transverse-longitudinal combined trajectory planning for a vehicle

Abstract

Method (400) for determining a transverse-longitudinal trajectory (112) for a driving maneuver of an ego vehicle (100), wherein the ego vehicle (100) travels on an ego driving curve, wherein the method (400) comprises, - Determine (401), at a current time, environmental data relating to an environment of the Ego vehicle (100); - Detect (402), based on the environment data, a set of relevant objects (102, 103, 104) in the environment of the ego vehicle (100); wherein the detection (402) of a relevant object (102, 103, 104) comprises: checking whether, at the current time, an object (103) is located on the ego travel path in the direction of travel in front of the ego vehicle (100); and checking whether, within a predefined time period from the current time, an object (102, 104) which is not located on the ego travel path at the current time can appear on the ego travel path; - Determine (403) a first longitudinal trajectory with respect to a first relevant object (102, 103, 104) from the set of relevant objects (102, 103, 104); and - Determine (404) a first transverse trajectory for the first longitudinal trajectory; and - Determining (405) a first transverse-longitudinal trajectory for the current time as a combination of the first transverse trajectory and the first longitudinal trajectory; where the set of relevant objects (102, 103, 104), in particular only those comprising one or more objects (102, 103, 104) in the vicinity of the Ego vehicle (100), which - are currently located on the ego driving curve in front of the ego vehicle (100) in the direction of travel; or - can appear on the ego driving curve within the predefined period from the current time; and whereby - for determining (403) the first longitudinal trajectory, one or more other relevant objects (102, 103, 104) from the set of relevant objects (102, 103, 104) are disregarded; - for determining (403) the first longitudinal trajectory, it is assumed that the first relevant object (102, 103, 104) is located on the ego lane; and - to determine (404) the first transverse trajectory, one or more other relevant objects (102, 103, 104) from the set of relevant objects (102, 103, 104) are taken into account.

Description

[0001] The invention relates to a method and a corresponding device for determining a trajectory for controlling and / or regulating the lateral / longitudinal guidance of a vehicle during a driving maneuver.

[0002] The realization of partially or highly automated driving operation for vehicles (especially road vehicles) is being pursued both in research and increasingly in the automotive industry. A key aspect of partially or highly automated driving operation is planning the most optimal trajectory possible for the vehicle, thereby avoiding collisions with other road users. Determining such a trajectory (e.g., an evasive maneuver, a following trajectory, and / or a lane-changing trajectory) involves a high level of computational effort, which is typically not possible or only possible to a limited extent by the control units in a vehicle.

[0003] An automatic braking and steering system for a vehicle, described in DE 100 36 276 A1, includes a sensor unit for recording vehicle status parameters, vehicle characteristics, and environmental conditions. Furthermore, a control unit and actuators for adjusting the vehicle brakes and / or steering are provided. To enable automatic evasive maneuvers to be carried out with the greatest possible safety, an alternative route is determined in the event of an obstacle in the vehicle's path. If another obstacle is located along the alternative route, the strategy for determining the alternative route is applied again. If a collision-free alternative route cannot be found, the route with the smallest difference between the remaining braking distance and the remaining distance to the obstacle is selected.

[0004] DE 10 2013 214 225 A1 describes a method for determining a vehicle's evasive trajectory. The evasive trajectory is determined with respect to an obstacle that interferes with a predicted vehicle trajectory. The method includes determining the vehicle's movement. It further includes determining the obstacle's position. In addition, the method includes transforming the vehicle's movement and the obstacle's position into state data relative to a reference trajectory. The reference trajectory corresponds to a straightened version of the predicted vehicle trajectory. Finally, the method includes determining a control variable to influence the vehicle's movement based on the state data, whereby the control variable causes the vehicle to move along an evasive trajectory.

[0005] DE 102 31 556 A1 proposes a method and a device for predicting the motion trajectories of a vehicle to prevent or mitigate the consequences of an impending collision. Only those trajectories are considered for predicting motion trajectories where, as a result of a combination of steering and braking interventions, the forces acting on the vehicle's wheels are within the range corresponding to the maximum force that can be transmitted from the wheel to the road. In particular, in systems that provide automatic braking and / or steering intervention to avoid a collision or reduce the severity of an accident with another object, automatic braking and / or steering intervention occurs depending on the predicted motion trajectories.

[0006] This document addresses the technical challenge of determining the most optimal transverse-longitudinal trajectory for a vehicle with reduced computational effort. A transverse-longitudinal trajectory typically comprises a longitudinal component and a transverse component. Specifically, the computational effort required to determine a transverse-longitudinal trajectory should be reduced to such an extent that trajectory planning can be implemented on the vehicle's control unit.

[0007] The problem is solved by the independent claims. Advantageous embodiments are described, among other things, in the dependent claims.

[0008] According to one aspect, a method for determining a transverse-longitudinal trajectory for a driving maneuver of an ego vehicle (in particular, a road vehicle) is described. The ego vehicle travels along an ego driving curve (e.g., an ego lane of a roadway, where the roadway may have multiple lanes). The ego driving curve can generally be a reference curve along which the ego vehicle is to be guided. The driving maneuver typically involves the longitudinal and / or lateral guidance of the ego vehicle. The method can, for example, be executed on a control unit of the ego vehicle. The determined transverse-longitudinal trajectory can be used to provide automatic assistance to a driver of the ego vehicle with regard to the longitudinal and / or lateral guidance of the ego vehicle.Furthermore, the determined transverse-longitudinal trajectory can be used to automatically guide the ego vehicle longitudinally and / or laterally. In particular, depending on the determined transverse-longitudinal trajectory, a steering input for an electronic power steering system and / or for the steering of the ego vehicle and / or a deceleration input for the braking system of the ego vehicle and / or a input for the propulsion of the ego vehicle can be determined and, if necessary, controlled.

[0009] The process involves determining, at a given moment, environmental data relating to the ego-vehicle's surroundings. This environmental data can be acquired by one or more sensors on the ego-vehicle. The surroundings can be located in front of the ego-vehicle in the direction of travel and, if necessary, to the sides.

[0010] The process further includes detecting, based on environmental data, a set of relevant objects in the vicinity of the ego-vehicle. Examples of such objects are other moving road users (e.g., other vehicles, pedestrians, cyclists, etc.) and / or stationary obstacles. The set of relevant objects typically comprises or corresponds to those objects in the ego-vehicle's environment that are relevant for guiding the ego-vehicle along its path (especially within its lane) at the current time, or that could become relevant within a predefined time period (e.g., 5 seconds or less) from the current time. The set of relevant objects may therefore (if necessary, only) include those objects in the ego-vehicle's environment that are relevant, or could become relevant, for planning a purely longitudinal trajectory at the current time.Other objects in the vicinity of the Ego vehicle can be ignored.

[0011] Detecting a relevant object can, for this purpose, involve checking whether an object is located in front of the ego vehicle in the direction of travel at the current time on the ego's travel path (specifically, on the ego's lane, i.e., the current lane of the ego vehicle). If so, this object can be considered a relevant object. Detecting a relevant object can further involve checking whether, within a predefined time period from the current time, an object that is not typically on the ego's travel path at the current time can appear on the ego's travel path (e.g., by changing lanes). If this occurs, such an object can be considered a relevant object. To detect such an object, its movement in the vicinity of the ego vehicle can be predicted.

[0012] The set of relevant objects can therefore only include the one or more objects in the vicinity of the ego vehicle that are located in front of the ego vehicle in the direction of travel at the current time, or that may appear on the ego vehicle's travel curve within the predefined period from the current time.

[0013] The procedure further includes determining a first longitudinal trajectory with respect to a first relevant object from the set of relevant objects. Furthermore, the procedure includes determining a first transverse trajectory for the first longitudinal trajectory. In particular, a first transverse trajectory can be determined under the assumption that the ego vehicle travels longitudinally along the first longitudinal trajectory. A first transverse-longitudinal trajectory for the current time can then be determined as a combination of the first transverse trajectory and the first longitudinal trajectory, specifically as a superposition of the first transverse trajectory with the first longitudinal trajectory.

[0014] By identifying one or more relevant objects that are important for the longitudinal guidance of the ego vehicle, the effort required to determine longitudinal trajectories can be reduced. In particular, the determination of longitudinal trajectories can be limited to these one or more relevant objects. This reduces the overall effort required to determine a combined transverse-longitudinal trajectory.

[0015] To determine the first longitudinal trajectory, one or more other relevant objects from the set of relevant objects are disregarded. In other words, the first longitudinal trajectory is determined as if the one or more other relevant objects from the set of relevant objects did not exist. This can be done analogously for the longitudinal trajectories of other relevant objects from the set of relevant objects. This simplifies the determination of a longitudinal trajectory.

[0016] Furthermore, to determine the first longitudinal trajectory, it is assumed that the first relevant object is already on the ego's travel path, even if the first relevant object is not on the ego's travel path at the current time. In other words, it is assumed that the first relevant object will appear on the ego's travel path within the predefined time period. The first longitudinal trajectory is then determined for this case.

[0017] To determine the first lateral trajectory, the one or more other relevant objects from the set of relevant objects are taken into account. In particular, a first lateral trajectory can be determined that does not collide with the one or more other relevant objects from the set of relevant objects (and also not with other objects in the vicinity of the ego vehicle).

[0018] In this way, a collision-free, combined transverse-longitudinal trajectory can be determined with reduced computational effort.

[0019] It is typically sufficient to determine at most one longitudinal trajectory for each of the relevant objects from the set of relevant objects. Furthermore, it is typically sufficient to determine at most one transverse trajectory for each longitudinal trajectory. Thus, the effort required to determine a combined transverse-longitudinal trajectory can be reduced.

[0020] The procedure can involve determining a set of longitudinal trajectories depending on the set of relevant objects. Specifically, for each relevant object, one longitudinal trajectory (at most or exactly one) can be determined. Furthermore, a corresponding set of transverse trajectories can be determined (i.e., exactly one transverse trajectory for each longitudinal trajectory). Additionally, a set of transverse-longitudinal trajectories can be determined as combinations of longitudinal and transverse trajectories. The first transverse-longitudinal trajectory can then be selected from this set.

[0021] For the selection of an (optimal) first transverse-longitudinal trajectory, a set of values ​​of a longitudinal selection measure (e.g. J) can be used. längs ) for the corresponding set of longitudinal trajectories. Furthermore, a set of values ​​of a transverse selection measure (e.g., J) can be determined. quer) for the corresponding set of transverse trajectories. A set of values ​​for a combined longitudinal-transverse selection measure for the set of transverse-longitudinal trajectories can then be determined based on the set of values ​​of the longitudinal selection measure and on the set of values ​​of the transverse selection measure (e.g., as a weighted average of a value of the longitudinal selection measure and a corresponding value of the transverse selection measure). The first transverse-longitudinal trajectory can then be selected from the set of transverse-longitudinal trajectories depending on the set of values ​​of the combined longitudinal-transverse selection measure (e.g., as the transverse-longitudinal trajectory with the optimal value of the combined longitudinal-transverse selection measure).

[0022] The set of longitudinal trajectories can also include a longitudinal trajectory for the ego vehicle traveling at a constant speed. This longitudinal trajectory can be used as a driving maneuver, particularly in the case of a (planned) lane change.

[0023] Determining a longitudinal or lateral trajectory for a driving maneuver can involve determining initial values ​​for a multitude of state variables of the ego-vehicle at an initial point in time of the longitudinal or lateral trajectory. These numerous state variables can include the ego-vehicle's position, velocity, acceleration, and / or jerk. The initial values ​​can be derived from the ego-vehicle's current state. Furthermore, final values ​​can be determined for the numerous state variables of the vehicle at an end point in time of the longitudinal or lateral trajectory. The final values ​​can be at least partially predetermined by the driving maneuver. In particular, the final values ​​for a longitudinal trajectory can be derived from the position and / or velocity of a relevant object.Furthermore, the longitudinal or transverse trajectory can be determined based on the initial values, the final values, the end time, and on the basis of a model of the dynamics of the ego vehicle.

[0024] Typically, the initial transverse-longitudinal trajectory can be determined for a sequence of time points. In other words, the transverse-longitudinal trajectory for a vehicle's maneuver can be determined repeatedly (e.g., at intervals of 1 second or less, or 100 ms or less). This is typically achieved by using current environmental data at each time point.

[0025] According to another aspect, a device for determining a combined transverse-longitudinal trajectory for a driving maneuver of an ego-vehicle is described, wherein the ego-vehicle travels on an ego-trajectory (in particular, on an ego-lane of a roadway). The device is configured to determine environmental data relating to the ego-vehicle's surroundings at a given time. Furthermore, the device is configured to detect a set of relevant objects in the ego-vehicle's surroundings based on this environmental data by checking whether an object is located in front of the ego-vehicle on the ego-trajectory in the direction of travel at the given time; and by checking whether an object can appear on the ego-trajectory within a predefined time period from the given time. The device is further configured to determine a first longitudinal trajectory with respect to a first relevant object from the set of relevant objects.Furthermore, the device is configured to determine a first transverse trajectory for the first longitudinal trajectory. Additionally, the device is configured to determine a first transverse-longitudinal trajectory for the current time as a combination of the first transverse trajectory and the first longitudinal trajectory.

[0026] According to another aspect, a vehicle (in particular a road motor vehicle such as a passenger car, a truck or a motorcycle) is described which includes the device described in this document for determining a transverse-longitudinal trajectory for a driving maneuver of the vehicle.

[0027] Another aspect described is a software (SW) program. The SW program can be configured to run on a processor (e.g., on a vehicle's control unit) and thereby execute the procedure described in this document.

[0028] Another aspect describes a storage medium. This storage medium can include a software program configured to run on a processor and thereby execute the procedure described in this document.

[0029] It should be noted that the methods, devices, and systems described in this document can be used both alone and in combination with other methods, devices, and systems described in this document. Furthermore, any aspect of the methods, devices, and systems described in this document can be combined with one another in a variety of ways. In particular, the features of the claims can be combined with one another in a variety of ways.

[0030] The invention will now be described in more detail using exemplary embodiments. Fig. 1 an exemplary traffic situation that requires the planning of a trajectory to carry out a driving maneuver; Fig. 2. A flowchart of an exemplary procedure for determining a trajectory; Fig. 3 exemplary coordinates for trajectory planning; and Fig. 4 a flowchart of an exemplary procedure for determining a combined transverse-longitudinal trajectory for a vehicle.

[0031] As stated at the outset, this document addresses the technical task of determining a combined transverse-longitudinal trajectory for a vehicle (also referred to as an ego-vehicle) with reduced computational effort. In this context, it shows Fig. 1 An exemplary traffic situation. The ego vehicle 100 is traveling on a multi-lane roadway 101. A vehicle 103 in the same lane of roadway 101 ahead of the ego vehicle 100 (i.e., a vehicle 103 in the ego lane) may be traveling at a relatively low speed. The ego vehicle 100 then has the option, for example, to remain in the ego lane and decelerate according to a trajectory 112, or to perform an overtaking maneuver and change lanes along a trajectory 112 to overtake vehicle 102. A collision with other vehicles 102, 104 must be avoided.

[0032] To carry out the in Fig. In the maneuver shown in Figure 1, a control unit of the ego vehicle 100 can determine a trajectory 112 that satisfies one or more boundary conditions. Vehicle dynamics aspects can be taken into account when determining a trajectory 112. In particular, a trajectory 112 that can realistically be driven by the vehicle 100 can be determined depending on one or more vehicle parameters and / or depending on the current driving situation. A curvature that the vehicle 100 can execute can be considered. Further examples of vehicle parameters that can be considered are acceleration or deceleration of the vehicle 100 (achievable in the current driving situation).

[0033] Furthermore, a trajectory 112 is typically determined such that a collision with the detected objects 102, 103, 104 in the vicinity of the ego vehicle 100 can be avoided. For example, a collision probability can be determined for a multitude of possible trajectories 112, and the possible trajectory 112 with the lowest collision probability can be selected as the trajectory 112 with which the driving maneuver is carried out.

[0034] The trajectory 112 thus determined can then be transmitted to one or more controllers for the lateral / longitudinal guidance of the vehicle 100. In particular, a path guidance controller can be used to ensure that the vehicle 100 travels along the determined trajectory 112. Furthermore, a vehicle guidance controller can ensure that the necessary braking / acceleration / steering torques are applied.

[0035] Fig. Figure 2 shows a flowchart of an exemplary method 200 for determining a trajectory (e.g., a longitudinal trajectory for longitudinal guidance or a transverse trajectory for lateral guidance) for a vehicle 100. The determination of a trajectory is preferably carried out in a straightened coordinate system, relative to a road alignment. The method 200 can therefore include the step of transforming state data or values ​​of state variables of the vehicle 100 (such as the position of the vehicle 100, a yaw angle of the vehicle 100, and / or a steering angle of the vehicle 100) from a Cartesian coordinate system into a (straightened) Frenet coordinate system.

[0036] The straightening is exemplified in Fig. Figure 3 illustrates this. For the straightening process, measurement signals regarding the state of vehicle 100 are transformed into a lane coordinate system. The trajectory planning itself therefore does not take place in a Cartesian coordinate system 301, but in a Frenet coordinate system. The Frenet coordinate system is described with respect to a reference curve 300 (e.g., the center of a lane). The vehicle position is thus described by the variables s(t) 303 in the longitudinal direction and d(t) 302 in the lateral direction. ṡ(t) and d(t) describe the longitudinal and lateral velocities, and s̈(t) and d̈(t) describe the longitudinal and lateral accelerations.

[0037] Both the vehicle's own motion and the other road users or objects to be considered can be taken into account in the Frenet coordinate system. Visually, this transformation corresponds to the straightening of the coordinate system 301 and thus allows the separate optimization of the longitudinal and lateral motion of the vehicle 100.

[0038] The lateral and longitudinal motion of a vehicle 100 can be described as an optimal control problem with output s(t) = x1(t) (in the case of longitudinal planning) or d(t) = x1(t) (in the case of lateral planning) of an integrator system (i.e., a model of the dynamics of a vehicle 100). Here, x1(t) is a first state variable of the vehicle 100, which describes the position of the vehicle 100 (in the longitudinal or lateral direction). The jerk can serve as the input of the integrator system. x1(3)(t) (t) (i.e. the 3 te Derivative of the state variable x1(t)) or the derivative of the jerk x1(4)(t) (i.e., the 4te The derivative of the state variable x1(t)) is defined.

[0039] An example integrator system can be defined as follows: x˙=[0100001000010000]x+

[0001] u where the input variable u is the derivative of the jerk x1(4)(t) (t) corresponds to the state of a vehicle100 at a specific time t. The state of a vehicle100 at a specific time t can be represented by the state vector x. T can be described as [x1, x2, x3, x4] where x2(t) = ẋ1(t), x3(t) = ẋ2(t) and x4(t) = ẋ3(t).

[0040] It can be shown that the state vector x(t) is given by x(t)=[1tt2t3012t3t20026t0006]︸=:M1(t)c0123+[t4t5t6t74t35t46t57t612t220t330t442t524t60t2120t3210t4]︸=:M2(t)c4567

[0041] The above equations describe a 7th order polynomial with respect to the spatial course x1 (t), i.e. the resulting longitudinal or transverse trajectory can be described by a 7th order polynomial.

[0042] To solve the optimization problem based on a 7th order polynomial, the following performance functional (also called a selection measure) can be used: J=12∫0tf(x(x)(t))2dt+k1(xref−x1)2+k2tf

[0043] The parameters c 0123 T = [c0, c1, c2, c3] are calculated from the initial conditions x(0) = x0 of a trajectory at time t = 0 as c0123=M1−1(0)x0

[0044] The parameters c 4567 T = [c4, c5, c6, c7] are calculated from the final conditions x(t f ) of the trajectory at time t = t f as c4567=M2−1(tf)(x(tf)−M1(tf)c0123)

[0045] The end conditions can be specified, as in the formula above. Alternatively, a reference curve can be described by x. ref = [x 1,ref , x 2,ref , x 3,ref , x 4,ref ] TThe optimization goal in this case is to get as close as possible to this reference curve. In this case, the parameters c 4567 T as follows: c4567=M3(tf)−1(xref−M1(tf)c0123) with M3(tf)=M2(tf)−(0005040k2000000000000).

[0046] The optimization problem now consists of determining both the end time or the end point t. f as well as, if applicable, the final state x(t f to determine the optimal trajectory. In particular, the optimization problem typically aims to determine the final time t. f and the position of vehicle 100 at the end time t f , i.e. x1 (t f ), or the speed of the vehicle 100 at the final time t f , dh ẋ1 (t f ). will be determined.

[0047] To calculate a transverse trajectory, a target area d can be used as the desired endpoint of a trajectory.ziel a specified range, for example, indicating an area on an adjacent lane (as in Fig. 1 shown). This target area can, for example, be the desired final position of the final state x(t). f ) be determined, with x1 (t f ) = d ziel .

[0048] The following function can then be used as a lateral selection parameter or as a lateral quality parameter for determining a trajectory for the lateral guidance of the vehicle 100: Jquer=12∫0tf(d(4)(t))2dt+kq1(dtarget−d(tf))2+kq2tf

[0049] The first expression evaluates the development of the derivative of the jerk along trajectory 112. The second expression evaluates the deviation of the final position d(t). f ) from the target position d ziel Furthermore, the third expression evaluates the time length of trajectory 112. This is determined using the weighting factors k. q1 and k q2 The characteristics of the trajectory can be weighted.

[0050] Longitudinal planning can be carried out in a similar manner. For longitudinal planning, the following longitudinal selection dimension or longitudinal quality dimension can be used, for example. Jla¨ngs=12∫0tf(s(4)(t))2dt+kl1(sziel−s(tf))2+kl2tf, especially if a specific target position s ziel to be achieved. Alternatively, the following longitudinal selection dimension or longitudinal quality dimension can be used. Jla¨ngs=12∫0tf(s(4)(t))2dt+kl1(s˙ziel−s˙(tf))2+kl2tf, especially when a certain target speed ṡ ziel to be achieved.

[0051] To determine an optimal longitudinal or transverse trajectory, the respective selection parameter J can be used for different values ​​of t. f and / or for different final states x(t f The above formulas can be used for this calculation. This results in a curve for the selection measure J, where a minimum value of the selection measure J represents the optimal value for time t.f and / or for the final state x(t f ). In a further step, one or more constraints can then be taken into account.

[0052] The constraints can therefore be considered after the optimization process. To do this, the best trajectory in terms of the cost functional J (i.e., the selection measure) can be chosen and checked for compliance with the constraints. If the constraints are met, the trajectory is implemented. Otherwise, the next best trajectory is selected and checked for compliance with the constraints. This procedure is repeated until an optimal solution is found that satisfies the constraints.

[0053] Constraints such as actuator and vehicle dynamics limitations can be considered. Furthermore, collision avoidance with predicted object trajectories of other objects / vehicles 102, 103, 104 can be taken into account.

[0054] The in Fig. The two illustrated methods 200 for determining a trajectory for the longitudinal and / or lateral guidance of a vehicle 100 thus comprise the determination 201 of initial values ​​or initial conditions x(0) = x0 for a plurality of state variables x of the vehicle 100. The plurality of state variables includes a position x1(t) of the vehicle 100, a velocity ẋ1(t) of the vehicle 100, an acceleration ẍ1(t) of the vehicle 100 and / or a jerk. x1(3) (t) of the vehicle 100. This gives x1(3) (t) the third derivative of the position x1(t) of vehicle 100.

[0055] Procedure 200 also includes determining 202 final values ​​x(t). f ) at a final time t ffor the multitude of state variables x of the vehicle 100. In addition, the procedure 200 includes the determination 203 of a longitudinal trajectory or a transverse trajectory based on the initial values ​​x(0) = x0, the final values ​​x(t) f ), the end time t f and based on a model of the vehicle dynamics 100.

[0056] To determine an optimal longitudinal or transverse trajectory (in the sense of a longitudinal or transverse selection measure J), ​​the values ​​of the selection measure J can be used for trajectories with different end times t. f and / or with different final values ​​x(t f The number of state variables can be determined. The (state) trajectory that optimizes the selection measure J can then be selected. Furthermore, it can be checked whether one or more constraints are met (as explained above).

[0057] The determined longitudinal or transverse trajectory can then be transformed from the Frenet coordinate system back into a Cartesian coordinate system. Furthermore, the determined longitudinal or transverse trajectory can be used to guide the vehicle (e.g., for an evasive maneuver or a parking maneuver).

[0058] To determine an optimal transverse-longitudinal trajectory 112, which can be used for both the lateral and longitudinal guidance of the vehicle 100, a large number of longitudinal trajectories (for longitudinal guidance) and a corresponding large number of values ​​of a longitudinal selection parameter J can first be determined. längs can be determined. Subsequently, for each longitudinal trajectory, a multitude of transverse trajectories and a corresponding multitude of values ​​of a transverse selection measure J can be determined. quer can be determined by combining the values ​​of the selection measures f. längs and J querValues ​​of a combined transverse-longitudinal selection measure can be determined for combined transverse-longitudinal trajectory planning. For example, a weighted average of the selection measure values ​​J can be calculated. längs and J quer The combination of longitudinal trajectory and transverse trajectory with the lowest value of the combined transverse-longitudinal selection parameter can then be selected as the optimal combined transverse-longitudinal trajectory 112.

[0059] Determining 100 longitudinal trajectories and 100 transverse trajectories each results in 10,000 possible combinations. This entails a substantial computational effort for determining a combined transverse-longitudinal trajectory. This computational effort cannot typically be achieved with a single vehicle control unit.

[0060] To reduce the computational effort, a first step can be to determine a reduced number of longitudinal maneuvers and a correspondingly reduced number of longitudinal trajectories. In particular, only those longitudinal maneuvers can be selected that are realistic to consider given the current environmental situation of the Ego vehicle 100.

[0061] The Ego-Vehicle 100 can include one or more environmental sensors (e.g., a camera, a radar sensor, a LiDAR sensor, an ultrasonic sensor, etc.) configured to acquire environmental data relating to the Ego-Vehicle 100's surroundings. Based on this environmental data, objects 102, 103, and 104 in the Ego-Vehicle 100's environment can be detected. Specifically, objects 102, 103, and 104 in the Ego-Vehicle 100's environment that are relevant for the longitudinal guidance of the Ego-Vehicle 100 (e.g., because object 103 is located on the Ego-Vehicle 100's path) or could become relevant (e.g., because object 102 or 104, as described in [reference to relevant information]) can be detected. Fig. (1, indicated by the dashed arrows, could switch to the ego lane of the ego vehicle 100). Thus, a set of relevant objects 102, 103, 104 can be determined.

[0062] Furthermore, each relevant object 102, 103, 104 can then be considered in isolation, without the other objects 102, 103, 104 in the vicinity of the ego vehicle 100. In particular, a longitudinal trajectory can be determined for each of the relevant objects 102, 103, 104 (possibly exactly) (e.g., by using the procedure 200 described above). For the determination of a longitudinal trajectory, it can be assumed that the object 102, 104, on which the longitudinal trajectory is determined, is already located on the ego lane of the ego vehicle 100. In particular, a position on the ego lane and / or a speed on the ego lane can be determined for each relevant object 102, 103, 104. From this information, the final state x(t) can be determined for each relevant object 102, 103, 104. f) for a longitudinal trajectory, e.g. to implement a following journey to a vehicle 102, 103, 104 and / or to implement a braking maneuver in front of a stationary obstacle.

[0063] Thus, exactly one longitudinal trajectory can be determined for each detected, relevant object 102, 103, 104. In particular, an optimal braking trajectory can be determined for each detected, relevant object 102, 103, 104. Furthermore, (if necessary, exactly) another longitudinal trajectory can be determined for the case of the ego vehicle 100 traveling at a constant speed.

[0064] In summary, this results in a significantly limited set of longitudinal trajectories. This set of longitudinal trajectories can be further reduced by checking whether the respective longitudinal trajectories fulfill the required constraints (such as drivability by the Ego-Vehicle 100, feasibility of the required deceleration, and / or collision-free operation). Longitudinal trajectories that do not fulfill the required constraints can be disregarded when determining a transverse-longitudinal trajectory 112.

[0065] For each longitudinal trajectory, exactly one (optimal) transverse trajectory can then be determined from the (remaining) set of longitudinal trajectories. The procedure described in this document 200 can be used for this purpose. In particular, for a given longitudinal trajectory, the transverse trajectory can be found that meets a selection criterion J. querminimizes the required constraints (such as collision-free operation and drivability). When determining the lateral trajectory (and especially when checking the constraints), all detected objects 102, 103, 104 in the vicinity of the ego vehicle 100 are typically taken into account. Furthermore, when determining a lateral trajectory for a specific longitudinal trajectory, it is typically assumed that the vehicle 100 is moving longitudinally according to the specified longitudinal trajectory.

[0066] For the set of longitudinal trajectories, values ​​of the longitudinal selection measure J can be used. längs to be determined, and for the corresponding set of transverse trajectories determined for this purpose, values ​​of the transverse selection measure J can be assigned. querThese values ​​can be determined. From this, values ​​of an overall or transverse-longitudinal selection measure can be determined (e.g., by weighted means), and the combined transverse-longitudinal trajectory that optimizes the overall selection measure can be selected.

[0067] Fig. Figure 4 shows a flowchart of an exemplary procedure 400 for determining a transverse-longitudinal trajectory 112 for a driving maneuver of an ego-vehicle 100. The ego-vehicle 100 travels on an ego-trajectory, specifically on an ego-lane of a roadway 101. The roadway 101 may include one or more additional lanes on which other vehicles, as exemplary objects, may be located in the vicinity of the ego-vehicle 100.

[0068] Procedure 400 comprises determining, at a current time, environmental data relating to the environment of the ego-vehicle 100. Furthermore, procedure 400 comprises detecting, based on the environmental data, a set of relevant objects 102, 103, 104 in the environment of the ego-vehicle 100. The detection 402 of a relevant object 102, 103, 104 includes checking whether, at the current time, an object 103 (e.g., another vehicle or other obstacle) is located on the ego-vehicle's travel path in the direction of travel in front of the ego-vehicle 100. Furthermore, the detection 402 of a relevant object 102, 103, 104 includes checking whether, within a predefined period from the current time, an object 102, 104 (which is typically not on the ego driving curve at the current time) can appear on the ego driving curve (such as a vehicle changing lanes).

[0069] Procedure 400 further comprises determining 403 a first longitudinal trajectory with respect to a first relevant object 102, 103, 104 from the set of relevant objects 102, 103, 104 (e.g., using procedure 200). In particular, the first longitudinal trajectory can be determined in isolation for the first relevant object 102, 103, 104, without considering the other relevant objects from the set of relevant objects 102, 103, 104. These other objects can be assumed to be non-existent when determining the first longitudinal trajectory.

[0070] Furthermore, procedure 400 includes determining 404 a first transverse trajectory for the first longitudinal trajectory (e.g., using procedure 200). When determining the first transverse trajectory, all objects in the vicinity of the ego-vehicle 100 (in particular, all relevant objects 102, 103, 104) can be taken into account. Procedure 400 also includes determining 405 a first transverse-longitudinal trajectory for the current time as a combination of the first transverse trajectory and the first longitudinal trajectory. To determine the first transverse-longitudinal trajectory, the first longitudinal trajectory can be superimposed on the first transverse trajectory.

[0071] In summary, the computational effort for determining a transverse-longitudinal trajectory 112 for a driving maneuver can be substantially reduced without substantial losses in terms of the optimality of the determined transverse-longitudinal trajectory 112.

[0072] The present invention is not limited to the embodiments shown. In particular, it should be noted that the description and the figures are intended only to illustrate the principle of the proposed methods, devices, and systems.

Claims

[1] Method (400) for determining a transverse-longitudinal trajectory (112) for a driving maneuver of an ego vehicle (100), wherein the ego vehicle (100) travels on an ego driving curve, the method (400) comprising, - Determine (401), at a current time, environmental data relating to an environment of the Ego vehicle (100); - Detect (402), based on the environment data, a set of relevant objects (102, 103, 104) in the environment of the ego vehicle (100); wherein the detection (402) of a relevant object (102, 103, 104) comprises: checking whether, at the current time, an object (103) is located on the ego travel path in the direction of travel in front of the ego vehicle (100); and checking whether, within a predefined time period from the current time, an object (102, 104) which is not located on the ego travel path at the current time can appear on the ego travel path; - Determine (403) a first longitudinal trajectory with respect to a first relevant object (102, 103, 104) from the set of relevant objects (102, 103, 104); and - Determine (404) a first transverse trajectory for the first longitudinal trajectory; and - Determining (405) a first transverse-longitudinal trajectory for the current time as a combination of the first transverse trajectory and the first longitudinal trajectory; where the set of relevant objects (102, 103, 104), in particular only those comprising one or more objects (102, 103, 104) in the vicinity of the Ego vehicle (100), which - are currently located on the ego driving curve in front of the ego vehicle (100) in the direction of travel; or - can appear on the ego driving curve within the predefined period from the current time; and whereby - for determining (403) the first longitudinal trajectory, one or more other relevant objects (102, 103, 104) from the set of relevant objects (102, 103, 104) are disregarded; - for determining (403) the first longitudinal trajectory, it is assumed that the first relevant object (102, 103, 104) is located on the ego lane; and - to determine (404) the first transverse trajectory, one or more other relevant objects (102, 103, 104) from the set of relevant objects (102, 103, 104) are taken into account. [2] Method (400) according to claim 1, wherein - for each of the relevant objects (102, 103, 104) from the set of relevant objects (102, 103, 104), at most one longitudinal trajectory is determined; and - for each longitudinal trajectory, a maximum of one transverse trajectory is determined. [3] Method (400) according to any one of the preceding claims, further comprising, - Determining a set of longitudinal trajectories depending on the set of relevant objects (102, 103, 104); - Determining a set of transverse trajectories corresponding to the set of longitudinal trajectories; - Determine as respective combinations of longitudinal and transverse trajectories of a set of transverse-longitudinal trajectories; and - Selecting the first transverse-longitudinal trajectory from the set of transverse-longitudinal trajectories. [4] Method (400) according to claim 3, further comprising, - Determining a set of values ​​of a longitudinal selection measure for the corresponding set of longitudinal trajectories; - Determine a set of values ​​of a transverse selection measure for the corresponding set of transverse trajectories; - Determining a set of values ​​of a combined longitudinal-transverse selection measure for the set of transverse-longitudinal trajectories based on the set of values ​​of the longitudinal selection measure and on the set of values ​​of the transverse selection measure; and - Selection of the first transverse-longitudinal trajectory from the set of transverse-longitudinal trajectories depending on the set of values ​​of the combined longitudinal-transverse selection measure. [5] Method (400) according to one of claims 3 to 4, wherein the set of longitudinal trajectories also includes a longitudinal trajectory for a journey of the ego vehicle (100) at constant speed. [6] Method (400) according to any one of the preceding claims, comprising determining a longitudinal trajectory and / or a transverse trajectory, - Determining (201) initial values ​​for a plurality of state variables of the ego vehicle (100); wherein the plurality of state variables is a position (x1(t)) of the ego vehicle (100), a velocity (ẋ1(t)) of the ego vehicle (100), an acceleration (ẍ1(t)) of the ego vehicle (100) and / or a jerk (x1(3)(t)) of the Ego vehicle (100) includes; - Determining (202) final values ​​at a final time for the multitude of state variables of the ego vehicle (100); and - Determining (203) a longitudinal trajectory and / or a transverse trajectory based on the initial values, the final values, the final time and based on a model of the dynamics of the ego vehicle (100). [7] Method (400) according to one of the preceding claims, further comprising determining a steering input for an auxiliary steering system of the Ego vehicle (100) and / or a deceleration input for a braking system of the Ego vehicle (100) and / or an acceleration input for a drive system of the Ego vehicle (100) depending on the first transverse-longitudinal trajectory. [8] Device for determining a transverse-longitudinal trajectory (112) for a driving maneuver of an ego vehicle (100), wherein the ego vehicle (100) travels on an ego driving curve, wherein the device is configured, - to determine environmental data relating to the environment of the Ego vehicle (100) at a current point in time; - based on the environmental data, to detect a set of relevant objects (102, 103, 104) in the vicinity of the ego vehicle (100) by checking whether an object (103) is located on the ego's travel path in the direction of travel in front of the ego vehicle (100) at the current time; and by checking whether an object (102, 104) can appear on the ego's travel path within a predefined period from the current time; - to determine a first longitudinal trajectory with respect to a first relevant object (102, 103, 104) from the set of relevant objects (102, 103, 104); - to determine a first transverse trajectory for the first longitudinal trajectory; and - to determine a first transverse-longitudinal trajectory for the current time as a combination of the first transverse trajectory and the first longitudinal trajectory; wherein the set of relevant objects (102, 103, 104), in particular only those comprising one or more objects (102, 103, 104) in the vicinity of the Ego vehicle (100), which - are currently located on the ego driving curve in front of the ego vehicle (100) in the direction of travel; or - can appear on the ego driving curve within the predefined period from the current time; and whereby - for determining (403) the first longitudinal trajectory, one or more other relevant objects (102, 103, 104) from the set of relevant objects (102, 103, 104) are disregarded; - for determining (403) the first longitudinal trajectory, it is assumed that the first relevant object (102, 103, 104) is located on the ego lane; and - to determine (404) the first transverse trajectory, one or more other relevant objects (102, 103, 104) from the set of relevant objects (102, 103, 104) are taken into account.

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