Method for detecting objects on the rear seats of a motor vehicle

Abstract

A method for detecting objects in the rear seats of a motor vehicle comprises the steps of: detecting (21) the opening of a rear door of the motor vehicle and the duration (23) of the opening; estimating (27) the presence of an object in the rear seat based on the duration of the opening. An object detection system and a motor vehicle comprising the system are also described. Figure to be published with the abbreviation: Fig 2

Description

Title of the invention: Method for detecting objects on the rear seats of a motor vehicle Technical field

[0001] The present invention relates to a method for detecting objects on the rear seats of a motor vehicle, a computer program product, a system for detecting objects on the rear seats and a motor vehicle comprising such a system. State of the art

[0002] Often a motor vehicle user will place an object (suitcase, briefcase, shopping bag, umbrella, etc.) on the rear seats of the vehicle before taking the wheel.

[0003] However, it is noted that, quite regularly, the user forgets this object when he has finished his journey and leaves the vehicle. This has the disadvantage of forcing him to return to the vehicle when he realizes he has forgotten it. But it also has the disadvantage of offering opportunities for theft when a malicious person sees this object left in the unoccupied vehicle.

[0004] There is therefore a real need for a method and system for detecting objects on the rear seats which can thus warn the user. Description of the invention

[0005] To resolve one or more of the drawbacks cited above, according to a first embodiment, a method for detecting objects on the rear seats of a motor vehicle comprises the steps of: • detection of opening of a rear door of the motor vehicle and the duration of the opening; • estimation of the presence of an object in the rear seat based on the duration of the opening.

[0006] Thus, the user can be informed of the presence of an object in the rear seat.

[0007] Particular characteristics or embodiments, usable alone or in combination are: • presence estimation is based on a deep learning algorithm • the estimation of the presence of the object is confirmed by an interrogation of the user via a human-machine interface; • the presence estimate is determined by a statistical model based on a history of rear door openings, each opening and its duration being associated with a confirmed or unconfirmed presence of an object; • the estimation of the presence of an object further includes the use of the geographical position of the vehicle when opening the rear door; • the estimation of the presence of an object further includes the detection of the presence of a passenger in the rear seat; and / or • when the presence of an object is considered probable, a reminder message of the presence of the object is sent to the user when the vehicle stops.

[0008] In a second embodiment, a computer program comprises instructions for implementing the steps of a method as defined above during an execution of the program by a computing unit of said apparatus.

[0009] In a third embodiment, a system for detecting objects on the rear seats of a motor vehicle comprises: • a detector for opening a rear door of the motor vehicle comprising a module for measuring the duration of the opening; connected to • an estimator of the presence of an object in the rear seat based on the duration of the opening.

[0010] In a fourth embodiment, a motor vehicle comprises a system according to the third embodiment. Brief description of the figures

[0011] The invention will be better understood on reading the following description, given solely by way of example, and with reference to the appended figures in which: • [Fig.l] represents a side view of a vehicle comprising an object detection system according to one embodiment; and • [Fig.2] represents a flowchart of an object detection method according to an embodiment. Methods of implementation

[0012] The embodiments presented below refer to a motor vehicle, a car. However, those skilled in the art understand that these are also usable with other types of vehicle such as vans, vans, etc.

[0013] The terms “front”, “rear”, “top”, “bottom”, “transverse” are understood in relation to the vehicle.

[0014] With reference to [Fig.l], a motor vehicle 1 comprises a rear door 3. This rear door 3 is connected to a detector 5 for detecting the opening of the rear door 3. The detector 5 includes a module 7 for recording the duration of opening of the rear door 3.

[0015] The motor vehicle 1 comprises a controller 9 connected to the opening detector 5.

[0016] The controller 9 may, for example, be integrated into the vehicle control system 1, such as an advanced driver assistance system, commonly called AD AS (for “Advanced driver-assistance Systems” in English terminology) which makes all driving decisions based on the environment and the programmed destination. The motor vehicle is then referred to as an autonomous motor vehicle. But it may also be a centralized vehicle management system including, or not, driving aids.

[0017] The transfer of data between the different elements is carried out by a CAN (for “Controller Area Network” in English) or LIN (for “Local Interconnect Network” in English) type data bus.

[0018] The controller 9 comprises an estimator 11 of the presence of an object in the rear seat as a function of the duration of the opening. For example, the estimator 11 is a software module running on the controller 9.

[0019] Furthermore, the controller 9 is connected to a person-machine interface 13 allowing communication with the user of the vehicle 1 and, in particular, entering certain information.

[0020] This interface 13 is constituted for example by the dashboard of the vehicle associated with the controls of the dashboard and the steering wheel.

[0021] The general operation of the object detection system is as follows, [Fig.2].

[0022] First, step 21, the opening detector 5 detects the opening of the rear door 3. Module 7 is activated, step 23, to measure the opening time.

[0023] When the rear door is closed, the opening event and its duration are sent to the controller 9, step 25. The estimator 11 then estimates, step 27, the presence of an object in the rear seat as a function of this duration.

[0024] In a so-called learning phase, the controller 9 sends, step 29, the result of the estimator 9 on the interface 13 and receives a confirmation, or an invalidation, of the presence estimation from the user, step 31.

[0025] This learning phase makes it possible to record a validated history associating opening duration and presence, or absence, of an object. The estimator 11 thus constructs a statistical model using, for example, deep learning techniques.

[0026] When the estimator reaches a reliability level higher than a predetermined level, this learning phase ends and steps 29 and 31 are no longer executed, unless the user requests to restart a learning phase, for example, following a change in habit or driver.

[0027] When the vehicle stops, when the journey is finished, and the presence of an object in the rear seat has been deemed probable, the controller 9 sends, step 33, a reminder message to the user. For example, the journey is considered finished when the user turns off the ignition, or if he gets out of the vehicle and locks it. The reminder message may be a voice message or a message displayed on the interface 13, but it may also be a message sent to the user's telephone. This message may only be sent to the user if the rear door 3 is not opened after the vehicle has stopped.

[0028] [Fig.l] illustrates a system according to certain embodiments. The breakdown presented has an educational purpose to highlight the different functions. However, it is understood that each block can be implemented using different means or their combinations, such as hardware components, software, one or more computers and / or electronic circuits. Each of the components can include at least one computer or a control-command unit. At least one memory can be included in each component. The memory can include computer program instructions or software code.

[0029] The computers can be implemented by any type of data processing device, such as a central computing unit, a signal processing processor, an application-specific integrated circuit, a programmable gate array, etc. The computers can be implemented as a single controller, or a plurality of controllers or computers.

[0030] The different modules are connected to each other by data links adapted to the environment. These can be wired or wireless.

[0031] For software, the implementation may include modules or units distributed in the form of procedures, functions, etc. The memories may be any type of storage circuit. They may be part of the processor circuit, or separate from it and connected via electrical data links. These may be non-volatile type memories, hard disks, random access memories, flash memories, etc.

[0032] Furthermore, the program instructions stored in the memory and processed by the computers can be any type of program code, for example, a compiled or interpreted program written in a suitable programming language.

[0033] The computer program instructions stored in the memory are such that, when executed by the computer, the latter carries out one or more of the steps of the methods described above.

[0034] The invention has been illustrated and described in detail in the drawings and the preceding description. This should be considered as illustrative and given by way of example and not as limiting the invention to this description alone. Numerous alternative embodiments are possible.

[0035] In a first variant, the system comprises a geographic position detector, such as a GNSS chip (“Geolocation and Navigation by a System of Satellites”). Estimator 11 then includes the position of the vehicle in its statistical model.

[0036] In a second variant, the vehicle 1 comprises sensors for detecting the presence of passengers in the rear seats. The estimator 11 then takes this presence into account to consider that the opening of the rear doors may not correspond to the placement of an object.

Claims

Claims

1. Method for detecting an object on the rear seats of a motor vehicle, comprising the steps of: • detecting (21) the opening of a rear door of the vehicle and the duration (23) of the opening; • estimating (27) the presence of an object in the rear seat as a function of the duration of the opening.

2. The method of claim 1, wherein the presence estimation is based on a deep learning algorithm.

3. Method according to claim 1 or 2, in which the estimation of the presence of object is confirmed by a query of the user via a human-machine interface.

4. Method according to claim 3, in which the estimation of the presence is determined by a statistical model based on a history of rear door openings, each opening and its duration being associated with a confirmed, or not, presence of an object.

5. A method according to any preceding claim, wherein estimating the presence of an object further comprises using the geographic position of the vehicle when opening the rear door.

6. A method according to any preceding claim, wherein estimating the presence of an object further comprises detecting the presence of a rear seat passenger.

7. Method according to any one of the preceding claims, in which, when the presence of an object is estimated to be probable, a reminder message of the presence of the object is sent to the user when the vehicle stops.

8. Computer program product downloadable from a communication network and / or recorded on a computer-readable medium and / or executable by a processor, characterized in that it comprises program code instructions for implementing the method according to at least one of claims 1 to 7.

9. System for detecting objects on the rear seats of a motor vehicle (1), comprising: • an opening detector (5) of a rear door (3) of the vehicle automobile comprising a module (7) for measuring the duration of the opening; connected to • an estimator (11) of the presence of an object in the rear seat as a function of the duration of the opening.

10. A motor vehicle comprising a system according to claim 9.

Images