DRIVING ASSISTANCE FOR THE LONGITUDINAL AND/OR LATERAL CONTROL OF A MOTOR VEHICLE

Abstract

The invention relates to a driving assistance system (3) for the longitudinal and/or lateral control of a motor vehicle, comprising an image processing device (31a) trained beforehand using a learning algorithm and configured so as to generate, at output, a control instruction (S.sub.com1) for the motor vehicle from an image (Im.sub.1) provided at input and captured by an on-board digital camera (2); a digital image processing module (32) configured so as to provide at least one additional image (Im.sub.2) at input of an additional device (31b), identical to the device (31a), for parallel processing of the image (Im.sub.1) captured by the camera (2) and said at least one additional image (Im.sub.2), such that said additional device (31b) generates at least one additional control instruction (S.sub.com2) for the motor vehicle, said additional image (Im.sub.2) resulting from at least one geometric and/or radiometric transformation performed on said captured image (Im.sub.1), and a digital fusion module (33) configured so as to generate a resultant control instruction (S.sub.com) on the basis of said control instruction (S.sub.com1) and of said at least one additional control instruction (S.sub.com2).

Claims

1. A driving assistance method for the longitudinal and/or lateral control of a motor vehicle, the method comprising: processing an image captured by a digital camera housed on board said motor vehicle using a processing algorithm that has been trained beforehand by a machine learning algorithm, so as to generate a longitudinal and/or lateral control instruction for the motor vehicle; in parallel with said step of processing the image, at least one additional image using said processing algorithm, so as to generate at least one additional longitudinal and/or lateral control instruction for the motor vehicle, said at least one additional image resulting from at least one geometric and/or radiometric transformation performed on said captured image; and generating a resultant longitudinal and/or lateral control instruction on the basis of said longitudinal and/or lateral control instruction and of said at least one additional longitudinal and/or lateral control instruction.

2. The method according to claim 1, wherein said at least one geometric and/or radiometric transformation comprises zooming, magnifying a region of interest of said captured image.

3. The method according to claim 1, wherein said at least one geometric and/or radiometric transformation comprises rotating, or modifying the brightness, or cropping said captured image or a region of interest of said captured image.

4. The method according to claim 1, wherein said longitudinal and/or lateral control instruction and said at least one additional longitudinal and/or lateral control instruction comprise information relating to a setpoint steering angle of the steering wheel of the motor vehicle.

5. The method according to claim 1, wherein said longitudinal and/or lateral control instruction and said at least one additional longitudinal and/or lateral control instruction comprise information relating to a setpoint speed and/or a setpoint acceleration.

6. The method according to claim 5, wherein said resultant longitudinal and/or lateral control instruction is generated by calculating an average of said longitudinal and/or lateral control instruction and said at least one additional longitudinal and/or lateral control instruction.

7. The method according to claim 5, wherein said resultant longitudinal and/or lateral control instruction corresponds to a minimum value out of a setpoint speed in relation to said longitudinal and/or lateral control instruction and an additional setpoint speed in relation to said at least one additional longitudinal and/or lateral control instruction.

8. A driving assistance system for the longitudinal and/or lateral control of a motor vehicle, the system comprising: an image processing device housed on board the motor vehicle, said image processing device having been trained beforehand using a machine learning algorithm and being configured to generate, at output, a longitudinal and/or lateral control instruction for the motor vehicle from an image; an on-board digital camera configured to generate the image; at least one additional image processing device identical to said image processing device; a digital image processing module configured to provide at least one additional image at input of said additional image processing device for parallel processing of the image captured by the camera and said at least one additional image, such that said additional image processing device generates at least one additional longitudinal and/or lateral control instruction for the motor vehicle, said at least one additional image resulting from at least one geometric and/or radiometric transformation performed on said image; and a digital fusion module configured so as to generate a resultant longitudinal and/or lateral control instruction on the basis of said longitudinal and/or lateral control instruction and of said at least one additional longitudinal and/or lateral control instruction.

9. A system according to claim 8, wherein the machine learning algorithm comprises a deep neural network.

Description

[0029] The invention will be better understood upon reading the following description, given with reference to the appended figures, in which:

[0030] FIG. 1, already described above, illustrates, in simplified form, an architecture shared by the driving assistance systems, housed on board a vehicle implementing processing of images coming from an on-board camera;

[0031] FIG. 2, already described above, is a simplified overview of a known system for the longitudinal and/or lateral control of a motor vehicle, using a neural network;

[0032] FIG. 3, already described above, is a known variant of the system from FIG. 2;

[0033] FIG. 4 shows, in the form of a simplified overview, one possible embodiment of a driving assistance system according to the invention;

[0034] FIGS. 5 and 6 illustrate principles applied by the system from FIG. 4 to two exemplary road situations.

[0035] In the remainder of the description, and unless provision is made otherwise, elements common to all of the figures bear the same references.

[0036] A driving assistance system according to the invention will be described with reference to FIG. 4, in the context of the longitudinal control of a motor vehicle. The invention is however not limited to this example, and may in particular be used to allow lateral control of a motor vehicle, or to allow both longitudinal and lateral control of a motor vehicle. In FIG. 4, the longitudinal control assistance system 3 comprises, as described in the context of the prior art, an image processing device 31a housed on board the motor vehicle, receiving, at input, an image Im.sub.1 captured by a digital camera 2 also housed on board the motor vehicle. The image processing device 31a has been trained beforehand using a learning algorithm and configured so as to generate, at output, a longitudinal control instruction S.sub.com1, for example a setpoint speed value or a setpoint acceleration, suited to the situation shown in the image Im.sub.1. The device 31a may be the device 31 described with reference to FIG. 2, or the device 31 described with reference to FIG. 3. If necessary, the system comprises a redimensioning module 30a configured so as to redimension the image Im.sub.1 to form an image Im.sub.1′ that is compatible with the image size that the device 31a is able to process.

[0037] The image processing device 31a comprises for example a deep neural network.

[0038] The image processing device 31a is considered here to be a black box, in the sense that the invention proposes to improve the responsiveness of the algorithm that it implements without acting on its internal operation.

[0039] To this end, the invention makes provision to perform, in parallel with the processing performed by the device 31a, at least one additional processing operation using the same algorithm as the one implemented by the device 31a, on an additional image formulated from the image Im.sub.1.

[0040] To this end, according to one possible embodiment of the invention, the system 3 comprises a digital image processing module 32 configured so as to provide at least one additional image Im.sub.2 at input of an additional image processing device 31b, identical to the device 31a and accordingly implementing the same processing algorithm, this additional image Im.sub.2 resulting from at least one geometric and/or radiometric transformation performed on the image Im.sub.1 initially captured by the camera 2. In this case too, the system 3 may comprise a redimensioning module 30b similar to the redimensioning module 30a, in order to provide an image Im.sub.2′ compatible with the input of the additional device 31b.

[0041] As illustrated by way of non-limiting example in FIG. 4, the digital module 32 is configured so as to perform zooming, magnifying a region of interest of the image Im.sub.1 captured by the camera 2, for example a central region of the image Im.sub.1. FIGS. 5 and 6 give two exemplary transformed images Im.sub.2 resulting from zooming, magnifying the centre of an image Im.sub.1 captured by a camera housed on board at the front of a vehicle. In the case of FIG. 5, the road scene ahead of the vehicle, shown in the image Im.sub.1, shows a completely clear straight road ahead of the vehicle. In contrast, the image Im.sub.1 in FIG. 6 shows the presence, ahead of the vehicle, of another vehicle whose rear stop lights are turned on. For both FIGS. 5 and 6, the image Im.sub.2 is a zoomed image, magnifying the central region of the image Im.sub.1. In the case of a hazard being present (situation in FIG. 6), the magnifying zoom gives the impression that the other vehicle is far closer than it actually is.

[0042] The system 3 according to the invention will thus be able to perform at least two parallel processing operations, specifically:

[0043] a first processing operation on the captured image Im.sub.1 (possibly on the redimensioned image Im.sub.1′) performed by the device 31a, allowing it to generate a control instruction S.sub.com1;

[0044] at least one second processing operation on the additional image Im.sub.2 (possibly on the additional redimensioned image Im.sub.2′) performed by the additional device 31b, allowing it to generate an additional control instruction S.sub.com2, possibly separate from the control instruction S.sub.com1.

[0045] The instruction S.sub.com1 and the additional instruction S.sub.com2 are of the same kind, and each comprise for example information relating to a setpoint speed to be adopted by the motor vehicle equipped with the system 3. As a variant, the two instructions S.sub.com1 and S.sub.com2 may each comprise a setpoint acceleration, having a positive value when the vehicle has to accelerate, or having a negative value when the vehicle has to slow down.

[0046] In other embodiments for which the system 3 should allow driving assistance with lateral control of the motor vehicle, the two instructions S.sub.com1 and S.sub.com2 will each comprise information preferably relating to a setpoint steering angle of the steering wheel of the motor vehicle.

[0047] In the example of the road situation shown in FIG. 5, the magnifying zoom will not have any real impact, since neither of the images Im.sub.1 and Im.sub.2 represent the existence of a hazard. The two processing operations performed in parallel will in this case generate two instructions S.sub.com1 and S.sub.com2 that are probably identical or similar.

[0048] On the other hand, for the example of the road situation shown in FIG. 6, the additional instruction S.sub.com2 will correspond to a setpoint deceleration whose value will be far higher than for the instruction S.sub.com1, due to the fact that the device 31b will judge that the other vehicle is far closer and that it is necessary to brake earlier.

[0049] The system 3 according to the invention furthermore comprises a digital fusion module 33 connected at output of the processing devices 31a and 31b and receiving the instructions S.sub.com1 and S.sub.com2 at input.

[0050] The digital fusion module 33 is configured so as to generate a resultant longitudinal control instruction S.sub.com on the basis of the instructions that it receives at input, in this case on the basis of the instruction S.sub.com1 resulting from the processing of the captured image Im.sub.1, and of the additional instruction S.sub.com2 resulting from the processing of the image Im.sub.2. Various fusion rules may be applied at this level so as to correspond to various driving styles.

[0051] For example, if the instruction S.sub.com1 corresponds to a setpoint speed for the motor vehicle and the additional instruction S.sub.com2 corresponds to an additional setpoint speed for the motor vehicle, the digital fusion module 33 will be able to generate:

[0052] a resultant instruction S.sub.com corresponding to the minimum value out of the setpoint speed and the additional setpoint speed, for what is called a “safe” driving style; or

[0053] a resultant instruction S.sub.com corresponding to the average value of the setpoint speed and the additional setpoint speed, for what is called a “conventional” driving style.

[0054] A geometric transformation other than the magnifying zoom may be contemplated without departing from the scope of the present invention. By way of non-limiting example, there may in particular be provision to configure the digital module 32 so that it rotates, crops or deforms the image Im.sub.1 or a region of interest of this image Im.sub.1.

[0055] A radiometric transformation, for example modifying the brightness or the contrast, may also be beneficial in terms of improving the responsiveness of the algorithm implemented by the devices 31a and 31b.

[0056] Of course, all or some of these transformations may be combined so as to produce a transformed image Im.sub.2.

[0057] As a variant, there may be provision for the system 3 to comprise a plurality of additional processing operations performed in parallel, each processing operation comprising a predefined transformation of the captured image Im.sub.1 into a second image Im.sub.2, and the generation of an associated instruction by a device identical to the device 31a. By way of example, it is possible, on one and the same image Im.sub.1, to perform various zooming at various scales, or to modify the brightness to various degrees, or to perform several transformations of various kinds.

[0058] The benefit of these parallel processing operations is that of being able to generate a plurality of possibly different instructions from transformations performed on one and the same image, so as to improve the overall behaviour of the algorithm used by the device 31a.

[0059] The fusion rules applied based on this plurality of instructions may be diverse depending on whether or not preference is given to safety. By way of example, the digital fusion module may be configured so as to generate:

[0060] a resultant instruction S.sub.com corresponding to the minimum value out of the various setpoint speeds resulting from the various processing operations, for what is called a “safe” driving style; or

[0061] a resultant instruction S.sub.com corresponding to the average value of the various setpoint speeds resulting from the various processing operations, for what is called a “conventional” driving style; or

[0062] a resultant instruction S.sub.com corresponding to the average value of the two highest setpoint speeds resulting from the various processing operations, for what is called an “aggressive” driving style.