Method for determining a target speed of a vehicle

Abstract

The invention relates to a method for determining a target speed of a vehicle, wherein, starting from a position-time trajectory that describes a predicted movement of a vehicle traveling ahead, a solution space defined by an upper time limit and a lower time limit is determined and the target speed is determined within the solution space.

Description

State of the art

[0001] Various methods exist for determining vehicle operating strategies. Known hybrid operating strategies are adapted to hybrid powertrain topologies and essentially consider the battery charging process under the influence of the torque distribution between the combustion engine and the electric motor.

[0002] A sailing assistance function maximizes the duration of the sailing state by estimating how long no propulsive torque will be required from the combustion engine. This is partly achieved using predictive data.

[0003] Driving strategy functions calculate speed trajectories designed to optimize comfort. Fuel efficiency is not taken into account.

[0004] Well-known functions that react to vehicles ahead, such as ACC, use information from the surroundings detection to predict the behavior of the vehicle ahead.

[0005] Since the functions known from the state of the art were each developed specifically for their special application and sometimes influence the same control variable (e.g. target speed), their combination in a vehicle represents a challenge. For example, a sailing assistant would specify the state "sailing" (i.e. essentially decoupling and switching off the internal combustion engine) as the target value, but a cruise control function could simultaneously demand acceleration in order to maintain a preset desired speed.

[0006] Functions that control a target speed depending on a route topology use an optimization algorithm whose solution space is defined as a speed band. However, fixed speed bands are unsuitable for considering non-stationary boundary conditions, such as the speed of a vehicle ahead. Disclosure of the invention

[0007] Since important elements in road traffic, such as vehicles driving ahead, cannot be represented by a speed band, the solution space for a target speed of a vehicle is extended by a temporal dimension according to the invention.

[0008] In the temporal dimension, a t-band is advantageously defined, i.e., a band of functions that assign a (required) time to a distance traveled or a location. The t-band is obtained by integrating a v-band, which is defined by functions that assign a speed to a distance or position. The v-band can be determined using methods known from the state of the art and, in particular, takes into account a route topology.

[0009] Advantageously, a preceding vehicle can be taken into account by limiting the t-band with a predicted spatial-time trajectory of the preceding vehicle. In other words, the t-band can be limited such that the implementation of the target speed of the ego vehicle (i.e., the vehicle whose target speed is determined within the scope of the present invention) cannot lead to a collision with the preceding vehicle. In a particularly advantageous embodiment, the spatial-time trajectory of the preceding vehicle is determined by integrating a predicted speed trajectory of the preceding vehicle. In a further preferred embodiment, the speed trajectory of the preceding vehicle is determined using a combination of sensor data, in particular radar data, and an electronic horizon.The electronic horizon can, for example, take into account that the vehicle in front is subject to a local speed limit or that the vehicle in front is likely to drive at a reduced speed on steep inclines or in tight bends.

[0010] The method according to the invention advantageously comprises the following steps: The speed of a preceding vehicle is predicted by assuming its current acceleration to be constant at the prediction time, based on its current speed. This yields a speed trajectory of the preceding vehicle. By integration, a position-time trajectory of the preceding vehicle is determined from the speed trajectory of the preceding vehicle.

[0011] A solution space is adapted to the current speed of the ego vehicle by choosing a beginning of the speed band (i.e. v-band, i.e. the band between the upper and lower raw speed limit) such that it includes the current speed of the ego vehicle, advantageously in particular such that it corresponds to the current speed of the ego vehicle.

[0012] A lower raw time limit is determined by integration from the upper raw speed limit.

[0013] An upper time limit is determined by integrating the lower speed raw limit.

[0014] Based on the location-time trajectory of the preceding vehicle, the lower time limit is modified, in particular partially raised, in such a way that the lower time limit thus obtained is above the location-time trajectory of the preceding vehicle.

[0015] A solution space is defined from the upper time limit and the lower time limit, which is then passed to an optimizer.

[0016] Based on the solution space, the optimizer determines an optimal target speed, in particular an optimal target speed trajectory of the ego vehicle.

[0017] When determining the target speed or the target speed trajectory, the optimizer takes into account, in particular, fuel consumption, absolute acceleration, a deviation from an average speed, and a deviation from an average acceleration. Furthermore, a predicted travel time and, in the case of a vehicle with a deactivatable internal combustion engine (for example, in the case of a correspondingly configured hybrid vehicle), a number of starts of the internal combustion engine are taken into account. In an advantageous development of the method according to the invention, the optimizer also takes into account a distance to the vehicle in front, for example by using a penalty function that assigns a penalty value to each time difference to the vehicle in front. Ideally, this penalty value is lowest at a time difference of 2 seconds.The form of the penalty function is advantageously chosen so that the optimizer recommends a rapid approach to the vehicle in front, but at the same time avoids driving too close.

[0018] In particular, the method according to the invention can provide that support points for determining the target speed trajectory are determined by first detecting an electronic horizon, which can in particular include raw speed limits, a gradient and / or curve radii. Breakpoints in the resulting array are then determined by determining the points at which rates of change in the array exceed a threshold value. Primary support points can then be defined at the breakpoints thus determined. The areas between the primary support points can then be iteratively filled with secondary support points by adding a further secondary support point to the largest distance between the primary and any already existing secondary support points until a predetermined number of primary and secondary support points is reached.The primary and secondary support points then combine to form the support points. Finally, interpolation can be performed between the support points, for example to determine the optimized target speed trajectory. This advantageous aspect of the method according to the invention offers, in particular, optimal determination of the target speed trajectory while simultaneously conserving computing resources. In particular, the number of support points can be adapted to the available computing resources. A particularly advantageous feature is that the method used to determine the support points ensures that the method always offers good performance, since all relevant areas of the array are provided with support points.

[0019] An embodiment of the present invention is explained in more detail below with reference to the accompanying drawings. Short description of the drawings Fig. 1 shows a sketchy signal flow to illustrate an embodiment of the method according to the invention; Fig. 2 a schematic representation of an upper and lower speed limit; Fig. 3 a schematic representation of an upper and lower time limit according to one aspect of the method according to the invention; Fig. 4 shows a schematic sequence of an aspect of an embodiment of the method according to the invention. Embodiments of the invention

[0020] Fig. 1 shows a schematic signal flow to illustrate an embodiment of the method according to the invention. A powertrain management module (10) provides a current vehicle state and transmits it to a solution space module (13) and an optimization module (14). A horizon module (11) provides an electronic horizon and transmits it to the solution space module (13). The electronic horizon includes, in particular, a gradient of a road section ahead as well as an upper and a lower speed limit. Optionally, the electronic horizon can additionally include a curve radius. An environment module (12) provides information about a vehicle traveling ahead and transmits it to the solution space module (13) and an implementation module (16). The information about the vehicle traveling ahead can include, in particular, its speed and the distance from the ego vehicle.The solution space module (13) processes the information provided to it and derives an upper and a lower speed limit and / or an upper and lower time limit therefrom. It transmits these, along with the gradient of the upcoming route section, to the optimization module (14). A vehicle state estimator (15) estimates the current vehicle state and transmits this to the optimization module (14) and the solution space module (13). The current vehicle state is advantageously taken into account when deriving the upper and lower speed limits, as well as the upper and lower time limits. The optimization module (14) can advantageously comprise a vehicle model. The optimization module (14) determines an optimized target speed, in particular a target speed trajectory for the ego vehicle, and transmits this to the implementation module (16).The implementation module implements the target speed trajectory by appropriately controlling the corresponding actuators of the vehicle, taking into account the information about the vehicle in front, provided by the environment module (12).

[0021] In particular, information about the preceding vehicle can override the implementation of the target speed trajectory for safety reasons, for example, if the preceding vehicle brakes sharply and its deceleration is not reflected quickly enough by the signal chain from the solution space module (13) and the optimization module (14). Alternatively, the implementation module (16) can display the target speed trajectory to a driver of the ego vehicle, who then manually implements the target speed trajectory. This is particularly advantageous if the implementation module does not guarantee direct access to the required actuators.

[0022] Fig. Figure 2 shows a schematic representation of an upper (43) and lower (42) raw speed limit, as can be determined, for example, using methods known from the prior art. A position axis (40) indicates the location of the ego vehicle. A speed axis (41) assigns an upper and a lower raw speed value to each point on the position axis (40), so that a representation of the upper (43) and lower (42) raw speed limits is obtained from all upper and lower raw speed values. The upper and lower raw speed limits define, for example, a speed solution space for an optimization algorithm.

[0023] Fig. 3 shows a schematic representation of an upper (52) and lower (55) time limit according to one aspect of the method according to the invention. A position axis (50) represents the abscissa, a time axis (51) the ordinate. An upper time limit (52) can be obtained, for example, by integrating the lower raw speed limit (42). A lower raw time limit (53) can be obtained by integrating the upper raw speed limit (43). A position-time trajectory of a preceding vehicle (54) assigns to each location a predicted time at which the preceding vehicle will be located at this location. The lower raw time limit (53) intersects the position-time trajectory of the preceding vehicle (54) in the illustrated example, which is why the lower raw time limit (53) is modified to obtain the lower time limit (55).If necessary, the lower time limit (53) is raised so that the lower time limit (55) is always above the position-time trajectory of the preceding vehicle (54). This can advantageously take into account a safety distance to the preceding vehicle, which the ego vehicle should not exceed. The upper time limit (52) and the lower time limit (55) define a solution space for an optimizer.

[0024] Fig. Figure 4 shows a schematic sequence of an aspect of an embodiment of the method according to the invention, in particular the determination of support points. In step 100, an electronic horizon is first acquired, which may include, in particular, raw speed limits, a gradient, and / or curve radii. An array is formed from the raw speed limits, gradients, and / or curve radii. Step 110 is then performed.

[0025] In step 110, breakpoints in the array are determined by determining at which points the array's change rates exceed a threshold. Primary support points can then be defined at the breakpoints thus determined. Step 120 is then performed.

[0026] In step 120, the areas between the primary support points are iteratively filled with secondary support points by adding another secondary support point to the largest distance between the primary and any existing secondary support points, until a predetermined number of primary and secondary support points is reached. The primary and secondary support points then form the support points. Step 130 is then performed.

[0027] In step 130, interpolation is carried out between the support points in order to determine, for example, the optimized target speed trajectory.

[0028] The support points are advantageously used to provide the electronic horizon by a horizon module (11). Alternatively, the support points thus determined are used by the solution space module (13). Alternatively, the support points thus determined are used by the optimization module (14).

[0029] Advantageously, the presented aspects of the method according to the invention are used to operate the ego vehicle. In particular, it is advantageous to operate the ego vehicle based on the determined target speed (trajectory) in such a way that the ego vehicle implements the target speed (trajectory).

Claims

[1] Method for determining a target speed, in particular a target speed trajectory, of a vehicle, characterized by that, starting from a space-time trajectory which describes a predicted movement of a vehicle in front, a solution space which is defined by an upper time limit and a lower time limit is determined and the target speed is determined within the solution space. [2] Method according to claim 1, characterized by that the lower time limit is chosen so that it is always greater than the space-time trajectory of the vehicle in front. [3] Method according to claim 1 or 2, characterized by that the upper and lower time limits are determined by integrating a lower and upper speed limit. [4] Method according to one of claims 1 to 3, characterized by that support points are determined to determine the target speed. [5] Method according to claim 4, characterized by that at least some of the support points are determined at break points in an array. [6] Method according to one of the preceding claims, characterized by that the vehicle is operated based on the determined target speed. [7] Device arranged to carry out the method according to one of claims 1 to 6. [8] Computer program which causes a computing unit to carry out the method according to one of claims 1 to 6 when the computer program is executed by the computing unit. [9] Storage medium on which the computer program according to claim 8 is stored.

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