Method for determining an expected driving trajectory of a motor vehicle
Patent Information
- Authority / Receiving Office
- EP · EP
- Patent Type
- Applications
- Current Assignee / Owner
- VOLKSWAGEN AG
- Filing Date
- 2024-08-06
- Publication Date
- 2026-07-01
Smart Images
Figure EP2024072244_27022025_PF_FP_ABST
Abstract
Description
[0001] Description
[0002] Method for determining an expected driving trajectory of a motor vehicle
[0003] The invention relates to a method for determining an expected travel trajectory of a motor vehicle. Furthermore, the invention relates to a motor vehicle, a control device for a motor vehicle, and a computer program product for implementing such a method.
[0004] A motor vehicle may have a driver assistance system that, for example, proactively adapts the speed of the motor vehicle to the course of a route. It may, for example, specify a reduction in the speed of the motor vehicle near an intersection and / or before negotiating a curve, particularly when turning. This reduction may, for example, occur automatically, so that the motor vehicle can be braked automatically without the driver having to intervene manually. In order to automatically adapt the speed of the motor vehicle at an intersection or when turning, the driver assistance system must be informed that the driver intends to turn.
[0005] DE 10 2021 207 181 B3 describes a method for the automatic detection of a right-before-left situation in road traffic by a motor vehicle. The motor vehicle has a camera and can access a digital map and swarm data from other vehicles. It determines whether an intersection or junction is ahead and checks for the presence of right-of-way traffic signs in the digital map, captured by the camera and in the swarm data. A right-before-left situation is concluded if no right-of-way traffic sign is found in any of the three checks.
[0006] US 2016 / 0229404 A1 discloses a method for controlling a vehicle based on crowdsourced data. The vehicle transmits a route request to a server and receives navigation information in response.
[0007] US 2020 / 0125102 A1 discloses a method for autonomous driving that uses standard navigation maps and lane configurations determined based on previously determined vehicle trajectories. The object of the invention is to provide a solution by means of which a driving trajectory that a motor vehicle is likely to follow can be reliably determined.
[0008] The problem is solved by the subject matter of the independent patent claims.
[0009] A first aspect of the invention relates to a method for determining an expected travel trajectory of a motor vehicle. The expected travel trajectory can alternatively be referred to as the most probable path the motor vehicle will follow. The expected travel trajectory includes, for example, several points along which the motor vehicle is expected to travel in the future.
[0010] The method comprises providing a map in which at least one road is drawn without differentiation of individual lanes of the road. Such a map can, for example, be in the form of a digital map, which is generated, for example, by a vehicle manufacturer and provided to the motor vehicle. Predictive route data, for example for a driver assistance system of the motor vehicle, can be taken from the map. It is assumed that the map only roughly shows the course of the road. The map therefore does not have lane-accurate resolution, so that, for example, in the case of a multi-lane road, only a single line representing the multi-lane road is drawn in the provided map.For example, if one of the multiple lanes is a turning lane located next to a lane continuing straight ahead, this cannot be determined from the map because the differentiation into individual lanes is missing. In this case, a single line is drawn on the map for both lanes, with the line splitting into two sub-lines as soon as the turning lane leads away from the straight-ahead lane. The lane can alternatively be referred to as a traffic lane.
[0011] The map is stored, for example, in the motor vehicle. It is stored, for example, in a storage device or storage unit in the motor vehicle. Alternatively or additionally, the map can be stored in an external device and received by the motor vehicle. For this purpose, it can be transmitted from the external device to the motor vehicle via a vehicle-to-vehicle or vehicle-to-infrastructure communication connection. The external device is, for example, another motor vehicle, a road or traffic management system, a backend, a server and / or a cloud server. Preferably, the map is stored in the motor vehicle when the method is carried out. The method comprises providing swarm data that describe a swarm trajectory for each lane of the at least one road. The swarm data can be understood as a swarm map.The swarm data can therefore describe a map in which swarm trajectories are plotted. The swarm data includes, for example, how many different lanes the road has, since a swarm trajectory is described by the swarm data for each lane. The swarm trajectory is determined, for example, by averaging over numerous individual trajectories traveled by swarm vehicles that provide the swarm data. It can be assumed that exactly one swarm trajectory is described by the swarm data for each lane. For the three-lane road, therefore, three swarm trajectories are described by the provided swarm data. The swarm data can be stored in the vehicle and / or received by the external device.
[0012] It can be provided that the method is carried out by a control device of the motor vehicle. In this case, both the map and the swarm data are provided in such a way that they are available to the control device, allowing it to carry out the method. The method can be understood as a computer-implemented method.
[0013] The method comprises generating an additional map. All lanes for at least one road are shown on the map. The additional map is generated by evaluating the provided swarm data and mapping the swarm trajectories onto the map. The provided swarm data and the provided map are thus merged. The additional map is therefore a combined, highly accurate map that shows, lane-by-lane, where motor vehicles typically drive on the road. In the example mentioned above, instead of the previous one line on the map, three individual lines, each representing one of the three lanes, are now shown on the additional map. In the case of the turning lane and the straight-ahead lane, these are each shown individually on the additional map.
[0014] The method comprises locating the motor vehicle on one of the lanes of the additional map by applying a location criterion. This determines where the motor vehicle is located in the additional map. For this location, for example, the motor vehicle can first be located on the map and the position of the motor vehicle determined in this way can be transferred to the additional map after the map has been generated. Alternatively or additionally, it is possible for the location to only be determined on the basis of the additional map. For example, at least one object can be shown on the map and / or at least one object in the vicinity of the lane can be described by the swarm data, so that the motor vehicle can be localized, for example by comparing it with camera data and / or other sensor data of the motor vehicle, such as radar data and / or lidar data.Alternatively or additionally, the location of the motor vehicle can be determined at least partially by using a positioning method based on data from a global navigation satellite system (GNSS), such as the global positioning system (GPS). The location criterion comprises at least one rule and / or regulation, the application of which allows the motor vehicle to be located within the map, the wider map, and / or the swarm data. The location criterion can be an algorithm.
[0015] The method comprises determining driving trajectory information that describes the expected driving trajectory of the motor vehicle. The driving trajectory information is determined by evaluating the further map. The expected driving trajectory runs on the lane in which the motor vehicle was located. For example, it can run on the swarm trajectory assigned to the lane. Alternatively or additionally, it can deviate at least partially from the swarm trajectory assigned to the lane. It can be provided that the expected driving trajectory only describes the course of the lane in which the motor vehicle was located, so that the expected driving trajectory follows the course of this lane. The expected driving trajectory therefore does not have to be specified with exact position on the lane, but can only include the information that the motor vehicle is traveling in a specific lane of, for example, several lanes on the road.
[0016] When determining the expected driving trajectory, driving data describing a motor vehicle's journey can also be used. These data describe, for example, a current steering angle, speed, acceleration, and / or other parameters describing the vehicle's journey. The driving data can alternatively be referred to as odometry data. Evaluating this data can, for example, help determine the expected driving trajectory as accurately as possible, which may depend, for example, on the vehicle's current steering angle.
[0017] The method comprises operating at least one driver assistance system of the motor vehicle taking into account the determined driving trajectory information. The information determined by the method regarding which lane, for example, of several lanes of a road, the motor vehicle is in can thus be made available to the driver assistance system of the motor vehicle so that the latter can, for example, control the motor vehicle taking into account and thus depending on the determined driving trajectory information. The driver assistance system can, for example, be designed to control a longitudinal guidance system of the motor vehicle, i.e., for example, a cruise control system and / or a speed control system that controls the speed of the motor vehicle depending on the environment and thus depending on the expected driving trajectory. Alternative or additional driver assistance systems are possible.Particularly preferably, the driver assistance system is a predictive driver assistance system, so that it can at least automatically adjust, in particular reduce, the speed of the motor vehicle before an intersection and / or a turn. Thus, with the described method, a driving trajectory that a motor vehicle is likely to follow can be reliably determined and further used in the motor vehicle to operate the driver assistance system.
[0018] One embodiment of the invention provides for checking whether the expected trajectory described by the determined trajectory information has a curve with a radius of curvature that lies within a predefined curvature radius range for which a predefined reduction in the speed of the motor vehicle is specified. This is determined by evaluating the additional map, i.e., the curve and its radius of curvature are identified using the additional map. Alternatively or in addition to evaluating the additional map, data that is already described by the map and / or plotted in it can be used. The degree of curvature of the curve is preferably plotted in the additional map, in particular in the map and / or in the swarm data.Depending on this curvature and thus the radius of curvature, it can be specified and / or evaluated whether or not the speed of the vehicle should be reduced when negotiating the curve compared to the current speed. The curvature radius range specifies a range of curvature radii in which a reduction in speed is typically necessary to negotiate the curve.
[0019] If the expected trajectory described by the determined trajectory information includes a curve with a radius of curvature that lies within the specified curvature radius range, the specified reduction in the speed of the motor vehicle is implemented when negotiating the curve. This occurs, for example, using the driver assistance system, i.e., the driver assistance system is additionally operated depending on the specified reduction in speed. This enables a fully automatic speed adjustment to the curve and maximum lateral acceleration of the motor vehicle when negotiating the curve, particularly when turning at an intersection or at a turn or junction, in particular at a highway exit. This is based on the previously described lane-accurate positioning of the motor vehicle.For example, if the vehicle is in the turning lane next to the straight-ahead lane, this can be determined by locating it in the wider map and determining the trajectory information. Depending on the radius of curvature of the curve in the turning lane, the driver assistance system can then automatically reduce the vehicle's speed to negotiate the curve. This provides a particularly reliable predictive driver assistance system.
[0020] Another embodiment provides that the specified reduction in speed occurs down to a curve passage speed that corresponds to a swarm speed when negotiating the curve. The swarm speed is described by the swarm data. In this case, the swarm speed is used that is specified for the swarm trajectory assigned to the lane in which the motor vehicle is located. For example, the swarm speed when negotiating the curve can be used independently of the further map and the information therein on the radius of curvature of the curve, and thus without the complex calculation of a target speed for negotiating the curve, and this can be set as the desired curve passage speed. The curve passage speed can alternatively be referred to as the target speed for negotiating the curve.The procedure described makes it easier to operate the driver assistance system with regard to specifying the speed for cornering.
[0021] Furthermore, one embodiment provides that, if no map is provided, the motor vehicle is located on a swarm trajectory of the swarm data, and the at least one driver assistance system is operated taking into account this swarm trajectory and / or a swarm speed described by the swarm data for this swarm trajectory. For example, if there are multiple swarm trajectories on the road that run parallel to one another or at least partially parallel to one another, the motor vehicle can be located on one of the multiple swarm trajectories, for example, according to the swarm data. For example, the motor vehicle can be located within the swarm map of the swarm data.For example, the driver assistance system can then be provided with exactly the swarm trajectory on or to which the motor vehicle was located, so that this swarm trajectory can be determined and / or assumed as the expected driving trajectory.
[0022] Furthermore, the driver assistance system can be provided directly with the swarm speed assigned to the swarm trajectory on or near which the motor vehicle was located. This is particularly suitable for simply reducing the speed to the curve passage speed, as this then corresponds to the swarm speed and does not need to be calculated. This makes it possible to carry out the process without a map. Mapping onto the digital map, i.e., the map, is therefore not always necessary, since a possible curve speed or a desired curve speed, i.e., the curve passage speed, can be calculated based on the curvature of the swarm trajectory, also in conjunction with, for example, a maximum lateral acceleration at each location.
[0023] In another exemplary embodiment, it is provided that a check is carried out to determine whether the at least one road has a plurality of lanes with a direction of travel that corresponds to the direction of travel of the motor vehicle. Only if this is the case is the further map generated and / or the motor vehicle is located on one of the plurality of lanes of the further map. In order to save resources and / or computing capacity, for example, it can first be checked whether a plurality of lanes are generally known for the road. If, for example, only a single lane is detected, it can be assumed that the motor vehicle is in precisely this lane, so that the generation of the further map can be prevented because it is already known which lane the motor vehicle must be in.Alternatively or additionally, the additional map can still be generated without determining the expected trajectory, since the course of the single lane, for example, can be directly assumed as trajectory information. This significantly simplifies the process in situations where only one lane is present.
[0024] In another exemplary embodiment, a check is carried out to determine whether the at least one road has only a single lane with a direction of travel that coincides with the direction of travel of the motor vehicle. It is furthermore checked whether this single lane has an area in which it splits into two different lanes. These two different lanes can then be understood, for example, as sub-lanes of the single lane. The splitting of the lane into two lanes occurs, for example, when a junction or turn begins from one lane, so that beforehand there is no spatial distinction on the lane between, for example, a turning lane and a lane continuing straight ahead.
[0025] If only a single lane exists and this is divided into two different lanes, a check is carried out to determine which of the two lanes the motor vehicle is likely to follow by evaluating an at least temporary activation of a turn signal on the motor vehicle. It is therefore checked whether it can be determined that, for example, by manually activating a turn signal on the motor vehicle, the driver of the motor vehicle has indicated that he wishes to continue following a specific lane of the two lanes, i.e. a specific sub-lane. If this is the case, i.e. if the lane that the motor vehicle will continue to follow can be ascertained or determined by evaluating the turn signal, the expected travel trajectory along the lane described by the ascertained travel trajectory information that is determined during this evaluation is assumed.It is therefore assumed here that the turn signal can still be used to determine whether the vehicle, for example, wants to continue in the lane or whether it wants to leave it, for example, by following the newly emerging turning lane. This allows the expected driving trajectory to be determined early on. The driver assistance system can thus operate reliably even in situations where the road does not have multiple lanes, but only one lane that splits into two lanes.
[0026] A further exemplary embodiment provides for a check to be carried out to determine whether the at least one road has only a single lane with a direction of travel that coincides with the direction of travel of the motor vehicle, and whether this single lane has an area in which it divides into two different lanes. If this is the case, a check is carried out to determine which of the two lanes the motor vehicle is likely to follow by comparing a speed of the motor vehicle with a swarm speed described by the swarm data for the respective lane of the two lanes. As an alternative to the above-described evaluation of the at least temporary activation of the motor vehicle's turn signal, a comparison can be made between the speed of the motor vehicle and the swarm speed.For this purpose, a separate swarm speed is assumed for each of the two lanes, i.e., for each sub-lane, which is described by the swarm data. It is assumed that, for example, two swarm trajectories can be spatially distinguished on the lane before the lane actually splits into the two lanes. For example, some swarm vehicles decelerate early and then drive into a specific lane of the two lanes. This can be detected in the swarm data. The swarm vehicles remaining in the other lane, for example, do not exhibit any reduction in speed and can therefore be identified.
[0027] Based on, for example, a reduction or maintenance of the speed of the motor vehicle, which can be determined by comparing the speed with the swarm speed, it is possible to determine which of the two lanes the motor vehicle is likely to follow. If one of the two lanes can be determined through this comparison of the speed, this is determined and the expected trajectory, which runs along the lane determined in this comparison, is described from the determined trajectory information. This trajectory information can therefore be determined early and precisely and made available to the driver assistance system. The method is therefore advantageously suited for roads that have only a single lane but may nevertheless have, for example, a curved junction or turn.
[0028] Another exemplary embodiment provides that the location criterion is applied to environmental information describing the surroundings of the motor vehicle. The environmental information is detected by a sensor device of the motor vehicle and transmitted, for example, to the control device. It is assumed here that the environmental information is available or provided to the control device of the motor vehicle so that it can access the environmental information. The environmental information can describe the at least one object in the surroundings and can be compared with an object marked on the map. This enables reliable localization of the motor vehicle.
[0029] The sensor device is preferably a camera, in particular a front camera, of the motor vehicle. Alternatively or additionally, it can be a side camera, a rear camera and / or a surround view camera. Alternatively or additionally, a radar device, a lidar device and / or an ultrasonic sensor of the motor vehicle is possible as the sensor device. What is relevant is that the motor vehicle itself detects the environmental information and this thus describes the environment from the perspective of the motor vehicle. In principle, it is possible, for example, for the environmental information to be determined using a traffic observation camera and / or a sensor device of the other motor vehicle that is in the vicinity of the motor vehicle and to be evaluated in such a way that the motor vehicle is described. The environmental information is then transmitted, for example, to the motor vehicle.
[0030] According to another exemplary embodiment, a check is carried out to determine whether the expected driving trajectory described by the determined driving trajectory information runs along a navigation route provided by a navigation system in the motor vehicle. For example, a check is carried out to determine whether the motor vehicle is currently following its navigation route or whether it is deviating from it. The navigation system can be installed in the motor vehicle and / or assigned to a mobile device that is arranged in the motor vehicle and shares its information, for example, with the control device of the motor vehicle, i.e., transmits it to it. The mobile device is, for example, a smartphone and / or a tablet. Only if the determined driving trajectory information does not describe the expected driving trajectory that runs along the navigation route is the driver assistance system operated taking the determined driving trajectory information into account.Otherwise, i.e., if the expected driving trajectory matches the navigation route, the driver assistance system can be operated based on data from the navigation route. This means, for example, that it may already be known which lane the vehicle must follow in order to continue following the navigation route. It can then be directly determined from the map, for example, which driving trajectory the vehicle will follow, allowing, for example, the speed through curves to be determined by evaluating the navigation route.
[0031] It is assumed that the method is particularly interesting when, for example, the navigation route is deviated from, that is to say when, for example, a parking space and / or rest area on the side of a highway is unexpectedly approached without, for example, activating the indicator, so that by changing to the lane leading to this parking space and / or rest area, according to the method described above, the departure from the navigation route and the entry into a specific lane can be detected and, as a result, for example, the speed of the motor vehicle can be reduced in accordance with the curve of this lane.
[0032] Alternatively, it can be provided that, regardless of a navigation route, the determined driving trajectory information is always used to operate the driver assistance system. Another exemplary embodiment comprises the driver assistance system at least assisting, in particular fully automatically, with longitudinal and / or lateral guidance of the motor vehicle taking into account the determined driving trajectory information. Thus, for example, lateral guidance can also be controlled since it is known which lane the motor vehicle is in. The driver assistance system can, for example, be a lane departure warning system or a lane guidance assistant that can be controlled taking into account the driving trajectory information. Particularly preferably, the driver assistance system specifies the longitudinal guidance of the motor vehicle, since the driver assistance system preferably anticipates and adjusts the speed when cornering.Alternative or additional driver assistance systems are possible.
[0033] With the assisted driver assistance system, for example, only a message can be output in the motor vehicle, which, for example, specifies control commands for the longitudinal and / or lateral guidance of the vehicle. With the fully automatic driver assistance system, this intervenes directly in the longitudinal and / or lateral guidance of the vehicle, i.e., it can, for example, control a braking system, a drive system, and / or a steering system of the vehicle. This makes it particularly clear in which situations the method according to the invention can be useful. For example, the method can be applied whenever the corresponding driver assistance system is activated.
[0034] Another embodiment comprises the motor vehicle receiving the swarm data from an external device. As already described above, the swarm data do not have to be stored in the motor vehicle itself. The motor vehicle can, for example, request this from the external device. Alternatively or additionally, the map can be received from the external device, in particular upon request. Alternatively or additionally, it is possible for the map and the swarm data to be provided in the external device, which generates the additional map and then, for example, transmits the additional map to the motor vehicle. The motor vehicle can transmit information about its position and / or environmental information to the external device so that the latter can locate the motor vehicle.The driving trajectory information can then also be determined by means of the external device and subsequently transmitted to the motor vehicle for operating the driver assistance system. Whether the individual method steps take place in the motor vehicle or outside the motor vehicle is therefore variable. However, all method steps are preferably carried out in the motor vehicle itself, in particular by means of the control device. In another exemplary embodiment, it is provided that the at least one road is drawn on the map in such a way that it has several consecutive route segments, which in particular are at least partially of different lengths. The location of the motor vehicle by applying the location criterion is then carried out with route segment precision. The road therefore has numerous individual sections, which are referred to as route segments.Each route segment has a clearly defined subsequent route segment that follows it. The navigation route can, for example, be provided as a sequence of such route segments. Each route segment can have a unique identification, which can, for example, include at least one number, at least one letter, and / or a combination of letters and numbers. For example, the individual route segments can be numbered sequentially.
[0035] In summary, the navigation system typically assumes that the driver intends to travel along their navigation route, for example, and thus remains on a highway and does not take an exit from the highway. However, according to the invention, it is still possible to detect an exit from the highway. This is based on the fact that a corresponding swarm trajectory is known for each drivable lane and thus for each lane of the road. This swarm trajectory describes, for example, in an x- and y-direction (longitudinal and transverse direction of the road), the course of the swarm's lane (swarm trajectory) in reality, i.e., how this lane was traveled on average by swarm vehicles.The swarm trajectory is then mapped onto the map and thus onto the digital map in order to identify the true driver intention—that is, a modified most probable path instead of the path stored, for example, in the navigation system. Using the map, the driver assistance system can determine the speed at any location based on the curvatures and angles of the individual route segments, eliminating the need for the driver to intervene in longitudinal control. Swarm data is generally information collected and accredited from real motor vehicles. A highly accurate map is created from this information, and thus from the swarm data, enabling localization based on landmarks, such as objects or other obstacles in the environment, to within centimeters.The swarm trajectory reflects the lane or path driven by the swarm, for example by individual swarm vehicles.
[0036] For use cases or application situations that may arise during the method and which are not explicitly described here, it may be provided that, in accordance with the method, an error message and / or a request to enter user feedback is issued and / or a default setting and / or a predetermined initial state is set.
[0037] A further aspect of the invention relates to a motor vehicle configured to perform the method described above. The motor vehicle is, for example, a passenger car, a truck, a bus, a motorcycle, and / or a moped. The motor vehicle may have the control device that performs the method described above.
[0038] Furthermore, one aspect of the invention comprises a control device for a motor vehicle, wherein the control device can carry out the method described above. The control device is designed to carry out the described method. The control device carries out the described method. The control device has, for example, a processor device which can have at least one microprocessor and / or at least one microcontroller and / or at least one FPGA (Field Programmable Gate Array) and / or at least one DSP (Digital Signal Processor). Furthermore, the processor device can have program code, which can alternatively be referred to as a computer program product. The program code can be stored in a data memory of the processor device.
[0039] Another aspect of the invention relates to a computer program product. The computer program product is a computer program. The computer program product comprises instructions that, when the program is executed by a computer, such as by the control devices, cause the computer to perform the corresponding steps of the method according to the invention.
[0040] The invention also includes further developments of the motor vehicle according to the invention, the control device according to the invention and the computer program product according to the invention, which have features as have already been described in connection with the further developments (embodiments) of the method according to the invention.
[0041] The invention comprises the combinations of the features of the described embodiments.
[0042] Exemplary embodiments of the invention are described below. Figure 1 shows a schematic representation of a motor vehicle on a road;
[0043] Fig. 2 shows a schematic representation of a signal flow graph of a method for determining an expected travel trajectory of a motor vehicle;
[0044] Fig. 3 shows a schematic representation of further method steps for a method according to Fig. 2 for the case of cornering; and
[0045] Fig. 4 shows a schematic representation of additional process steps for the process according to Figs. 2 and 3.
[0046] The exemplary embodiments explained below are preferred exemplary embodiments of the invention. In the exemplary embodiments, the described components each represent individual, independently considered features of the invention, which also further develop the invention independently of one another and are thus also to be considered as components of the invention, either individually or in a combination other than that shown. Furthermore, the described exemplary embodiments can also be supplemented by further features of the invention already described.
[0047] In the figures, functionally identical elements are provided with the same reference numerals.
[0048] Fig. 1 shows a motor vehicle 1 traveling on a road 2. It travels in a lane 3. Lane 3 can alternatively be referred to as a lane of road 2. Here, lane 3 is bordered laterally by lane markings 4, which are shown here as a solid line and a center line.
[0049] The motor vehicle 1 here has a control device 5, by means of which a driver assistance system 6 can be provided. The driver assistance system 6 is, for example, a predictive driving assistant that can automatically or at least semi-automatically adapt a speed 32 (see reference numeral 32 in Fig. 3) of the motor vehicle 1 when negotiating a curve 29 (see reference numeral 29 in Fig. 2). The driver assistance system 6 can generally be designed for longitudinal and / or lateral guidance of the motor vehicle 1. The longitudinal and / or lateral guidance is at least assisted. Preferably, it is fully automatic. The motor vehicle 1 can have at least one sensor device 7, which here is designed as a front camera on an upper edge of a windshield 8 of the motor vehicle 1.Alternatively or additionally, the sensor device 7 can be a side camera, a rear camera, a surround-view camera, a radar device, a lidar device, and / or an ultrasonic sensor of the motor vehicle 1. The sensor device 7 can include several individual environmental sensors.
[0050] An external device 9 may be provided, which has a communication interface 10, so that it can transmit data to and / or receive data from a communication interface 10 of the motor vehicle 1. The external device 9 is, for example, another motor vehicle 1, a road or traffic management system, a traffic monitoring camera, a backend, a server, and / or a cloud server.
[0051] Fig. 2 outlines steps of a method for determining an expected travel trajectory 28 of the motor vehicle 1. The method is preferably carried out by means of the control device 5 of the motor vehicle 1. In a method step S1, a map 20 is provided, in which at least the road 2 is drawn without differentiating individual lanes 3 of the road 2. It is outlined here that individual route segments that follow one another can be drawn on the map 20. For this purpose, route segment boundaries 21 of the route segments are drawn. The at least one road 2 can therefore be designed such that it has several consecutive route segments, which in particular are at least partially of different lengths. Within the scope of the method, a route-segment-precise location of the motor vehicle 1 can be carried out. The road 2 shown in the map 20 can, for example, actually be a three-lane road 2.However, on map 20, this is shown as a single line that splits into two lines. Furthermore, here, lane 3 meets lane 3 that has turned off from the straight lanes 3, which also results in the joining lane and the already turned lane 3 being shown as a single line. This specific course of road 2 becomes particularly clear in connection with a method step S2.
[0052] In method step S2, swarm data 22 are provided, which describe a swarm trajectory 23 for each lane 3 of the at least one road 2. Here, the three adjacent lanes 3 are initially identified based on their respective swarm trajectories 23. The bent lane 3 partially runs as a two-lane lane due to the lane 3 that adjoins it. In a method step S3, a further map 24 is generated, in which all lanes 3 for the at least one road 2 are shown. This is done by evaluating the provided swarm data 22 and mapping the swarm trajectories 23 onto the map 20. Therefore, a map is sketched here purely as an example, in which the information from the map 20 is superimposed over the individual lanes 3 according to the swarm trajectories 23 using dashed lines. It is also marked on the further map 24 where the motor vehicle 1 is located in the further map 24.Specifically, the motor vehicle 1 is located on one of the lanes 3 of the additional map 24 by applying a location criterion. The location criterion can, for example, be applied to environmental information that describes the surroundings of the motor vehicle 1 and was detected by the sensor device 7 of the motor vehicle 1. The sensor device 7 provides the environmental information to the control device 5, i.e., transmits it to it.
[0053] Here, purely as an example for method step S3, it is shown that motor vehicle 1 is located at a position 25, which here is located on the outermost lane 3 of the three lanes 3. This lane 3 is specially marked as ego lane 26.
[0054] In a method step S4, driving trajectory information 27 is determined, which describes an expected driving trajectory 28 of the motor vehicle 1. The driving trajectory information 27 can be determined by evaluating the further map 24. The expected driving trajectory 28 runs on lane 3, on which the motor vehicle 1 was located, i.e., here along the ego lane 26. In a method step S5, the driver assistance system 6 is operated taking into account the determined driving trajectory information 27. The driver assistance system 6 therefore knows that the motor vehicle 1 is in a turning lane that does not exactly follow the previous course of road 2, but rather leaves it.
[0055] Further possible method steps are outlined in Fig. 3. In a method step S6, a check is carried out to determine whether the expected travel trajectory 28 described by the travel trajectory information 27 has a curve 29 with a radius of curvature 30 that lies within a predetermined curvature radius range 31. The curvature radius range 31 is defined such that a predetermined reduction in a speed 32 of the motor vehicle 1 is predetermined for it. If this check determines that this is the case, the predetermined reduction in the speed 32 of the motor vehicle 1 when negotiating the curve 29 can be carried out in a method step S7. It can be provided that the predetermined reduction takes place up to a curve passage speed 33 that corresponds to a swarm speed 34 when negotiating the curve 29. The swarm speed 34 is described by the swarm data 22.However, if it is determined that no curve 29 is approaching, or that no curve 29 with the radius of curvature 30 is approaching within the radius of curvature range 31, the speed 32 of the motor vehicle 1 can be maintained, for example, in a method step S8. Depending on the course of the road 2 and in particular of the lane 3, the speed 32 can alternatively be increased.
[0056] It can generally be provided that, before method step S1, a check is performed to determine whether the map 20 is available at all. If this is the case, the motor vehicle 1 can be located on a swarm trajectory 23 of the swarm data 22. The at least one driver assistance system 6 is then operated taking into account this swarm trajectory 23 and / or the swarm speed 34 for this swarm trajectory 23.
[0057] Further possible method steps S9 to S13 are outlined in Fig. 4. In a method step S9, it can be checked whether the at least one road 2 has a plurality of lanes 3 in a direction of travel 35 that coincides with the direction of travel 35 of the motor vehicle 1. It can be provided that only if this is the case, the further map 24 is generated and / or the location of the motor vehicle 1 on one of the plurality of lanes 3 of the further map 24 is carried out. Thus, for example, the execution of method steps S3 and thus also of method step S4 can depend on how this check ends. Here, for example, it is assumed that there are a plurality of lanes 3 with the same direction of travel 35, so that method steps S3 and S4 and method steps S5 to S8 can follow.
[0058] However, if it is determined that road 2 has only a single lane 3 with a direction of travel 35 that coincides with the direction of travel 35 of motor vehicle 1, a method step S10 can be used to check whether this single lane 3 has an area 36 in which it divides into two different lanes 3. These are referred to here as sub-lanes 37a, 37b. If this is the case, a method step S11 and / or a method step S12 can be carried out. Method step S11 provides for a check to determine whether, by evaluating an at least temporary activation of a turn signal 38 of motor vehicle 1, it is possible to determine which of the two sub-lanes 37a, 37b the motor vehicle 1 is likely to follow.If this is the case, in a method step S13, the expected travel trajectory 28 described by the determined travel trajectory information 27 is assumed to be lane 3 running along sub-lane 37a, 37b, which can be determined during the described evaluation. Here, for example, this is sub-lane 37b, which has curve 29. The described evaluation can therefore be performed.
[0059] Method step S12 may include checking whether, by comparing the speed 32 of the motor vehicle 1 and the swarm speed 34 described by the swarm data 22 for the respective lane 3 of the two lanes 3, it is possible to determine which of the two lanes 3 the motor vehicle 1 is likely to follow. Thus, by comparing the speed 32 of the motor vehicle 1 and the respective swarm speed 34 for the sub-lane 37a and for the sub-lane 37b, it is checked whether the motor vehicle 1 is likely to drive into the sub-lane 37a or the sub-lane 37b. If this comparison can be determined, in method step S13 the expected travel trajectory 28 is described by the determined travel trajectory information 27, which runs along the sub-lane 37a, 37b, which is determined via this comparison, which can be carried out according to method step S12.The comparison described can therefore be carried out.
[0060] It may further be provided that a check is performed to determine whether the expected travel trajectory 28 described by the determined travel trajectory information 27 runs along a navigation route provided by a navigation system in the motor vehicle 1. Only if this is not the case is the driver assistance system 6 operated taking into account the determined expected travel trajectory 28, i.e., method step S5 is performed.
[0061] In general, the driver assistance system 6 can control the longitudinal and / or lateral guidance of the motor vehicle 1 taking into account the determined driving trajectory information 27. The swarm data 22 and the map 20 can be transmitted from the external device 9 to the motor vehicle 1 and thus received by it.
[0062] Overall, the examples show that swarm trajectories 23 can map lane 3, which the swarm actually traveled. This means that one knows exactly where to travel along these swarm trajectories 23 by precisely locating motor vehicle 1 in lane 3. Thus, highly accurate positioning is possible without the need for high-definition maps. By mapping with map 20, the actual probable path, i.e., the travel trajectory information 27, can be predictively formed using various swarm trajectories 23. The position 25 of motor vehicle 1 is clearly visible. Lane 3, on which motor vehicle 1 is located, exhibits a strong curvature to the right and thus differs significantly from the other two lanes 3.
[0063] Looking at map 20, it can be determined that an exit, turn, or exit begins at position 25, which also has a sharp curve to the right and thus differs from the straight-ahead path of the adjacent lanes 3. This allows a specific route segment in map 20 to be identified as the relevant route segment and to be predictively slowed down to the exit. Due to the highly precise localization, driver assistance system 6 knows at all times which swarm trajectory 23 the motor vehicle 1 is on and thus which lane 3 it is in. It can thus identify a driver's turn request as such, even without, for example, manually signaling.
[0064] List of reference symbols
[0065] Motor vehicle
[0066] Street
[0067] lane
[0068] Lane markings
[0069] Control device
[0070] Driver assistance system
[0071] Environmental sensor device
[0072] Windshield external device communication interface map
[0073] Route segment boundary
[0074] Swarm data
[0075] Swarm trajectory further map position
[0076] Ego lane
[0077] Driving trajectory information expected driving trajectory curve
[0078] radius of curvature
[0079] Curvature radius range
[0080] speed
[0081] Curve passing speed
[0082] Swarm speed
[0083] Direction of travel
[0084] Area a Sub-lane b Sub-lane indicator - S13 Procedural steps
Claims
Patent claims 1. A method for determining an expected travel trajectory (28) of a motor vehicle (1), comprising: Providing (S1) a map (20) in which at least one road (2) is drawn without differentiating individual lanes (3) of the road (2); providing (S2) swarm data (22) that describe a swarm trajectory (23) for each lane (3) of the at least one road (2); Generating (S3) a further map (24) in which all lanes (3) are marked for the at least one road (2) by evaluating the provided swarm data (22) and mapping the swarm trajectories (23) onto the map (20); Locating the motor vehicle (1) on one of the lanes (3) of the further map (24) by applying a location criterion; Determining (S4) a driving trajectory information item (27) that describes an expected driving trajectory (28) of the motor vehicle (1) by evaluating the further map (24), wherein the expected driving trajectory (28) runs on the lane (3) on which the motor vehicle (1) was located; and Operating (S5) at least one driver assistance system (6) of the motor vehicle (1) taking into account the determined driving trajectory information (27).
2. Method according to claim 1, wherein it is checked whether the expected travel trajectory (28) described by the determined travel trajectory information (27) has a curve (29) with a radius of curvature (30) which lies in a predetermined radius of curvature range (31) for which a predetermined reduction in a speed (32) of the motor vehicle (1) is predetermined, by evaluating the further map (24), wherein if this is the case, the predetermined reduction in the speed (32) of the motor vehicle (1) is carried out when driving through the curve (29).
3. Method according to claim 2, wherein the predetermined reduction takes place up to a curve crossing speed (32) which corresponds to a swarm speed (34) when crossing the curve (29), wherein the swarm speed (34) is described by the swarm data (22).
4. Method according to one of the preceding claims, wherein if no map (20) is provided, a location of the motor vehicle (1) is determined on a swarm trajectory (23) of the swarm data (22) and the at least one driver assistance system (6) is operated taking into account this swarm trajectory (23) and / or a swarm speed (34) which is described by the swarm data (22) for this swarm trajectory (23).
5. Method according to one of the preceding claims, wherein it is checked whether the at least one road (2) has a plurality of lanes (3) with a direction of travel (35) that corresponds to the direction of travel (35) of the motor vehicle (1), wherein only if this is the case, the further map (24) is generated and / or the location of the motor vehicle (1) is carried out on one of the plurality of lanes (3) of the further map (24).
6. Method according to one of the preceding claims, wherein it is checked whether the at least one road (2) has only a single lane (3) with a direction of travel (35) that corresponds to the direction of travel (35) of the motor vehicle (1), and whether this single lane (3) has an area (36) in which it divides into two different lanes (3), wherein if this is the case, it is checked whether it is possible to determine which of the two lanes (3) the motor vehicle (1) is likely to follow by evaluating an at least temporary activation of a turn signal (38) of the motor vehicle (1), wherein if this is the case, the expected travel trajectory (28) described by the determined travel trajectory information (27) runs along the lane (3) that is determined during the evaluation.
7. Method according to one of the preceding claims, wherein it is checked whether the at least one road (2) has only a single lane (3) with a direction of travel (35) that corresponds to the direction of travel (35) of the motor vehicle (1), and whether this single lane (3) has an area (36) in which it divides into two different lanes (3), wherein if this is the case, it is checked whether it is possible to determine which of the two lanes (3) the motor vehicle (1) is likely to follow by comparing a speed (32) of the motor vehicle (1) with a swarm speed (34) described by the swarm data (22) for the respective lane (3), wherein if this is the case, the expected trajectory (28) described by the determined trajectory information (27) runs along the lane (3) that is determined during the comparison.
8. Method according to one of the preceding claims, wherein the location criterion is applied to environmental information which describes an environment of the motor vehicle (1) and was determined by means of a sensor device (7) of the motor vehicle (1).
9. Method according to one of the preceding claims, wherein it is checked whether the expected driving trajectory (28) described by the determined driving trajectory information (27) runs along a navigation route provided by a navigation system in the motor vehicle (1), wherein only if this is not the case, the driver assistance system (6) is operated taking into account the determined driving trajectory information (27).
10. Method according to one of the preceding claims, wherein the driver assistance system (6) at least assists, in particular fully automatically, a longitudinal and / or transverse guidance of the motor vehicle (1) taking into account the determined travel trajectory information (27).
11. Method according to one of the preceding claims, wherein the motor vehicle (1) receives the swarm data (22) and / or the map (20) and / or the further map (24) from an external device (9).
12. Method according to one of the preceding claims, wherein the at least one road (2) is shown in the map (20) in such a way that it has a plurality of successive route segments which in particular are at least partially of different lengths, and the location of the motor vehicle (1) is carried out with route segment accuracy.
13. Motor vehicle (1) designed to carry out a method according to one of the preceding claims.
14. Control device (5) for a motor vehicle (1), wherein the control device (5) is designed to carry out a method according to one of claims 1 to 12.
15. Computer program product comprising instructions which, when executed, program by a computer causing it to carry out a method according to one of claims 1 to 12