Method for identifying an AVP motor vehicle for an AVP process

Abstract

The invention relates to a method for identifying an AVP motor vehicle for an AVP process, in which a driving behavior of an AVP motor vehicle which is manually guided in the region of a parking lot is determined on the motor vehicle side, the driving behavior determined on the motor vehicle side is compared with the driving behavior determined on the infrastructure side of one motor vehicle located in the same area of the parking lot or of a plurality of motor vehicles located in the same area of the parking lot in order to identify an AVP motor vehicle. The invention relates to a further method for identifying an AVP motor vehicle for an AVP process, to a device, to a motor vehicle, to a computer program, to a machine-readable storage medium, and to a system for identifying an AVP motor vehicle for an AVP process.

Description

Technical Field

[0001] The present invention relates to a method for identifying an AVP motor vehicle for an AVP procedure, a device, a motor vehicle, a computer program and a machine-readable storage medium, and a system for identifying an AVP motor vehicle for an AVP procedure. Background Art

[0002] In so-called "Automated Valet Parking" (AVP) with infrastructure support, one or more automated vehicles are guided through a parking lot by an external infrastructure. To achieve this function, the infrastructure must recognize and locate the individual automated vehicles in its area of ​​use. Once recognition is successful, the infrastructure environment sensors locate the recognized vehicle and begin guided driving in the parking lot.

[0003] The abbreviation "AVP" stands for "Automated Valet Parking" and can be translated into German as "automatischer Parkservice (automatic valet parking)". The AVP process includes, for example, at least highly automated guidance of an AVP motor vehicle from a drop-off area (also called a handover position or drop-off area) to a parking position and, for example, at least highly automated guidance of the motor vehicle from a parking position to a pick-up position (also called a drop-off area). At the handover position, i.e. the drop-off area, the driver of the motor vehicle hands over the motor vehicle for the AVP process. At the pick-up position, i.e. the pick-up area, the motor vehicle is removed after the end of the AVP process. The AVP process thus begins, in particular, at the drop-off area. The AVP process thus ends, in particular, at the pick-up area. The pick-up area can be the same as or different from the drop-off area.

[0004] That is, an AVP vehicle is a vehicle that can participate in the AVP process.

[0005] One possibility for identifying a motor vehicle for the AVP process is to identify the motor vehicle by light code recognition, wherein the direction indicators of the motor vehicle are used as light sources. The details of the recognition process are described below.

[0006] The AVP vehicle is located in the drop-off area or "drop-off zone" for short and is wirelessly connected to the infrastructure. The infrastructure sends a code to the vehicle via the wireless communication interface. The relevant motor vehicle should light the turn indicators in accordance with the code. The infrastructure monitors the drop-off area with a camera and tries to recognize the flashing code in the camera image. If the code is recognized correctly, the infrastructure can associate its camera image with the specific AVP vehicle. The motor vehicle is thus identified and located, which means that the posture of the motor vehicle is also determined. Summary of the invention

[0007] The object of the present invention is to provide a concept for identifying an AVP motor vehicle for an AVP procedure.

[0008] This object is achieved by means of the respective subject matter of the independent claims. Advantageous embodiments of the invention are the subject matter of the respective dependent claims.

[0009] According to a first aspect, a method for identifying an AVP vehicle for an AVP procedure is provided, comprising the following steps:

[0010] receiving, on the infrastructure side, driving behavior data describing a first driving behavior of an AVP motor vehicle that is manually guided in an area of ​​a parking lot that is monitored by the infrastructure environment sensor arrangement,

[0011] receiving, at the infrastructure side, monitoring data based on monitoring of the area by infrastructure environmental sensor means,

[0012] processing the monitoring data on the infrastructure side in order to detect on the infrastructure side a motor vehicle that is in an area monitored by the infrastructure surroundings sensor system based on the monitoring data,

[0013] When a motor vehicle in the area is detected on the infrastructure side based on the monitoring data, a second driving behavior of the motor vehicle detected on the infrastructure side is determined on the infrastructure side based on the monitoring data,

[0014] comparing the first driving behavior with the second driving behavior on the infrastructure side,

[0015] Based on the comparison, the AVP motor vehicle is identified on the infrastructure side as a motor vehicle detected on the infrastructure side.

[0016] According to a second aspect, a method for identifying an AVP vehicle for an AVP procedure is provided, comprising the following steps:

[0017] determining, on the motor vehicle side, driving behavior data describing a first driving behavior of an AVP motor vehicle being manually guided in an area of ​​a parking lot monitored by the infrastructure surroundings sensor arrangement,

[0018] receiving, on the motor vehicle side, monitoring data based on monitoring of the area by means of the infrastructure environment sensor means,

[0019] processing the monitoring data on the motor vehicle side in order to detect on the motor vehicle side a motor vehicle that is located in the area monitored by the infrastructure surroundings sensor system based on the monitoring data,

[0020] When a motor vehicle located in the area is detected on the motor vehicle side based on the monitoring data, a second driving behavior of the motor vehicle detected on the motor vehicle side is determined on the motor vehicle side based on the monitoring data,

[0021] comparing the first driving behavior with the second driving behavior on the motor vehicle side,

[0022] Based on the comparison, the AVP motor vehicle is identified on the motor vehicle side as a motor vehicle detected on the motor vehicle side.

[0023] According to a third aspect, a device is provided, which is configured to perform all steps of the method according to the first aspect and / or according to the second aspect.

[0024] According to a fourth aspect, a motor vehicle is provided, comprising a device according to the third aspect, which is configured to carry out all steps of the method according to the second aspect.

[0025] According to a fifth aspect, a computer program is provided, comprising instructions which, when executed by a computer, such as a device according to the third aspect, cause the computer, such as a device according to the third aspect, to perform a method according to the first aspect and / or according to the second aspect.

[0026] According to a sixth aspect there is provided a machine-readable storage medium on which the computer program according to the fifth aspect is stored.

[0027] According to a seventh aspect, a system for identifying an AVP motor vehicle for an AVP process is provided, comprising a device according to the third aspect and an infrastructure environment sensor mechanism, wherein the device is configured to perform all steps of the method according to the first aspect, and the infrastructure environment sensor mechanism is configured to monitor an area of ​​a parking lot and output monitoring data based on the monitoring to the device.

[0028] The present invention is based on and includes the following knowledge, and achieves the above-mentioned task by comparing the driving behavior (first driving behavior) determined by the AVP motor vehicle itself with the driving behavior (second driving behavior or additional driving behavior) determined on the infrastructure side of a motor vehicle located in the same area of ​​the parking lot motor vehicles or multiple motor vehicles located in the same area of ​​the parking lot to identify the AVP motor vehicle.

[0029] Therefore, the above task is particularly accomplished by comparing the relative movement (driving behavior) recorded by the AVP vehicle with the driving behavior determined on the infrastructure side, which driving behavior is determined on the infrastructure side based on monitoring data, wherein the area in which the AVP vehicle is located is monitored by infrastructure environment sensors while the driver still manually controls the movement of the AVP vehicle. Based on the monitoring, the infrastructure environment sensors output corresponding monitoring data.

[0030] Vehicle movement is characterized in particular by the vehicle position and the change in position over time. For example, an AVP motor vehicle measures this movement with the aid of its internal odometer. An infrastructure measures or detects the same movement with the aid of infrastructure environment sensors.

[0031] For example, the data required to coordinate the movement are transmitted via the infrastructure side or the network. The wireless interface of the vehicle has been changed. The AVP vehicle or the infrastructure, or both, analyzes the respective driving behavior and tries to coordinate. For example, once a match is found, the AVP vehicle is identified as a vehicle whose driving behavior determined by the infrastructure side is consistent with the driving action determined by the AVP vehicle itself. For example, after successful identification, the identified AVP vehicle is located.

[0032] Positioning within the scope of the description refers in particular to the positioning of a motor vehicle in an absolute or relative coordinate system. This includes the orientation or alignment in which the motor vehicle is parked (initial attitude). Positioning thus includes in particular the determination of the attitude of the motor vehicle.

[0033] The solution described here has the following advantages in particular:

[0034] Motor vehicle identification and in particular motor vehicle positioning can advantageously already be carried out during the manually guided travel through the parking lot, that is to say even before the driver has left the AVP motor vehicle. Thus, when the driver arrives at the drop-off area, the AVP motor vehicle, for example, has already been identified. This thereby eliminates waiting times for motor vehicle identification in the drop-off area. This is beneficial to the driver and increases the possible throughput of AVP motor vehicles for the AVP process. For example, both the odometer of the AVP motor vehicle and the infrastructure environment sensors can have a high measurement rate. Thus, a small amount of measurement data is sufficient to achieve an accurate identification of the AVP motor vehicle among many other motor vehicles. The identification process is advantageously not visible from the outside.

[0035] A further advantage of this approach is, for example, that the initialization of the AVP procedure can take place more quickly, since no additional waiting time is required for the lighting signal to be recognized.

[0036] A further advantage of the described solution is, for example, that the initialization of the AVP procedure can be performed invisibly. The initialization is, for example, invisible to the user.

[0037] A further advantage of this solution is, for example, that the user can cancel the manual confirmation when he is in the drop-off zone.

[0038] A further advantage of the solution is that, for example, the identification of an AVP vehicle in a drop-off zone is more reliable than by manual confirmation, because the user can confirm even if he is not in the drop-off zone. The AVP vehicle does not need to emit a light signal according to the procedure described in the introduction to the description.

[0039] The advantage of the method according to the second aspect is, for example, that the AVP vehicle can verify that it is located in the parking lot and has been identified by the infrastructure. This is advantageous for certain types of AVP processes, in which the AVP vehicle bears more responsibility, for example, the AVP vehicle must locate itself.

[0040] A parking lot can also be referred to as a parking area within the scope of the description and is used as a parking space for vehicles. A parking lot thus constitutes in particular a connected area having a plurality of parking spaces (in a private parking lot) or parking spaces (in a public parking lot). A parking lot can be comprised by a parking building according to one embodiment. A parking lot is in particular comprised by a garage.

[0041] In one embodiment of the method according to the first aspect, it is provided that when a plurality of motor vehicles are detected in the area on the infrastructure side based on the monitoring data, corresponding driving behaviors of the plurality of motor vehicles detected on the infrastructure side are determined on the infrastructure side based on the monitoring data, wherein the corresponding driving behaviors are respectively compared with the first driving behaviors on the infrastructure side, wherein the AVP motor vehicle is identified on the infrastructure side as one of the plurality of motor vehicles detected on the infrastructure side based on the corresponding comparison.

[0042] This achieves the technical advantage that, for example, an AVP motor vehicle can also be identified from among a plurality of motor vehicles.

[0043] In one embodiment of the method according to the first aspect, it is provided that a difference between a first driving behavior and a corresponding driving behavior of a motor vehicle detected on the infrastructure side is determined on the infrastructure side based on a comparison on the infrastructure side, wherein the AVP motor vehicle is identified on the infrastructure side as a motor vehicle detected on the infrastructure side based on the determined difference.

[0044] This achieves the technical advantage that, for example, AVP motor vehicles can be easily identified.

[0045] In one specific embodiment of the method according to the first aspect, it is provided that a time profile of the determined difference is determined on the infrastructure side, wherein the AVP motor vehicle is identified on the infrastructure side as a motor vehicle detected on the infrastructure side based on the determined time profile of the determined difference.

[0046] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0047] In one specific embodiment of the method according to the first aspect, it is provided that the AVP motor vehicle is identified on the infrastructure side as a motor vehicle detected on the infrastructure side if the time profile of the determined difference remains within a predetermined tolerance interval for a predetermined time.

[0048] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0049] In one specific embodiment of the method according to the first aspect, it is provided that the AVP motor vehicle is identified on the infrastructure side as a motor vehicle detected on the infrastructure side if the determined difference is less than or equal to a predetermined difference threshold value.

[0050] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0051] In one embodiment of the method according to the first aspect, it is provided that the driving behavior is described by at least one of the following driving behavior parameters: position, speed, acceleration, jerk, posture, orientation, curvature of the motor vehicle trajectory, the time variation curve of the position, the time variation curve of the speed, the time variation curve of the acceleration, the time variation curve of the jerk, the time variation curve of the posture, the time variation curve of the orientation, and the time variation curve of the motor vehicle trajectory.

[0052] This achieves, for example, the technical advantage that the driving behavior is described by suitable and reasonable driving behavior parameters.

[0053] In one specific embodiment of the method according to the first aspect, it is provided that respective differences between corresponding driving behavior parameters describing the respective driving behavior are determined as differences on the infrastructure side.

[0054] This achieves the technical advantage, for example, that particularly suitable and sensible differences can be determined.

[0055] In one embodiment of the method according to the first aspect, it is provided that when the AVP motor vehicle is identified on the infrastructure side as a motor vehicle detected on the infrastructure side, the confidence level of the identification is determined on the infrastructure side, wherein, based on the determined confidence level, another identification method is performed on the infrastructure side in order to identify the AVP motor vehicle again as a motor vehicle detected on the infrastructure side.

[0056] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0057] Another identification method includes, for example, one or more of the following steps: Identifying an AVP motor vehicle by light code recognition, wherein the direction indicator of the AVP motor vehicle is used as a light source. On the infrastructure side, the code is sent to the AVP motor vehicle via a wireless communication interface. The AVP motor vehicle flashes the direction indicator corresponding to the code. On the infrastructure side, infrastructure environmental sensors monitor the area, wherein monitoring data corresponding to the monitoring is processed on the infrastructure side to detect or identify the flashing code in the monitoring data. If the code is correctly identified or detected on the infrastructure side, the corresponding monitoring data, in particular the camera image, is associated with the AVP motor vehicle. The AVP motor vehicle is thereby identified, in particular located.

[0058] In one specific embodiment of the method according to the first aspect, it is provided that the driving behavior data are received by the AVP vehicle on the infrastructure side via a radio connection to the AVP vehicle and / or that the driving behavior data are received by a backend on the infrastructure side.

[0059] The technical advantage achieved thereby, for example when receiving via a radio link, is that the driving behavior data can be received quickly on the infrastructure side.

[0060] The advantage when receiving driving behavior data via the backend is in particular that before the AVP vehicle establishes a direct connection, ie a radio connection, with the infrastructure, it can first be determined on the infrastructure side that the AVP vehicle is in a parking lot.

[0061] The backend is, for example, the backend of the manufacturer of the motor vehicle. The driving behavior data are received by the AVP motor vehicle, for example, via one or more radio connections to the AVP motor vehicle. The radio connection is, for example, a WLAN connection or a mobile communication connection.

[0062] It can be provided that the motor vehicle transmits the driving behavior data directly to the infrastructure via one or more radio connections. Alternatively or additionally, it can be provided that the motor vehicle transmits the driving behavior data to a background, which transmits the driving behavior data to the infrastructure.

[0063] The sending and receiving are, for example, sending and receiving through one or more communication networks, such as a WLAN network or a mobile communication network, such as the Internet.

[0064] In one embodiment of the method according to the second aspect, it is provided that when a plurality of motor vehicles are detected in the area on the motor vehicle side based on the monitoring data, corresponding driving behaviors of the plurality of motor vehicles detected on the motor vehicle side are determined on the motor vehicle side based on the monitoring data, wherein the corresponding driving behaviors are respectively compared with the first driving behaviors on the motor vehicle side, wherein the AVP motor vehicle is identified on the motor vehicle side as one of the plurality of motor vehicles detected on the motor vehicle side based on the corresponding comparison.

[0065] This achieves the technical advantage that, for example, an AVP motor vehicle can also be identified from among a plurality of motor vehicles.

[0066] In one embodiment of the method according to the second aspect, it is provided that a difference between a first driving behavior and a corresponding driving behavior of a motor vehicle detected on the motor vehicle side is determined on the motor vehicle side based on a comparison on the motor vehicle side, wherein the AVP motor vehicle is identified on the motor vehicle side as a motor vehicle detected on the motor vehicle side based on the determined difference.

[0067] This achieves the technical advantage that, for example, AVP motor vehicles can be easily identified.

[0068] In one specific embodiment of the method according to the second aspect, it is provided that a time profile of the determined difference is determined on the motor vehicle side, wherein based on the determined time profile of the determined difference an AVP motor vehicle is identified on the motor vehicle side as a motor vehicle detected on the motor vehicle side.

[0069] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0070] In one specific embodiment of the method according to the second aspect, it is provided that the AVP motor vehicle is identified on the motor vehicle side as a motor vehicle detected on the motor vehicle side if the time profile of the determined difference remains within a predetermined tolerance interval for a predetermined time.

[0071] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0072] In one specific embodiment of the method according to the second aspect, it is provided that the AVP motor vehicle is identified on the motor vehicle side as a motor vehicle detected on the motor vehicle side if the determined difference is less than or equal to a predetermined difference threshold value.

[0073] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0074] In one embodiment of the method according to the second aspect, it is provided that the driving behavior is described by at least one of the following driving behavior parameters: position, speed, acceleration, jerk, posture, orientation, curvature of the motor vehicle trajectory, the time variation curve of the position, the time variation curve of the speed, the time variation curve of the acceleration, the time variation curve of the jerk, the time variation curve of the posture, the time variation curve of the orientation, and the time variation curve of the motor vehicle trajectory.

[0075] This achieves, for example, the technical advantage that the driving behavior is described by suitable and reasonable driving behavior parameters.

[0076] In one specific embodiment of the method according to the second aspect, it is provided that respective differences between corresponding driving behavior parameters describing the respective driving behavior are determined as differences on the motor vehicle side.

[0077] This achieves the technical advantage, for example, that particularly suitable and sensible differences can be determined.

[0078] In one embodiment of the method according to the second aspect, it is provided that when the AVP motor vehicle is identified on the motor vehicle side as a motor vehicle detected on the motor vehicle side, the confidence level of the identification is determined on the infrastructure side, wherein, based on the determined confidence level, another identification method is performed on the motor vehicle side in order to re-identify the AVP motor vehicle as a motor vehicle detected on the motor vehicle side.

[0079] This achieves the technical advantage that, for example, AVP motor vehicles can be reliably identified.

[0080] In one specific embodiment of the method according to the second aspect, it is provided that the driving behavior data are transmitted on the motor vehicle side via a radio connection, for example to a backend and / or, for example, to an infrastructure of a parking garage.

[0081] The technical advantage achieved thereby, for example when transmitting via a radio link, is that the driving behavior data can be received quickly by the infrastructure.

[0082] The advantage when sending the driving behavior data to the background is in particular that the background can send the driving behavior data to the infrastructure, so that the infrastructure can first determine on the infrastructure side that the AVP motor vehicle is in the parking lot before the AVP motor vehicle establishes a direct connection, i.e. a radio connection, on the motor vehicle side with the infrastructure.

[0083] The embodiments implemented in conjunction with the method according to the first aspect apply analogously to the method according to the second aspect and vice versa. This means that the method features of the method according to the second aspect are derived from the corresponding method features of the method according to the first aspect with the following changes, namely that the corresponding method features are performed on the motor vehicle side.

[0084] The method according to the first aspect and / or the method according to the second aspect is, for example, a computer-implemented method.

[0085] Within the scope of the description, the method can be carried out, for example, by means of a corresponding device and / or by means of a corresponding system.

[0086] The abbreviation "AVP" stands for "Automated Valet Parking" and can be translated into German as "automatischer Parkservice (automatic valet parking)". The AVP process includes, for example, at least highly automated guidance of an AVP motor vehicle from a drop-off area (also called a handover position or drop-off area) to a parking position and, for example, at least highly automated guidance of the motor vehicle from a parking position to a pick-up position (also called a drop-off area). At the handover position, i.e. the drop-off area, the driver of the motor vehicle hands over the motor vehicle for the AVP process. At the pick-up position, i.e. the pick-up area, the motor vehicle is removed after the AVP process has ended. The AVP process therefore begins, in particular, at the drop-off area. The AVP process therefore ends, in particular, at the pick-up area. The pick-up area can be the same as or different from the drop-off area.

[0087] That is, an AVP vehicle is a vehicle that can participate in the AVP process.

[0088] The motor vehicle is an at least highly automated motor vehicle. Such a motor vehicle is designed for at least highly automated driving. Highly automated driving corresponds to automation level 3 according to the Federal Roads Authority (BASt).

[0089] The motor vehicle is provided at least for highly automated guidance, which includes the case where the motor vehicle is provided for highly automated guidance and fully automated guidance, as well as for autonomous guidance. Fully automated guidance corresponds to automation level 4 according to the definition of BASt.

[0090] Highly automated guidance means that the longitudinal and lateral guidance of the motor vehicle is automatically controlled for a certain period of time in certain situations (e.g. driving on motorways, driving in parking lots, overtaking objects, driving in lanes defined by lane markings). The driver of the motor vehicle does not have to manually control the longitudinal and lateral guidance of the motor vehicle himself. The driver does not have to constantly monitor the automatic control of the longitudinal and lateral guidance in order to be able to intervene manually if necessary. If necessary, a request to assume control of the longitudinal and lateral guidance is automatically made to the driver, in particular with sufficient time left. This means that the driver must be able to assume control of the longitudinal and lateral guidance. The limits of the automatic control of the lateral and longitudinal guidance are automatically identified. With highly automated guidance, it is not possible to automatically reach a risk-minimized state in every initial situation.

[0091] Fully automatic guidance means that the longitudinal and lateral guidance of the vehicle is automatically controlled in certain situations (e.g. driving on motorways, driving in parking lots, overtaking an object, driving in a lane defined by lane markings). The driver of the motor vehicle does not have to manually control the longitudinal and lateral guidance of the motor vehicle. The driver does not have to monitor the automatic control of the longitudinal and lateral guidance in order to intervene manually if necessary. Before the automatic control of the lateral and longitudinal guidance is terminated, a request to take over (control of the lateral and longitudinal guidance of the motor vehicle) is automatically made to the driver, in particular with sufficient time, in particular with sufficient time reserve. If the driver does not take over the driving task, he is automatically returned to the lowest risk state. The limits of the automatic control of the lateral and longitudinal guidance are automatically detected. An automatic return to the lowest risk system state is possible in all situations.

[0092] Autonomous guidance or driving means that the longitudinal and lateral guidance of the motor vehicle is automatically controlled in all situations, not just in one or more specific situations. A driver is no longer required as a backup. The motor vehicle can thus be driven without a driver. Autonomous guidance corresponds to automation level 5 according to SAE (J3016), where SAE stands for "Society of Automotive Engineers".

[0093] The infrastructure environment sensor arrangement comprises, for example, one or more environment sensors, which are, for example, spatially distributed within the infrastructure, i.e., arranged within the parking lot. The infrastructure environment sensor arrangement monitors one or more areas of the parking lot. If the area is used in the singular, it should always be interpreted as the plural, and vice versa. This means, in particular, that embodiments relating to one area also apply to a plurality of areas, and vice versa. The environment sensors of the infrastructure environment sensors monitor areas of the parking lot, i.e., detect these areas. The infrastructure environment sensor arrangement or the environment sensors, for example, output monitoring data based on the monitoring or detection. The monitoring data represent or describe the monitored area.

[0094] Within the scope of this description, an environmental sensor is, for example, one of the following environmental sensors: a radar sensor, an image sensor, in particular an image sensor of a camera, for example an image sensor of a stereo camera, an ultrasonic sensor, a lidar sensor, a magnetic field sensor and an infrared sensor.

[0095] The abbreviation "at least one" means "one or more".

[0096] In one embodiment of the method according to the first aspect, it is provided that, when an AVP motor vehicle is positively identified on the infrastructure side as a motor vehicle detected on the infrastructure side, this result is transmitted on the infrastructure side to the AVP motor vehicle via a radio connection in order to verify the identification on the infrastructure side by the AVP motor vehicle.

[0097] In one embodiment of the method according to the second aspect, it is provided that, when the AVP vehicle is positively identified as a vehicle detected on the vehicle side, this result is transmitted on the vehicle side to the infrastructure by means of a radio connection in order to verify the identification on the vehicle side by the infrastructure machine.

[0098] The result of the corresponding verification is sent back to the sender, for example.

[0099] For example, the AVP process is not started until positive identification or positive verification of the identification on the vehicle side or on the infrastructure side.

[0100] The area of ​​the parking lot may include, for example, one or more drop-off areas.

[0101] The embodiments and exemplary embodiments described here can be combined with one another in any desired manner, even if this is not explicitly stated.

[0102] The device according to the third aspect and / or the system for identifying an AVP motor vehicle for an AVP procedure is, for example, programmed to execute a computer program according to the fifth aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] The present invention will be described in detail below with the aid of preferred embodiments.

[0104] Figure 1 A flow chart showing a method according to the first aspect,

[0105] Figure 2 A flow chart showing a method according to the second aspect,

[0106] Figure 3 A device according to a third aspect is shown,

[0107] Figure 4 A machine-readable storage medium according to the sixth aspect is shown,

[0108] Figure 5 A system for identifying an AVP vehicle for an AVP procedure is shown.

[0109] Figure 6 Shows the device,

[0110] Figure 7 Show parking lots, and

[0111] Figure 8 The time profile of the vehicle speed is shown.

[0112] The same reference numerals may be used below for the same features. DETAILED DESCRIPTION

[0113] Figure 1 A flow chart showing a method for identifying an AVP vehicle for an AVP process includes the following steps:

[0114] receiving 101 driving behavior data on the infrastructure side, which describes a first driving behavior of an AVP motor vehicle that is manually guided in an area of ​​a parking lot that is monitored by an infrastructure environment sensor system,

[0115] receiving 103 at the infrastructure side monitoring data based on monitoring of the area by infrastructure environmental sensor means,

[0116] the monitoring data are processed 105 on the infrastructure side in order to detect on the infrastructure side a motor vehicle which is in an area monitored by the infrastructure surroundings sensor system based on the monitoring data,

[0117] When a motor vehicle in the area is detected 107 on the infrastructure side based on the monitoring data, a second driving behavior of the motor vehicle detected on the infrastructure side is determined 109 on the infrastructure side based on the monitoring data,

[0118] Comparing the first driving behavior with the second driving behavior on the infrastructure side 111,

[0119] Based on the comparison, the AVP motor vehicle is identified 113 on the infrastructure side as a motor vehicle detected on the infrastructure side.

[0120] Figure 2 A flow chart showing a method for identifying an AVP vehicle for an AVP process includes the following steps:

[0121] At the motor vehicle side, driving behavior data are determined 201 , which describe a first driving behavior of an AVP motor vehicle that is manually guided in an area of ​​a parking lot that is monitored by the infrastructure environment sensor system,

[0122] receiving 203 on the motor vehicle side monitoring data based on monitoring of the area by infrastructure environment sensor means,

[0123] the monitoring data are processed 205 on the motor vehicle side in order to detect on the motor vehicle side a motor vehicle that is located in the area monitored by the infrastructure surroundings sensor system based on the monitoring data,

[0124] When a motor vehicle in the area is detected 207 on the motor vehicle side based on the monitoring data, a second driving behavior of the motor vehicle detected on the motor vehicle side is determined 209 on the motor vehicle side based on the monitoring data,

[0125] The first driving behavior is compared with the second driving behavior on the vehicle side 211,

[0126] Based on the comparison, an AVP vehicle is identified 213 on the vehicle side as a vehicle detected on the vehicle side.

[0127] Figure 3 A device 301 is shown which is configured to carry out all steps of the method according to the first aspect and / or according to the second aspect.

[0128] Figure 4 A machine-readable storage medium 401 is shown on which a computer program 403 is stored. The computer program 403 comprises instructions which, when executed by a computer, cause the computer to perform the method according to the first aspect and / or according to the second aspect.

[0129] Figure 5 A system 500 for identifying an AVP vehicle for an AVP procedure is shown.

[0130] The system 500 comprises an apparatus 501, which is arranged to perform all steps of the method according to the first aspect. The apparatus 501 comprises a communication device 503, which is arranged to perform a receiving step on the infrastructure side. Thus, the communication device 503 is arranged to receive driving behavior data on the infrastructure side and to receive monitoring data on the infrastructure side. The communication device 503 is, for example, arranged to send the result of identifying the vehicle on the infrastructure side as a vehicle detected on the infrastructure side to the AVP vehicle.

[0131] The device 501 comprises a process device 505, which may, for example, comprise one or more processors. The process device 505 is configured to process monitoring data on the infrastructure side so as to detect on the infrastructure side a motor vehicle in an area monitored by an infrastructure environment sensor mechanism based on the monitoring data. The process device 505 is configured to perform the step of determining on the infrastructure side a second driving behavior of a motor vehicle detected on the infrastructure side based on the monitoring data. Thus, the process device 505 is configured to determine on the infrastructure side a second driving behavior of a motor vehicle detected on the infrastructure side based on the monitoring data. The process device 505 is configured to compare on the infrastructure side a first driving behavior with a second driving behavior. The process device 505 is configured to identify on the infrastructure side an AVP motor vehicle as a motor vehicle detected on the infrastructure side based on the comparison.

[0132] The system 505 comprises an infrastructure environment sensor mechanism 507, which comprises one or more environment sensors. The infrastructure environment sensor mechanism 507 comprises, for example, a first environment sensor 509 and a second environment sensor 511. In an embodiment not shown, the infrastructure environment sensor mechanism 507 comprises more than two environment sensors 509, 511 or less than two environment sensors 509, 511. The infrastructure environment sensor mechanism 507 monitors the area of ​​the parking lot and outputs monitoring data corresponding to or based on the monitoring to the device 501. This means in particular that the infrastructure environment sensor mechanism 507 sends the monitoring data to the communication device 503 of the device 501. The communication device 503 receives the monitoring data of the infrastructure environment sensor mechanism 507.

[0133] The communication device 503 includes, for example, one or more communication interfaces, such as a WLAN communication interface, a mobile communication interface, or an Ethernet communication interface.

[0134] Figure 6 A device 601 is shown, which is configured to perform all steps of the method according to the second aspect. The device 601 comprises a determination device 603, which is configured to determine driving behavior data on the motor vehicle side. The determination device 603 comprises an odometer system 605, which is configured to determine mileage data of the motor vehicle. The odometer system 605 comprises, for example, one or more odometer sensors.

[0135] The device 601 includes a communication device 607, which is configured to receive monitoring data on the motor vehicle side. The device 601 includes a processing device 609, which can, for example, include one or more processors. The processing device 609 is configured to process the monitoring data on the motor vehicle side and determine the second driving behavior of the motor vehicle detected on the motor vehicle side based on the monitoring data when the motor vehicle side detects a motor vehicle in the area. The processing device 609 is configured to compare the first driving behavior with the second driving behavior on the motor vehicle side. The processing device 609 is configured to identify the AVP motor vehicle as a motor vehicle detected on the motor vehicle side based on the comparison.

[0136] The device 601 includes, for example, a vehicle (not shown). The vehicle is, for example, an AVP vehicle.

[0137] Figure 7 A parking lot 701 is shown, in which a first environmental sensor 703, a second environmental sensor 705, a third environmental sensor 707 and a fourth environmental sensor 709 are spatially distributed. The four environmental sensors 703 to 709 monitor an area 711 of the parking lot 701. The area 711 includes a first drop-off area 713, a second drop-off area 715 and a third drop-off area 717.

[0138] include Figure 6 The AVP vehicle 719 of the device 601 is manually guided by a driver (not shown) in the area 711. The driver of the AVP vehicle 719 wants to park his AVP vehicle in the third drop-off area 717 so that the AVP process for the AVP vehicle 719 can be started there.

[0139] A further motor vehicle 721 is located in area 711. The trajectory of AVP motor vehicle 719 is indicated by an arrow with reference numeral 723. The trajectory of further motor vehicle 721 is indicated by reference numeral 725.

[0140] For the sake of simplicity, the coordinate system 727 includes a horizontal axis 729 and a vertical axis 731. The horizontal axis 729 represents the x-axis, and the vertical axis 731 represents the y-axis. The orientation of the AVP vehicle 719 or the orientation of the vehicle 721 is determined by the angle This can be defined by the coordinate system 727 consisting of the coordinates x, y and The posture of the vehicle is determined.

[0141] The AVP vehicle 719 is identified on the infrastructure side according to the approach described here. In this case, the environmental sensors 703 to 709 detect two vehicles 719, 721, wherein the vehicle speed of the AVP vehicle 719 and the vehicle speed of the further vehicle 721 are determined on the infrastructure side based on the detection, i.e. based on the corresponding monitoring data. The AVP vehicle 719 determines its appropriate vehicle speed on the vehicle side and transmits it directly to the infrastructure and / or to a backend, wherein the backend then transmits the vehicle speed to the infrastructure.

[0142] The vehicle speed determined on the vehicle side and the vehicle speed determined on the infrastructure side are thus provided on the infrastructure side. The vehicle speed determined on the vehicle side of AVP vehicle 719 is compared with the vehicle speeds determined on the infrastructure side of AVP vehicle 719 and of further vehicles 721. Based on the comparison, AVP vehicle 719 can be identified, which is referred to below as Figure 8 Explain in detail.

[0143] Figure 8 A diagram 801 is shown, which comprises an abscissa 803 and an ordinate 805. The abscissa 803 has seconds as a unit, ie represents time. The ordinate 805 represents the speed of the motor vehicle, ie has the unit m / s.

[0144] Three speed change curves are shown in diagram 801: a first curve 807, which represents the speed change curve of the vehicle speed of the AVP vehicle 719 determined on the infrastructure side. Reference numeral 809 denotes a second curve, which represents the speed change curve of the vehicle speed of the AVP vehicle 719 determined on the vehicle side. Reference numeral 811 denotes a tolerance interval. Reference numeral 811 shows a predetermined tolerance interval 811, within which the first curve 807 lies. In order to achieve a positive matching consistency between the speed change curve determined on the infrastructure side and the speed change curve determined on the vehicle side, the speed change curve determined on the vehicle side must lie within the predetermined tolerance interval 811. This applies in particular to a predetermined time or a predetermined time interval 813.

[0145] Furthermore, a third curve is indicated with reference numeral 815 , which represents the time speed profile of the vehicle speed of further motor vehicle 815 , wherein the speed profile was determined on the motor vehicle side.

[0146] Since the speed of the other motor vehicle 721 is not within the tolerance window or tolerance interval 811, there is no match, so the other motor vehicle 721 is not identified as AVP motor vehicle 719. However, the speed profile 809 is within the predetermined tolerance interval 811 for the predetermined time 813, so there is a match here. Accordingly, the AVP motor vehicle 719 is identified as a motor vehicle detected based on the monitoring data.

[0147] The approach described here is based on a comparison of relative movement data (first driving behavior) of, for example, an AVP motor vehicle with second or further driving behaviors of one or more motor vehicles detected by the infrastructure surroundings sensor system, which are determined based on the monitoring data of the infrastructure surroundings sensor system. Figure 8 The concept of vehicle speed is shown. This principle can be applied to one or more other driving behavior parameters, such as the direction of the AVP vehicle, the (relative) position x, y, the curvature of the vehicle trajectory, the relevant time changes or a combination thereof, in addition to or instead of the vehicle speed.

[0148] For example, a pattern comparison is performed to identify an AVP vehicle whose vehicle speed is determined by the infrastructure and the vehicle, respectively. vI represents the vehicle speed determined on the infrastructure side. vK represents the vehicle speed determined by the vehicle. Both determined values ​​of vI and vK correspond approximately to the actual vehicle speed v. For example, the differences between v, vI and vK are due to the inherent limitations of the accuracy of the sensors used to determine the vehicle speed. For example, the similarity of vI and vK is evaluated within the time interval Δt according to a predefined metric. For example, the acceptance window 811 for positive match consistency defines the maximum allowable difference between the two vehicle speeds along time t within a specific time (time interval 813). Other indicators can be defined as the integral difference of |vI-vK| over the entire time interval Δt, which must not exceed a predefined difference threshold Tmax. The characteristics of the unique algorithm can be selected according to the accuracy requirements for the application, so that an unrelated third-party vehicle with a speed vT will not erroneously lead to a positive match consistency. In order to successfully perform a pattern comparison, the time base t between vI and vK does not have to be absolutely synchronized. The time bases of the AVP vehicle to be identified and the infrastructure are offset, resulting in an offset between the two curves vI and vK. Mathematical methods such as autocorrelation can then be used to detect the similarity between the two curves. This means that, for example, if the absolute time between the AVP vehicle and the infrastructure is not synchronized, the speed curve recorded by the AVP vehicle and the curve of the infrastructure will be offset from each other on the x-axis (time axis). Mathematical methods can still be used to determine the correspondence of the curves.

[0149] AVP vehicles are particularly capable of measuring their own relative motion at high frequencies, such as on the order of 100 Hz. Relative motion is characterized by attitude (x, y and direction) ) and changes in posture over time. Scan the vehicle speed, acceleration or deceleration, curvature of the driving trajectory and similar motion characteristics. The infrastructure environment sensor monitors the area where the AVP vehicle and potentially other vehicles are located or traveling. That is, the infrastructure environment sensor detects the motor vehicles located or traveling in the parking area and outputs monitoring data based on the detection or monitoring. Based on the monitoring data, the same features of the motor vehicles detected on the infrastructure side that are in the area are determined on the infrastructure side. These features, i.e., driving behavior parameters, are compared with the driving behavior parameters determined by the AVP vehicle itself. For example, the corresponding driving behavior parameters are compared according to predefined metrics. For example, the metrics are selected according to the accuracy of various measurement systems (motor vehicle sensors and infrastructure environment sensor mechanisms) and the requirements for positive matching consistency. Through this concept, positive comparisons can be made for AVP vehicles, and negative comparisons can be made for third-party vehicles.

Claims

1. A method for identifying an AVP vehicle (719) for an AVP procedure, comprising the following steps: receiving (101) driving behavior data on the infrastructure side, the driving behavior data describing a first driving behavior of an AVP motor vehicle (719) being manually guided in an area of ​​a parking lot (701) monitored by the infrastructure environment sensor arrangement (507), receiving (103) at the infrastructure side monitoring data based on monitoring of the area by the infrastructure environmental sensor mechanism (507), processing (105) the monitoring data on the infrastructure side in order to detect on the infrastructure side a motor vehicle that is in an area monitored by the infrastructure environment sensor arrangement (507), based on the monitoring data, When a motor vehicle in the area is detected (107) on the infrastructure side based on the monitoring data, a second driving behavior of the motor vehicle detected on the infrastructure side is determined (109) on the infrastructure side based on the monitoring data, comparing the first driving behavior with the second driving behavior on the infrastructure side (111), Based on the comparison, the AVP vehicle (719) is identified (113) on the infrastructure side as a vehicle detected on the infrastructure side.

2. The method according to claim 1, wherein: When a plurality of motor vehicles (721) located in the area are detected on the infrastructure side based on the monitoring data, corresponding driving behaviors of the plurality of motor vehicles (721) detected on the infrastructure side are determined on the infrastructure side based on the monitoring data, wherein the corresponding driving behaviors are respectively compared with the first driving behaviors on the infrastructure side, wherein the AVP motor vehicle (719) is identified on the infrastructure side as one of the plurality of motor vehicles (721) detected on the infrastructure side based on the corresponding comparison.

3. The method according to claim 1 or 2, wherein: Based on a comparison on the infrastructure side, a difference between the first driving behavior and a corresponding driving behavior of a motor vehicle detected on the infrastructure side is determined on the infrastructure side, wherein the AVP motor vehicle (719) is identified on the infrastructure side as a motor vehicle detected on the infrastructure side based on the determined difference.

4. The method according to claim 3, wherein: The time profile of the determined difference is determined on the infrastructure side, wherein the AVP motor vehicle (719) is identified on the infrastructure side as a motor vehicle detected on the infrastructure side based on the determined time profile of the determined difference.

5. The method according to claim 4, wherein: If the time profile of the determined difference remains within a predetermined tolerance interval (811) for a predetermined time (813), the AVP vehicle (719) is identified on the infrastructure side as a vehicle detected on the infrastructure side.

6. The method according to any one of claims 3 to 5, wherein: If the determined difference is less than or equal to a predetermined difference threshold, the AVP vehicle (719) is identified on the infrastructure side as a vehicle detected on the infrastructure side.

7. A method according to any one of the preceding claims, wherein: The driving behavior is described by at least one of the following driving behavior parameters: position, speed, acceleration, jerk, attitude, orientation, curvature of the vehicle trajectory, the time profile of the position, the time profile of the speed, the time profile of the acceleration, the time profile of the jerk, the time profile of the attitude, the time profile of the orientation, and the time profile of the vehicle trajectory.

8. The method according to any one of claims 7 and claims 3 to 6, wherein: A respective difference between corresponding driving behavior parameters describing the respective driving behavior is determined as a difference on the infrastructure side.

9. A method according to any one of the preceding claims, wherein: When the AVP motor vehicle (719) is identified on the infrastructure side as a motor vehicle detected on the infrastructure side, the confidence of the identification is determined on the infrastructure side, wherein, based on the determined confidence, another identification method is performed on the infrastructure side in order to re-identify the AVP motor vehicle (719) as a motor vehicle detected on the infrastructure side.

10. A method according to any one of the preceding claims, wherein: The driving behavior data are received by the AVP vehicle (719) on the infrastructure side via a radio connection to the AVP vehicle (719), and / or the driving behavior data are received by a backend on the infrastructure side.

11. A method for identifying an AVP vehicle (719) for an AVP procedure, comprising the steps of: Determining (201) driving behavior data on the vehicle side, the driving behavior data describing a first driving behavior of an AVP vehicle (719) being manually guided in an area of ​​a parking lot (701) monitored by the infrastructure environment sensor system (507), receiving (203) on the motor vehicle side monitoring data based on monitoring of the area by means of the infrastructure environment sensor means (507), processing (205) the monitoring data on the motor vehicle side in order to detect on the motor vehicle side a motor vehicle that is located in the area monitored by the infrastructure environment sensor arrangement (507) based on the monitoring data, When a motor vehicle in the area is detected (207) on the motor vehicle side based on the monitoring data, a second driving behavior of the motor vehicle detected on the motor vehicle side is determined (209) on the motor vehicle side based on the monitoring data, The first driving behavior is compared with the second driving behavior on the motor vehicle side (211), Based on the comparison, the AVP vehicle (719) is identified on the vehicle side as a vehicle detected on the vehicle side.

12. An apparatus (301) arranged to perform all the steps of the method according to any one of the preceding claims.

13. A motor vehicle (719) comprising a device (301) according to claim 12, said device being configured to carry out all the steps of the method according to claim 11.

14. A computer program (403) comprising instructions which, when the computer program (403) is executed by a computer, cause the computer to perform the method according to any one of claims 1 to 11.

15. A machine-readable storage medium (401) on which a computer program (403) according to claim 14 is stored.

16. A system (500) for identifying an AVP motor vehicle (719) for an AVP process, comprising a device (301) according to claim 12 and an infrastructure environment sensor mechanism (507), wherein the device is configured to perform all steps of the method according to any one of claims 1 to 10, and the infrastructure environment sensor mechanism is configured to monitor an area of ​​a parking lot (701) and output monitoring data based on the monitoring to the device (301).

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