FR3141911A1 - Method and system for managing the longitudinal speed of a vehicle - Google Patents

Abstract

TITLE: Method and system for managing the longitudinal speed of a vehicle in the rolling phase Method and system for managing the longitudinal speed of a vehicle in the rolling phase equipped with at least one driving assistance system allowing , when a speed limit sign is detected, to implement the reconstruction of an external environment in order to define a longitudinal speed adapted to the type of road on which the vehicle is traveling when other systems or means equipping the vehicle, such as a means of location, do not present performances adapted to optimal longitudinal speed recommendations. No figure for the abstract

Description

Method and system for managing the longitudinal speed of a vehicle

The invention relates to a method for managing the longitudinal speed of a vehicle, in particular when a traffic sign indicating a longitudinal speed is detected. The invention also relates to a system for managing the longitudinal speed of a vehicle. The invention also relates to a computer program product implementing the mentioned method.

In the automotive industry, it is known to equip vehicles with driving assistance systems, or ADAS, from the English “Advance Driving Assist System” including in particular a Contextual adaptive automatic cruise control system, also known under the acronym ACC Contextual or Contextual ACC from the English “Contextual Adaptive Cruise Control”, making it possible to adapt the speed of the vehicle according to the context in which the vehicle is traveling, in particular according to authorized longitudinal speed limit signs detected. In such systems, the speed limit signs are detected by a camera located at the front of the vehicle and/or via a mapping system, for example communicated by a location means such as a GPS .

Conventionally, a CASP module, from the English acronym “Contextual Adaptive Speed Prevention”, provides the ADAS system with a speed recommendation to apply. This recommendation can be made from the images provided by the camera and/or on the basis of positioning information of the vehicle in the road infrastructure provided by the location means. However, in the case of complex road infrastructures, for example around intersections, junctions or a plurality of roads overlapping on several levels, it has been noted that the speed recommendation to be applied could be incorrect. For example, such a recommendation may be based on the detection of irrelevant speed limit signs relating to a road adjacent to that traveled by the vehicle, to a fork or exit from a road, particularly a motorway.

In such situations, the map information provided by the tracking means is essential to the identification of relevant speed limits. The precision of the means of locating the vehicle in the road infrastructure is nevertheless dependent on numerous conditions, external and internal to the vehicles, such as weather conditions, topographies, satellites, or even the longitudinal speed of the vehicle. The precision of the location means may then be too low to allow suitable longitudinal speed recommendations.

Due to these drawbacks, the Contextual ACC system may be required to impose on the vehicle a longitudinal speed that is unsuitable for its driving situation, particularly in untimely braking situations. This can then result, on the one hand, in anxiety-provoking situations for the driver and passengers of the vehicle and, on the other hand, in risky situations, for the equipped vehicle and the surrounding vehicles.

The invention is part of this context and aims to provide a method for managing the longitudinal speed of an ego vehicle in the driving phase equipped with at least one location means and a driving assistance system capable of regulating the longitudinal speed of said vehicle, the method comprising, when a speed limit sign indicative of a longitudinal speed is detected:
- a step of verifying the precision of a position of the ego vehicle in a road infrastructure, implemented via the location means;
- a step of detecting an external environment surrounding the vehicle via at least one detection means;
- a step of reconstructing the external environment on the basis of the acquired data relating to the external environment so as to define whether a road traveled by the ego vehicle is a main road, on which a first longitudinal speed limit is imposed, or a secondary road, coming from the main road and on which a second speed limit is imposed, strictly lower than the first speed limit;
- a step of determining a longitudinal speed to be applied to the ego vehicle on the basis of the calculated reconstruction data of the environment external to the ego vehicle depending on whether the route traveled is defined as being a main road or a secondary road.

The step of verifying the precision of a position of the ego vehicle may include a sub-step of evaluating, via the location means, a confidence index defined as a function of a context external to the vehicle ego and representative of a degree of precision of the position of the ego vehicle, the step of determining the longitudinal speed being implemented when the defined confidence index is less than a predefined confidence threshold.

The reconstruction step may include a sub-step of detecting the presence or absence of a traffic lane of the road traveled by the ego vehicle laterally interposed between the detected speed limit sign and the ego vehicle when the latter passes to the right of said sign, the route traveled being defined as being secondary if:
- when the ego vehicle does not detect the presence of a traffic lane interposed between the speed limit sign and the ego vehicle, a lateral distance separating the ego vehicle from the sign is greater than a first predefined lateral distance threshold; and or
- when the ego vehicle detects the presence of at least one traffic lane interposed between the speed limit sign and the ego vehicle, a lateral distance separating the ego vehicle from the sign is greater than a second predefined lateral distance threshold, the second threshold being defined as a function of the first lateral distance threshold and as a function of the number of interposed traffic lanes(s) detected.

In particular, the second threshold can be defined as a function of an average width of the at least one traffic lane interposed between the ego vehicle and the speed limit sign, estimated over a predefined distance.

In particular, during the reconstruction stage, the route traveled can be defined as secondary if:
- a variation of a detection angle, in particular an angle of view, of at least one detection means, in particular of a camera, greater than or equal to a predefined variation threshold is detected over a predetermined period;
- a radius of curvature of the route traveled less than or equal to a predefined curvature threshold is detected by at least one detection means, in particular a camera; and or
- an approaching roundabout is detected.

In particular, during the reconstruction step, the route traveled can be defined as being main if, for a vehicle approaching in a direction of travel opposite to a direction of travel of the ego vehicle, a lateral interval separating said approaching vehicle from the ego vehicle is included in a range of predefined lateral distance values estimated representative of the position and/or dimensions of a road adjacent to the road traveled by the ego vehicle within the road infrastructure.

In particular, during the reconstruction stage, a road is defined as being main if:
- a situation of instability is detected in the detection of the longitudinal speed, corresponding to a situation of successive detections of a plurality of speed limit signs indicating one or more distinct longitudinal speeds over a predefined detection period; and or
- a situation of inconsistency is detected between data relating to the environment external to the ego vehicle, measured by the at least one detection means, and navigation and/or mapping data; and or
- speed limit signs are detected on either side of the road traveled by the ego vehicle.

The step of determining the longitudinal speed may include a sub-step of grouping one or more types of data for reconstructing the external environment, the determination step comprising:
- the confirmation or denial of a longitudinal speed previously recommended to the driving assistance system on the basis of the reconstruction data; Or
- calculating a longitudinal speed to be applied on the basis of the reconstruction data.

The invention also relates to a system for managing the longitudinal speed of a vehicle in the driving phase for a vehicle, the system comprising hardware and/or software elements implementing the method according to the invention, the hardware elements comprising at least memory element, a processing unit, a location means and at least one means for detecting the external environment.

The invention also relates to a computer program product comprising program code instructions recorded on a computer readable medium for implementing the steps of the method according to the invention when said program operates on a computer. Alternatively, the invention relates to a computer program product downloadable from a communications network and/or recorded on a data carrier readable by a computer and/or executable by a computer, comprising instructions which, when the program is executed by the computer, lead it to implement the method according to the invention.

The invention also relates to a motor vehicle equipped with a management system according to the invention.

The present invention also extends to a computer program product comprising program code instructions recorded on a computer-readable medium for implementing the steps of the method as explained above when said program operates on a computer . Alternatively, the invention may relate to a computer program product downloadable from a communications network and/or recorded on a data medium readable by a computer and/or executable by a computer, the program comprising instructions which, when the program is executed by the computer, lead it to implement the method according to the invention.

The invention also relates to a data recording medium, readable by a computer, on which is recorded a computer program comprising program code instructions for implementing the method according to the invention or on a medium of computer-readable record comprising instructions which, when executed by a computer, cause it to implement the management method according to the invention.

Finally, the invention may relate to a signal from a data carrier carrying the computer program product as explained previously.

Other details, characteristics and advantages will emerge more clearly on reading the detailed description given below, for information only and not limitation, in relation to the different examples of embodiment illustrated in the following figures:

There schematically represents an embodiment of a vehicle equipped with a management system according to the invention.

There is a general flowchart for executing a management method according to the invention.

There is a flowchart detailing the stages of the management process.

There is a schematic representation of the road infrastructure in which the vehicle travels.

There schematically illustrates a motor vehicle 1 according to one embodiment of the invention. The vehicle can be of any type. In particular, it can be a private vehicle, a utility vehicle, a truck or a bus. Also, the vehicle can be an autonomous vehicle.

Throughout the description below, the vehicle 1 comprising the means of implementing the invention can also be called "ego" vehicle in order to distinguish it from other surrounding vehicles and does not in itself confer any technical limitation. to the motor vehicle.

The vehicle 1 comprises hardware and/or software elements capable of implementing a method of managing 100 the longitudinal speed of the vehicle during the driving phase, as illustrated in Figures 2 and 3 and detailed below.

The vehicle 1 is equipped with at least one driving assistance system 2, or ADAS, from English "Advance Driving Assist System", including in particular a Contextual adaptive automatic cruise control system, also known as acronym ACC Contextual or Contextual ACC from the English “Contextual Adaptive Cruise Control”, making it possible to adapt the speed of the vehicle according to the context in which the vehicle is traveling, in particular according to authorized longitudinal speed limit signs. In known manner, such a driving assistance system 2 is capable of identifying situations relating to the external environment, particularly traffic or speed limit signs.

The vehicle also includes a CASP 3 module, from the English acronym "Contextual Adaptive Speed Prevention", capable of providing the driving assistance system 2 with a longitudinal speed recommendation to be applied to the ego vehicle based on data relating to the the environment external to the vehicle, in particular, in a conventional and non-limiting manner, relative to the geometry and/or topology of a road traveled by the vehicle. In particular, the CASP module can be included in the driving assistance system 2.

The driving assistance system 2 and/or the CASP module 3 operate in particular on the basis of data relating to the external environment provided by at least one detection means 4 of the external environment fitted to the vehicle. For example, such detection means 4, or sensor, can be a radar and/or a lidar and/or a camera. Preferably, the ego vehicle 1 comprises a plurality of detection means 4, these being in particular capable of detecting traffic and/or speed limit signs, topography and/or geometry of the road, vehicles and/or or obstacles surrounding the ego vehicle. One or more detection means 4 can in particular be equipped at the front or on the side parts of the ego vehicle, for example at the side doors or mirrors.

The vehicle also includes means 5 for locating the position of the vehicle 1 in a road infrastructure, in particular by satellite. It integrates, for example, a vehicle location system 1 and/or a map of the road infrastructure. In particular, the location of vehicle 1 can be provided by a GPS type system, from the English acronym “Global Positioning system”. The location of the vehicle makes it possible to extract from a mapping database information concerning the road infrastructure and/or the topology and/or the geography of roads within a radius of a few hundred meters around the position of the vehicle 1 Alternatively or in addition, the location means 5 can be a location system on board the vehicle. The location means 5 may preferably include an inertial unit, also referred to as a vehicle dynamics motion analyzer, IMU or ADMA, from the English acronym “Automotive Dynamic Motion Analyzer”.

Vehicle 1 can also, preferably, be equipped with a horizon provider module, or “horizon provider” module in English. Such a module communicates with the location means 5 in order to provide it with an electronic horizon, also called e-horizon, comprising a set of possible roads or routes located in front of the vehicle, particularly over a defined distance, on the basis of the cartography. The electronic horizon associates with each road or route a probability of being traveled, that is to say selected, by the vehicle. In a manner known in the state of the art, a disadvantage of such modules in their conventional use lies in the fact that, in the event of a malfunction of the location means 5 resulting in the transmission of erroneous positioning data, the data provided by the horizon provider module, and therefore the electronic horizon, are also incorrect.

The vehicle 1 is also equipped with a management system 6 for the longitudinal speed of the vehicle. Said system comprises the hardware and/or software elements necessary for the implementation of the longitudinal speed management method 100 according to the invention, as explained below.

The management system 6 comprises at least one data processing unit 7, memory elements 8, a location means 5, in particular the location means 5 fitted to the vehicle as described above, and at least one detection means 4 of the external environment.

The processing unit 7 comprises at least one calculation unit comprising hardware and software resources, more precisely at least one processor, or microprocessor, cooperating with the memory elements 8. This calculation unit is capable of executing instructions for updating implementation of a computer program. The processing unit 7 of the longitudinal speed management system 6 is in particular capable of receiving data from the detection means(s) 4, the driving assistance system 2 and the location means 5.

The location means 5 of the longitudinal speed management system 6 is that fitted to the vehicle, described previously. It is particularly capable of transmitting data relating to the positioning of the vehicle in the road infrastructure to the processing unit 7. Similarly, the longitudinal speed management system 6 may include the horizon provider module as described previously or , alternatively, be able to receive data transmitted by said module, for example data relating to the electronic horizon.

The detection means 4 correspond to those described above and can be exclusive to the longitudinal speed management system 6 or, preferably, be common to other systems fitted to the vehicle, for example to the driving assistance system 2.

Optionally, the longitudinal speed management system 6 may include at least one of:
- a longitudinal speed control unit 9;

- a communication device 10 with a connected device;
- one or more measuring elements 11 of data relating to the vehicle 1, in particular the longitudinal speed of the vehicle 1.

- a human-machine interface 12, for example comprising a screen.

The longitudinal speed control unit 9 is able to intervene on the vehicle, for example on the driving assistance system 2, in order to modify its operation, in this case in order to modify its speed longitudinal, for example by acceleration or braking, or in order to maintain a longitudinal speed implemented by the vehicle.

The communication device 10 allows the vehicle 1 to receive data from connected devices. The connected devices can be a connected telephone of a passenger of the ego vehicle or of a surrounding vehicle, a connected remote vehicle or even an element of road or urban infrastructure connected by means of a low frequency wireless link or high frequency. It may, for example, be a wireless connection based on “cellular”, “Wifi” or “Bluetooth” technologies. Such data may, in a non-exhaustive manner, relate to conditions external to the vehicle, for example weather or traffic conditions, or even topological or geographical conditions of the road infrastructure. Alternatively or in combination, the communication device 10 can be connected to a remote server in order to receive information relating to the environment outside the vehicle, for example depending on the location of the vehicle.

The measuring devices 11 fitted to the vehicle are configured to transmit to the processing unit 7 data relating to the interior environment of the vehicle, that is to say relating to the operation of the ego vehicle itself. Such measurements can be carried out, for example, in real time or at regular time intervals. In particular, the measuring elements 11 may be capable of carrying out, in a non-limiting manner, measurements relating to at least one of:
- the longitudinal speed of the ego vehicle;
- the acceleration and/or deceleration of the ego vehicle;
- the angle of the steering wheel, for example in order to define a heading for the ego vehicle.

The processing unit 7 of the longitudinal speed management system 6 is thus capable of receiving data from the communication device 10 and/or any measuring device 11 previously exposed when the ego vehicle is equipped with it.

An example of execution of the longitudinal speed management method 100 of a vehicle in the driving phase is described below with reference to Figures 2 and 3. The longitudinal speed management method 100 can also be considered as being a method of operating the longitudinal speed management system 6 according to the invention or as a method of operating a motor vehicle equipped with such a system.

The method 100 of managing the longitudinal speed of a vehicle in the driving phase according to the invention comprises, beforehand, a step of detecting a signaling sign E0 indicative of a longitudinal speed, in other words a speed limit sign. the legal longitudinal speed of vehicle circulation on a road traveled by the ego vehicle. Such a detection step E0 is executed according to known principles and means, in particular via the driving assistance system 2 and/or via at least one of the detection means 4, by example via at least one camera fitted to the vehicle. Also, the detection of such signs can be optimized by the location means 5, the positioning of the vehicle in the infrastructure making it possible to identify speed limit signs located near the vehicle. The vehicle is thus able to detect traffic signs, and particularly speed limit signs, located near a road traveled by the vehicle.

A disadvantage of such detections, noted in the state of the art, lies in the fact that the detection means 4 can, depending on the heading of the vehicle, detect signs relating to traffic lanes close to that traveled by the vehicle. . For example, when the vehicle is traveling on a highway type road, the detection means 4 can detect a sign relating to a bifurcation or exit road. The result is that the driving assistance system 2 detects unsuitable events relating to a road which is not relevant and, under recommendation of the CASP module 3, can impose on the vehicle a longitudinal speed which may be incorrect. Such a situation may be accompanied by untimely braking of the ego vehicle likely to create a danger for vehicles surrounding the ego vehicle.

Also, the location means 5 may, for variable reasons, have low precision, resulting in unsuitable positioning of the vehicle in the road infrastructure. If it is known to equip vehicles with alignment modules, or "map matching", aimed at repositioning the vehicle on a traffic route within the mapping of the road infrastructure, such positioning may be erroneous in the event of of a plurality of roads having a certain proximity, for example around bifurcations, intersections, or in the case of roads arranged on several vertical levels. The precision of the location means 5 may in particular be affected by numerous factors, such as relief, infrastructure elements such as bridges or tunnels, meteorological or atmospheric conditions, conditions relating to the universe, such as solar storms or obstacles present between the satellite and the vehicle, or the longitudinal speed of the vehicle. As a result, the positioning error can be greater than ten meters and the vehicle can be repositioned on an unsuitable road. The vehicle registration module then does not always allow the vehicle to be repositioned in an appropriate manner and speed limits detected via the location means 5 are then incorrect.

In order to resolve the aforementioned drawbacks, the method according to the invention comprises, when a traffic sign, and particularly a longitudinal speed limit sign, is detected during step E0, a verification step E1 of the precision of a position of the vehicle in the road infrastructure.

In particular, such a verification step is implemented by the location means 5. For example, the location means 5 can perform a sub-step E11 of evaluating a confidence index of the positioning data of the vehicle in the road infrastructure, representative of a degree of precision of said location means 5. The confidence index is in particular defined as a function of a context external to the vehicle, on the basis of data measured by the at least one detection means 4 and/or by the communication device 10. For example, such data may relate to the topology and/or geography of the road, to weather conditions or to all types of aforementioned factors likely to influence the precision of the location means 5. Additionally, the confidence index can be defined on the basis of the context internal to the vehicle, for example its longitudinal speed, provided by at least one of the measuring elements 11 fitted to the vehicle.

The processing unit 7 then executes a comparison sub-step E12 of the confidence index evaluated relative to at least one predefined confidence threshold S _c1 . For example, the confidence index can be defined in a confidence level scale produced as a function of a level of positioning precision, or in other words, an error distance, for example defined in meters. As a non-limiting example, the positioning of the vehicle in the road infrastructure has a high confidence index when the error distance is less than or equal to 5 meters, or even less than or equal to 3 meters. Conversely, the confidence index is low when the error distance is greater than such a value.

Thus, the precision of the location means 5 is considered reliable, therefore suitable for detection of speed limit signs and for operation of the driving assistance system 2 when the confidence index is present, during sub- comparison step, a value greater than or equal to the predefined confidence threshold S _c1 . Preferably, the method according to the invention can then be interrupted and the driving assistance system 2 can operate as it usually would.

Conversely, the precision of the location means 5 is considered insufficient, therefore unsuitable for reliable detection of speed limit signs, when the confidence index has a value lower than the predefined confidence threshold S _c1 . In order to remedy such a precision problem, the method according to the invention then executes the steps described below.

Alternatively, a similar principle can apply, mutatis mutandis , directly based on the error distance instead of a confidence index.

Optionally, the execution of the subsequent steps of the method according to the invention can, in addition, be conditioned on the detection of at least one additional road, that is to say in addition to a road traveled by the vehicle, near the ego vehicle. Such detection is carried out by the at least one detection means 4 fitted to the vehicle, in particular by a camera, and/or on the basis of data received via the communication device 10. In other words, the The execution of the subsequent steps of the method can be conditioned on the level of precision of the location means 5 and on the detection of a plurality of roads having a high proximity within the road infrastructure. Here we mean roads “near” or having “high proximity” to roads present at a distance less than or equal to 10 meters relative to a road traveled by the vehicle. For example, such proximity can be evaluated laterally relative to the vehicle. In particular, such proximity can be adapted depending on the context external to the vehicle as described above, for example depending on the topology and/or weather conditions.

The method according to the invention can thus include, when the precision of the location of the vehicle in the road infrastructure is insufficient:
- a step of detection E2 and reconstruction E3 of an external environment of the ego vehicle; And

- a step E4 of determining a longitudinal speed to be applied aimed at modifying or not the longitudinal speed implemented by the vehicle as a function of the reconstructed external environment.

During the detection step E2, the vehicle, via the at least one detection means 4, in particular via a camera and/or a RADAR and/or a LIDAR, extracts data relating to the immediate external environment surrounding the vehicle. We mean, for example, by “immediate” an external environment extending several hundred meters, around, and particularly in front and/or laterally, relative to the vehicle. These data can, generically, relate to the topology and/or geography of the route traveled, to a number of lanes forming the route traveled, to distances relative to objects or events, to vehicles surrounding the vehicle ego , traveling on the same road or on neighboring roads. In particular, in a non-limiting manner, the vehicle can extract, detect and/or calculate at least one of the following types of data:
- a lateral distance separating the vehicle from a speed limit sign, measured when the vehicle passes in line with such a sign, or separating the vehicle from an approaching vehicle;
- a width of a lane and/or a road comprising one or more lanes;
- an average width of one lane or several lanes;
- the presence of one or more lateral lane(s) relative to a lane in which the vehicle is traveling, that is to say one or more lane(s) laterally interposed between the vehicle and a lane emergency stop and/or a speed limit sign for example;
- a detection angle, or view, of the vehicle, in particular of the at least one detection means 4 and/or a variation of such a detection angle;
- a radius of curvature of a lane and/or a road comprising one or more lanes.

These data are then transmitted to the processing unit in order to define one or more factors for reconstructing the environment outside the vehicle.

The reconstruction step E3 of the external environment of the vehicle on the basis of all or part of the aforementioned acquired data aims to reconstruct the immediate external environment of the vehicle in order to define whether the vehicle is traveling on a main road or on a secondary road. , such a road can include one or more lanes, and thus adapt the speed of the ego vehicle only when the situation requires it.

In particular, the detection step E2 and/or the reconstruction step E3 is carried out when the vehicle is traveling in line with the detected speed limit sign.

Genericly, the term “main road” means a road on which a first longitudinal speed limit is imposed and the term “secondary road” means a road coming from the main road and on which a second speed limit is imposed, strictly lower than the first speed limit. In particular, the term “main road” means a road of the motorway or expressway type at which the first longitudinal speed is imposed and from which one or more secondary road(s) emerge. “Secondary roads” means roads coming off a main road, such as motorway exits, motorway ramps, “express lanes”, junctions or branches, that is to say non-main roads at meaning of the highway code.

The reconstruction step E3 can be based on one or more of the data types extracted from the environment, thus making it possible to define different identification factors of a type of road.

According to an example of execution of the method according to the invention, the processing unit 7 is capable of reconstructing the environment of the vehicle as a function of a factor based on the lateral distance Y_L _{_panel} separating the vehicle from a limitation panel previously detected speed, measured when the vehicle passes such a sign.

In particular, the reconstruction step E3 comprises, initially, a detection sub-step E31 of the presence or absence of a traffic lane of the road traveled by the vehicle laterally interposed between the speed limit sign and the vehicle when it passes to the right of said panel. It should be noted that the term "traffic lane" means a conventional traffic lane, temporary or not, and not a safety lane, emergency lane or emergency stopping lane, the processing unit 7 being capable of detecting differences in marking making it possible to distinguish an emergency stopping lane from a traffic lane. In particular, the processing unit 7 is capable of distinguishing differences in marking length and the interval of successive bands of a marking, for example on the basis of data provided by the camera.

Such a principle can be applied to the right of the vehicle as well as to its left, depending on the direction of travel of the vehicle and depending on the position of the speed limit sign considered relative to the vehicle.

In order to detect the presence or not of one or more lanes located laterally between the ego vehicle and the speed limit sign, in other words one or more lanes adjacent to a lane in which the vehicle is traveling. vehicle, the vehicle makes an estimate of a width LW _{_adj} of a lane or several lanes. To this end, the vehicle estimates the width separating two demarcation lines, or markings, delimiting the lane in question, one of said lines being qualified as a proximal line, because it presents the greatest proximity relative to the ego vehicle or to the lane in which circulates the ego vehicle, and the other being qualified as the distal line. As an example, the width LW _{_adj} of a lane considered can be defined as follows:

Or :

Pos_p_line corresponds to the detected position of the proximal line.

Pos_d_line corresponds to the detected position of the distal line.

Thus, if it is detected that none or only one demarcation line, and not a plurality, is laterally interposed between the vehicle, the processing unit 7 determines that no traffic lane is present between the lane in which the vehicle is traveling and the speed limit sign detected.

If a plurality of demarcation lines are detected as being laterally interposed between the vehicle and the detected speed limit sign, the processing unit 7 determines that no traffic lane is present between these if the width LW _{_adj} calculated between two adjacent lines is less than a track width threshold S _LW , defined as a function of a known track width, for example defined by national standards. In particular, the track width threshold S _LW is strictly less than a conventional known track width. For example, for tracks typically having a width of around 3 meters, or greater than 3 meters, the track width threshold S _LW can be of the order of 2 meters. Thus, if the processing unit 7 determines, on the basis of the data provided by the camera, that the width LW _{_adj} separating two adjacent lines is less than the lane width threshold S _LW , the processing unit 7 defines that no lane of traffic is present between the lane in which the vehicle is traveling and the speed limit sign detected.

Conversely, if the width LW _{_adj} calculated between two adjacent demarcation lines is greater than the lane width threshold S _LW , the processing unit 7 determines that a lane of traffic is laterally interposed between the ego vehicle, or the traffic lane in which it is traveling, and the speed limit sign.

A similar principle applies, mutatis mutandis , for a plurality of lanes interposed between the ego vehicle and the detected speed limit sign. In this case, the processing unit 7 calculates, for each detected lane, the lane width LW _{_adj_x} specific to each lane V _x .

Such a principle makes it possible to define at least in part whether the vehicle is traveling on a road with one or more lanes and, in the case of a road comprising a plurality of lanes, the positioning of the vehicle relative to said plurality of lanes. .

Once the processing unit 7 has defined whether or not one or more lanes were interposed between the vehicle and the speed limit sign, the processing unit 7 reconstructs the environment in order to 'evaluate whether the vehicle is moving on a secondary road or not via a comparison sub-step E32 of the lateral distance Y_L _{_panel} separating the vehicle from the speed limit sign with at least one predefined lateral distance threshold .

The lateral distance threshold to be taken into consideration is determined based on the presence or absence of one or more lanes interposed laterally between the vehicle and the speed limit sign. Such a threshold can be defined beforehand or calculated so as to take into account half the width of the traffic lane in which the ego vehicle is traveling as well as the presence of an emergency stopping lane laterally interposed between the ego vehicle. or the lane in which it is traveling, and the speed limit sign. Note that the half lane width can be calculated using a principle similar to that explained previously for calculating the width of an adjacent lane, so the previous description applies mutatis mutandis . Thus, in general, the lateral distance threshold considered is defined on the basis of half a width of the traffic lane in which the ego vehicle is traveling, a width of the emergency stopping lane and, so preferential of a distance margin of error, for example of the order of 1 meter.

In such a case, the lateral distance threshold can be a predefined fixed value or a parameterized value, for example selected or calculated according to the geographical location, in particular the country, of circulation of the ego vehicle.

According to an alternative not shown, the lateral distance threshold can be defined on the basis of a calculation carried out in real time on the basis of an estimate of the half width of the lane in which the ego vehicle is traveling and an estimate of the width of an emergency stop lane produced according to known methods, via the at least one detection means 4 and the processing unit 7.

When the vehicle does not detect the presence of a traffic lane interposed between the traffic sign and the vehicle during detection step E31 and it detects that the lateral distance Y_L _{_panel} separating the vehicle from the sign is greater than a first predefined lateral distance threshold S _LW1 , the processing unit 7 defines that, on the basis of the factor “lateral distance relative to the sign”, the road traveled by the vehicle is a secondary road. By way of non-limiting example, the first lateral distance threshold S _LW1 can be of the order of 6 meters in order to take into consideration a half lane width of the order of 2 meters, a stopping lane of emergency whose width is of the order of 3 meters and a distance margin of error of the order of 1 meter.

Similarly, when the vehicle detects the presence of at least one traffic lane laterally interposed between the traffic sign during step E32, if the processing unit 7 detects that the lateral distance Y_L_{_sign}is greater than a second lateral distance threshold S_LW2predefined, the processing unit 7 defines that, on the basis of the “lateral distance relative to the sign” factor, the road traveled by the vehicle is a secondary road. The second lateral distance threshold S_LW2can then be defined on the basis of the first lateral distance threshold S_LW1as well as on the basis of the number of previously detected traffic lanes laterally located between the ego vehicle and the detected speed limit sign. The second lateral distance threshold S_LW2 can then take into consideration a fixed, predefined width applied to each lane or, conversely, take into consideration the width LW_{_adj}previously calculated. By way of non-limiting example, when a traffic lane is laterally interposed between the ego vehicle, or its traffic lane, and the speed limit sign, the second lateral distance threshold S_LW2can be of the order of 10 meters in order to take into consideration the first width threshold of 6 meters previously defined and a width LW_fixedtrack of the laterally interposed traffic lane.

In the situations explained above, the different predefined thresholds can thus be defined on the basis of a width of the laterally interposed traffic lanes, or even of the traffic lane in the case of half width, predefined on the basis of standards, databases or even on the basis of information available via the mapping data provided by the location means 5.

Alternatively, such a width can be measured or estimated on an ad hoc basis, as explained above.

Optionally, and in particular preferentially in the case of the second lateral distance threshold, the value taken into consideration can be an average of the width HQ_LW _{_mean} of the traffic lane, laterally interposed, and/or an average of the width of the lane in which the ego vehicle is traveling, calculated over a predefined driving distance, instead of the lane width defined in a fixed manner or by one-off measurement as explained previously. For example, in a non-limiting manner, the driving distance allowing such a calculation can be of the order of 30 or 50 meters, such a distance being able to be adjusted as a function of the longitudinal speed of the ego vehicle and/or as a function of the frequency of data capture relating to the external environment.

In such an example of execution, the method can, in addition, be configured to take into consideration the quality of the demarcation lines of the track whose width is to be estimated. In this sense, at least one detection means 4 fitted to the vehicle, in particular a camera, is capable of extracting data relating to the demarcation lines, in particular capturing images of the lane and/or the road comprising the lane considered. , and the processing unit 7 is able to implement an evaluation sub-step E33 of a quality of the captured demarcation lines.

In other words, such a principle makes it possible to define a confidence coefficient for the quality of the data captured and/or the quality of the demarcation line of the lane considered. The confidence coefficient thus defined is compared to at least one data quality threshold S _q by the processing unit 7. When it is detected that, for the average lane width HQ_LW _{_mean} calculated, the data captured along of the defined driving distance have a confidence coefficient greater than or equal to the quality threshold S _q selected, the average track width HQ_LW _{_mean} calculated is saved and/or applied in the steps as explained above.

Conversely, when it is detected that, for the average track width calculated, all or part of the data captured along the defined driving distance has a confidence coefficient lower than the quality threshold S _q selected, the calculated lane width average HQ_LW _{_mean} is ignored and the applied lane width average may be the last saved lane width average HQ_LW _{_mean_x-1} value for which the captured data has a suitable confidence coefficient. Thus, if the quality of the captured data is deemed suitable, the calculated lane width average HQ_LW _{_mean} is adapted to the data obtained in real time or at a defined instant, conversely, if the quality of this data is insufficient, the last saved lane width average value HQ_LW _{_mean_x-1} , calculated with suitable quality data, is used.

It is understood that the examples of execution of the reconstruction step E3 explained above apply equally well to speed limit signs, and therefore laterally interposed traffic lanes, located on the right or on the left. of the vehicle.

According to an additional or alternative execution example, the reconstruction step E3 can also be implemented so as to take into consideration different factors based respectively on a variation of a detection angle ΔVR of the at least one means of detection 4 and/or a radius of curvature RC and/or detection of the approach of a roundabout.

In particular, the processing unit 7 can determine that the route traveled is a secondary road when a variation of a detection angle ΔVR, in particular an angle of view, of at least one of the detection means 4, by example of a camera, greater than or equal to a predefined detection angle variation threshold S _VR is detected over a predetermined period.

In particular, the processing unit 7 determines that the route traveled is a secondary road when a reduction in a detection angle, in particular an angle of view, of at least one of the detection means 4 is detected over a predetermined period. In particular, such a principle can be applied in the event of detection of a reduction greater than a predefined reduction threshold.

By way of non-limiting example, if at a time t, a VR detection angle of less than 30 meters is detected while, at a time t-2 seconds, the measured detection angle was greater than 50 meters, the processing unit 7 detects a decrease in the viewing angle, in particular a decrease of 20 meters, over a period of 2 seconds. The processing unit 7 then defines that the road traveled is a secondary road since the geography and/or topography of said road is accompanied by a variation in detection angle ΔVR, here a non-negligible reduction in the the angle of view of the at least one detection means 4, for example of the camera.

In a particular, optional manner, the variation threshold S _VR and/or the reduction threshold and/or the duration of the period for estimating the variation of a detection angle can be defined and /or adjusted as a function of a level of visibility measured via the at least one detection means 4 and/or as a function of the longitudinal speed of the vehicle, measured via at least one a measuring device 11 fitted to the vehicle, and/or as a function of weather conditions external to the vehicle, for example transmitted via the communication device 10, a connected device and/or at least one means of detection 4. For example, the detection of a fog or precipitation situation can be accompanied by the adjustment of said thresholds.

Similarly, the processing unit 7 determines that the road traveled is a secondary road when the processing unit 7 detects that part of the road traveled by the ego vehicle, located in front of the vehicle, has a lower radius of curvature RC or equal to a predefined S _RC curvature threshold. The radius of curvature RC of the road can be obtained via the at least one detection means 4, for example via the camera.

The curvature threshold S _RC can be a predefined value based on information provided by databases and/or on the basis of standards specific to a location, for example a country.

By way of non-limiting example, the processing unit 7 determines that the road traveled is a secondary road when the measured radius of curvature RC is strictly less than a curvature threshold S _RC of the order of 800 meters. Indeed, it is known, for example in a driving situation in a country such as France, that main roads of the motorway type have regulated bends with radii of curvature greater than or equal to 800 meters, and in particular less than 2000 meters .

Also, the longitudinal speed management system 6 can be configured to detect particular elements of the road infrastructure, specific to secondary roads, such as roundabouts or even speed bumps.

The management system 6 detects the presence of such elements when they are located in front of the vehicle, for example in an area of the order of a few hundred meters, for example of the order of 100 meters, located at the front of the vehicle on the basis of the data acquired by the at least one detection means 4, for example a camera.

For example, the processing unit 7 is able to identify the presence of an upcoming roundabout when it detects a widening of the lane in which the vehicle is traveling and/or a spacing of the demarcation lines delimiting such a lane . The management system 6 then executes a sub-step E34 of calculating the width of the lane in which the ego vehicle is traveling at different times of a defined period and compares the values obtained. The calculation of the width of the lane can be carried out in a manner similar to what was explained above with reference to the calculation of the widths LW _{_adj} of lanes interposed between the vehicle and a speed limit sign or with reference to the calculation of half the width of the lane in which the vehicle is traveling. Also the preceding description applies mutatis mutandis . The width of the track can be evaluated on an ad hoc basis. Alternatively, the evaluation of an increase in lane width can be based on the comparison of average widths of the lane in which the vehicle is traveling, each average width being estimated over a defined distance, for example from the order of 5 meters, similar to what was explained above.

The processing unit 7 then detects the presence of a roundabout when a variation in the calculated lane width ΔLW greater than or equal to a predefined lane width variation threshold S _VLW is detected. As a non-limiting example, such a threshold can be of the order of 0.5 meters.

According to one mode of execution, the reconstruction step E3 can, additionally or alternatively, be based on different identification factors allowing the identification of a main road.

In particular, the reconstruction step E3 can be based on the detection of one or more vehicle(s) approaching in a direction of traffic opposite to a direction of traffic of the ego vehicle. An approaching vehicle can be detected via at least one detection means 4, for example, preferably, via a RADAR fitted to the vehicle.

The method according to the invention then comprises a sub-step E35 of detecting the presence of an approaching vehicle and determining the position of said vehicle relative to the ego vehicle and within the road architecture.

In this sense, the management system 6 estimates a lateral interval Y_L_obj, that is to say a lateral distance, separating the ego vehicle from the approaching vehicle. Such an interval can be directly evaluated relative to the approaching vehicle when the ego vehicle passes in line with it. Alternatively, as illustrated in or 4, the lateral interval Y_L_obj can be evaluated between the ego vehicle or an estimated trajectory of the ego vehicle on the one hand, and an estimated trajectory of the approaching vehicle. For example, such estimates can be made via the processing unit 7.

On the basis of the estimated lateral interval Y_L_obj, the management system 6 evaluates whether the vehicle approaching the vehicle ego is included in a range of values of predefined, estimated lateral intervals, representative of the position and/or dimensions of a road adjacent to the route traveled by the ego vehicle within the road infrastructure.

In particular, the range of defined lateral interval values aims to delimit a range of lateral intervals corresponding to the road directly adjacent to the road traveled by the ego vehicle, each of these roads may include one or more lanes, and not another neighboring road, not directly adjacent to the route traveled. The directly adjacent road here is of the "main road" type, that is to say a highway or expressway type road, whose direction of traffic is opposite to a direction of traffic of the road traveled by the ego vehicle.

In this sense, the processing unit 7 compares the value of the estimated lateral interval Y_L_obj to a first lateral positioning threshold S _{1_obj} , estimating the position of a distal limit of the adjacent road relative to the ego vehicle. The first lateral positioning threshold S _{1_obj} is estimated on the basis of the number of lanes of the adjacent road considered and on the basis of a fixed, estimated lane width LW or, alternatively but preferentially, of an average width estimated track LW _{_mean} specific to the route traveled. The fixed, estimated lane width or the average estimated lane width can be obtained or calculated in a manner similar to what was explained previously. Such a principle allows an estimation of the dimension of the adjacent road based on measurements taken on the road traveled by the ego vehicle. The number of lanes of the adjacent road considered can in particular be estimated by dividing a maximum difference detected between demarcation lines, or markings, detected on the adjacent road, by the fixed, estimated lane width LW or, by the average width of estimated track LW _{_mean} specific to the road traveled by the ego vehicle. For example, if a maximum difference of 7.2 meters is detected between the boundary lines of the adjacent road and the average estimated lane width LW _{_mean} calculated is of the order of 3.6 meters, the processing unit 7 determines that there are two lanes on the adjacent road.

Alternatively or additionally, the location means 5 can transmit to the ego vehicle information relating to the adjacent road, for example the number of lanes Nb _Lanes that it includes and/or their dimensions. Likewise, surrounding vehicles or connected devices can transmit such data to the ego vehicle, via the communication device 10.

Or alternatively:

Thus, the processing unit 7 can discard data relating to vehicles located on more distant neighboring roads.

Also, the processing unit 7 compares the value of the estimated lateral interval Y_L_obj to a second lateral positioning threshold S _{2_ obj} , estimating the position of a proximal limit of the adjacent road relative to the vehicle ego and/or to the route traveled by the ego vehicle. The second lateral positioning threshold is estimated on the basis of the number of lanes of the road traveled by the vehicle and on the basis of an estimated lane width or, alternatively but preferentially, of the average estimated lane width, specific to the route traveled, in a manner similar to what has been explained. The second lateral positioning threshold S _{2_obj} can also take into account an error margin K.

The track width can be a fixed value, as indicated above. The track width LWm and/or the average track width LWm _{_mean} can be estimated by calculations in a manner similar to what was explained previously. Such a principle allows an estimation of the dimension and the position of the road traveled by the ego vehicle and an estimation of the position of the approaching vehicle detected so as to ignore the detection of vehicles traveling on the road traveled, for example when an overtaking situation. Reconstruction based on moving objects can thus be carried out based on approaching vehicles located on one or more roads directly adjacent to a road traveled by the ego vehicle.

Alternatively or additionally, the location means 5 can transmit to the ego vehicle information relating to the route traveled, for example the number of lanes it includes and/or their dimensions. Likewise, surrounding vehicles traveling on the same road can transmit such data to the ego vehicle, via the communication device 10.

Or alternatively:

Thus, the processing unit 7 can discard data relating to vehicles traveling on the road traveled by the ego vehicle, that is to say in the same direction of traffic.

Thus, if an approaching vehicle is detected and has a lateral interval relative to the ego vehicle included in a range of lateral distance values delimited by the first and second lateral positioning thresholds, the processing unit 7 determines that a road intended for traffic in the opposite direction is present in an area directly adjacent to the road traveled, and that the road traveled is of the “main road” type, and not a secondary road. Indeed, conventionally, secondary roads such as intersections or bifurcations of motorways or expressways are not directly positioned adjacent to a road presenting such traffic in the opposite direction.

It is understood that such a principle can apply to an approaching vehicle located to the left or to the right of the ego vehicle.

Additionally or alternatively, according to another example of identification factor, during the reconstruction step E3 of the environment external to the vehicle, a road traveled by the vehicle can be defined as being a main road if a situation of Instability in longitudinal speed detection is detected. By “instability situation” is meant a situation of successive detections of a plurality of speed limit signs indicating one or more distinct longitudinal speeds over a predefined detection period T _det . For example, the management system 6 and/or the driving assistance system 2 detect(s) more than two speed limit signs in succession, over a predefined period. For example, such a detection period T _det can be of the order of 10 seconds, or even 5 seconds. A situation of instability can in particular be observed in areas comprising a plurality of neighboring roads, the vehicle then being able, depending on its heading, to detect speed limit signs relating to the road traveled or to different neighboring roads.

Alternatively, the management system 6 and/or the driving assistance system 2 can be configured to detect a situation of instability in speed orders or recommendations to be applied to the vehicle, that is to say, on the basis of the plurality of detected panels, such systems successively recommend a slowdown then an acceleration during the predefined detection period T _det .

The management system 6 thus executes, during the reconstruction step E3, a comparison sub-step E36 of detected speed limitations and/or speed recommendations or successive actions to be applied when such limitations and/or recommendations take place over a detection period T _det less than a predefined detection duration threshold S _det .

For example, in a driving situation, the vehicle can detect at a time t a speed limit of 90 km/h then, at a time t+1 a limitation of 70 km/h, requiring braking, then, at a time t +2, a limitation to 90 km/h which would require acceleration compared to the previous recommendation of slowing down.

If the management system 6 detects, over a detection period T _det less than the predefined detection duration threshold S _det , such an instability situation, whether directly, on the basis of the speed limitations detected or indirectly, on the basis of the recommendations given by the driving assistance system 2 or the CASP module 3 in particular, the management system 6 can then define that the vehicle is traveling on a main road.

A similar principle can apply if the management system 6, and particularly the processing unit 7, detects a situation of inconsistency between data relating to the environment external to the vehicle, measured by the at least one means of detection 4, and navigation and/or mapping data, for example provided by the location means 5 and/or by the driving assistance system 2 and/or by surrounding vehicles or devices connected via of the communication device 10.

Particularly, such a principle can be applied to the detection of a RC radius of curvature present at the front of the vehicle on the road traveled by the ego vehicle. For example, if the detection means 4 detects the presence of a radius of curvature characteristic of a secondary road as described above, but the location data does not indicate the presence of a bend, the processing unit 7 determines that the vehicle is traveling on a main road and that the radius of curvature RC momentarily detected is specific to an adjacent secondary road. The processing unit 7 thus carries out a sub-step of comparing a measured radius of curvature of the route traveled with a radius of curvature provided from data received via the location means 5 and/or the system d driving assistance 2 and/or surrounding vehicles, the system detecting an inconsistency when the value of the measured radius of curvature is strictly greater than the radius of curvature indicated, for example at least 1.2 times greater, or even 1.5 times superior.

Likewise, the management system 6 can be configured in order to carry out, during the step of detecting a limitation panel E0, a sub-step E0' of verifying the presence or not of a limitation panel of similar speed, placed on an opposite side of the road traveled and placed to the right of the speed limit sign initially detected. In fact, the main one-way roads present, in a known manner, two signs, located at the same level and arranged on each side of the road in question. The processing unit 7 is thus able to define that the road traveled is a main road when it detects, via the data provided by the at least one detection means 4, that such signs are present.

Once the reconstruction step E3 has been carried out, the management system executes the determination step E4 of the longitudinal speed to be applied to the vehicle on the basis of the various reconstruction data of the environment external to the vehicle, i.e. - say on the basis of one or more identification factors exposed previously. Particularly, the management system executes a grouping sub-step E41 of one or more types of reconstruction data of the external environment, relating to one or more road identification factors, so as to define what type of recommendation , or order, of longitudinal speed must be transmitted depending on whether it is determined that the vehicle is traveling on a main road or a secondary road.

In this sense, during the execution of the grouping sub-step E41, the processing unit 7 merges, or groups, a plurality of types of data, in other words identification factors of a main road and/or or a secondary road, as explained above with reference to reconstruction step E3.

The processing unit 7 further associates with such data the type of road, main or secondary, previously identified on the basis of the factor considered. When an identification factor is used, for example a lateral distance relative to a detected speed limit sign, such data as well as the type of road identified at the end of the reconstruction step E3 can be used directly. in order to define a speed to apply.

Conversely, when the reconstruction step E3 implements the reconstruction of the environment on the basis of a plurality of identification factors, the determination step E4 of the longitudinal speed to be applied may include a sub -confirmation step E42 of the road type identified during the reconstruction step E3 and/or an evaluation sub-step E43 of a probability rate of belonging to a type of road, among a main road or a secondary route.

For example, when, on the basis of each of the factors used during the reconstruction step E3, the processing unit 7 determines that the road traveled belongs to the same type, the type of road identified on the basis of the 'one of the factors is confirmed by the other factors.

Conversely, when, on the basis of certain factors, the processing unit 7 determines that the route traveled is of a first type, but at least one factor used results in the identification of a type of distinct road, the processing unit 7 can implement the evaluation sub-step E43 of a probability rate of belonging to a type of road, among a main road or a secondary road, so that the type road identified is then the type of road presenting the highest probability rate.

Also, optionally, during the grouping step E41 of the reconstruction data, the processing unit 7 can associate with each type of data relating to the external environment, in other words with each identification factor, a weight representative of a degree of relevance and/or reliability of the type of data considered. Such a weight can then be taken into consideration when evaluating the probability rate.

The step E4 of determining the longitudinal speed to be applied can then be executed according to two distinct modes of execution, illustrated in the .

According to a first example of execution, the management system 6 can implement the confirmation or denial of a longitudinal speed previously recommended to the driving assistance system 2 on the basis of the reconstruction data. Such a longitudinal speed can, for example, be calculated by a CASP 3 module or by any other type of module fitted to the ego vehicle capable of recommending a longitudinal speed to be applied to the vehicle. The management system 6 then does not communicate directly with such modules but transmits data to the driving assistance system 2. Thus, the driving assistance system 2 receives two distinct recommendations, one provided by the CASP module 3 for example, the other provided by the management system according to the invention, and the driving assistance system 2 adapts the speed according to the most suitable recommendation. These recommendations may be issued simultaneously or successively to one another.

According to a second example of execution, the management system 6 can implement the calculation of a longitudinal speed to be applied directly on the basis of the reconstruction data. A speed recommendation is then calculated on the basis of information provided by the management system 6 according to the invention on the one hand, and on the basis of information obtained and/or coming from different systems or modules fitted to the vehicle, such as the CASP 3 module in particular or by any other type of module fitted to the vehicle capable of recommending a longitudinal speed to be applied to the vehicle. The management system 6 then communicates beforehand with said modules, a recommended longitudinal speed is defined on the basis of the combined data and information of the management system 6 and said modules, then such a recommendation is transmitted to the driving assistance system 2 Thus, the driving assistance system 2 receives a single recommendation, the management system consolidating the information provided by the different modules of the vehicle.

The recommendations issued by the management system define the longitudinal speed to be implemented based on the reconstruction data provided. The longitudinal speed of the vehicle is maintained, or is not modified, by the driving assistance system 2 when it is defined that the vehicle is traveling on a main road. Such a situation corresponds in fact to a vehicle maintaining its course on a main road and not to the selection of a secondary road presenting a more restricted longitudinal speed limit. Conversely, if it is defined that the vehicle is traveling on a secondary road, the longitudinal speed of the vehicle is modified according to the speed limit sign.

The driving assistance system 2 and/or the vehicle can then execute E5 a recommendation directly or indirectly transmitted by the management system 6.

The present invention thus proposes a method and a system for managing the longitudinal speed of a vehicle in the driving phase equipped with at least one driving assistance system. The method and the management system advantageously make it possible, when a speed limit sign is detected, to implement the reconstruction of an external environment in order to define a longitudinal speed adapted to the type of road on which the vehicle is traveling when d other systems or means fitted to the vehicle, such as a location means, do not have performances adapted to optimal longitudinal speed recommendations. The method and the system according to the invention thus make it possible to prevent inappropriate behavior of the vehicle, in particular untimely braking, and the generation of possible dangerous situations for surrounding vehicles.

The present invention cannot, however, be limited to the means and configurations described and illustrated here and it also extends to any equivalent means or configuration and to any technically effective combination of such means insofar as they ultimately fulfill the functionalities described and illustrated. in this document.

Claims (10)

Method for managing (100) the longitudinal speed of an ego vehicle in the driving phase equipped with at least one location means (5) and a driving assistance system (2) capable of regulating the longitudinal speed of said vehicle, the method comprising, when a speed limit sign indicating a longitudinal speed is detected (E0):
- a step of verifying (E1) the precision of a position of the ego vehicle in a road infrastructure, implemented via the location means (5);
- a step of detecting (E2) an external environment surrounding the vehicle via at least one detection means (4);
- a step of reconstruction (E3) of the external environment on the basis of the acquired data relating to the external environment so as to define whether a road traveled by the ego vehicle is a main road, on which a first limitation of longitudinal speed, or a secondary road, coming from the main road and on which a second speed limit is imposed, strictly lower than the first speed limit;
- a step of determining (E4) a longitudinal speed to be applied to the ego vehicle on the basis of the data calculated for reconstructing the environment external to the ego vehicle depending on whether the route traveled is defined as being a main road or a secondary road . Method according to the preceding claim, in which the step of verifying (E1) the precision of a position of the ego vehicle comprises an evaluation sub-step (E11), via the location means (5), of a confidence index defined as a function of a context external to the ego vehicle and representative of a degree of precision of the position of the ego vehicle, the step of determining (E4) the longitudinal speed being implemented when the The defined confidence index is lower than a predefined confidence threshold. Method according to one of the preceding claims, in which the reconstruction step (E3) comprises a detection sub-step (E31) of the presence or absence of a traffic lane of the road traveled by the ego vehicle laterally interposed between the detected speed limit sign and the ego vehicle when the latter passes in line with said sign, the route traveled being defined as secondary if:
- when the ego vehicle does not detect the presence of a traffic lane interposed between the speed limit sign and the ego vehicle, a lateral distance (Y_L _{_panel} ) separating the ego vehicle from the sign is greater than a first distance threshold lateral (S _LW1) predefined; and or
- when the ego vehicle detects the presence of at least one traffic lane interposed between the speed limit sign and the ego vehicle, a lateral distance (Y_L _{_panel} ) separating the ego vehicle from the sign is greater than a second distance threshold predefined lateral distance (S _LW2 ), the second threshold (S _LW2 ) being defined as a function of the first lateral distance threshold (S _LW1 ) and as a function of the number of interposed traffic lanes(s) detected. Method according to the preceding claim, in which the second threshold (S _LW2 ) is defined as a function of an average width ( _{HQ_LW_mean} ) of _the at least one traffic lane interposed between the ego vehicle and the speed limit sign , estimated over a predefined distance. Method according to one of the preceding claims, in which during the reconstruction step (E3), the route traveled is defined as being secondary if:
- a variation of a detection angle (ΔVR), in particular an angle of view, of at least one detection means (4), in particular of a camera, greater than or equal to a predefined variation threshold (S _VR ) is detected over a predetermined period;
- a radius of curvature (RC) of the route traveled less than or equal to a predefined curvature threshold (S _RC ) is detected by at least one detection means (4), in particular a camera; and or
- an approaching roundabout is detected. Method according to one of the preceding claims, in which, during the reconstruction step (E3), the route traveled is defined as being main if, for a vehicle approaching in a direction of movement opposite to a direction of movement of the vehicle ego, a lateral interval separating said approaching vehicle from the ego vehicle is included in a range of predefined lateral distance values estimated representative of the position and/or dimensions of a road adjacent to the road traveled by the ego vehicle within the road infrastructure. Method according to one of the preceding claims, in which, during the reconstruction step, a road is defined as being main if:
- a situation of instability is detected in the detection of the longitudinal speed, corresponding to a situation of successive detections of a plurality of speed limit signs indicating one or more distinct longitudinal speeds over a detection period (T _det ) predefined; and or
- a situation of inconsistency is detected between data relating to the environment external to the ego vehicle, measured by the at least one detection means 4, and navigation and/or mapping data; and or
- speed limit signs are detected on either side of the road traveled by the ego vehicle. Method according to one of the preceding claims, in which the step of determining (E4) the longitudinal speed comprises a sub-step of grouping (E41) one or more types of data for reconstructing the external environment, determination step comprising:
- confirmation or denial of a longitudinal speed previously recommended to the driving assistance system (2) on the basis of the reconstruction data; Or
- calculating a longitudinal speed to be applied on the basis of the reconstruction data. System for managing (6) the longitudinal speed of a vehicle in the driving phase for a vehicle, the system comprising hardware and/or software elements implementing the method according to one of the preceding claims, the hardware elements comprising at least memory element (8), a processing unit (7), a location means (5) and at least one detection means (4) of the external environment. A computer program product comprising program code instructions recorded on a computer readable medium for implementing the steps of the method according to any of claims 1 to 8 when said program is running on a computer.