Method for providing lane change assistance for vehicles, and lane change assistance method for a vehicle

Abstract

The present invention relates to a method (100) for providing lane change assistance for vehicles (10, FF), comprising providing (110) travel data of a vehicle (10), wherein the travel data relate to a first driving situation of the vehicle (10, FF); carrying out (120) a simulation of a second driving situation on the basis of the travel data of the first travel situation in order to generate simulation data, wherein the first driving situation comprises at least one lane change and the second driving situation comprises no lane change, or wherein the second driving situation comprises at least one lane change and the first driving situation comprises no lane change; and training (130) a lane change algorithm on the basis of the travel data and / or the simulation data.

Description

[0001] Method for providing lane change assistance for vehicles and lane change assistance method for a vehicle

[0002] The present disclosure relates to a method for providing lane change assistance for vehicles, a lane change assistance method for a vehicle, and a system for carrying out said methods. In particular, the present disclosure relates to calculating and initiating optimal lane changes, for example, in automated driving.

[0003] State of the art

[0004] Driver assistance systems for automated driving are becoming increasingly important. Automated driving can be achieved with various levels of automation. Examples of automation levels include assisted, partially automated, conditionally automated, highly automated, or fully automated driving. The five levels of automation mentioned above correspond to SAE Levels 1 to 5 of the SAE J3016 standard (SAE - Society of Automotive Engineering) as of April 30, 2021. With fully automated driving (SAE Level 5), the system can perform all aspects of the dynamic driving task under any road and environmental conditions that can also be mastered by a human driver.

[0005] Modern vehicles are increasingly equipped with so-called lane change assistants. Depending on the level of automation, the driver can perform a lane change themselves, trigger an automated lane change, or the vehicle can perform a lane change completely automatically. In at least some of these cases, the vehicle can perform automated lane change planning, for example, checking whether there is sufficient space, whether the navigation indicates a lane change is necessary to remain on the planned route, whether the vehicle in the current lane is being slowed down by a slower vehicle in front, etc.

[0006] Changing lanes is generally associated with an increased safety risk, as collisions with other vehicles are more likely than remaining in the current lane. With lane change assistance according to SAE Level 2, the driver must monitor the function, which puts the driver on heightened alert, thus reducing driving comfort. Similarly, driving comfort can be reduced due to too many lane changes that must be monitored by the driver. This can prompt the driver to deactivate the function. Deactivating lane change assistance can have a negative impact on road safety, as lane change assistance often offers greater safety than manual driving. Furthermore, too many or too few lane changes can negatively impact the vehicle's travel time and / or traffic flow.

[0007] Disclosure of the invention

[0008] It is an object of the present disclosure to provide a method for providing lane change assistance for vehicles, a lane change assistance method for a vehicle, and a system for executing said methods, which enable a reliable estimation in advance of whether or not a lane change is advisable in a current situation. Furthermore, it is an object of the present disclosure to maximize the service life of a lane change assistance system and thus increase road safety.

[0009] This object is achieved by the subject matter of the independent claims. Advantageous embodiments are specified in the subclaims.

[0010] According to an independent aspect of the present disclosure, a method for providing lane change assistance for vehicles, in particular motor vehicles, is specified. The method comprises providing travel data of a vehicle, wherein the travel data relate to a first driving situation of the vehicle; performing a simulation of a second driving situation based on the travel data of the first driving situation to generate simulation data, wherein the first driving situation comprises at least one lane change and the second driving situation does not comprise a lane change, or wherein the second driving situation comprises at least one lane change and the first driving situation does not comprise a lane change; and training a lane change algorithm based on the travel data and / or the simulation data.

[0011] According to the invention, a data-driven approach is used to train a lane change algorithm that can determine whether a lane change is advantageous or not in a current situation. For this purpose, real journeys, e.g. of a fleet of vehicles, are evaluated. In particular, a corresponding journey without a lane change is simulated for a real journey with a lane change, or a corresponding journey with a lane change is simulated for a real journey without a lane change. Based on a comparison of the real and simulated driving situations with and without a lane change, it can then be deduced whether the lane change is advantageous or not. The lane change algorithm trained on the basis of these findings can then be implemented in real vehicles and, in real operation, enable a reliable assessment of whether a lane change is advisable or not in a current situation.The lane change algorithm is trained based on the driving data and / or the simulation data. In some embodiments, the lane change algorithm can be trained using (only) the data corresponding to the better alternative. In other embodiments, the lane change algorithm can be trained using both the real-world driving data and the simulation data.

[0012] Preferably, performing the simulation of the second driving situation comprises determining a driving behavior of the vehicle and a driving behavior of at least one other vehicle. In particular, a change in the driving behavior of the vehicle and a change in the driving behavior of the at least one other vehicle can be determined with respect to the addition or omission of the lane change. This makes it possible to determine and analyze the driving behavior in both situations, i.e., once with a lane change and once without a lane change.

[0013] Preferably, the method further comprises performing a comparison of the first driving situation and the second driving situation (or corresponding driving situation-related data); and determining, based on the comparison, whether the at least one lane change is favorable or unfavorable. The terms "favorable" and "unfavorable" refer to objective criteria that indicate which of the driving situations is more efficient and / or advantageous.

[0014] Preferably, the comparison is carried out with respect to the first driving situation and the second driving situation based on at least one comparison criterion. The at least one comparison criterion is an objective criterion that indicates which of the driving situations is more favorable or advantageous. This allows the first driving situation and the second driving situation to be objectively compared and thus evaluated.

[0015] In some embodiments, the at least one comparison criterion is selected from the group comprising (or consisting of) the following: a travel time difference; and / or a speed difference to at least one other vehicle; and / or a distance to at least one other vehicle; and / or a difference in driver attention; and / or an energy consumption of the vehicle; and / or an acceleration behavior of the vehicle and / or at least one other vehicle.

[0016] With regard to the travel time difference, for example, it can be determined whether a destination can be reached more quickly with or without changing lanes. The driving situation with the shorter travel time can then be classified as the most favorable driving situation.

[0017] With regard to the speed difference to at least one other vehicle, for example, the size of the speed difference to another vehicle driving in front of the vehicle or the vehicle in front can be determined. If the speed difference is large and the ego vehicle is faster than the vehicle in front, changing lanes to overtake the vehicle in front may be more advantageous than not changing lanes or remaining behind the vehicle in front. If, on the other hand, the speed difference is small and the ego vehicle is faster than the vehicle in front, changing lanes to overtake the vehicle in front may be less advantageous than not changing lanes or remaining behind the vehicle in front due to only a minimal reduction in travel time and an increased collision risk caused by the lane change.

[0018] With regard to the distance to at least one other vehicle, for example, the distance to another vehicle or the vehicle in front of the vehicle can be determined. If the distance is large and the ego vehicle is only minimally faster than the vehicle in front, changing lanes to overtake the vehicle in front may be less advantageous than not changing lanes or remaining behind the vehicle in front due to only minimally reduced travel time and an increased risk of collision caused by the lane change. With regard to the driver's attention difference, a required level of attention of the driver can be determined in both driving situations, whereby in a driving situation with a lane change, a higher level of attention is often required from the driver than in a driving situation without a lane change. If the attention difference is large, not changing lanes may be more advantageous than changing lanes.In particular, the large difference in attention can be associated with a greatly increased risk of an accident, so it may be more advantageous to avoid changing lanes.

[0019] With regard to the vehicle's energy consumption (e.g., fuel and / or electrical energy), it is possible to determine the energy consumption in both driving situations and / or the magnitude of the difference in energy consumption. The driving situation with the lower energy consumption can be classified as the favorable driving situation.

[0020] With regard to the acceleration behavior of the vehicle and / or of the at least one other vehicle, it can be determined, for example, whether the acceleration behavior present in both driving situations is to be assessed positively or negatively. For example, it may be necessary for the ego vehicle to accelerate sharply in order to overtake a vehicle in front. In this case, changing lanes to overtake the vehicle in front may be less favorable than not changing lanes or remaining behind the vehicle in front due to the increased risk of collision caused by the lane change. In a further example, it may be necessary for the ego vehicle to brake sharply without changing lanes in order to avoid colliding with a vehicle in front. In this case, changing lanes to overtake the vehicle in front may be more favorable than not changing lanes or remaining behind the vehicle in front.

[0021] In some embodiments, the driving data of the first or real driving situation is selected from the group comprising (or consisting of) the following:

[0022] Vehicle position data; and / or

[0023] Dynamic data of the vehicle, in particular speed data; and / or environmental data from an environmental sensor system of the vehicle; and / or operating data of the vehicle; and / or driving maneuver data of the vehicle.

[0024] Regarding the vehicle's position data, GPS positions from the initial or real driving situation can be fed into the simulation. The position data makes it possible, for example, to determine the vehicle's driving path in the initial or real driving situation.

[0025] With regard to the vehicle's dynamic data, variables describing the vehicle's movement from the initial or real driving situation can be fed into the simulation. The dynamic data can include, for example, speed data and / or acceleration data (e.g., longitudinal acceleration and / or lateral acceleration), but are not limited to these.

[0026] With regard to the environmental data from the vehicle's environmental sensors from the first or real driving situation, these can be fed into the simulation selectively and / or (pre-)processed (e.g., as detections). The environmental sensors preferably comprise at least one LiD AR system and / or at least one radar system and / or at least one camera and / or at least one ultrasound system. The environmental sensors can provide the environmental data (also referred to as "environmental data") that maps an area surrounding the vehicle.

[0027] With regard to the vehicle's operating data from the first or real driving situation, this can be fed into the simulation in order to depict the vehicle's behavior in the simulation as accurately as possible and to enable a correlation between the first or real driving situation and the second or simulated driving situation. The vehicle's operating data can, for example, relate to the operation of a drive (e.g. combustion engine, electric drive, operating mode, etc.) and / or the operation of driver assistance systems and / or a vehicle state (e.g. tire pressure), but are not limited to these examples. With regard to the vehicle's driving maneuver data from the first or real driving situation, this can indicate which driving maneuvers the vehicle has performed. The driving maneuvers can, for example, relate to lane changes, steering maneuvers, braking maneuvers, acceleration maneuvers, etc., but are not limited to these examples.

[0028] Preferably, the simulation of the second driving situation is carried out based on the driving data of the first driving situation and additional data.

[0029] In some embodiments, the additional data is selected from the group comprising (or consisting of): digital map data; and / or

[0030] Other vehicle information (e.g. positions, speeds, vehicle types, etc.); and / or dynamic traffic information (e.g. traffic jams, slow traffic, etc.); and / or

[0031] Environmental information (e.g. hazard warnings, construction sites, weather conditions, etc.); and / or

[0032] Traffic infrastructure information (e.g. lanes, number of lanes, lane geometry, etc.).

[0033] Preferably, the method further comprises providing the trained lane-changing algorithm to a vehicle fleet comprising a plurality of vehicles. In particular, the trained lane-changing algorithm can be installed in the vehicles of the vehicle fleet and used there in real-life operation to enable an assessment of whether or not a lane change is advisable in a current situation.

[0034] The lane-changing algorithm preferably comprises, or is, at least one neural network, in particular a trained neural network. Neural networks consist of a series of processing units, known as neurons, that are connected to one another via communication channels. The neurons process input data and pass the result of the processing on to other neurons via the communication channels. Through the parallel processing of data, which is made possible by linking the neurons and their processing functions, complex, nonlinear dependencies in the input data can be mapped. Neural networks are trained using a suitable learning technique, e.g., machine learning, so that they learn these dependencies. The neural networks can be trained using empirical data, the so-called training data.

[0035] Preferably, the lane-changing algorithm is a machine learning-based algorithm. Machine learning (ML) refers to the artificial generation of knowledge from experience. Algorithms learn from empirical data and, after completing the learning phase, are able to generalize from the experience. To do this, the algorithms build a statistical model based on the empirical data. The empirical data used to train the algorithms is generally referred to as "training data."

[0036] According to a further independent aspect of the present disclosure, a system for providing lane change assistance for vehicles is provided. The system comprises one or more processors; and at least one memory connected to the one or more processors and containing instructions executable by the one or more processors to perform the method described in this document for providing lane change assistance for vehicles.

[0037] Preferably, the system comprises at least one server and / or at least one backend, or is implemented by the at least one server and / or the at least one backend.

[0038] A processor or processor module is a programmable computing unit, i.e. a machine or an electronic circuit that controls other elements according to given instructions and thereby drives an algorithm (process).

[0039] According to a further independent aspect of the present disclosure, a lane change assistance method for a vehicle, in particular a motor vehicle, is provided. The lane change assistance method comprises determining, using a lane change algorithm trained with the method described in this document, whether or not a lane change should be performed in a current driving situation of the vehicle.

[0040] Preferably, the lane change assistance method further comprises issuing a corresponding recommendation to a driver of the vehicle and / or performing an automated lane change when it is determined that a lane change should be performed.

[0041] Preferably, the lane change assistance method further comprises determining at least one driving maneuver to be performed based on whether or not the lane change should be performed in the current driving situation of the vehicle. The at least one driving maneuver to be performed may relate to a driving maneuver other than the lane change or may be a driving maneuver other than the lane change, and may in particular be an additional driving maneuver. In some embodiments, the at least one driving maneuver to be performed may include an acceleration maneuver and / or a braking maneuver, but is not limited to these examples.

[0042] Preferably, the lane change assistance method further comprises issuing a corresponding recommendation with regard to the at least one driving maneuver to be performed to a driver of the vehicle and / or automatically performing the at least one driving maneuver.

[0043] According to a further independent aspect of the present disclosure, a driver assistance system for vehicles is provided. The driver assistance system comprises one or more processors; and at least one memory connected to the one or more processors and containing instructions executable by the one or more processors to carry out the lane change assistance method described in this document. Preferably, the driver assistance system is configured for automated driving.

[0044] In this document, the term "automated driving" refers to driving with automated longitudinal and / or lateral guidance. Automated driving can, for example, involve extended driving on the highway or limited-time driving while parking. The term "automated driving" encompasses automated driving with any degree of automation. Examples of levels of automation include assisted, partially automated, conditionally automated, highly automated, and fully automated driving (each with an increasing degree of automation). The five levels of automation mentioned above correspond to SAE Levels 1 to 5 of the SAE J3016 standard (SAE - Society of Automotive Engineering) as of April 30, 2021.

[0045] In assisted driving (SAE Level 1), the system provides longitudinal or lateral guidance in specific driving situations. In partially automated driving (SAE Level 2), the system assumes longitudinal and lateral guidance in specific driving situations, although the driver must continuously monitor the system, as with assisted driving. In conditionally automated driving (SAE Level 3), the system assumes longitudinal and lateral guidance in specific driving situations without the driver having to continuously monitor the system; however, the driver must be able to take over vehicle control within a certain time period when requested by the system. In highly automated driving (SAE Level 4), the system assumes vehicle control in specific driving situations even if the driver does not respond to a request to intervene, thus eliminating the driver as a fallback.In fully automated driving (SAE Level 5), the system can perform all aspects of the dynamic driving task under any road and environmental conditions that can also be mastered by a human driver.

[0046] Furthermore, the term "at least partially automated driving or maneuvering" is also understood in this document to include partially automated, conditionally automated, highly automated, and fully automated driving. In other words, the term "at least partially automated driving" refers to a level of automation up to and including SAE Level 2.

[0047] Preferably, the driver assistance system comprises, or is, a lane change assistant that is configured to perform lane changes automatically.

[0048] However, the embodiments of the present disclosure are not limited to automated driving or automated lane changing. In alternative embodiments, the driver assistance system can output driver instructions using at least one output device when the vehicle is being driven manually. The driver instruction can, for example, be a recommendation as to whether or not a lane change should be performed in a current driving situation of the vehicle.

[0049] The at least one output device can comprise at least one display device and / or at least one loudspeaker. The at least one display device can comprise a display, in particular an LCD display, a plasma display or an OLED display. Additionally or alternatively, the at least one display device can comprise a projection device that is configured to display information directly in the driver's field of vision, in particular to project it onto a windshield. In some embodiments, the at least one display device can be a central information output device of an infotainment system, such as a head unit or a pillar-to-pillar display. Preferably, the at least one output device is permanently installed in the vehicle.

[0050] According to a further independent aspect of the present disclosure, a vehicle, in particular a motor vehicle, is specified. The vehicle comprises the driver assistance system according to the embodiments of the present disclosure.

[0051] The term "vehicle" encompasses cars, trucks, vans, buses, mobile homes, motorcycles, etc., that are used to transport people, goods, etc. In particular, the term includes motor vehicles for passenger transport. According to a further independent aspect of the present disclosure, a software (SW) program is specified. The SW program can be configured to run on one or more processors and thereby to carry out the methods described in this document.

[0052] According to a further independent aspect of the present disclosure, a storage medium is provided. The storage medium may comprise a software program configured to be executed on one or more processors and thereby to carry out the methods described in this document.

[0053] According to a further independent aspect of the present disclosure, software comprising program code is provided. The software is configured to perform the methods described in this document when the software is executed on one or more software-controlled devices.

[0054] Short description of the drawings

[0055] Embodiments of the disclosure are illustrated in the figures and are described in more detail below. They show:

[0056] Figure 1 is a flowchart of a method for providing lane change assistance for vehicles according to embodiments of the present disclosure,

[0057] Figure 2 shows a system for providing lane change assistance for vehicles according to embodiments of the present disclosure,

[0058] Figure 3 is a flowchart of a lane change assistance method according to embodiments of the present disclosure, and Figure 4 is a schematic view of a vehicle with a driver assistance system for automated driving according to embodiments of the present disclosure.

[0059] Embodiments of the disclosure

[0060] In the following, unless otherwise stated, the same reference symbols are used for identical and equivalent elements.

[0061] Figure 1 schematically shows a flowchart of a method 100 for providing lane change assistance for vehicles according to embodiments of the present disclosure. Figure 2 shows a system for providing lane change assistance for vehicles according to embodiments of the present disclosure. In particular, the system may include a central unit 200 configured to execute the method 100. The central unit 200 may be a server or backend.

[0062] The method 100 comprises, in block 110, providing driving data of a vehicle, wherein the driving data relate to a first driving situation of the vehicle; in block 120, performing a simulation of a second driving situation based on the driving data of the first driving situation to generate simulation data, wherein the first driving situation comprises at least one lane change and the second driving situation does not comprise a lane change, or wherein the second driving situation comprises at least one lane change and the first driving situation does not comprise a lane change; and in block 130, training a lane change algorithm based on the driving data and / or the simulation data.

[0063] According to the invention, a data-driven approach is used to train a lane change algorithm that can determine whether a lane change is advantageous or not in a current situation. For this purpose, real journeys, e.g. of a vehicle fleet FF, are evaluated. In particular, a corresponding journey without a lane change is simulated for a real journey with a lane change, or a corresponding journey with a lane change is simulated for a real journey without a lane change. Based on a comparison of the real and simulated driving situations with and without a lane change, it can then be deduced whether the lane change is advantageous or not. The lane change algorithm trained on the basis of these findings can then be implemented in real vehicles 10 and, in real operation, enable a reliable assessment of whether a lane change is advisable or not in a current situation.

[0064] In detail, large amounts of data on real journeys of the FF vehicle fleet are collected and evaluated in the backend 200. The result of the evaluation is whether a lane change was advantageous at a specific time t during this journey or whether it would have been better for the vehicle to remain in its current lane at that time.

[0065] For each decision point t, both variants are calculated and compared. In addition to the real driving situation, a possible implementation is also simulated. This simulation is fed with data from the vehicle, a digital map, dynamic traffic information, and / or environmental information. Examples of such input data include, but are not limited to, the positions, speeds, and / or types of other vehicles in space and time; the current lane, route, number of lanes, and roadway geometries in the current and following route sections; traffic information, hazard warnings, and / or construction sites.

[0066] The behavior of other vehicles, if not present in the data, can be predicted using modern microsimulation. The behavior of the ego vehicle is recalculated and predicted based on the control software in the ego vehicle. The comparison of the implementation variants at time t can take into account the travel time difference, the speed differences to other vehicles, the distances to other vehicles, the additional driver attention required, the fuel consumption, the differences in the acceleration values ​​of all vehicles, etc.

[0067] The dataset prepared in this way can be used to train an ML model that calculates whether a lane change is advisable at the current time or at a future time, depending on the vehicle's current situation in relation to an environment model, a position, a selected route, etc. This model is transferred to the vehicle fleet and runs on the control units in the vehicles.

[0068] Figure 3 shows a flowchart of a lane change assistance method 300 according to embodiments of the present disclosure.

[0069] The lane change assistance method 300 includes, at block 310, determining, using a lane change algorithm trained with the method described in this document, whether or not a lane change should be performed in a current driving situation of the vehicle; and, at block 320, issuing a corresponding recommendation to a driver of the vehicle and / or performing an automated lane change if it is determined that a lane change should be performed.

[0070] In some embodiments, a probability can also be calculated that indicates the reasonableness of the lane change. Additionally or alternatively, an additional maneuver, such as braking or acceleration, can be associated with the lane change. Additionally or alternatively, the lane change can be offered to the driver as a suggestion, which they must first agree to. Additionally or alternatively, the process can be personalized by having the driver provide feedback after a lane change regarding whether the lane change was perceived as positive or negative. This feedback can then be incorporated into the algorithm training.

[0071] In an illustrative example, an ego vehicle with Level 3 functionality is traveling in automatic mode on a two-lane highway at 130 km / h in the right lane. A convoy of trucks traveling at 80 km / h appears in front of the ego vehicle. Traffic is heavy, and the vehicle is due to exit the highway in two kilometers. Driving time could potentially be saved by changing lanes, overtaking the trucks, and rejoining them. However, the system, which had previously been trained for similar situations, does not recommend overtaking. In similar situations, it has been found that re-entering the right lane was impossible due to heavy traffic, and the exit was missed.

[0072] Figure 4 schematically shows a vehicle 10 with a driver assistance system 400 for automated driving according to embodiments of the present disclosure.

[0073] The driver assistance system 400 includes a lane change assistant, is a lane change assistant, or can implement the functionalities of a lane change assistant. In particular, the driver assistance system 400 can determine, using the lane change algorithm trained using the method described in this document, whether or not a lane change should be performed in a current driving situation of the vehicle 10. If it is determined that the lane change should be performed, the driver assistance system 400 can perform the lane change automatically.

[0074] In automated driving according to the embodiments of the present disclosure, the lateral guidance (and optionally the longitudinal guidance) of the vehicle 10 is performed automatically. The driver assistance system 400 thus assumes vehicle guidance. To this end, the driver assistance system 400 controls the steering system 26 and optionally the drive system 20, the transmission 22, and the service brake 24 via intermediate units (not shown).

[0075] To plan and implement automated driving, driver assistance system 400 receives environmental information from an environmental sensor system that monitors the vehicle's surroundings. In particular, vehicle 10 may include at least one environmental sensor 12 configured to record environmental data indicating the vehicle's surroundings. The at least one environmental sensor 12 may, for example, include one or more LiDAR systems, one or more radar systems, one or more ultrasonic sensors, and / or one or more cameras.

[0076] In some embodiments, the driver assistance system 400 includes an actuating element for a direction indicator, wherein the actuating element can be configured to automatically perform the lane change when actuated or triggered by a driver. The actuating element can be a turn signal lever and have a multiple function, namely activating the direction indicator and triggering the lane change. In other embodiments, the driver assistance system 400 can perform the lane change independently without any driver intervention.

[0077] However, the embodiments of the present disclosure are not limited to automated driving. In alternative embodiments, the driver assistance system may output driver instructions regarding lane changes using at least one output device when the vehicle is manually driven. The driver instructions may provide the driver with guidance regarding lane changes, such as whether they are possible, impossible, safe, dangerous, advantageous, etc. For example, the driver assistance system 400 may suggest the lane change if the lane change algorithm determines that it is favorable or advantageous.

[0078] The at least one output device can comprise at least one display device and / or at least one loudspeaker. The at least one display device can comprise a display, in particular an LCD display, a plasma display or an OLED display. Additionally or alternatively, the at least one display device can comprise a projection device that is configured to display information directly in the driver's field of vision, in particular to project it onto a windshield. In some embodiments, the at least one display device can be a central information output device of an infotainment system, such as a head unit or a pillar-to-pillar display. Preferably, the at least one output device is permanently installed in the vehicle.

[0079] Although the invention has been illustrated and explained in detail by means of preferred embodiments, the invention is not limited by the disclosed examples, and other variations may be derived therefrom by those skilled in the art without departing from the scope of the invention. It is therefore clear that a multitude of possible variations exist. It is also clear that the embodiments mentioned by way of example are truly only examples and should not be construed as limiting the scope, possible applications, or configuration of the invention in any way.Rather, the preceding description and the description of the figures enable the person skilled in the art to implement the exemplary embodiments in concrete terms, whereby the person skilled in the art, with knowledge of the disclosed inventive concept, can make various changes, for example with regard to the function or the arrangement of individual elements mentioned in an exemplary embodiment, without departing from the scope of protection defined by the claims and their legal equivalents, such as further explanations in the description.

Claims

Patent claims 1. A method (100) for providing lane change assistance for vehicles (10), comprising: Providing (110) travel data of a vehicle (10, FF), wherein the travel data relate to a first travel situation of the vehicle (10, FF); Carrying out (120) a simulation of a second driving situation based on the driving data of the first driving situation to generate simulation data, wherein the first driving situation comprises at least one lane change and the second driving situation does not comprise a lane change, or wherein the second driving situation comprises at least one lane change and the first driving situation does not comprise a lane change; and Training (130) a lane change algorithm based on the driving data and / or the simulation data.

2. The method (100) according to claim 1, wherein performing (120) the simulation of the second driving situation comprises determining a driving behavior of the vehicle and determining a driving behavior of at least one other vehicle.

3. The method (100) according to claim 1 or 2, further comprising: Performing a comparison of the first driving situation and the second driving situation; and Determine, based on the comparison, whether the at least one lane change is favorable or unfavorable.

4. The method (100) according to claim 3, wherein the comparison is carried out with respect to the first driving situation and the second driving situation based on at least one comparison criterion, wherein the at least one comparison criterion comprises: a travel time difference; and / or a speed difference to at least one other vehicle; and / or a distance to at least one other vehicle; and / or a difference in the driver's attention; and / or an energy consumption of the vehicle (10, FF); and / or an acceleration behavior of the vehicle (10, FF) and / or at least one other vehicle.

5. Method (100) according to one of claims 1 to 4, wherein the travel data comprise: position data of the vehicle (10, FF); and / or Dynamic data of the vehicle (10, FF), in particular speed data; and / or Environmental data from an environmental sensor system of the vehicle (10, FF); and / or Operating data of the vehicle (10, FF); and / or Driving maneuver data of the vehicle (10, FF).

6. The method (100) according to any one of claims 1 to 5, wherein the simulation of the second driving situation is carried out based on the driving data of the first driving situation and additional data, wherein the additional data comprises: digital map data; and / or Other vehicle information; and / or dynamic traffic information; and / or environmental information; and / or Transport infrastructure information.

7. The method (100) according to any one of claims 1 to 6, further comprising: Providing the trained lane change algorithm for a vehicle fleet (FF) consisting of a plurality of vehicles (10).

8. Lane change assistance method (300) for a vehicle (10), comprising: Determining (310), using a lane change algorithm trained with the method (100) according to one of claims 1 to 7, whether or not a lane change should be performed in a current driving situation of the vehicle (10); and Outputting (320) a corresponding recommendation to a driver of the vehicle (10) and / or performing an automated lane change if it is determined that a lane change should be performed.

9. Lane change assistance method (300) according to claim 8, further comprising: Determining at least one driving maneuver to be performed based on whether or not the lane change should be performed in the current driving situation of the vehicle (10), in particular wherein the at least one driving maneuver to be performed relates to a driving maneuver other than the lane change; and outputting a corresponding recommendation regarding the at least one driving maneuver to be performed to a driver of the vehicle (10) and / or automatically performing the at least one driving maneuver to be performed.

10. A system (200, 400) comprising: one or more processors; and at least one memory connected to the one or more processors and containing instructions executable by the one or more processors to perform the method (100) according to any one of claims 1 to 7 or the lane change assistance method (300) according to claim 8 or 9.

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