Method and device for controlling a cruise control system for an autonomous vehicle

Abstract

The invention relates to a method and a device for controlling a cruise control of an autonomous vehicle, comprising the steps of: Receiving (201) at least one set of information relating to a characterization of said road along the future trajectory; For each distance, Determining (202) a type of road from said set of data characterizing a type of road; Determining (203) a curvature threshold as a function of the type of road; Determining (204) a corrected curvature as a function of said curvature of the road and said curvature threshold, said corrected curvature being equal to 0 when said curvature of the road is less than said curvature threshold; Determining (205) a set of corrected curvatures from the set of each corrected curvature for each distance; Transmitting (206) said set of corrected curvatures. Figure to be published for the abstract: Figure 2

Description

Title of the invention: Method and device for controlling a cruise control system for an autonomous vehicle Technical field of the invention

[0001] The invention is in the field of autonomous vehicle driving assistance systems. In particular, the invention relates to controlling a cruise control of an autonomous vehicle. State of the art

[0002] The term "vehicle" means any type of vehicle such as a motor vehicle, a moped, a motorcycle, a storage robot in a warehouse, etc. The term "autonomous driving" of a "vehicle" means any process capable of assisting the driving of the vehicle; the "vehicle" is then also called an "autonomous vehicle". The process may thus consist of partially or totally steering the vehicle or providing any type of assistance to a natural person driving the vehicle. The process thus covers all autonomous driving, from level 0 to level 5 in the OICA scale, for International Organization of Motor Vehicle Manufacturers.

[0003] Methods capable of assisting the driving of the vehicle are also called AD AS (from the English acronym "Advanced Driver Assistance Systems"), AD AS systems or driving assistance systems. The cruise control systems of a vehicle are part of the AD AS systems and are known. The speed of the vehicle is regulated to a set speed without the driver needing to press the accelerator pedal.

[0004] It is also known to automatically modify the set speed when the vehicle is turning for comfort and safety purposes. For this, for example, a navigation system, comprising a geolocation system associated with mapping, makes it possible to provide road characteristics.

[0005] The navigation system determines, over a horizon, the future trajectory of the vehicle on a road on which the vehicle is traveling. The horizon is understood as the total length or distance of the determined trajectory. For example, this total distance is between approximately 20 and 200 meters.

[0006] On this horizon, the mapping is able to provide a set of information relating to a characterization of said road along the future trajectory. This set of information is provided at different relative distances from the vehicle, for example every 1 meter or when data characterizing the road changes, the data being able to be a curvature of the road, a location of a traffic sign, a start of a roundabout, data characterizing a type of road as a road shape and a road functionality class... "Curvature of the road at a location on the road", also called "curvature", means the inverse of a radius of curvature of the road at that location.

[0007] Vehicle cruise control systems that modify the set speed when the vehicle is cornering for comfort and safety purposes receive a set of curvatures along the trajectory. The vehicle cruise control system is said to be curvature-driven. Generally, a modified set speed at a location on the road is close to where is a desired maximum transverse acceleration and where R is a radius of curvature (thus the inverse of the curvature) at that location on the road.

[0008] This set of curvature supplied to the cruise control system is quite large, and involves many calculations, sometimes unnecessary, by the cruise control. Indeed, for example on a motorway, in a straight line, at each traffic sign a curvature close to 0 is sent. When turning, since the design of the turns is based on clothoids, the curvatures change continuously, it is not easy to find a speed for passing through the turn. Summary of the invention

[0009] An object of the present invention is to remedy the aforementioned problem, in particular to optimize the transmission, to the cruise control, of the curvatures of a road along a trajectory determined by a navigation system, and to limit the calculations by a cruise control system modifying a set speed when the vehicle is turning for comfort and safety purposes.

[0010] To this end, a first aspect of the invention relates to a method for controlling a cruise control of an autonomous vehicle, said vehicle traveling on a lane of a road, a navigation system determining, on a horizon, a future trajectory of said vehicle on said road, said method being implemented by a processor and comprising the steps of: • Receiving at least one set of information relating to a characterization of said road along the future trajectory, each set comprising a distance from said vehicle, a set of data characterizing a type of road at said distance, a curvature of said road at said distance, a type of road categorizing a road according to a reference speed and its accesses; • For each distance, • Determination of a road type from said set of data characterizing a road type; • Determination of a curvature threshold depending on the type of road; • Determination of a corrected curvature as a function of said road curvature and said curvature threshold, said corrected curvature being equal to 0 when said road curvature is less than said curvature threshold; • Determination of a set of corrected curvatures from the set of each corrected curvature for each distance; • Transmission of said set of corrected curvatures to said speed regulator, said speed regulator modifying a regulation setpoint speed as a function of the corrected curvatures.

[0011] Thus, the set speed of the vehicle cruise control is a function of a set of corrected curvatures. A certain number of said set of corrected curvatures along the trajectory become identical and zero. This simplifies the calculations. Also, the set speed is then a function of the type of road, allowing, for example, to have higher curvature thresholds in certain situations and thus increase the number of corrected curvatures equal to 0.

[0012] Advantageously, two categories of road type are determined, a first category bringing together roads of a type similar to a motorway, a second category bringing together other types of road, said curvature threshold determined for the first category of road type being lower than said curvature threshold determined for the second category of road type.

[0013] This avoids having to calibrate too many thresholds per road type. It has been found that it is useful to have at least one different threshold between roads of a type similar to a motorway and other road types.

[0014] Advantageously, the set of data characterizing a type of road at said distance comprises: • data characterizing a form of the road, the form of the road being at least a motorway or expressway excluding access or exit roads, or another form of road; and • data characterizing a road functionality class, the functionality class being at least a high-traffic road with a speed limit greater than substantially 80% of a maximum traffic speed of a country in which said vehicle is traveling, or another functionality class.

[0015] Thus, with navigation systems using low-resolution maps, called SD maps, from the English acronym "Simple Definition", a road type is determined more reliably. SD maps can only provide information per road and not per lane. This type of map can provide road shape information and functionality class information.

[0016] Advantageously, highway-like roads are determined when • the shape of the road is a motorway or expressway excluding access or exit roads; and • the functionality class is a high-traffic road with a speed limit that is significantly higher than 80% of the maximum traffic speed of the country in which the vehicle is traveling.

[0017] Advantageously, said method further comprises a step of optimizing all of the corrected curvatures, said optimization reducing the number of data.

[0018] Advantageously, when said curvature of the road for a given distance is greater than or equal to said curvature threshold, said corrected curvature for said given distance is a function of the set, for each distance, of the curvatures of the road and the corrected curvatures.

[0019] Thus, it is possible to filter the corrected curvatures. This makes it possible to make the variations in curvatures, between two different distances, smoother, and thus to make the variations in the set speed smoother. This also makes it possible to limit the possible values ​​of the corrected curvatures according to the chosen resolution.

[0020] A second aspect of the invention relates to a device comprising a vehicle speed control system, a navigation system, a memory associated with at least one processor configured to implement the method according to the first aspect of the invention.

[0021] The invention also relates to a vehicle comprising the device.

[0022] The invention also relates to a computer program comprising instructions which, when the program is executed by the device according to the second aspect of the invention, lead the latter to implement the method according to the first aspect of the invention. Brief description of the figures

[0023] Other characteristics and advantages of the invention will emerge from the description of the non-limiting embodiments of the invention below, with reference to the appended figures, in which:

[0024] [Fig.l] schematically illustrates a device, according to a particular example of embodiment of the present invention.

[0025] [Fig.2] schematically illustrates a method for controlling a cruise control of an autonomous vehicle, according to a particular exemplary embodiment of the present invention. Detailed description of the invention

[0026] The invention is described below in its non-limiting application to the case of an autonomous motor vehicle traveling on a road or on a traffic lane. Other applications such as a robot in a storage warehouse or a motorcycle on a country road are also conceivable.

[0027] [Fig. 1] represents an example of a device 101 included in the vehicle, in a network (“cloud”) or in a server. This device 101 can be used as a centralized device in charge of at least certain steps of the method described below with reference to [Fig. 2]. In one embodiment, it corresponds to an autonomous driving computer.

[0028] In the present invention, the device 101 is included in the vehicle.

[0029] This device 101 can take the form of a box comprising circuits printed, from any type of computer or even from a mobile phone (“smartphone”).

[0030] The device 101 comprises a random access memory 102 for storing instructions for the implementation by a processor 103 of at least one step of the method as described below. The device also comprises a mass memory 104 for storing data intended to be retained after the implementation of the method.

[0031] The device 101 may further comprise a digital signal processor (DSP) 105. This DSP 105 receives data to format, demodulate and amplify, in a manner known per se, this data.

[0032] The device 101 also comprises an input interface 106 for receiving the data implemented by the method according to the invention and an output interface 107 for transmitting the data implemented by the method according to the invention.

[0033] For example, the input interface 106 can receive the following data: position or geographical location of the vehicle, speed and / or acceleration of the vehicle, set or predetermined positions / speeds / accelerations, engine speed, position and / or travel of the clutch, brake and / or acceleration pedal, detection of other vehicles or objects, position or geographical location of the other vehicles or objects detected, speed and / or acceleration of the other vehicles or objects detected, operating states of sensors, confidence index of data originating from or processed by sensors and / or devices similar to the device 101. For example, the sensors capable of providing data are: GPS associated or not with mapping, tachometers, accelerometers, RADAR, LIDAR, lasers, ultrasound, camera, navigation system, etc.

[0034] The input interface 106 can also receive the following data: a future trajectory of the vehicle, at least one set of information relating to a characterization of said road along the future trajectory, each set comprising a distance from said vehicle, a set of data characterizing a type of road at said distance, a curvature of said road at said distance, a data ca characterizing a shape of the road, data characterizing a class of functionality of the road, ...

[0035] For example, the output interface 107 can transmit data similar to the data received by the input interface 106. Also, the output interface 107 can transmit: at least one type of road, at least one curvature threshold, at least one corrected curvature, a set of corrected curvatures, a category of road type bringing together roads of a type similar to a motorway, a category of road type bringing together other types of road, a set of optimized corrected curvatures, ...

[0036] [Fig.2] schematically illustrates a method 200 for controlling a cruise control of an autonomous vehicle, according to a particular exemplary embodiment of the present invention.

[0037] Said vehicle travels on a lane of a road. A road allows the circulation of vehicles between two given geographical points. A road comprises at least one carriageway, a part reserved for the circulation of vehicles. A roadway comprises at least one lane, a part generally arranged in one direction.

[0038] A navigation system determines, over a horizon, a future trajectory of said vehicle on said road. A navigation system generally comprises a geolocation system, such as a GPS, associated with a map, a database. For reasons, mainly, of memory capacity limitation, so-called low-resolution maps, called SD maps, from the English acronym "Simple Definition", are used. These types of maps are configured to provide characteristics at the level of a road. These types of maps cannot provide information for a specific lane of a road.

[0039] Said method is implemented by the processor 103 and comprises several steps.

[0040] Step 201, Rx, is a step of receiving at least one set of information relating to a characterization of said road along the future trajectory, each set comprising a distance relative to said vehicle, a set of data characterizing a type of road at said distance, a curvature of said road at said distance, a type of road categorizing a road according to a reference speed and its accesses.

[0041] For example, said at least one set of information relating to a characterization of said route along the future trajectory may be transmitted by said navigation system. Other devices similar to the device 101 may transmit this information.

[0042] For example, said at least one set of information relating to a characterization of said road along the future trajectory may be a matrix which, for each column, indicates, per row, a distance from said vehicle, a set of data characterizing a road type, a curvature of said road. A road type categorizes a road according to a reference speed and its accesses. A reference speed can be a maximum regulatory speed, an authorized speed limit, a practiced speed, ... an access can be with or without resident access, that is to say with or without controlled access (toll for example), or a grade-separated intersection or roundabout or plane, ...

[0043] In one operating mode, the data set characterizing a type of road at said distance comprises: • data characterizing a form of the road, the form of the road being at least a motorway or expressway excluding access or exit roads, or another form of road; and • data characterizing a functionality class of the road, the functionality class being at least a high-traffic road with a speed limit greater than approximately 80% of a maximum traffic speed of a country in which said vehicle is traveling, or another functionality class.

[0044] For example, said other form of road includes a single-lane road, a roundabout, an intersection, etc. For example, in France, approximately 80% of a maximum traffic speed is of the order of 100 km / h.

[0045] A curvature of a road at a location, curvature, or curvature of the road at a location on the road, also called "curvature", is the inverse of a radius of curvature of the road at that location.

[0046] Step 202, DetTypRd, is a step, for each distance, of determining a type of road from said set of data characterizing a type of road. Thus, along the future trajectory, at different distances, the type of road is known, a type of road categorizing a road according to a reference speed and its accesses.

[0047] Advantageously, two categories of road type are determined, a first category bringing together roads of a type similar to a motorway, a second category bringing together other types of road, said curvature threshold determined for the first category of road type being lower than said curvature threshold determined for the second category of road type. Roads similar to a motorway are roads whose traffic speed is potentially high and whose access is regulated because they are priority roads and without roundabouts or plan.

[0048] Advantageously, roads of a type similar to a motorway are determined when: the shape of the road is a motorway or expressway excluding the lanes access or exit; and • the functionality class is a high-traffic road with a speed limit that is significantly higher than 80% of the maximum traffic speed of the country in which the vehicle is traveling.

[0049] The combination of these two criteria makes it possible to make the determination of a road similar to a motorway more reliable. Indeed, SD maps include inaccuracies or errors. One cause of these inaccuracies or errors comes from the fact that these maps are not often updated (at best every 6 months, generally every 12 months). In the event of a change in the road network, the map no longer represents the current state of the road network well.

[0050] Step 203, DetCurv, is a step, for each distance, of determining a curvature threshold according to the type of road. It is then possible to have different thresholds. We adapt according to the situation. For example, for the first category of road, it is interesting to have a lower threshold than for the second category. It has been found that having different thresholds allows for a variation in the set speed of the cruise control that is smoother, more comfortable and more suitable for a driver of the vehicle when traveling at a speed close to the speed limit of the road.

[0051] For example, for the first category of road type, the curvature threshold is of the order between 0.00030 m 1 and 0.00070 m1, preferably close to 0.0006 m1 but other values ​​are possible. For the second category of road type, the curvature threshold is of the order of 0.00080 m1 and 0.00150 m1, preferably close to 0.00120 m 1 but other values ​​are possible.

[0052] Step 204, DetCurvC, is a step, for each distance, of determining a corrected curvature as a function of said road curvature and said curvature threshold, said corrected curvature being equal to 0 when said road curvature is less than said curvature threshold. Depending on the type of road, unhelpful curvature values ​​are replaced by 0.

[0053] Step 205, Optim, is a step of determining a set of corrected curvatures from the set of each corrected curvature for each distance. In step 206, this set is transmitted to said speed regulator.

[0054] Advantageously, said method further comprises a step of optimizing all of the corrected curvatures, said optimization reducing the number of data.

[0055] Taking the example above where said at least one set of information relating to a characterization of said road along the future trajectory is a matrix which, for each column, indicates, per row, a distance from said vehicle, a set of data characterizing a type of road, a curvature of said road, said set of corrected curvatures may be another matrix which, for each column, indicates, per row, a distance from said vehicle, and said corrected curvature.

[0056] In this example, furthermore, the dimension of said other matrix can be reduced and eliminating the curvature duplicates (same curvature value between two successive distances). This simplifies the calculations for a regulation setpoint speed calculation.

[0057] Advantageously, when said curvature of the road for a given distance is greater than or equal to said curvature threshold, said corrected curvature for said given distance is a function of the set, for each distance, of the curvatures of the road and the corrected curvatures. Thus, the curvatures are smoothed.

[0058] It is also possible to set a curvature resolution per curvature range such as, for example, a resolution of 0.0001 m1 for curvatures ranging from 0 to 0.0008 m1, for example, a resolution of 0.0002 m1 for curvatures ranging from 0.0008 to 0.0015 m1, etc. This limits the number of values ​​and simplifies the calculations.

[0059] Finally, step 206, TX, is a step of transmitting said set of corrected curvatures to said cruise control, said cruise control modifying a regulation setpoint speed as a function of the corrected curvatures. The cruise control receiving this list of corrected curvatures will adapt the setpoint speed as a function of a speed of the vehicle and the corrected curvatures received, making it possible to maximize the comfort of the vehicle's passengers and to maximize safety according to the type of road.

[0060] The present invention is not limited to the embodiments described above as examples: it extends to other variants.

[0061] For example, the method has been described according to a sequence of steps. Certain steps can be carried out in parallel or according to another sequence.

Claims

1.

2. Claims Method for controlling a cruise control system of an autonomous vehicle, said vehicle traveling on a lane of a road, a navigation system determining, on a horizon, a future trajectory of said vehicle on said road, said method being implemented by a processor (103) and comprising the steps of: • Reception (201) of at least one set of information relating to a characterization of said road along the future trajectory, each set comprising a distance relative to said vehicle, a set of data characterizing a type of road at said distance, a curvature of said road at said distance, a type of road categorizing a road according to a reference speed and its accesses; • For each distance, • Determination (202) of a type of road from said set of data characterizing a type of road; • Determination (203) of a curvature threshold depending on the type of road; • Determination (204) of a corrected curvature as a function of said curvature of the road and said curvature threshold, said corrected curvature being equal to 0 when said curvature of the road is less than said curvature threshold; • Determination (205) of a set of corrected curvatures from the set each corrected curvature for each distance; • Transmission (206) of said set of corrected curvatures to said speed regulator, said speed regulator modifying a regulation setpoint speed as a function of the corrected curvatures. Method according to claim 1, in which two categories of road type are determined, a first category grouping roads of a type similar to a motorway, a second category grouping other types of road, said curvature threshold determined for the first category of road type being lower than said curvature threshold curvature determined for the second category of road type.

3. Method according to any one of the preceding claims, in which the set of data characterizing a type of road at said distance comprises: • data characterizing a shape of the road, the shape of the road being at least a motorway or expressway excluding access or exit roads, or another shape of road; and • data characterizing a class of functionality of the road, the class of functionality being at least a high-traffic road with a speed limit greater than substantially 80% of a maximum traffic speed of a country in which said vehicle is traveling, or another class of functionality.

4. A method according to claims 2 and 3, wherein the highway-like roads are determined when • the road shape is a highway or expressway excluding access or exit lanes; and • the functionality class is a busy road with a speed limit greater than substantially 80% of the maximum traffic speed of the country in which said vehicle is traveling.

5. A method according to any preceding claim, wherein said method further comprises a step of optimizing the set of corrected curvatures, said optimization reducing the number of data.

6. A method according to any preceding claim, wherein when said road curvature for a given distance is greater than or equal to said curvature threshold, said corrected curvature for said given distance is a function of the set, for each distance, of the road curvatures and the corrected curvatures.

7. Device (101) comprising a vehicle speed control system, a navigation system, a memory (102) associated with at least one processor (103) configured to implement the method according to one of the preceding claims.

8.

9. Vehicle comprising the device according to the preceding claim. Computer program comprising instructions which, when the program is executed by the device (101) according to claim 7, cause the latter to implement the method according to one of claims 1 to 6.

Images