Determining a travel trajectory

Abstract

Method (300) for determining a driving trajectory (145) of a motor vehicle (105), comprising the following steps: - Determining (305) positions (205) of the motor vehicle (105) by means of a receiver (120) of a satellite-based navigation system (125); - Determining (325) the travel trajectory (145) on the basis of the determined positions (205), characterized in that - each position (205) is weighted depending on a first number of other determined positions (205) that are located within a first predetermined spatial distance (210) from the position (205), - and depending on a second number of other specific positions (205) located within a second predetermined spatial distance (215) from the position (205), - where the first distance (210) is smaller than the second distance (215); - and the travel trajectory (145) is determined on the basis of weighted positions (205) (325).

Description

[0001] The invention relates to the determination of a motor vehicle's trajectory. In particular, the invention relates to the creation of a trajectory based on multiple information sources.

[0002] To determine the trajectory of a motor vehicle traveling on a road, various information sources can be evaluated. A first source of information can include an absolute positioning device that can determine the vehicle's position relative to a global surveying system. A second source of information can include an odometric data source that, for example, determines the vehicle's distance traveled within a predetermined time interval based on measurements from wheel speed sensors.

[0003] DE 10 2013 208 521 A1 describes the determination of a model for a roadway based on a large number of measurement runs with motor vehicles. During these measurement runs, driving trajectories and perception data are recorded.

[0004] DE 10 2013 015 705 A1 teaches a method for determining a current position of a motor vehicle in a geodetic coordinate system from a time series of first geodetic position data and self-motion data recorded by at least one self-motion sensor.

[0005] DE 10 2016 223 999 A1 concerns the determination of a reference trajectory with a Posen graph using odometry position data and absolute position data.

[0006] DE 11 2012 003 467 T5 discloses a lane storage device comprising a location detection device, a position lane generation device, a movement distance detection device, a driving direction detection device, a dead reckoning navigation lane generation device for generating a dead reckoning navigation lane in which respective vectors determined from a vehicle movement distance and a vehicle driving direction are arranged chronologically, a correction position lane generation device for generating a correction position lane obtained by removing a location that is a predetermined distance or more from the dead reckoning navigation lane, a correction dead reckoning navigation lane generation device for generating a correction dead reckoning navigation lane obtained by correcting the dead reckoning navigation lane, and an absolute lane generation device for generating an absolute lane.which is obtained by synthesizing the correction position track and the correction coupling navigation track, and an absolute track memory for storing the absolute track.

[0007] It has been shown that the influence of absolute position determinations, compared to odometric determinations, often leads to unrealistic results. One of the problems underlying the present invention is therefore to provide an improved technique for determining the trajectory of a motor vehicle. The invention solves this problem by means of the subject matter of the independent claims. Dependent claims describe preferred embodiments.

[0008] According to a first aspect of the invention, a method for determining the trajectory of a motor vehicle comprises steps of determining the positions of the motor vehicle by means of a receiver of a satellite-based navigation system; and determining the trajectory based on the determined positions. Each position is weighted according to a distance from at least one of the other determined positions, and the trajectory is determined based on the weighted positions.

[0009] Variable weighting allows for the consideration of the fact that individual positions are not entirely independent measurements but are subject to common sources of error, such as multipath propagation or ionospheric influence on satellite signals. The described method can reduce the weighting of closely spaced positions without discarding any measurements. Position determination is typically performed by the receiver at fixed time intervals. The slower the vehicle moves, the closer the determined positions can be to each other. Particularly when the vehicle is stationary, a large number of positions can be determined, all subject to nearly identical errors. The proposed weighting of the determined positions reduces the concentration of error influences along the vehicle's trajectory.

[0010] In a particularly preferred embodiment, a further sensor on board the motor vehicle is scanned, and the vehicle's trajectory is additionally determined based on the sensor's scan. The further sensor can, in particular, comprise an odometric information source that provides an indication of the motor vehicle's movement, speed, or acceleration. The sensor can, for example, comprise a wheel speed sensor, an acceleration sensor, or a yaw rate sensor. The sensor can also be part of a non-contact, particularly optical, odometry system. In this system, the motor vehicle's surroundings can be scanned, and the motor vehicle's movement can be determined based on the relative movement of a scanned object. The scanning can be performed, for example, using an optical camera, a radar sensor, a lidar sensor, or an ultrasonic sensor. The sensor can further be used for detection or...The sensor can be used to detect the vehicle's surroundings. For example, it can detect a lane of the road the vehicle is on. The relative position of scanned objects to each other, or of an object relative to the vehicle and its trajectory, can also be checked to determine, for example, a change in the position of a landmark such as a traffic sign. Determining the vehicle's position and scanning an object in its environment can be integrated, for example, using a SLAM (Simultaneous Localization and Mapping) algorithm.

[0011] It is further preferred that each position of the vehicle determined by the receiver is weighted according to a number of other determined positions located within a predetermined spatial distance of that position. The predetermined spatial distance can be selected depending on the prevailing driving situation, for example, the vehicle's speed. The higher the vehicle's speed, the greater the spatial distance can be. This keeps processing overhead within reasonable limits. Positions subject to different error influences can be processed separately and more effectively.

[0012] It is further preferred that a covariance matrix be assigned to each position to account for normally distributed or approximately normally distributed errors. The weighting can be achieved, in particular, by scaling the covariance matrix. The covariance matrix essentially indicates the magnitude of the measurement uncertainty to which a specific position is subject. If the covariance matrix is ​​multiplied by a scalar factor, the measurement uncertainty for the specific position increases. Further processing of the position preferably takes place in conjunction with the covariance matrix. In particular, determining the vehicle's trajectory can be carried out by considering the covariance matrices assigned to the respective positions.

[0013] The method can also be carried out in multiple stages by considering differently sized groups of other positions for each position. According to the invention, each position is weighted depending on a first number of other specific positions located within a first predetermined spatial distance from the position, and additionally depending on a second number of other specific positions located within a second predetermined spatial distance from the position. The first distance is smaller than the second distance.

[0014] For example, by considering the additional positions within the first distance, an error caused by multipath propagation can be minimized, while the positions within the second predetermined distance can allow the minimization of an error caused by ionospheric influences.

[0015] The first distance can be in the range of approximately 30 m, preferably approximately 20 m, and more preferably approximately 10 m. The second distance can be in the range of approximately 30 km, preferably approximately 20 km, and more preferably approximately 10 km. The geometric distances between specific positions considered here can only refer to a horizontal distance between the positions.

[0016] In yet another embodiment, each position is additionally weighted depending on the time interval between a position determination time and a determination time of a position immediately before or after it. This allows for consideration of the possibility that an error influencing the determined positions may be time-dependent. In the case of multipath propagation, this time dependency can, for example, be caused by a moving object, and in the case of ionospheric influence, by fluctuations in the ionosphere.

[0017] According to a second aspect of the invention, a device for determining the trajectory of a motor vehicle comprises a receiver of a satellite-based navigation system, wherein the receiver is configured to determine the positions of the motor vehicle; and a processing unit configured to determine the trajectory based on the determined positions. The processing unit is further configured to weight each position depending on a distance from at least one of the other determined positions and to determine the trajectory based on the weighted positions.

[0018] The device, and in particular the processing unit, may be configured to perform a method described herein. For this purpose, the processing unit may include a programmable microcomputer or microcontroller, and the method may be in the form of a computer program product with program code. The computer program product may also be stored on a computer-readable data carrier. Features or advantages of the method may be transferred to the device, or vice versa.

[0019] According to a third aspect of the present invention, a motor vehicle comprises a device described herein.

[0020] The invention will now be described in more detail with reference to the attached drawings, in which: Fig. 1 a system; Fig. 2. A driving trajectory of a motor vehicle and exemplary positions; and Fig. 3. A flowchart of a process is illustrated.

[0021] Fig. Figure 1 shows a system 100 comprising a motor vehicle 105 with a device 110. The device 110 comprises a processing unit 115 and a receiver 120 for signals from a satellite-based navigation system 125. Preferably, the device 110 further comprises an interface 130 for connection to another sensor or system on board the motor vehicle 105.

[0022] The satellite-based navigation system 125 typically comprises a number of satellites 135 orbiting the Earth in predetermined orbits. Each satellite 135 can transmit time and orbital information, which can be received by the receiver 120. The signals received by the receiver 120 can be subject to various sources of error. One source of error is multipath propagation, in which the signal transmitted by the satellite 135 propagates along paths of different lengths, so that signals from the same origin arrive at the receiver 120 with a time delay. A second source of error is the influence of the ionosphere 140, which is a global layer between the satellite 135 and the receiver 120. The ionosphere 140 is generally assumed to begin at an altitude of approximately 80 km, exert its strongest influence at an altitude of approximately 300 km, and end at an altitude of approximately 1,000 km.Other ionospheric boundaries can also be assumed. Ionosphere 140 contains a relatively large number of free electrons that can influence a passing radio signal.

[0023] The receiver 120 is configured to determine the absolute position of the motor vehicle 105 relative to the Earth based on received satellite signals. The receiver 120 typically operates at a fixed measurement frequency of approximately 1 Hz, 2 Hz, 5 Hz, 10 Hz, or 20 Hz. The positions determined by the receiver 120 are processed to determine the trajectory 145 of the motor vehicle 105 along a road 150. The road 150 may comprise one or more lanes 155, and the motor vehicle 105 may travel in one of these lanes. Changing between adjacent lanes 155 may be permitted or prohibited.

[0024] The vehicle trajectory 145 can additionally be determined based on an odometric data source, which can be connected via interface 130. This data source can, in particular, comprise a system or subsystem on board the vehicle 105 or a dedicated sensor 160. The sensor 160 can, for example, comprise a camera, a radar sensor, a lidar sensor, or an ultrasonic sensor. Based on the information acquired at interface 130, odometric information can be determined that indicates how the vehicle 105 is moving. In particular, the direction of movement, the speed of movement, the acceleration, or the rotational acceleration of the vehicle 105 can be determined.

[0025] The sources of error that can influence the positions determined by means of receiver 120 typically change over time and usually also with respect to the location of the vehicle 105. Therefore, positions that are close together in time or space may be subject to similar errors. Such positions should then no longer be considered as independent measurements.

[0026] Fig. Figure 2 shows a travel trajectory 145 of a motor vehicle 105 and exemplary positions 205 on the basis of which the travel trajectory 145 can be determined. For illustrative purposes, it is assumed that the motor vehicle 105 is depicted as follows: Fig. The vehicle 105 travels from bottom to top along the trajectory 145, initially slowing down, stopping approximately in the middle of the diagram, and after a certain waiting period, accelerating again and continuing upwards. Positions 205 are determined at equal time intervals. Positions 205 determined on the moving vehicle 105 are shown in light colors as positions 205.1, and positions 205 of the stationary vehicle 105 are shown in dark colors as positions 205.2.

[0027] In the example shown, a heightened systematic error, for example due to multipath propagation, affects positions 205 at the point where the vehicle 105 stops, shifting them to the left in the representation. If all determined positions 205 were weighted equally when determining the driving trajectory 145, the driving trajectory 145 would have to lie further to the left at this point.

[0028] It is proposed to determine the driving trajectory 145 based on weighted positions 205. Each position 205 can be assigned a weight, which in one variant expresses its significance or in another its measurement uncertainty. Each position 205 typically comprises several components, which are assigned, for example, to a longitude, a latitude, and an altitude of a geoid. A covariance matrix can be assigned to the determined position 205, the components of which each express the measurement uncertainty of one of the components of the position 205. By scaling the covariance matrix, the assumed measurement uncertainty can be increased or decreased, thereby decreasing or increasing the weight of the position 205 in determining the driving trajectory 145.

[0029] The following considers an exemplary position 205.3. It is proposed that the weight of position 205.3 be determined to be greater the fewer other positions 205 are located within a predetermined first spatial distance 210 from it. Fig. Figure 2 shows the first spatial distance 210 as a circle with a predetermined radius around the considered position 205.3. All positions 205 lying within the circle 210 can thus reduce the weight of the considered position 205.3 for determining the driving trajectory 145 or scale the covariance matrix assigned to the considered position 205.3 by a factor greater than 1, so that an associated measurement uncertainty is increased. In a further embodiment, a second spatial distance 215 around the considered position 205.3 is provided, wherein the second spatial distance 215 is larger than the first spatial distance 210. All positions 205 lying within the second spatial distance 215 can contribute to reducing the weight or increasing the scaling of the covariance matrix of the considered position 205.3. The first spatial distance 210, for example, lies in a range of approximately...The first spatial distance 210 is 20 m, while the second spatial distance 215 can be in a range of, for example, approximately 20 km. Positions 205 that lie within both spatial distances 210 and 215 can thus also reduce the weight of the considered position 205.3 multiple times or scale its associated covariance matrix. In particular, a systematic error due to multipath propagation can be reduced using the first spatial distance 210, and a systematic error caused by the ionosphere 140 can be reduced based on the second spatial distance 215.

[0030] Fig. Figure 3 shows a flowchart of a method 300, which can be carried out in particular by means of the device 110 on board the motor vehicle 105.

[0031] In step 305, a position 205 is determined using receiver 120. In step 310, positions 205 can be determined that are in a predetermined proximity relationship to the determined position 205. In particular, positions 205 can be determined that lie within a predetermined distance 210, 215.

[0032] Based on the determined neighboring positions 205, a weighting of the position 205 determined in step 305 can be determined in step 315. Instead of a weighting, a measurement uncertainty can also be determined. With an increasing number of additional positions 205 in the predetermined neighborhood relationship to the determined position 205, the weight can decrease or the measurement uncertainty can increase. In step 320, a weighted position 205 or a position 205 with an adjusted measurement uncertainty can be determined.

[0033] In step 325, the driving trajectory 145 can be determined based on a plurality of specific positions 205 and their respective assigned weights or measurement uncertainties. It is preferred that the determination of the driving trajectory 145 is additionally based on one or more odometric data points. For this purpose, an odometer and / or a further sensor 160 on board the motor vehicle 105 can be scanned in step 330 and / or in step 335. The scanned odometric data can then be used together with the determined positions 205 to improve the determination of the driving trajectory 145.

[0034] In a further embodiment, the driving trajectory 145 can be used to map the driving route 150. For this purpose, driving trajectories 145 of a large number of motor vehicles 105 can be collected and evaluated. The driving trajectories 145 can be collected at a central location, to which they can be transmitted, for example, by means of a wireless communication device. In addition to the driving trajectories 145, scans acquired, for example, in steps 330 or 335 can be evaluated. The determination of the driving trajectory 145 in step 325 can additionally take into account the position, existence, or nature of an object in the vicinity of the motor vehicle 105. On the one hand, the driving trajectory 145 can be determined based on the scan; on the other hand, the object can be considered in relation to the determined driving trajectory.The simultaneous determination of the object and the trajectory can be achieved using SLAM. Reference sign 100 System 105 motor vehicles 110 Device 115 Processing unit 120 recipients 125 satellite-based navigation system 130 interface 135 satellites 140 Ionosphere 145 Travel trajectory 150 road 155 lanes 160 Sensor 205 Position 205.1 Position while driving 205.2 Position at standstill 205.3 exemplary position 210 first spatial distance 215 second spatial distance 300 procedures 305 Determine position 310 Determine adjacent positions (first, second distance) 315 Determine weighting 320 Determine weighted position 325 Determine travel trajectory 330 Odometer scans 335 Scanning another sensor

Claims

[1] Method (300) for determining a driving trajectory (145) of a motor vehicle (105), comprising the following steps: - Determining (305) positions (205) of the motor vehicle (105) by means of a receiver (120) of a satellite-based navigation system (125); - Determining (325) the travel trajectory (145) based on the determined positions (205), characterized by , that - each position (205) is weighted depending on a first number of other determined positions (205) that are located within a first predetermined spatial distance (210) from the position (205), - and depending on a second number of other specific positions (205) located within a second predetermined spatial distance (215) from the position (205), - where the first distance (210) is smaller than the second distance (215); - and the travel trajectory (145) is determined on the basis of weighted positions (205) (325). [2] Method (300) according to claim 1, wherein a further sensor (160) on board the motor vehicle (105) is scanned and the driving trajectory (145) is additionally determined on the basis of the scanning of the sensor (160). [3] Method (300) according to claim 1 or 2, wherein each specific position (205) is weighted depending on a number of other specific positions (205) located within a predetermined spatial distance (210, 215) from the position (205). [4] Method (300) according to one of the preceding claims, wherein a covariance matrix is ​​assigned to a position (205) to take account of normally distributed errors and the weighting (320) is carried out by scaling the covariance matrix. [5] Method (300) according to one of the preceding claims, wherein the first distance (210) is below approximately 20 m. [6] Method (300) according to one of the preceding claims, wherein the second distance (215) is below approximately 20 km. [7] Method (300) according to any of the preceding claims, wherein each position (205) is additionally weighted depending on a time interval between a determination time of position (205) and a determination time of a position (205) determined immediately before or after it. [8] Device (110) for determining a driving trajectory (145) of a motor vehicle (105), wherein the device (110) comprises the following: - a receiver (120) of a satellite-based navigation system (125) designed to determine the positions (205) of the motor vehicle (105); and - a processing unit (115) designed to determine the travel trajectory (145) based on the specified positions (205), - wherein the processing facility (115) is designed to, - to weight each position (205) depending on a first number of other determined positions (205) that are located within a first predetermined spatial distance (210) from the position (205), - and depending on a second number of other specific positions (205) located within a second predetermined spatial distance (215) from the position (205); - where the first distance (210) is smaller than the second distance (215); and - to determine the travel trajectory (145) based on the weighted positions (205). [9] Motor vehicle (105) comprising a device (110) according to claim 8.

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