limitation de vitesse vraisemblable et en prenant en considération ledit contexte routier extrait.

The present invention also relates to a system for automatically determining a speed limit in force on a road taken, or about to be borrowed, by a motor vehicle, comprising a first system, said navigation system, making interfering in particular with a geographical positioning system and mapping data to establish a probable speed limitation, characterized in that it comprises:

• means capable of extracting, from at least one attribute issued by the navigation system and relating to a road context datum, a road context in which the vehicle is located;
• means for determining the speed limit in force on the road considered, based on said probable speed limitation and taking into consideration said road context extracted.

• la figure 1 représente schématiquement un système pour la détermination automatique d'une limitation de vitesse en vigueur sur une route empruntée, ou sur le point d'être empruntée, par un véhicule automobile selon une mise en oeuvre possible d' l'invention;
• la figure 2 illustre un exemple d'une table dite de contextes établie en fonction de contextes de navigation, conformément au principe de la présente invention ;
• la figure 3 illustre un exemple de calcul pour la détermination d'une vitesse de limitation, utilisant la table de contextes de la figure 2;
• la figure 4 donne un exemple d'une table de transition de vitesses susceptible d'être utilisée dans une variante du procédé selon l'invention ;
• la figure 5 illustre un autre exemple de calcul intervenant dans la détermination d'une vitesse de limitation, utilisant la table de contextes de la figure 2 et la table de transition de vitesses de la figure 4 ;
• la figure 6 représente schématiquement une autre architecture d'un système implémentant l'invention.

The invention will be better understood on reading the description which follows, made with reference to the appended figures, in which:

• the figure 1 schematically represents a system for the automatic determination of a speed limit in effect on a road taken, or about to be taken, by a motor vehicle according to a possible implementation of the invention;
• the figure 2 illustrates an example of a so-called context table established according to navigation contexts, in accordance with the principle of the present invention;
• the figure 3 illustrates an example of calculation for the determination of a speed of limitation, using the context table of the figure 2 ;
• the figure 4 gives an example of a speed transition table that can be used in a variant of the method according to the invention;
• the figure 5 illustrates another example of calculation involved in the determination of a limiting speed, using the context table of the figure 2 and the speed transition table of the figure 4 ;
• the figure 6 schematically represents another architecture of a system implementing the invention.

The different elements appearing in several figures will have kept, unless otherwise stated, the same reference.

With reference to the figure 1 , a possible architecture for a system 1 for automatically determining a speed limit in force on a road taken, or about to be borrowed, by a motor vehicle according to the invention will now be described: The system 1 uses, in accordance with the invention, information delivered by an on-board navigation system 2 including a data receiver 10 of a geographical positioning system embedded on said motor vehicle associated with an antenna 21 and mapping data from of a database 22. The navigation system 2 may furthermore use other sensors 23 (speed sensor, gyroscope, etc.) capable of delivering various information making it possible in particular to check the coherence between the route actually taken by the vehicle, and the route provided by the navigation system 2.

The navigation system 2 provides a likely speed limitation which will be noted in the SL _NAV suite.

The navigation system 2 will also provide, in a known and non-detailed manner, a certain number of attributes, for example a first attribute relating to the type of road (motorway, national, departmental, municipal ...), and a second attribute relating to the driving situation (city, out of town, intersection ..).

According to the invention, a processing module 10 of the system 1 will extract, from at least one attribute Att issued by the navigation system 2 and relating to a road context data, the road context in which the vehicle is traveling. find and then determine the speed limit in effect SL _S on the considered route, starting from the probable speed limitation SL _NAV and taking into consideration the said road context extracted.

• ville,
• autoroute,
• sortie,
• autre.

By way of nonlimiting example, the joint use of the first attribute relating to the type of road, and the second attribute relating to the driving situation makes it possible to distinguish the following four road contexts:

• city,
• highway
• exit,
• other.

pour chaque contexte.Once the road context has been extracted, the processing module 10 uses a prior context table 11, which groups, for each possible speed limit SLi corresponding to a regulatory speed limit, confidence indices. ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$

for each context.

pour seize limitations de vitesse possibles, notées de SL1 à SL16, et dans chacun des quatre contextes routiers précités (V = Ville ; A= Autoroute ; S= Sortie ; O= Autre).The figure 2 gives an example of contents of a table 11 giving values of the confidence indices ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$

for sixteen possible speed limits, noted from SL1 to SL16, and in each of the four aforementioned road contexts (V = city, A = highway, S = exit, O = other).

• { 5 ; 10 ; 20 ; 30 ; 45 ; 50 ; 60 ; 70 ; 80 ; 90 ; 100 ; 110 ; 120, 998, 999}

The speed limits SL1 to SL14 correspond here to all the regulatory speed limits (SL _R in km / hour) that we find depending on the country in which the vehicle is driven, for example, for France. following set:

• {5; 10; 20; 30 ; 45; 50; 60; 70; 80; 90; 100; 110; 120, 998, 999}

Two speed limits SL15 and SL16 are furthermore preferably used for unknown speed, for example 998 when the navigation is not able to deliver information on the speed of a portion of road and implicit speed, for example 999, during an end of speed limit detection.

The number in bold in each of the last four columns of the table 11 corresponds to the highest confidence index of the column, and thus makes it possible to identify the most likely speed limit for a given context. Thus, in the "City" context or in the "Exit" context, it is the speed limit SL6, ie 50 km / h in France, which has the highest probability of being met (confidence index equal to 0.936 or at 0.436) while in the "Other" context, the most likely speed limit is SL10, which is 90 km / h in France, with a confidence index of 0.76.

Table 11 of contexts, such as the one shown in figure 2 , is obtained beforehand and stored in the system 1 on board the vehicle. It can be advantageously updated by learning by performing statistics on the different contexts encountered when the vehicle is traveling.

dans laquelle :

• ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$
  
  est l'indice de confiance fonction de chaque limitation de vitesse SLi possible et du contexte extrait, que l'on retrouve dans la table 21 de contextes ;
• ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$
  
  est un indice de confiance fonction de chaque limitation de vitesse SLi possible et de la limitation de vitesse vraisemblable SL_NAV fournie par le système 2 de navigation; et
• C_CONT et C_NAV sont deux coefficients de pondération prédéfinis liés respectivement au contexte et à la navigation.

From this table 11 of contexts, the processing module 10 will calculate, for each possible speed limitation, and according to the context extracted a probability P (SLi) function of the following linear combination: $${\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$$

in which :

• ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$
  
  is the confidence index function of each possible speed limit SLi and the extracted context, which is found in the context table 21;
• ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$
  
  is a confidence index according to each speed limitation SLi possible and the probable speed limitation SL _NAV supplied by the navigation system 2; and
• C _CONT and C _NAV are two predefined weighting coefficients related respectively to context and navigation.

avec ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=1$

si SLi = SL_NAV et
${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=0$

sinonEach probability P (SLi) is for example calculated by applying the following relation: $$\mathrm{P}\left(\mathrm{SLi}\right)=\frac{{\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{<figure-callout\; id="2"\; label="\alpha \; NAV\; i"\; filenames="imgf0001.png,imgf0004.png"\; state="\{\{state\}\}">\alpha \; </figure-callout>}}_{\mathrm{NAV}\mathrm{i}}^{\mathrm{}}}{\mathrm{2}}$$

with ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=1$

if SLi = SL _NAV and
${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=0$

if not

• C_CONT = 0,7
• C_NAV = 0,2

The values of the weighting coefficients C _LOD and C _NAV depend on the importance that we want to give to the navigation system 2 on the one hand, and to the table 11 of the contexts on the other hand. The weighting coefficient C _CONT associated with the context preferably has a value greater than that of the weighting coefficient C _NAV associated with the navigation. We can choose for example:

• C _CONT = 0.7
• C _NAV = 0.2

pour le contexte « Autre » (valeur récupérée dans la table 11 de contexte), la cinquième colonne donne la valeur utilisée pour le coefficient de pondération C_NAV, et la sixième colonne donne la valeur de l'indice de confiance ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}\mathrm{.}$

Dans cet exemple, seule la limitation de vitesse SL8 (70 km/h) a un indice de confiance ${\mathrm{\alpha }}_{\mathrm{NAV}}^8$

égal à 1, puisque la limitation de vitesse vraisemblable SL_NAV fournie par le système 2 de navigation est de 70km/h. La dernière colonne de la figure 3 indique le résultat du calcul de la probabilité P(SLi) avec l'équation (1) ci-dessus. Dans cette colonne, le nombre en gras identifie la probabilité la plus forte, ici 0,266, qui correspond à la limitation de vitesse SL10 (soit 90 km/h).The figure 3 gives an example of the probability calculations performed by the processing module 10 in a particular situation for which the navigation system 2 provides the value of 70 km / h as a probable speed limitation SL _NAV , while the context extracted by the module 10 of treatment corresponds to the "Other" road context. The first column of the figure 3 indicates all possible speed limits SLi. The second column gives the correspondence with the regulatory speed limits, according to the country, the third column gives the value used for the weighting coefficient C _CONT , the fourth column gives the value of the confidence index ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$

for the "Other" context (value retrieved in the context table 11), the fifth column gives the value used for the weighting coefficient C _NAV , and the sixth column gives the value of the confidence index ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}\mathrm{.}$

In this example, only the speed limit SL8 (70 km / h) has a confidence rating ${\mathrm{\alpha }}_{\mathrm{NAV}}^{}$${\mathrm{}}_8^{}$

equal to 1, since the probable speed limitation SL _NAV provided by the navigation system 2 is 70km / h. The last column of the figure 3 indicates the result of the calculation of the probability P (SLi) with equation (1) above. In this column, the number in bold identifies the highest probability, here 0.266, which corresponds to the speed limit SL10 (ie 90 km / h).

Here, the system 1 will therefore determine that the speed limit SL _S prevailing on the road taken is the speed limit SL10 (ie 90 km / h), while the navigation system proposed 70 km / h.

pour chaque transition possible de vitesse.In a variant of the method according to the invention, it is possible to use, in addition to the table 11 of contexts described above, another table 12, called speed transition table, grouping, for each possible speed limitation SLi corresponding to a limitation regulatory speed, confidence indexes ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

for each possible transition of speed.

pour les seize limitations de vitesse possibles SL1 à SL16. Chaque ligne de cette table 12 donne la probabilité pour qu'il y ait une transition d'une première limitation de vitesse possible à une deuxième limitation de vitesse possible. Par exemple, pour la limitation de vitesse possible SL8 (ici 70 km/h), l'indice de confiance correspondant à la probabilité que l'on passe de la limitation de vitesse SL8 à l'une quelconque des lim itations de vitesse SL1 à SL5 est égal à 0, alors que l'indice de confiance correspondant à la probabilité que l'on passe de la limitation de vitesse SL8 à la limitation de vitesse SL6 (soit 50 km/h) est de 0,4642. Ici encore, la valeur la plus importante dans chaque ligne a été mise en gras.The figure 4 gives an example of the contents of a table 12 giving values of the confidence indices ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

for the sixteen possible speed limits SL1 to SL16. Each row of this table 12 gives the probability that there is a transition from a first possible speed limit to a second possible speed limitation. For example, for the possible speed limit SL8 (in this case 70 km / h), the confidence index corresponding to the probability that the SL8 speed limit is passed to any of the speed limits SL1 to SL5 is equal to 0, while the confidence index corresponding to the probability of passing from the SL8 speed limit to the speed limit SL6 (ie 50 km / h) is 0.4642. Here again, the most important value in each row has been bolded.

The speed transition table 12, such as that shown in FIG. figure 3 , is also obtained beforehand and stored in the system 1 on board the vehicle. It can be advantageously updated by learning by performing statistics on the situations encountered when the vehicle is traveling.

dans laquelle ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

est un indice de confiance fourni par la table 12 de transitions de vitesses ; etIn this variant, the probability P (SLi) then becomes a function of the following linear combination: $${\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{TRANS}}{\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$$

in which ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

is a confidence index provided by the table 12 of transitions of speeds; and

C _TRANS is a predefined weighting factor related to the possible speed transition.

Here again, the value of the weighting coefficient C _TRANS depends on the importance that is to be given to the table 12 of speed transitions. The weighting coefficient C _TRANS preferably has a value between the value of the weighting coefficient C _CONT associated with the context and the value of the weighting coefficient C _NAV associated with the navigation.

avec ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=1$

si SLi = SL_NAV et
${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=0$

sinonEach probability P (SLi) is for example calculated by applying the following relation: $$\mathrm{P}\left(\mathrm{SLi}\right)=\frac{{\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{TRANS}}{\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}}{3}$$

with ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=1$

if SLi = SL _NAV and
${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}=0$

if not

• C_CONT = 0,7
• C_NAV = 0,2 et
• C_TRANS = 0,3

We can choose for example:

• C _CONT = 0.7
• C _NAV = 0.2 and
• C _TRANS = 0.3

pour le contexte « Autre » (valeur récupérée dans la table 11 de contexte), la cinquième colonne donne la valeur utilisée pour le coefficient de pondération C_NAV, la sixième colonne donne la valeur de l'indice de confiance ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}},$

la septième colonne donne la valeur utilisée pour le coefficient de pondération C_TRANS, et la huitième colonne donne la valeur de l'indice de confiance ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

pour une transition de la limitation de vitesse précédemment conseillée (dans notre exemple 50 km/h) à l'une quelconque des limitations de vitesses possible. La huitième colonne correspond donc à la ligne SL6 de la table 12 montrée en figure 4. Dans cet exemple, seule la limitation de vitesse SL8 (70 km/h) a un indice de confiance ${\mathrm{\alpha }}_{\mathrm{NAV}}^8$

égal à 1, puisque la limitation de vitesse vraisemblable SL_NAV fournie par le système 2 de navigation est de 70km/h. La dernière colonne de la figure 5 indique le résultat du calcul de la probabilité P(SLi) avec l'équation (2) ci-dessus. Dans cette colonne, le nombre en gras identifie la probabilité la plus forte, ici 0,207333, qui correspond à la limitation de vitesse SL10 (soit 90 km/h).The figure 5 gives an example of the calculations of probabilities performed by the processing module 10 according to this variant, always in a particular situation for which the navigation system 2 provides the value of 70 km / h as a probable speed limitation SL _NAV , while the context extracted by the processing module 10 corresponds to the "Other" road context. It is also assumed that the speed limit previously recommended by system 1 was 50 km / h. The first column of the figure 5 indicates all possible speed limits SLi. The second column gives the correspondence with the regulatory speed limits, according to the country, the third column gives the value used for the weighting coefficient C _CONT , the fourth column gives the value of the confidence index ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$

for the "Other" context (value retrieved from the context table 11), the fifth column gives the value used for the weighting coefficient C _NAV , the sixth column gives the value of the confidence index ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}},$

the seventh column gives the value used for the weighting coefficient C _TRANS , and the eighth column gives the value of the index of confidence ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

for a transition from the previously recommended speed limit (in our example 50 km / h) to any of the possible speed limits. The eighth column thus corresponds to the line SL6 of the table 12 shown in figure 4 . In this example, only the speed limit SL8 (70 km / h) has a confidence rating ${\mathrm{\alpha }}_{\mathrm{NAV}}^{}$${\mathrm{}}_8^{}$

equal to 1, since the probable speed limitation SL _NAV provided by the navigation system 2 is 70km / h. The last column of the figure 5 indicates the result of the calculation of the probability P (SLi) with equation (2) above. In this column, the number in bold identifies the strongest probability, here 0.207333, which corresponds to the speed limit SL10 (ie 90 km / h).

Here again, the system 1 will therefore determine that the speed limit SL _S in force on the road taken is the speed limit SL10 (ie 90 km / h), while the navigation system proposed 70 km / h.

The method for determining the speed limitation SL _S is applicable when the data coming from a navigation system 2 is used, in this case the probable speed limitation SL _NAV and the attributes making it possible to extract the speed. road context.

As shown schematically on the figure 6 , the system 1 as just described can also be a subsystem of a more complex system 3, such as that described in the document EP 2 017 807 , which merges in normal time a probable speed limitation data SL _NAV supplied by a navigation system 2, and a probable speed limitation data item SL _IMG provided by an image processing system 4 notably involving a camera 41 and image processing applications 42 capable of identifying and interpreting speed limitation arranged in the vicinity of the road. In this case, the subsystem 1 will be activated only in situations where the system 3 operates in a degraded mode in which only a probable speed limitation SL _NAV is available. Such a situation is encountered, for example, when the image processing system 4 detects a panel corresponding to a speed limit end, for example a city exit, or a panel dedicated to the end of limitation (generally a panel circular barred), and then delivers an EOSL signal (English initials set for End of Speed Signal Limitation).

Claims (15)

A method for automatically determining a speed limit (SL _S ) in force on a road taken, or about to be taken, by a motor vehicle, in which a first system (2) is established , said navigation system including a data receiver (20, 21) of a geographical positioning system embarked on said motor vehicle and mapping data (22), a probable speed limitation (SL _NAV ), the method characterized in that it comprises the following steps: extracting, from at least one attribute (Att) delivered by the navigation system (2) and relating to a road context datum, a road context in which the vehicle is located; - determine the speed limit in force (SL _S ) on the considered route, from the said probable speed limitation (SL _NAV ) and taking into consideration the said road context extracted. Method according to claim 1, characterized in that said at least one attribute relating to a road context data makes it possible to distinguish the road contexts in the whole {city, motorway, exit, other}. Method according to claim 2, characterized in that the extraction step comprises a determination of said road context from a first attribute relating to the type of road, and a second attribute relating to the driving situation, the first and second attributes being delivered by the navigation system (2). Method according to one of the preceding claims, characterized in that the determining step comprises, for each possible speed limitation SLi taken in a predetermined set of regulation speed limits, a calculation of a probability P (SLi) function of the following linear combination: $${\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$$

in which ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$

is a confidence index function of each possible speed limit SLi and the extracted context;
${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$

is a confidence index according to each possible speed limit SLi and the probable speed limitation SL _NAV supplied by the navigation system (2); and
C _CONT and C _NAV are two predefined weighting coefficients related respectively to context and navigation. Method according to Claim 4, characterized in that the calculation of the probability P (SLi) is a function of the following linear combination: $${\mathrm{VS}}_{\mathrm{CONT}}{\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{NAV}}{\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}+{\mathrm{VS}}_{\mathrm{TRANS}}{\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$$

in which ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

is a confidence index according to each speed limitation SLi possible and a possible speed transition; and
C _TRANS is a predefined weighting factor related to the possible speed transition. Process according to Claim 5, characterized in that the confidence index ${\mathrm{\alpha }}_{\mathrm{TRANS}}^{\mathrm{i}}$

is extracted from a predefined transition table (12) giving all the confidence index values for each possible speed limit and for each possible speed transition. Process according to one of Claims 4 to 6, characterized in that the confidence index ${\mathrm{\alpha }}_{\mathrm{CONT}}^{\mathrm{i}}$

is extracted from a table (11) of previously established contexts, giving all the confidence index values for each possible speed limitation and for each context. Method according to claim 7, characterized in that said context table (11) is updated by learning. Method according to one of Claims 4 to 8, characterized in that the weighting coefficient C _CONT associated with the context has a value greater than that of the weighting coefficient C _NAV associated with the navigation. Method according to claims 5 and 9, characterized in that the weighting coefficient C _TRANS associated with the possible speed transition to a value between the value of the weighting coefficient C _CONT associated with the context and the value of the weighting coefficient C _NAV associated with navigation. Process according to one of Claims 4 to 10, characterized in that the confidence index ${\mathrm{\alpha }}_{\mathrm{NAV}}^{\mathrm{i}}$

is set to 1 if the speed limit SLi possible is equal to the probable speed limitation SL _NAV , and to 0 otherwise. Method according to one of Claims 4 to 11, characterized in that the current speed limit (SL _S ) on the considered route corresponds to the possible speed limitation associated with the highest probability P (SLi). A method as claimed in any one of claims 4 to 12, characterized in that the predetermined set of regulatory speed limits is country dependent. System (1) for automatically determining a speed limit (SL _S ) in force on a road taken, or about to be taken, by a motor vehicle, comprising a first system (2), said navigation system , including geographical positioning system (20, 21) and mapping data (22) for establishing a probable speed limitation (SL _NAV ), characterized in that it comprises: means (10) capable of extracting, from at least one attribute issued by the navigation system (2) and relating to a road context datum, a road context in which the vehicle is located; means (10, 11, 12) for determining the speed limitation in effect (SL _S ) on the road in question, based on said probable speed limitation (SL _NAV ) and taking into consideration said extracted road context. System (1) according to Claim 14, characterized in that it constitutes a subsystem of a fusion system (3) capable of automatically determining a speed limit in force on a borrowed road, or on the point of departure. be borrowed, by a motor vehicle, on the one hand, from the probable speed limitation (SL _NAV ) provided by the navigation system, and on the other hand, from a probable speed limitation (SL _IMG ) provided by an image processing system (4) including in particular a camera (41) and image processing applications (42) able to identify and interpret speed limitation panels arranged in the vicinity of the road, said sub-station the system (1) being activated when the image processing system (4) delivers a signal (EOSL) representative of the detection of an end of speed limitation panel.

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