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 while driving Method and system for managing the longitudinal speed of a vehicle in the driving 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 fitted to the vehicle, such as a location means, do not present performances adapted to speed recommendations optimal longitudinal. 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 driver assistance systems, or ADAS, from the English "Advance Driving Assist System" including in particular a Contextual adaptive cruise control system, also known by the acronym ACC Contextuel 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 detected authorized longitudinal speed limit signs. 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.

Traditionally, 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 information on the positioning of the vehicle in the road infrastructure provided by the localization means. However, in the case of complex road infrastructures, for example near intersections, junctions or multiple roads overlapping on several levels, it has been found that the speed recommendation to apply could be erroneous. For example, such a recommendation can be based on the detection of irrelevant speed limit signs relating to a road adjoining the one traveled by the vehicle, at a junction or exit from a road, in particular a motorway.

In such situations, the map information provided by the location means is essential for identifying the relevant speed limits. The accuracy of the vehicle location means in the road infrastructure is nevertheless dependent on many conditions, both external and internal to the vehicle, such as weather conditions, topography, satellites, or even the longitudinal speed of the vehicle. The accuracy of the location means may then be too low to allow for appropriate 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 cases of untimely braking. This may result in anxiety-provoking situations for the driver and passengers of the vehicle and, on the other hand, risky situations for both the equipped vehicle and surrounding vehicles.

The invention falls within 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 indicating a longitudinal speed is detected:
- a step of verifying the accuracy of a position of the ego vehicle in a road infrastructure, implemented via the localization means;
- a step of detecting an external environment surrounding the vehicle by means of 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 travelled 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 data of reconstruction of the environment external to the ego vehicle according to whether the road traveled is defined as being a main road or a secondary road.

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

The reconstruction step may comprise 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 in line with said sign, the road 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 lane(s) detected.

In particular, the second threshold can be defined based on 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 step, the route traveled can be defined as secondary if:
- a variation of a detection angle, in particular a viewing angle, of at least one detection means, in particular a camera, greater than or equal to a predefined variation threshold is detected over a predetermined period;
- a radius of curvature of the road 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 road traveled may 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 to be 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 step, a road is defined as primary 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 outside 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 both sides of the road traveled by the ego vehicle.

The step of determining the longitudinal speed may comprise a sub-step of grouping one or more types of reconstruction data of the external environment, the determination step comprising:
- confirmation or denial of a longitudinal speed previously recommended to the driver assistance system on the basis of the reconstruction data; or
- the calculation of 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 during 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 one memory element, a processing unit, a location means and at least one means of detecting the external environment.

The invention further 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 runs on a computer. Alternatively, the invention relates to a computer program product downloadable from a communication network and/or recorded on a computer-readable data medium and/or executable by a computer, comprising instructions which, when the program is executed by the computer, cause the latter 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 set out above when said program runs on a computer. Alternatively, the invention may relate to a computer program product downloadable from a communication 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 the latter to implement the method according to the invention.

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

Finally, the invention may relate to a signal of a data medium carrying the computer program product as set out above.

Other details, characteristics and advantages will emerge more clearly on reading the detailed description given below, for information purposes only and without limitation, in relation to the various 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 steps in the management process.

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

There schematically illustrates a motor vehicle 1 according to an embodiment of the invention. The vehicle can be of any nature. 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 for implementing the invention may also be referred to as an "ego" vehicle in order to distinguish it from other surrounding vehicles and does not in itself confer any technical limitation on the motor vehicle.

The vehicle 1 comprises hardware and/or software elements capable of implementing a method 100 for managing 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 the English “Advance Driving Assist System”, including in particular a Contextual adaptive cruise control system, also known by the acronym ACC Contextuel 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 a known manner, such a driving assistance system 2 is capable of identifying situations relating to the external environment, particularly to traffic signs 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 environment outside the vehicle, in particular, in a conventional and non-limiting manner, relating to the geometry and/or topology of a road traveled by the vehicle. In particular, the CASP module may be included in the driving assistance system 2.

The driver 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 means 4 for detecting the external environment fitted to the vehicle. For example, such a means 4 for detecting, or sensor, may 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 signs and/or speed limits, a topography and/or geometry of the road, vehicles and/or obstacles surrounding the ego vehicle. One or more detection means 4 may in particular be equipped at the front or on the side parts of the ego vehicle, for example at the side doors or the rearview mirrors.

The vehicle also comprises a means 5 for locating the position of the vehicle 1 in a road infrastructure, in particular by satellite. It integrates, for example, a system for locating the vehicle 1 and/or a map of the road infrastructure. In particular, the location of the 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 embedded in the vehicle. The location means 5 can preferably comprise an inertial unit, also called a vehicle dynamics motion analyzer, IMU or ADMA, from the English acronym “Automotive Dynamic Motion Analyzer”.

The vehicle 1 may also, preferably, be equipped with a horizon provider module. Such a module communicates with the location means 5 in order to provide it with an electronic horizon, also called an 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 mapping. The electronic horizon associates with each road or route a probability of being traveled, i.e. selected, by the vehicle. As is known in the prior art, a drawback 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 emission of erroneous positioning data, the data provided by the horizon provider module, and therefore the electronic horizon, are also erroneous.

The vehicle 1 is also equipped with a system 6 for managing the longitudinal speed of the vehicle. Said system comprises the hardware and/or software elements necessary for implementing the method 100 for managing the longitudinal speed according to the invention, as set out 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 equipping the vehicle as described above, and at least one means 4 for detecting 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 implementing 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 4, the driving assistance system 2 and the location means 5.

The location means 5 of the longitudinal speed management system 6 is that equipping the vehicle, described above. It is in particular 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 comprise the horizon provider module as described above or, alternatively, be capable of receiving data emitted by said module, for example data relating to the electronic horizon.

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

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

- a communication device 10 with a connected device;
- one or more measuring devices 11 for 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 capable of intervening on the vehicle, for example on the driving assistance system 2, in order to modify its operation, in this case in order to modify the longitudinal speed, for example by acceleration or by 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 may be a connected telephone of a passenger of the vehicle ego or of a surrounding vehicle, a connected remote vehicle or even an element of road or urban infrastructure connected by means of a wireless connection, low frequency 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 may be connected to a remote server in order to receive information relating to the environment external to the vehicle, for example according to the location of the vehicle.

The measuring members 11 equipping the vehicle are configured to transmit to the processing unit 7 data relating to the interior environment of the vehicle, i.e. relating to the operation of the vehicle ego itself. Such measurements can be carried out, for example, in real time or at regular time intervals. In particular, the measuring members 11 can be capable of carrying out, in a non-limiting manner, measurements relating to at least one of:
- the longitudinal speed of the ego vehicle;
- acceleration and/or slowing down of the ego vehicle;
- the steering wheel angle, 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 able to receive data from the communication device 10 and/or from any measuring device 11 previously described when the ego vehicle is equipped with it.

An example of execution of the method 100 for managing the longitudinal speed of a vehicle in the rolling phase is described below with reference to FIGS. 2 and 3. The method 100 for managing the longitudinal speed 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 for managing the longitudinal speed of a vehicle in the driving phase according to the invention comprises, firstly, a step of detecting a traffic sign E0 indicating a longitudinal speed, in other words a sign limiting the legal longitudinal speed of vehicles on a road traveled by the vehicle ego. Such a detection step E0 is carried out according to known principles and means, in particular by means of the driving assistance system 2 and/or by means of at least one of the detection means 4, for example by means of at least one camera equipping the vehicle. Also, the detection of such signs can be optimised 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 travelled 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 junction or exit road. As a result, the driving assistance system 2 detects inappropriate events relating to a road that is not relevant and, on the recommendation of the CASP module 3, can impose on the vehicle a longitudinal speed that may be erroneous. Such a situation may be accompanied by untimely braking of the vehicle ego likely to generate a danger for the vehicles surrounding the vehicle ego.

Also, the location means 5 may, for various reasons, have low accuracy, resulting in unsuitable positioning of the vehicle in the road infrastructure. While it is known to equip vehicles with recalibration 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 case of a plurality of roads having a certain proximity, for example near junctions, intersections, or in the case of roads arranged on several vertical levels. The accuracy of the location means 5 may in particular be affected by numerous factors, such as reliefs, elements of the infrastructure such as bridges or tunnels, weather or atmospheric conditions, conditions relating to the universe, such as solar storms or obstacles present between the satellite and the vehicle, or even 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 recalibration module then does not always allow the vehicle to be repositioned appropriately and speed limits detected by the location means 5 are then erroneous.

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 step E1 of verifying the accuracy 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 vehicle positioning data in the road infrastructure, representative of a degree of precision of said location means 5. The confidence index is in particular defined according to 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 can 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 members 11 equipping 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 carried out according to a level of precision of the positioning, 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 accuracy of the location means 5 is deemed reliable, therefore suitable for detecting speed limit signs and for operating the driving assistance system 2 when the confidence index has, during the comparison sub-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 normally would.

Conversely, the accuracy of the location means 5 is deemed insufficient, and 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 an accuracy problem, the method according to the invention then executes the steps described below.

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

Optionally, the execution of the subsequent steps of the method according to the invention may, in addition, be conditioned on the detection of at least one additional road, i.e. 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 equipping the vehicle, in particular by a camera, and/or on the basis of data received via the communication device 10. In other words, the execution of the subsequent steps of the method may 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, roads “nearby” or having a “high proximity” are understood to mean roads present at a distance less than or equal to 10 meters relative to a road traveled by the vehicle. For example, such proximity may 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 comprise, when the precision of the location of the vehicle in the road infrastructure is insufficient:
- a detection step E2 and reconstruction step 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 depending on the reconstructed external environment.

During the detection step E2, the vehicle, by means of the at least one detection means 4, in particular by means of a camera and/or a RADAR and/or a LIDAR, extracts data relating to the immediate external environment surrounding the vehicle. For example, “immediate” means an external environment extending several hundred meters, around, and particularly in front and/or laterally, relative to the vehicle. This data may, generically, relate to the topology and/or geography of the road traveled, to a number of lanes forming the road 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 front of 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 or more lanes;
- the presence of one or more side lanes relative to a lane in which the vehicle is travelling, i.e. one or more side lanes interposed between the vehicle and an emergency stopping lane and/or a speed limit sign, for example;
- a detection angle, or view angle, 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.

This data is 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 being able to comprise one or more lanes, and thus adapt the speed of the vehicle ego 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.

In general, a “main road” means a road on which a first longitudinal speed limit is imposed and a “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, a “main road” means a road such as a motorway or expressway on which the first longitudinal speed limit is imposed and from which one or more secondary roads emerge. “Secondary roads” means roads coming from a main road, such as motorway exits, motorway slip roads, “expressways”, junctions or branches, i.e. non-main roads within the meaning of the Highway Code.

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

According to an exemplary 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 speed limit sign previously detected, measured when the vehicle passes in front of such a sign.

In particular, the reconstruction step E3 comprises, firstly, a sub-step E31 of detecting 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 the latter passes in line with said sign. It should be noted that here, by “traffic lane” is meant a conventional traffic lane, temporary or not, and not a safety lane, emergency stopping lane or emergency stopping lane, the processing unit 7 being able to detect the differences in markings making it possible to distinguish an emergency stopping lane from a traffic lane. In particular, the processing unit 7 is able to distinguish differences in marking length and the interval between successive strips of a marking, for example on the basis of the data provided by the camera.

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

In order to detect the presence or absence of one or more lanes laterally located between the vehicle ego and the speed limit sign, in other words one or more lanes adjacent to a lane in which the vehicle is traveling, the vehicle estimates a width LW _{_adj} of one or more lanes. For this purpose, the vehicle estimates the width separating two demarcation lines, or markings, delimiting the lane considered, one of said lines being called the proximal line, because it presents the greatest proximity relative to the vehicle ego or to the lane in which the vehicle ego is traveling, and the other being called 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 is 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 detected speed limit sign.

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 them if the width LW _{_adj} calculated between two adjacent lines is less than a lane width threshold S _LW , defined according to a known width, for example defined by national standards, of the lane. In particular, the lane width threshold S _LW is strictly less than a conventional known lane width. For example, for lanes conventionally having a width of the order of 3 meters, or greater than 3 meters, the lane width threshold S _LW may 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 traffic lane is present between the lane in which the vehicle is traveling and the detected speed limit sign.

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 traffic lane is laterally interposed between the vehicle ego, 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 vehicle ego 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 moving 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 are interposed between the vehicle and the speed limit sign, the processing unit 7 reconstructs the environment in order to assess whether or not the vehicle is moving on a secondary road by means of a comparison sub-step E32 of the lateral distance _{Y_L_sign} 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 laterally interposed between the vehicle and the speed limit sign. Such a threshold may be previously defined 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 stop 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 previously set out for calculating the width of an adjacent lane, so the previous description applies mutatis mutandis . Thus, generally speaking, the lateral distance threshold considered is defined on the basis of half the width of the traffic lane in which the ego vehicle is travelling, an emergency stopping lane width and, preferably, a margin of error distance, for example of the order of 1 metre.

In such a case, the lateral distance threshold may be a predefined fixed value or a parameterized value, for example selected or calculated based on 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 carried out according to known methods, by means of 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 the detection step E31 and it detects that the lateral distance Y_L _{_sign} 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. As a non-limiting example, the first lateral distance threshold S _LW1 may be of the order of 6 meters in order to take into consideration a half-lane width of the order of 2 meters, an emergency stop lane whose width is of the order of 3 meters and a margin of error distance 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 factor "lateral distance relative to the sign", 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 laterally located traffic lanes 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. As a non-limiting example, when a traffic lane is laterally interposed between the vehicle ego, or its traffic lane, and the speed limit sign, the second lateral distance threshold S_LW2may 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_fixedof the lane of the laterally interposed traffic lane.

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

Alternatively, such width may be measured or estimated on a one-time basis, as discussed above.

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

In such an exemplary embodiment, the method may, in addition, be configured to take into consideration the quality of the demarcation lines of the lane whose width is to be estimated. In this sense, at least one detection means 4 equipping the vehicle, in particular a camera, is capable of extracting data relating to the demarcation lines, in particular image captures of the lane and/or the road comprising the lane considered, and the processing unit 7 is capable of implementing a sub-step E33 of evaluating a quality of the captured demarcation lines.

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

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

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

According to an additional or alternative exemplary embodiment, 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 detection means 4 and/or a radius of curvature RC and/or the detection of the approach of a roundabout.

In particular, the processing unit 7 can determine that the road traveled is a secondary road when a variation in a detection angle ΔVR, in particular a viewing angle, of at least one of the detection means 4, for example 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 road traveled is a secondary road when a decrease in a detection angle, in particular a viewing angle, 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 decrease greater than a predefined decrease threshold.

As a non-limiting example, if at a time t, a detection angle VR 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 the detection angle ΔVR, here a decrease, not negligible, in the viewing angle of the at least one detection means 4, for example of the camera.

In particular, optionally, 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 may be defined and/or adjusted as a function of a visibility level measured by means of the at least one detection means 4 and/or as a function of the longitudinal speed of the vehicle, measured by means of at least one measuring member 11 equipping the vehicle, and/or as a function of weather conditions external to the vehicle, for example transmitted by means of the communication device 10, a connected device and/or the at least one detection means 4. For example, the detection of a fog or precipitation situation may 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 a portion of the road traveled by the vehicle ego, located in front of the vehicle, has a radius of curvature RC less than or equal to a predefined curvature threshold S _RC . 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 S _RC curvature threshold can be a predefined value based on information provided by databases and/or based on standards specific to a location, for example a country.

As a 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 road infrastructure elements specific to secondary roads, such as roundabouts or 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 in 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 vehicle ego 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 that set out 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 a half-width of the lane in which the vehicle is traveling. Also the preceding description applies mutatis mutandis . The width of the lane can be evaluated punctually. Alternatively, the assessment of an increase in lane width may be based on the comparison of average widths of the lane in which the vehicle is travelling, each average width being estimated over a defined distance, for example of the order of 5 metres, similarly to what has been set out 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 may be of the order of 0.5 meters.

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

In particular, the reconstruction step E3 may be based on the detection of one or more vehicles approaching in a direction of travel opposite to a direction of travel of the vehicle ego. An approaching vehicle may be detected by means of at least one detection means 4, for example, preferably, by means of a RADAR, equipping 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, i.e. a lateral distance, separating the ego vehicle from the approaching vehicle. Such an interval can be evaluated directly relative to the approaching vehicle when the ego vehicle passes right thereon. Alternatively, as illustrated in or 4, the lateral interval Y_L_obj may be estimated 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 estimations may be performed via the processing unit 7.

Based on the estimated lateral interval Y_L_obj, the management system 6 assesses whether the vehicle approaching the ego vehicle is within a range of predefined, estimated lateral interval values 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, the range of values of defined lateral intervals 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 being able to comprise one or more lanes, and not another neighbouring road, not directly adjacent to the road traveled. The directly adjacent road is here of the “main road” type, that is to say a road of the motorway or expressway type, the direction of traffic of which 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 preferably, of an estimated lane width average LW _{_mean} specific to the road traveled. The fixed, estimated lane width or the estimated lane width average can be obtained or calculated in a manner similar to that set out above. Such a principle allows an estimation of the dimension of the adjacent road according to the measurements carried out on the road traveled by the ego vehicle. The number of lanes of the adjacent road considered may in particular be estimated by dividing a maximum gap detected between demarcation lines, or markings, detected on the adjacent road, by the fixed lane width LW, estimated or, by the estimated lane width average LW _{_mean} specific to the road traveled by the vehicle ego. For example, if a maximum gap of 7.2 meters is detected between the demarcation lines of the adjacent road and the estimated lane width average 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 it comprises and/or their dimensions. Similarly, 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 neighbouring 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 ego vehicle and/or to the road 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 preferably, of the average estimated lane width, specific to the road traveled, in a manner similar to what has been explained. The second lateral positioning threshold S _{2_obj} can also take into account a margin of error K.

The lane width may be a fixed value, as indicated above. The lane width LWm and/or the lane width mean LWm _{_mean} may be estimated by calculations in a similar manner to what has been explained above. Such a principle allows an estimation of the dimension and position of the road traveled by the ego vehicle and an estimation of the position of the detected approaching vehicle so as to ignore the detection of vehicles traveling on the road traveled, for example during an overtaking situation. The reconstruction based on moving objects may thus be carried out as a function of 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 road traveled, for example the number of lanes it comprises and/or their dimensions. Similarly, 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 exclude data relating to vehicles traveling on the road traveled by the ego vehicle, i.e. in the same direction of travel.

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 an 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 junctions 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 equally well to an approaching vehicle located to the left or to the right of the ego vehicle.

Additionally or alternatively, according to another example of an 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 the detection of the longitudinal speed is detected. The term "instability situation" means 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 a row, over a predefined period. For example, such a detection period T _det can be of the order of 10 seconds, or even 5 seconds. An instability situation can in particular be observed at the level of zones 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 may be configured to detect a situation of instability in speed orders or recommendations to be applied to the vehicle, that is to say that, on the basis of the plurality of detected signs, such systems successively recommend slowing down then accelerating 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 actions to be applied successively 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 may detect at a time t a speed limit of 90 km/h then, at a time t+1 a limit of 70 km/h, requiring braking, then, at a time t+2, a limit of 90 km/h which would require acceleration compared to the previous recommendation to slow 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 detected speed limits 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 may apply if the management system 6, and particularly the processing unit 7, detects a situation of inconsistency between data relating to the environment outside the vehicle, measured by the at least one detection means 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 the communication device 10.

In particular, such a principle can be applied to the detection of a radius of curvature RC present in front of the vehicle on the road traveled by the vehicle ego. For example, if the detection means 4 detects the presence of a radius of curvature characteristic of a secondary road as described above, but 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 performs a sub-step of comparing a measured radius of curvature of the road traveled with a reported radius of curvature from data received via the location means 5 and/or the driving assistance system 2 and/or the surrounding vehicles, the system detecting an inconsistency when the value of the measured radius of curvature is strictly greater than the reported radius of curvature, for example at least 1.2 times greater, or even 1.5 times greater.

Similarly, the management system 6 can be configured to perform, during the step of detecting a speed limit sign E0, a sub-step of verifying E0' the presence or absence of a similar speed limit sign, arranged on an opposite side of the road traveled and arranged to the right of the speed limit sign initially detected. Indeed, one-way main roads have, in a known manner, two signs, located at the same level and arranged on each side of the road considered. The processing unit 7 is thus able to define that the road traveled is a main road when it detects, by means of 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 step E4 of determining the longitudinal speed to be applied to the vehicle on the basis of the various reconstruction data of the environment outside the vehicle, i.e. on the basis of one or more identification factors set out above. In particular, the management system executes a sub-step E41 of grouping one or more types of reconstruction data of the external environment, relating to one or more road identification factors, so as to define which type of recommendation, or order, of longitudinal speed must be transmitted depending on whether it is determined that the vehicle is travelling on a main road or a secondary road.

In this sense, when executing 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 a secondary road, as set out above with reference to the 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 directly used in order to define a speed to be applied.

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 comprise a sub-step E42 of confirmation of the type of road identified during the reconstruction step E3 and/or a sub-step E43 of evaluation of a probability rate of belonging to a type of road, among a main road or a secondary road.

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 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 road traveled is of a first type, but at least one factor used results in the identification of a distinct type of road, the processing unit 7 can implement the sub-step E43 of evaluating a probability rate of belonging to a type of road, among a main road or a secondary road, such that the type of road identified is then the type of road having 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 carried out according to two distinct execution modes, illustrated in .

According to a first exemplary embodiment, 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 module 3 or by any other type of module equipping 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 separate 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 can be issued simultaneously or successively one after the other.

According to a second exemplary embodiment, 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 originating from different systems or modules equipping the vehicle, such as the CASP module 3 in particular or by any other type of module equipping 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 from 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 driver 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 with 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 driver 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 management method and 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 other systems or means equipping 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 to generate 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 operative combination of such means to the extent that they ultimately fulfill the functionalities described and illustrated in the present 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 accuracy of a position of the ego vehicle in a road infrastructure, implemented by means of the localization means (5);
- a step of detecting (E2) an external environment surrounding the vehicle by means of 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 travelled 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 (E4) a longitudinal speed to be applied to the ego vehicle on the basis of the calculated data of reconstruction of the environment external to the ego vehicle according to whether the road 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 accuracy of a position of the ego vehicle comprises a sub-step of evaluating (E11), by means of the localization means (5), a confidence index defined as a function of a context external to the ego vehicle and representative of a degree of accuracy of the position of the ego vehicle, the step of determining (E4) the longitudinal speed being implemented when 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 sub-step of detecting (E31) 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 road 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 (Y_L _{_sign} ) separating the ego vehicle from the sign is greater than a first predefined lateral distance threshold (S _LW1) ; 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 predefined lateral distance threshold (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 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 a viewing angle, of at least one detection means (4), in particular 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 road 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 road traveled is 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 to be representative of the position and/or the 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 predefined detection period (T _det ); and/or
- a situation of inconsistency is detected between data relating to the environment outside the vehicle ego, measured by the at least one detection means 4, and navigation and/or mapping data; and/or
- speed limit signs are detected on both sides 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 reconstruction data of the external environment, the determination step comprising:
- confirmation or denial of a longitudinal speed previously recommended to the driver assistance system (2) on the basis of the reconstruction data; or
- the calculation of a longitudinal speed to be applied on the basis of the reconstruction data. System (6) for managing the longitudinal speed of a vehicle during 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 one memory element (8), a processing unit (7), a location means (5) and at least one means (4) for detecting 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 one of claims 1 to 8 when said program runs on a computer.