METHOD FOR DETERMINING A SAFE SPEED AT A FUTURE WAYPOINT

Description

[0001] The invention relates to a method and a device for determining a safe speed at a future waypoint of a moving vehicle. Unless expressly stated otherwise, the terms "maximum friction coefficient" and "coefficient of friction" are used synonymously below.

[0002] In general, the assessment of road conditions is the responsibility of the driver, who must adjust their driving style accordingly. Vehicle control systems such as ESC (Electronic Stability Control) / TCS (Traction Control System) or ABS (Anti-lock Braking System) help the driver stabilize the vehicle at the limit, making it easier to perform their driving task in extreme situations. The effectiveness of such vehicle control systems depends crucially on the maximum coefficient of friction µ (also known as the maximum adhesion coefficient) available at the current point in time. The interaction between tires, surface, and intermediate medium is crucial for this. Wet conditions, snow, and ice significantly reduce the available coefficient of friction between tires and road surface compared to that available on a dry road surface.Sudden changes in friction coefficients, such as those caused by changing environmental conditions, can lead to unstable driving situations and thus increase the risk of accidents. This is particularly dangerous if the driver approaches a curve too quickly due to an incorrect assessment of the available friction coefficient.

[0003] To date, determining a safe cornering speed has only involved considering the road layout based on map data. Furthermore, a constant maximum friction coefficient (often µ = 1) is assumed. Ideally, the calculation would also include a vehicle model that reflects the specific characteristics of the vehicle in question. Furthermore, knowing the maximum friction coefficient could allow the vehicle to be decelerated sufficiently before the curve to ensure it can be negotiated without problems.

[0004] EP 1 870 674 A2 discloses a method for implementing a curve advance warning for motor vehicles. A control unit loads map data from a memory and determines a current position using position-determining means. For a predefined section of road ahead, a curvature of the road is calculated based on the map data. Based on the curvature, a recommended curve speed is calculated and displayed.

[0005] The object of the invention is to provide a method for determining a safe speed at a future waypoint of a vehicle traveling along a route with a known course. A further object of the invention is to provide a corresponding device.

[0006] These objects are achieved by a method according to the features of patent claim 1 and a device according to the features of patent claim 10. Advantageous embodiments emerge from the dependent patent claims.

[0007] A method is proposed for determining a safe speed at a future waypoint of a vehicle traveling along a route with a known course, comprising the following steps: providing at least one piece of route information characterizing the course of the route; providing a first probability distribution of a maximum friction coefficient at the current waypoint and / or at the future waypoint of the vehicle; determining a second probability distribution of a vehicle speed at the future waypoint from the at least one piece of route information and the first probability distribution; and determining the safe speed from the second probability distribution.

[0008] The method according to the invention is based on the consideration of taking into account not only the route ahead of the vehicle, but also potentially changing environmental conditions, which can significantly limit the maximum forces that can be transmitted to the tire. The starting point for this is a continuous or discrete probability distribution of the maximum friction coefficient at the vehicle's current waypoint and / or at the vehicle's future waypoint.

[0009] The method can detect whether the vehicle is moving too fast for the prevailing environmental conditions. If the speed is too high, this can be used to determine whether action is required before reaching the future waypoint. This can be output, for example, in the form of information, a warning, or an automated driving intervention (vehicle deceleration, etc.). In automated vehicles, e.g., those using one or more vehicle assistance systems, the safe speed can be used to calculate a driving strategy, for example, by defining an optimization space within which a speed trajectory is sought that under no circumstances exceeds the safe speed for the future waypoint.

[0010] The safe speed at the future waypoint can be determined by choosing a q-quantile of the second probability distribution. As is known to those skilled in the art, a quantile is a measure of position in statistics. The q-quantile corresponds to the integral from the selected safe speed to infinity over the second probability distribution. This means that the actual speed at which the vehicle can stably pass the future waypoint is greater than or equal to the safe speed with a probability of the selected q-quantile × 100%. The safe speed at the future waypoint can be determined by the equation ∫ v * ∞ P v dv = q S In equation (1), v* represents the safe speed, P(v) the second probability distribution, and qs the selected q-quantile. The q-quantile qs is specified, and the safe speed v* is determined using equation (1).

[0011] Alternatively, the p-quantile of the second probability distribution can be used to determine a safe speed, ie the integral from 0 to the safe speed v*. For the selected p-quantile ps, the following applies: ∫ 0 v * P v dv = p S = 1 − q S

[0012] As the at least one piece of route information, a curve curvature at and / or before the future waypoint of the vehicle can be processed. If the curve curvature is known, the step of determining the second probability distribution can be carried out using the equation a x 2 + κ 2 s ∗ v x 4 − g 2 ∗ μ 2 s = 0 The formula includes a x is the vehicle's longitudinal acceleration, κ is the curve curvature, s is the path, g is the gravitational constant, vx is the vehicle's speed along its longitudinal axis (vehicle longitudinal speed), µ is the coefficient of friction. Equation (2) is based on the assumption that the vehicle can be simplified to a point mass. Of course, more complex vehicle models can also be used to determine the second probability distribution.

[0013] According to a further embodiment, the step of determining the second probability distribution is carried out under the assumption that the vehicle travels the route, in particular the future waypoint, without acceleration. This allows the term in equation (2) a x 2 be neglected, so that a simple conversion of the probability distribution of the friction coefficient µ at the relevant waypoint s into the probability distribution of the vehicle speed v x can be made.

[0014] In particular, a value is chosen as the q-quantile that depends on a vehicle type, a chassis type, or a selected driving mode. The q-quantile characterizes a system that processes the safe speed. Depending on the vehicle type, for example, a sports car, a luxury sedan, an off-road vehicle, etc., the safe speed can be selected differently. If a vehicle has a vehicle assistance system that allows the chassis to be adjusted to different modes, a respective q-quantile can also be defined for different modes, which takes the vehicle's driving characteristics into account.

[0015] The q-quantile is preferably chosen such that the resulting selected safe speed is lower than the true safe speed at the future selected waypoint. This ensures that no dangerous situation arises for the vehicle at the future waypoint.

[0016] According to a further expedient embodiment, a device for determining a safe speed at a future waypoint of a vehicle traveling along a route with a known route is proposed. The device comprises a first means for determining a second probability distribution of a vehicle speed at the future waypoint from at least one piece of route information characterizing the route and a first probability distribution of a maximum friction coefficient at the current waypoint and / or at the future waypoint of the vehicle; and a second means for determining the safe speed from the second probability distribution. The first probability distribution can be determined by a computing unit of the vehicle and made available for further processing to determine the safe speed.

[0017] The device according to the invention has the same advantages as those described above in connection with the method according to the invention.

[0018] The device may comprise further means for carrying out the described method.

[0019] The invention is described in more detail below using an exemplary embodiment in the drawing. In the drawings: Fig. 1 a schematic representation of a program flow chart of the method according to the invention, and Fig. 2 a schematic representation of the procedure for determining a safe speed at a future waypoint of a vehicle.

[0020] Fig. 1 shows the schematic sequence of the method according to the invention for determining a safe speed v* of a vehicle at a future waypoint s* in a flow chart. The future waypoint s* is, for example, a curve towards which the vehicle moving along a (known) route in the vehicle's longitudinal direction is moving. In particular, the apex of this curve can be regarded as the future waypoint s*. Alternatively, the future waypoint s* can be located at a constant distance in front of the vehicle (look-ahead horizon). The data on the route ahead of the vehicle and the next curve ahead of the vehicle can be determined by a computing unit of the vehicle from map data of a navigation system. In a step S1, one or more items of route information characterizing the course of the route are provided.Such route information characterizing the route's course includes, in particular, a curve curvature κ at the future waypoint s*. Additionally, the curve curvature before and / or after the vehicle's future waypoint s* can be processed as route information.

[0021] In a second step S2, a first probability distribution P total of a maximum friction coefficient µ at the current waypoint s and / or at the future waypoint s* of the vehicle is provided. The provided probability distribution P total (µ) can be in discrete or continuous form. The method by which such a probability distribution is determined is not the subject of the present method.

[0022] In general, the maximum coefficient of friction can be determined using direct or indirect methods. The determination of the maximum coefficient of friction using direct methods is referred to as effect-based and can be divided into direct, active methods and direct, passive methods. With a direct, active method, there is active intervention in the vehicle's driving dynamics through braking and / or steering. With a direct, passive method, there is no active intervention in the vehicle's driving dynamics. Instead, the effects of the coefficient of friction on the tire tread, the vehicle, and the like are simply observed during driving maneuvers carried out by the vehicle to reach a predetermined navigation destination. In order to measure the effects of the coefficient of friction and from this to determine a maximum coefficient of friction with sufficient certainty, the transmission of high forces on the tire is a prerequisite.

[0023] Indirect, cause-based methods determine the maximum coefficient of friction based on parameters that physically influence it. These can include, for example, the tire tread, the tire's rubber compound, its temperature, tire pressure, the road surface, its temperature, its condition (e.g., snow or wetness), etc.

[0024] The estimation of a friction coefficient at a future waypoint of a vehicle can be described, for example, using a method with the following steps: from a first number of parameters that are or were determined for a current waypoint of the vehicle and that characterize the maximum friction coefficient at the current waypoint of the vehicle, a prediction of a first probability distribution for the maximum friction coefficient at the current waypoint of the vehicle is carried out using a Bayesian network. Furthermore, a second probability distribution for the maximum friction coefficient at the future waypoint of the vehicle is estimated from a second number of pieces of information about the future waypoint. Finally, a resulting, combined probability distribution from the first and second probability distributions is determined.To estimate the friction coefficient distribution at the future waypoint in front of the vehicle, this exemplary procedure processes variables influencing the maximum available friction coefficient both below the vehicle (i.e., at the current waypoint) and in front of the vehicle. By utilizing a wide range of available information below and in front of the vehicle, the prediction quality of the friction coefficient distribution at the future waypoint is high.

[0025] In principle, other procedures for providing a probability distribution of the maximum friction coefficient at the current waypoint and / or at the future waypoint of the vehicle can also be processed within the scope of the present method.

[0026] Using an analytical relationship and the route information(s), in particular the curve curvature κ, the existing probability distribution P ges (µ) at the future waypoint s* can be converted into a probability distribution P v (v), where v represents the vehicle speed. This determination is carried out in the Fig. 1 shown diagram as step S3.

[0027] In a further step S4, the safe speed v* is determined from the now determined probability distribution of the speed P v (v) at the waypoint s*. This procedure is described with reference to Fig. 2 described.

[0028] Fig. 2 The upper half shows a continuous probability distribution P total (µ) as a function of the maximum friction coefficient µ. The diagram shows, for example, the probability distribution P total (µ) at the current waypoint and / or at the future waypoint s* of the vehicle. The probability distribution P total (µ) can, for example, be generated by combining several probability distributions at respective waypoints between the current waypoint and the future waypoint s*. This is assumed to be given.

[0029] The conversion of the probability distribution P ges (µ) into the probability distribution P v (v) of the speed at the future waypoint s* is carried out, for example, using the differential equation according to equation (2). In this formula, vx represents the speed of the vehicle in the direction of its longitudinal axis (vehicle longitudinal speed, a x represents the acceleration of the vehicle in the direction of its longitudinal axis (vehicle longitudinal acceleration), κ the curve curvature, s the distance, g the gravitational constant, and µ the coefficient of friction. For the sake of simplicity, when processing equation (2), the vehicle is considered as a mass point. However, a different vehicle model could also be used. The curve curvature κ is derived from the above-mentioned map data for the relevant waypoint, in this case the selected future waypoint s*. Furthermore, for the sake of simplicity, it is assumed that the vehicle passes through the considered waypoint s* without acceleration, which is why the term a x 2 from equation (2) is omitted. From this, the various friction values ​​can be calculated according to the Fig. 2 A respective probability value of the speed can be determined from the probability distribution shown above. For example, the Fig. 2 Probability distribution P v (v) shown below as a function of vehicle speed v.

[0030] The determination of the safe speed v* at the future waypoint s* (also called look-ahead point) is carried out by choosing a q-quantile qs of the determined probability distribution P v (v) over the speed v. In Fig. 2 the q-quantile is denoted by qs, where qs represents a safety parameter.

[0031] According to equation (1), qs corresponds to the integral from the safe speed v* to infinity over the probability distribution P v . This means that the actual speed at which the future waypoint s* can be passed stably is greater than or equal to the selected speed v* with a probability of qs × 100%. The larger qs is chosen, the safer the speed selection.

[0032] To determine the safe speed, a specific value for qs is specified for a vehicle type (e.g. sports car, sedan or off-road vehicle) and / or depending on the chassis present in a vehicle (sports chassis, comfort chassis or chassis tuning selectable by mode selection). The choice of the q-quantile qs is fixed for a vehicle type and / or a chassis type / driving mode of the vehicle. The safe speed v* can then be calculated from the specified q-quantile qs and equation (1). It is clear that the selected safe speed v* does not correspond to the true safe speed, which is actually unknown. However, the safe speed v* is selected by appropriately selecting the q-quantile so that it is highly likely to be lower than the true safe speed.

[0033] Based on the now available safe speed v* for the future waypoint s*, an action strategy can then be derived. If it is determined that the actual speed of the vehicle at waypoint s* is greater than the determined safe speed v* or only slightly below the safe speed v*, a need for action can be derived. Such a need for action can include information or a warning for the driver or, if a driver assistance system is present, automated vehicle deceleration. In automated vehicles, the safe speed v* can be used to delimit an optimization space within which a suitable speed trajectory is determined.

[0034] The present method is based on the idea of ​​predicting the criticality of the driving situation at a future waypoint, given available traction information about this waypoint, based on the calculated safe speed at this waypoint and a speed forecast based on the driver's current friction coefficient utilization, taking route information into account. From this, the aforementioned recommended action can be derived, such as preconditioning a chassis system, decelerating the vehicle, or issuing a warning to the driver. Bezugszeichen

[0035] scurrent waypoint s*future waypoint κcurve curvature P ges (µ)first probability distribution P v (v)second probability distribution µfriction coefficient qs q-quantile vx vehicle longitudinal speed ax vehicle longitudinal acceleration

Claims

1. Method for determining a safe speed (v*) at a future waypoint (s*) of a vehicle moving along a route, comprising the following steps: - providing at least one item of route information characterizing the route course of the route (in particular curve curvature κ); - providing a first probability distribution (Pges) of a maximum coefficient of friction (µ) at the current waypoint (s) and / or at the future waypoint (s*) of the vehicle; - ascertaining a second probability distribution (Pv) of a vehicle speed (v) at the future waypoint (s*) from the at least one item of route information (κ) and the first probability distribution (Pges); - determining the safe speed (v*) from the second probability distribution (Pv), e.g. by statistical analysis.

2. Method according to Claim 1, wherein the safe speed (v*) at the future waypoint (s*) is determined by selecting a q-quantile of the second probability distribution (Pv).

3. Method according to Claim 1, wherein the safe speed (v*) at the future waypoint (s*) is determined by selecting a p-quantile of the second probability distribution (Pv).

4. Method according to Claim 1 or 2, wherein a curve curvature (κ) at and / or before the future waypoint (s*) of the vehicle is processed as the at least one item of route information.

5. Method according to any of the preceding claims, wherein the step of ascertaining the second probability distribution (Pv) takes place according to: a x 2 + kappa 2 s ∗ v x 4 − g 2 ∗ μ 2 s = 0 .

6. Method according to any of the preceding claims, wherein the step of ascertaining the second probability distribution (Pv) takes place on the assumption that the vehicle is a mass point having the given mass of the vehicle.

7. Method according to any of the preceding claims, wherein the step of ascertaining the second probability distribution (Pv) takes place on the assumption that the vehicle travels along the route, in particular the future waypoint (s*), in an unaccelerated manner.

8. Method according to any of Claims 2 to 6, wherein a value which is fixed for the vehicle and which is dependent on a vehicle type, a chassis type or a driving mode is selected as the p- or q-quantile.

9. Method according to any of Claims 2 to 7, wherein the p- or q-quantile is selected such that the selected safe speed (v*) resulting therefrom is lower than the true safe speed at the future waypoint (s*).

10. Device for determining a safe speed at a future waypoint (s*) of a vehicle moving along a route, comprising: - a first means for ascertaining a second probability distribution (Pv) of a vehicle speed (v) at the future waypoint (s*) from at least one item of route information (κ) characterizing the route course of the route and a first probability distribution (Pges) of a maximum coefficient of friction (µ) at the current waypoint (s) of the vehicle and / or at the future waypoint (s*); - a second means for ascertaining the safe speed (v*) from the second probability distribution (Pv).