DE102023112022A1 - DETERMINATION DEVICE AND METHOD FOR DETERMINING A TRAFFIC RISK CAUSED BY A MOVING TWO-WHEEL - Google Patents

Abstract

A determination device (1) is provided for determining a traffic risk caused by a moving two-wheeler. The determination device (1) is designed to receive sensor data from at least one intelligent item of clothing (2) that can be worn or is worn by a driver of the two-wheeler (S1) and to evaluate the received sensor data in order to determine a number of how many hands of the driver are on a handlebar of the two-wheeler (S2). The determination device (1) is designed to determine the traffic risk depending on the determined number (S3) and to provide the determined traffic risk for a motor vehicle (10) that is in the vicinity of the two-wheeler (S4).

Description

The present disclosure relates to a determination device for determining a traffic risk caused by a moving two-wheeler, a determination system comprising the determination device, and/or a method for determining a traffic risk caused by a moving two-wheeler. Additionally or alternatively, a computer program is provided which comprises instructions which, when the program is executed by a computer, cause the computer to at least partially carry out the method. Additionally or alternatively, a computer-readable medium is provided which comprises instructions which, when the instructions are executed by a computer, cause the computer to at least partially carry out the method.

Numerous communication systems are known that enable data to be exchanged between or with one another to regulate traffic flow for motor vehicles via Car2X communications, e.g. V2V or V2I communications. In addition, there are a large number of different technologies for identifying the respective environment of the motor vehicles, which are implemented, for example, using vehicle sensors.

However, there is a lack of sufficient preventive techniques that can detect traffic risks posed by weaker road users at an early stage and take them into account when regulating traffic flow.

A weaker road user can be, for example, a cyclist, whereby the traffic risk posed by the cyclist increases if he or she rides his or her bicycle with only one hand or even without hands on the handlebars.

Against the background of this prior art, the object of the present disclosure is to provide a device and/or a method which are each suitable for enriching the prior art.

The problem is solved by the features of the independent claims. The subordinate claims and the dependent claims each contain optional further developments of the disclosure.

The task is then solved by a detection device for determining a traffic risk posed by a moving two-wheeler, e.g. a bicycle.

The detection device is designed to receive sensor data from at least one intelligent garment that is wearable or worn by a driver of the two-wheeler (or a two-wheeler rider).

The detection device is designed to evaluate the received sensor data in order to determine how many of the driver's hands are on a handlebar of the two-wheeler.

The detection device is designed to determine the traffic risk depending on the number detected.

The detection device is designed to provide the determined traffic risk for (at least) one, e.g. autonomous, motor vehicle that is in the vicinity of the two-wheeler.

The detection device can be designed for electronic data processing and/or can be implemented as an electronic data processing device, which can, for example, have one or more microprocessors and data memories. Software for data processing can be operated on the detection device. The data processing can include evaluating the sensor data and determining the traffic risk.

The detection device can be or is connected to the at least one intelligent item of clothing by means of signal technology, e.g. wirelessly via a mobile network and/or e.g. via Bluetooth, WLAN and/or UMTS.

The detection device can be connected (directly or indirectly) to the (at least one) motor vehicle, optionally wirelessly, using signal technology. The detection device can be designed to communicate with the motor vehicle directly or indirectly via Car2X communication (also: vehicle-to-everything, V2X).

It is also conceivable that the determined traffic risk can be made available on an external server or backend, on which the determined traffic risk for the motor vehicle can be retrieved, for example. The determination device can be connected or linked to the external server or backend using signal technology, optionally wirelessly.

The at least one intelligent item of clothing can have at least one sensor for detecting, for example, movements and/or postures (and/or health data) of the driver (or a wearer of the at least one item of clothing). The at least one intelligent item of clothing can also be referred to, for example, as a smart wearable, smart gadget, smart device and/or wearable. Computing. Such intelligent clothing items, such as smartwatches and/or smart jackets, are well known and widely used, with more and more types of clothing being available as intelligent clothing items. Therefore, their functionality is not explained further here.

The two-wheeler can be a (non-motorized or motorized) means of transport that can, for example, tip over while driving. The two-wheeler can have at least two wheels, e.g. two or three wheels. The two-wheeler can, for example, be a bicycle or a trike.

The detection device described above offers a number of advantages. Among other things, a detection device is provided for a system for assessing the risks of cyclists in, for example, autonomous road traffic.

The use of sensor data from at least one intelligent item of clothing advantageously makes it possible to determine the number of hands on the handlebars without the respective handlebars having to be within sight or field of vision of the motor vehicle. In contrast, an implementation using camera recording by at least one vehicle camera on the motor vehicle would only be able to determine the number of hands when the two-wheeler is coming towards the motor vehicle. This is the only way to visually identify the hand position and thus the number of hands on the handlebars. However, if the two-wheeler is driving in the same direction as the motor vehicle, for example, the hands and handlebars are covered by the driver and therefore cannot be identified by the camera recording.

Possible further developments of the device described above are explained in detail below.

The determination device can be designed to evaluate the received sensor data in order to determine (in addition to the number) a period of time for how long the determined number of the driver's hands are on the handlebars of the two-wheeler. The determined period of time can include a time stamp, for example.

The detection device can be designed to determine the traffic risk depending on the detected number and the detected time period.

The received sensor data may include a first data set relating to a left upper body half, a left hand and/or a left arm of the driver. The first data set may describe a movement (e.g. a movement frequency and/or a movement amplitude) and/or a posture or an orientation direction of the left upper body half, the left hand and/or the left arm of the driver. The first data set may include at least a first sensor value.

The received sensor data may include a second data set relating to a right upper body half, a right hand and/or a right arm of the driver. The second data set may describe a movement (e.g. a movement frequency and/or a movement amplitude) and/or a posture or an orientation direction of the right upper body half, the right hand and/or the right arm of the driver. The second data set may include at least one second sensor value.

The determination device may be equipped to determine the number in order to compare the first data set and the second data set with each other or with a reference data set.

The determining device may be configured to determine that both of the driver's hands are on the handlebar when the first data set and the second data set deviate from each other within a predetermined reference deviation.

The determination device may be configured to determine that both of the driver's hands are on the handlebars if the first data set and the second data set each deviate from the reference data set within the predetermined reference deviation.

The detection device can be designed to determine that only one of the driver's hands is on the handlebar if the first data set and the second data set differ from each other by more than the predetermined reference deviation.

The determination device can be designed to determine that only one of the driver's hands is on the handlebar if only one of the first data set and the second data set deviates from the reference data set by more than the predetermined reference deviation.

The determination device can be designed to determine that none of the driver's hands are on the handlebars if the first data set and the second data set each deviate from the reference data set by more than the predetermined reference deviation.

It is conceivable that the reference data set and/or the reference deviation depends on at least one occurrence of a route that the two-wheeler is (currently) traveling. The determination device can be designed to select and/or change the reference data set and/or the reference deviation depending on the at least one occurrence.

The determination device can, for example, be designed to receive a (e.g. global) position of the two-wheeler and to determine the at least one event based on the received position and (stored and/or received) map data that include route events. The at least one event (and/or the route events) can include a geometry, a profile and/or a type of surface covering of the route. Furthermore, the determination device can, for example, be designed to select the reference data set and/or the reference deviation from a plurality of reference data sets and/or reference deviations depending on the at least one event.

The first data set and the second data set can each describe at least a movement frequency, a movement deflection and/or an orientation direction of the respective (left or right) arm of the driver.

The detection device can be designed to determine that at least one of the driver's hands is not on the handlebars if a pendulum movement of the respective arm has been determined based on at least one periodic movement frequency, periodic movement deflections and/or a periodic change in the direction of alignment.

The determination device can be designed to determine that one of the driver's hands is not on the handlebars if an asynchronicity and/or a frequency deviation between the at least one movement frequency of the first data set and the at least one movement frequency of the second data set, e.g. outside a predetermined reference frequency deviation, has been determined.

The determination device can be designed to determine that the left hand is not on the handlebar if the at least one movement frequency of the first data set is lower than the at least one movement frequency of the second data set. The determination device can be designed to determine that the right hand is not on the handlebar if the at least one movement frequency of the second data set is lower than the at least one movement frequency of the first data set.

It is also conceivable that the determination device can be designed to compare the at least one movement frequency of the first data set and the at least one movement frequency of the second data set with a distance frequency of the route that the two-wheeler is (currently) traveling. The determination device can be designed to determine the distance frequency based on the at least one occurrence of the route. The determination device can be designed to determine that at least one of the driver's hands is not on the handlebars if the at least one movement frequency of the first data set and/or the second data set deviates from the distance frequency, e.g. outside of a predetermined reference distance frequency deviation.

The detection device can be designed to determine that at least one of the driver's hands is not on the handlebars if it has been determined based on at least one direction of orientation outside a predetermined direction range that the respective arm is making a pointing movement, holding an object and/or hanging down from the driver's body.

Providing the determined traffic risk may include warning the motor vehicle depending on the determined traffic risk.

The detection device can be designed to propose at least one preventive measure depending on the determined traffic risk for the motor vehicle.

The detection device can be designed to control the motor vehicle to initiate at least one preventive measure.

The at least one preventive measure may include changing lanes, reducing speed and/or pre-applying the brakes of the motor vehicle.

It is conceivable that at least one preventive measure should only be proposed and/or initiated when there is an increased traffic risk, for example when it has been established that only one or neither of the driver's hands are on the handlebars.

The detection device can be implemented as part of a mobile communication device (e.g. a smartphone), a Car2X data processing device (or an external server and/or a backend) and/or the motor vehicle.

The determination device can be designed to determine a lower traffic risk with a higher number of hands on the handlebars. In other words, the determination device can be designed to determine a low (or low-risk) traffic risk when both of the driver's hands are on the handlebars, to determine an increased traffic risk when only one of the driver's hands is on the handlebars, and/or to determine a high traffic risk when neither of the driver's hands is on the handlebars.

The traffic risk determined, e.g. when only one or none of the driver's hands are on the handlebars, may also vary depending on the determined time period. The determination device may, for example, be designed to determine a lower (or reduced) traffic risk the shorter the determined time period is when only one or none of the driver's hands are on the handlebars.

The above can be summarized in other words and in a possible more concrete embodiment of the disclosure as described below, whereby the following description is not to be interpreted as limiting the disclosure.

The present disclosure describes the detection device or a detection system that detects information from weaker road users, e.g. cyclists, and examines this information for a risk (low risk: both hands are on the handlebars, high risk: at least one hand is not on the handlebars). The parameters for evaluating the risk can be recorded for each individual cyclist via the smart wearables and this data can be sent to an external server, e.g. via a mobile phone (or the mobile communication device). The server and/or the mobile phone can evaluate the risk and send the signals on to the surrounding autonomous traffic in a network.

For example, signals can be recorded via smart wearables or gadgets and evaluated via the mobile phone and/or the external server. The cyclist is at low risk or poses a low traffic risk if both of the cyclist's hands are on the handlebars. This can be the case, for example, if high frequencies, which can be detected using gyro sensors, are induced by the vibrations of the ground via the bicycle and the handlebars on both hands (and the fingers of the hands) and the forearms. Furthermore, small movement deflections can be measured on both hands when the cyclist is riding on a flat stretch of road.

The cyclist poses a high traffic risk if, for example, at least one hand is not on the handlebars. This can be the case, for example, if lower frequencies are measured on at least one hand than on the other hand, or if higher movement amplitudes are measured on one hand/forearm than on the other hand/forearm.

A motor vehicle approaching the cyclist, e.g. an autonomous one, can be warned about the traffic risk, e.g. an increased risk, and preventive measures (e.g. changing lanes, reducing speed, applying the brakes) can be initiated.

Furthermore, a detection system for determining a traffic risk posed by a moving two-wheeler is provided.

The detection system comprises the detection device described above and the at least one intelligent garment that is wearable or worn by a driver of the two-wheeler.

The at least one intelligent garment can have at least a first gyro, acceleration and/or position sensor which is arranged on a left upper body half, a left hand and/or a left arm of the driver in a worn state for detecting a first data set.

The at least one intelligent garment may comprise at least one second gyro, acceleration and/or position sensor arranged on a right upper body half, a right hand and/or a right arm of the driver in a worn state for detecting a second data set.

The at least one intelligent garment may comprise a combination of several intelligent garments, which, for example, in the combination have at least one first gyro, acceleration and/or position sensor and at least one second gyro, acceleration and/or position sensor.

The at least one intelligent item of clothing can be, for example, a smart hat (cap, headware), smart shoes, a smart scarf, a smart jacket, a smart vest, a smart hair band or head band, a smart watch, smart armbands, smart bracelets, smart socks, a smart belt, an intelligent smart ring, smart gloves, a pedometer (e.g. designed as a bracelet or as shoes or shoe soles) and/or wireless headphones (wireless headset).

It is also conceivable to provide intelligent handles on the handlebars of the bicycle in addition to, or as an alternative to, the at least one intelligent item of clothing. The intelligent handles can be designed to record the same data sets as the at least one intelligent item of clothing. For example, a left handle of the intelligent handles can have the at least one first gyro, acceleration and/or position sensor and a right handle of the intelligent handles can have the second gyro, acceleration and/or position sensor.

The detection system may further comprise the (at least one), e.g. autonomous, motor vehicle.

What is described above with reference to the detection device also applies analogously to the detection system and vice versa.

Furthermore, a motor vehicle is provided which can comprise the detection device described above.

The motor vehicle may be a passenger car, in particular an automobile, or a commercial vehicle, such as a truck.

The motor vehicle can be automated and/or autonomous. The motor vehicle can be designed to at least partially and/or at least temporarily assume longitudinal guidance and/or lateral guidance by means of the determination device during automated driving of the motor vehicle.

Automated driving can be carried out in such a way that the movement of the motor vehicle is (largely) autonomous. Automated driving can be controlled at least partially and/or temporarily by the detection device.

It is conceivable that the motor vehicle intervenes in the lateral guidance of the motor vehicle actively, e.g. by adjusting an actual steering wheel position, and optionally passively, e.g. by displaying a turning instruction, through a driver assistance system.

The motor vehicle can be a motor vehicle with autonomy level 0, i.e. the driver takes over the dynamic driving task, even if supporting systems (e.g. ABS or ESP) are present.

The motor vehicle may be a motor vehicle of autonomy level 1, i.e. have certain driver assistance systems that support the driver in operating the vehicle, such as adaptive cruise control (ACC).

The motor vehicle may be a motor vehicle of autonomy level 2, i.e. it may be so partially automated that functions such as automatic parking, lane keeping or lateral guidance, general longitudinal guidance, acceleration and/or braking are taken over by driver assistance systems.

The motor vehicle can be a level 3 autonomy motor vehicle, i.e. so automated that the driver does not have to continuously monitor the vehicle system. The motor vehicle independently carries out functions such as activating the indicator, changing lanes and/or keeping in lane. The driver can attend to other activities, but will be prompted by the system to take over control within a pre-warning period if necessary.

The motor vehicle can be a motor vehicle with autonomy level 4, i.e. it can be so highly automated that the vehicle's system permanently takes over control of the vehicle. If the system can no longer handle the driving tasks, the driver can be asked to take over control.

The motor vehicle can be a level 5 autonomy motor vehicle, i.e. so fully automated that the driver is not required to perform the driving task. No human intervention is required other than setting the destination and starting the system. The motor vehicle can operate without a steering wheel and pedals.

What is described above with reference to the detection device and the detection system also applies analogously to the motor vehicle and vice versa.

Furthermore, a method for determining a traffic risk caused by a moving two-wheeler, e.g. a bicycle, is solved.

The method includes receiving sensor data from at least one smart garment that is wearable or worn by a rider of the two-wheeler.

The method includes evaluating the received sensor data to determine a number determine how many of the rider's hands are on the handlebars of the two-wheeler.

The procedure involves determining the traffic risk depending on the number detected.

The method includes providing the determined traffic risk for (at least) one motor vehicle located in the vicinity of the two-wheeler.

The control method may be a computer-implemented method, i.e. one, several or all steps of the method can be carried out at least partially by a computer or a data processing device, optionally the determination device.

What is described above with reference to the detection device, the detection system and the motor vehicle also applies analogously to the method and vice versa.

Furthermore, a computer program is provided, comprising instructions which, when the program is executed by a computer, cause the computer to at least partially carry out or implement the method described above.

A program code of the computer program can be in any code, in particular in a code that is suitable for controlling motor vehicles.

What is described above with reference to the investigation device, the investigation system, the motor vehicle and the method also applies analogously to the computer program and vice versa.

Furthermore, a computer-readable medium, in particular a computer-readable storage medium, is provided. The computer-readable medium comprises instructions which, when executed by a computer, cause the computer to at least partially carry out or implement the method described above.

That is, a computer-readable medium may be provided that comprises a computer program as defined above. The computer-readable medium may be any digital data storage device, such as a USB stick, a hard disk, a CD-ROM, an SD card or an SSD card (or SSD drive/SSD hard disk).

The computer program does not necessarily have to be stored on such a computer-readable storage medium in order to be made available to the motor vehicle, but can also be obtained via the Internet or otherwise externally.

What is described above with reference to the method, the investigative device, the investigative system, the computer program and the motor vehicle also applies analogously to the computer-readable medium and vice versa.

• 1 zeigt schematisch ein offenbarungsgemäßes Ermittlungssystem mit einer Ermittlungsvorrichtung zum Ermitteln eines Verkehrsrisikos durch ein fahrendes Zweirad, und
• 2 zeigt schematisch ein Ablaufdiagramm eines offenbarungsgemäßen Verfahrens zum Ermitteln eines Verkehrsrisikos durch ein fahrendes Zweirad.

Below, an optional embodiment is described with reference to 1 and 2 described.

• 1 shows schematically a detection system according to the disclosure with a detection device for determining a traffic risk caused by a moving two-wheeler, and
• 2 shows a schematic flow diagram of a method according to the disclosure for determining a traffic risk caused by a moving two-wheeler.

The 1 The detection system 5, which is only shown schematically, comprises the detection device 1 and the at least one intelligent item of clothing 2 that can be worn or is worn by a driver of the two-wheeler. The detection device 1 and the at least one intelligent item of clothing 2 are connected to one another by signaling, e.g. wirelessly via a mobile network and/or e.g. via Bluetooth, WLAN and/or UMTS.

The determination device 1 can be designed as part of a mobile communication device and/or a Car2X data processing device. It is also conceivable that the determination device can be designed as part of the motor vehicle 10.

The at least one intelligent item of clothing 2 comprises sensors for recording sensor data relating to the driver of the two-wheeler. For example, the at least one intelligent item of clothing 2 can have at least one first gyro, acceleration and/or position sensor, which is arranged on a left upper body half, a left hand and/or a left arm of the driver in a worn state to record a first data set. Furthermore, the at least one intelligent item of clothing 2 can have at least one second gyro, acceleration and/or position sensor, which is arranged on a right upper body half, a right hand and/or a right arm of the driver in a worn state to record a second data set.

In order to be able to determine a traffic risk caused by a moving two-wheeler, the detection device 1 is designed to detect the following with reference to 2 to carry out the method 100 described in detail.

In a first method step S1, sensor data are received from the at least one intelligent item of clothing 2 that is wearable or worn by a driver of the two-wheeler.

The received sensor data may include a first data set relating to a left upper body, a left hand and/or a left arm of the driver. The received sensor data may further include a second data set relating to a right upper body, a right hand and/or a right arm of the driver.

In a second method step S2, the received sensor data are evaluated to determine how many of the driver's hands are on the handlebars of the two-wheeler.

For this purpose, the first data set and the second data set can be compared with each other or with a reference data set.

For example, it can be determined that both of the driver's hands are on the handlebars if the first data set and the second data set deviate from each other within the specified reference deviation, and/or the first data set and the second data set each deviate from the reference data set within the specified reference deviation.

It can be determined that only one of the driver's hands is on the handlebars if, for example, the first data set and the second data set deviate from each other by more than the specified reference deviation, and/or only one of the first data set and the second data set deviates from the reference data set by more than the specified reference deviation.

It can be determined that none of the driver's hands are on the handlebars if the first data set and the second data set each deviate from the reference data set by more than the specified reference deviation.

The first data set and the second data set can, for example, each describe at least one movement frequency, one movement deflection and/or one direction of alignment of the respective arm of the driver. Based on these values, it can be determined, for example, that at least one of the driver's hands is not on the handlebars if a pendulum movement of the respective arm has been determined based on at least one periodic movement frequency, periodic movement deflections and/or a periodic change in the direction of alignment. It is also conceivable that at least one of the driver's hands is not on the handlebars if it has been determined based on at least one direction of alignment outside a predetermined directional range that the respective arm is making a pointing movement, holding an object and/or hanging down from the driver's body.

In a third method step S3, the traffic risk is determined depending on the number determined, whereby, for example, a low traffic risk may exist if both of the driver's hands are on the handlebars, and an increased or high traffic risk may exist if only one or neither of the hands are on the handlebars.

In a fourth method step S4, the determined traffic risk for the motor vehicle 10 located in the vicinity of the two-wheeler is provided.

In addition to providing the determined traffic risk, it is conceivable to propose at least one preventive measure depending on the determined traffic risk for the motor vehicle 10 and/or to actively control the motor vehicle 10 to initiate at least one preventive measure.

list of reference symbols

1

investigative device

2

intelligent piece of clothing

5

investigation system

10

motor vehicle

100

Proceedings

S1-S4

procedural steps

Claims (10)

Determination device (1) for determining a traffic risk caused by a moving two-wheeler, characterized in that the determination device (1) is designed to: - receive sensor data from at least one intelligent item of clothing (2) that can be worn or is worn by a driver of the two-wheeler (S1); - evaluate the received sensor data in order to determine a number of how many hands of the driver are on a handlebar of the two-wheeler (S2); - determine the traffic risk depending on the determined number (S3); and - to provide the determined traffic risk for a motor vehicle (10) located in the vicinity of the two-wheeler (S4). Detecting device (1) according to claim 1 , characterized in that - the received sensor data comprise: - a first data set relating to a left upper body half, a left hand and/or a left arm of the driver; and - a second data set relating to a right upper body half, a right hand and/or a right arm of the driver; and - the determination device (1) is equipped for determining the number in order to: - compare the first data set and the second data set with one another or with a reference data set in each case. Detecting device (1) according to claim 2 , characterized in that the determination device (1) is designed to determine that: - both of the driver's hands are on the handlebars if: - the first data set and the second data set deviate from one another within a predetermined reference deviation, and/or - the first data set and the second data set each deviate from the reference data set within the predetermined reference deviation; and/or - only one of the driver's hands is on the handlebars if: - the first data set and the second data set deviate from one another by more than the predetermined reference deviation, and/or - only one of the first data set and the second data set deviates from the reference data set by more than the predetermined reference deviation; and/or - neither of the driver's hands are on the handlebars if: - the first data set and the second data set each deviate from the reference data set by more than the predetermined reference deviation. Detecting device (1) according to claim 2 or 3 , characterized in that - the first data set and the second data set each describe at least one movement frequency, one movement deflection and/or one direction of alignment of the respective arm of the driver; and - the determination device (1) is designed to determine that at least one of the driver's hands is not on the handlebars if: - a pendulum movement of the respective arm has been determined based on at least one periodic movement frequency, periodic movement deflections and/or a periodic change in the direction of alignment; and/or based on at least one direction of alignment outside a predetermined directional range, it has been determined that the respective arm is making a pointing movement, holding an object and/or hanging down from the driver's body. Determination device (1) according to one of the preceding claims, characterized in that the determination device (1) is designed to: - propose at least one preventive measure depending on the determined traffic risk for the motor vehicle (10); and/or - control the motor vehicle (10) to initiate the at least one preventive measure. Determination device (1) according to one of the preceding claims, characterized in that the determination device (1) is designed as part of a mobile communication device, a Car2X data processing device and/or the motor vehicle (10). Determination system (5) for determining a traffic risk caused by a moving two-wheeler, characterized in that the determination system (5) comprises: - the determination device (1) according to one of the preceding claims; and - the at least one intelligent item of clothing (2) which is wearable or worn by a driver of the two-wheeler. Investigation system (5) according to claim 7 , characterized in that the at least one intelligent item of clothing (2) has: - at least one first gyro, acceleration and/or position sensor, which is arranged on a left upper body half, a left hand and/or a left arm of the driver for detecting a first data set in a worn state; and - at least one second gyro, acceleration and/or position sensor, which is arranged on a right upper body half, a right hand and/or a right arm of the driver for detecting a second data set in a worn state. Method (100) for determining a traffic risk caused by a moving two-wheeler, characterized in that the method (100) comprises: - receiving (S1) sensor data from at least one intelligent garment (2) that is wearable or worn by a driver of the two-wheeler; - evaluating (S2) the received sensor data in order to determine a number of how many hands of the driver are located on a handlebar of the two-wheeler; - determining (S3) the traffic risk depending on the determined number; and - providing (S4) the determined traffic risk for a motor vehicle (10) that is in the vicinity of the two-wheeler. Computer program and/or computer-readable medium, characterized in that the computer program and/or computer-readable medium comprises instructions which, when executed by a computer, cause the computer to carry out the method (100) according to claim 9 to execute.

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