Method for determining a driving trajectory

Abstract

The method for determining a driving track provided by the present disclosure relates to automatic driving technology, and comprises the following steps: acquiring a confidence degree of a positioning result output by a combined navigation system arranged in a vehicle; if the confidence degree indicates that the positioning result is invalid, acquiring a last moment position of the vehicle and high-precision map data; determining information of a local lane line according to the last moment position and the high-precision map data; acquiring a real-time speed of the vehicle, and determining driving information of the vehicle according to the information of the local lane line and the real-time speed, and determining a driving track of the vehicle according to the driving information. The method, device, equipment, storage medium and program product for determining a driving track provided by the present disclosure can deduce the driving track of the vehicle for a long time in combination with the vehicle speed and the lane line in the high-precision map when the positioning result output by the combined navigation system is invalid, so that the current position of the vehicle can be inferred according to the driving track.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to automatic driving technology, and in particular, to a method for determining a driving trajectory. BACKGROUND

[0002] At present, many vehicles are provided with positioning systems, especially in assisted driving vehicles, the vehicle needs to formulate a driving strategy according to the positioning result in the positioning system.

[0003] The positioning scheme of automatic driving is generally dominated by Kalman filter, which outputs centimeter-level positioning by fusing GPS-RTK (Global Positioning System-Real-time kinematic), IMU (Inertial Measurement Unit), road element (lane line, signboard, etc.) matching information, etc.

[0004] Among them, IMU has cumulative error in the process of track extrapolation. If effective observation data cannot be obtained for a long time, the error of the position information obtained by secondary integration will quickly diverge with time, resulting in an unusable positioning result.

[0005] In actual driving process, many scenes will have invalid observation data: urban canyons, tunnels and other scenes will affect GPS signals; rain, snow and other scenes will affect the recognition function of visual equipment, and IMU has cumulative error, which will lead to inaccurate observation data and track extrapolation results, and thus the vehicle cannot obtain accurate positioning results. SUMMARY

[0006] The present disclosure provides a method for determining a driving trajectory to solve the problem of inaccurate track extrapolation results in the prior art.

[0007] The first aspect of the present disclosure is to provide a method for determining a driving trajectory, comprising:

[0008] obtaining the confidence of the positioning result output by the integrated navigation system provided in the vehicle, if the confidence represents that the positioning result is invalid, obtaining the last position of the vehicle and high-definition map data;

[0009] determining the information of the local lane line according to the last position and the high-definition map data;

[0010] obtaining the real-time speed of the vehicle, and determining the driving information of the vehicle according to the information of the local lane line and the real-time speed, and determining the driving trajectory of the vehicle according to the driving information, wherein the driving trajectory is used to determine the position of the vehicle.

[0011] Another aspect of the present disclosure is to provide a device for determining a driving trajectory, comprising:

[0012] an acquisition unit configured to acquire a confidence level of a positioning result output by a combined navigation system arranged in a vehicle;

[0013] the acquisition unit is further configured to acquire a last position of the vehicle and high-definition map data if the confidence level indicates that the positioning result is invalid;

[0014] a local lane determination unit configured to determine information of a local lane line based on the last position and the high-definition map data;

[0015] the acquisition unit is further configured to acquire a real-time speed of the vehicle;

[0016] a trajectory determination unit configured to determine driving information of the vehicle based on the information of the local lane line and the real-time speed, and determine a driving trajectory of the vehicle based on the driving information, the driving trajectory being used to determine a position of the vehicle.

[0017] Another aspect of the present disclosure is to provide a vehicle-mounted device, comprising:

[0018] a memory;

[0019] a processor; and

[0020] a computer program;

[0021] wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method for determining a driving trajectory according to the first aspect.

[0022] Another aspect of the present disclosure is to provide a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the method for determining a driving trajectory according to the first aspect.

[0023] The method for determining a driving trajectory provided by the present disclosure comprises: acquiring a confidence level of a positioning result output by a combined navigation system arranged in a vehicle, acquiring a last position of the vehicle and high-definition map data if the confidence level indicates that the positioning result is invalid, determining information of a local lane line based on the last position and the high-definition map data, acquiring a real-time speed of the vehicle, determining driving information of the vehicle based on the information of the local lane line and the real-time speed, and determining a driving trajectory of the vehicle based on the driving information. The method for determining a driving trajectory provided by the present disclosure can deduce a driving trajectory of a vehicle for a longer time by combining a vehicle speed and a lane line in a high-definition map when a positioning result output by a combined navigation system is invalid, so that a current position of the vehicle can be inferred based on the driving trajectory. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 A flowchart of a method for determining a driving trajectory according to an example embodiment of the present disclosure;

[0025] Figure 2 A schematic diagram of determining a driving trajectory of a vehicle according to an example embodiment of the present disclosure;

[0026] Figure 3 A flowchart of a method for determining a driving trajectory according to another example embodiment of the present disclosure;

[0027] Figure 4 A schematic diagram of superimposing driving information on a previous position according to an example embodiment of the present disclosure;

[0028] Figure 5 A schematic diagram of determining a lateral offset according to an example embodiment of the present disclosure;

[0029] Figure 6 A schematic diagram of a vehicle driving according to an example embodiment of the present disclosure;

[0030] Figure 7 A structural diagram of a device for determining a driving trajectory according to an example embodiment of the present disclosure;

[0031] Figure 8 A structural diagram of a device for determining a driving trajectory according to another example embodiment of the present disclosure;

[0032] Figure 9 A structural diagram of a vehicle-mounted device according to an example embodiment of the present disclosure. DETAILED DESCRIPTION

[0033] At present, the positioning scheme provided in a vehicle needs to fuse positioning information of multiple approaches, which can specifically include GPS-RTK (Global Positioning System-Real-time kinematic), IMU (Inertial Measurement Unit), road element (lane line, signboard, etc.) matching information, and the like.

[0034] In a general positioning scheme, the dependence on a GPS-RTK signal is higher. However, in some specific environments, accurate positioning information can not be obtained, for example, in a tunnel, a GPS signal can be affected, and in a rainy or snowy environment, road element (lane line, signboard, etc.) matching information obtained based on a visual device can be affected.

[0035] Therefore, when accurate GPS-RTK signals cannot be obtained, the IMU can perform short-time trajectory prediction between two effective GPS signal intervals, and output high-frequency relative motion information to meet the needs of automatic driving. Road element matching information can be used as an auxiliary means to correct the IMU predicted state quantity when the GPS signal quality is poor (in special road scenes such as urban canyons and tunnels), and can also eliminate the influence of abnormal GPS data.

[0036] However, the IMU has accumulated errors in the process of trajectory prediction. If the interval between two effective GPS signals is long, the vehicle position and attitude determined based on the IMU prediction result in this period of time can be inaccurate. Therefore, how to accurately determine the driving trajectory of the vehicle is a technical problem to be solved in the present case.

[0037] To solve the above technical problems, the scheme provided by the present disclosure can be based on the lane lines in the high-precision map to predict the driving trajectory of the vehicle, so as to determine the driving trajectory of the vehicle for a long time.

[0038] Figure 1 A flowchart of a method for determining a driving trajectory according to an exemplary embodiment of the present disclosure.

[0039] As shown in Figure 1 The method for determining a driving trajectory provided by the present disclosure comprises:

[0040] In step 101, the confidence of the positioning result output by the combined navigation system arranged in the vehicle is obtained. If the confidence indicates that the positioning result is invalid, the last position of the vehicle and the high-precision map data are obtained.

[0041] The scheme provided by the present disclosure can be executed by an electronic device with computing capability, which can be a vehicle terminal. The scheme provided by the present disclosure can be arranged in the vehicle terminal, so that the vehicle terminal can determine the driving trajectory of the vehicle based on the method provided by the present disclosure.

[0042] In one application scenario, in the case of GPS signal failure, the vehicle terminal can determine the driving trajectory of the vehicle based on the method provided by the present disclosure. The vehicle terminal can also determine the positioning result of the vehicle according to the determined driving trajectory, thereby solving the problem of being unable to obtain accurate positioning results due to GPS signal failure.

[0043] In another application scenario, when the vehicle terminal needs to fuse GPS-RTK, IMU, and road element matching information to obtain a positioning result, the vehicle terminal can also determine the driving trajectory of the vehicle based on the method provided by the present disclosure, so that the driving trajectory can be fused to obtain the final positioning result.

[0044] The vehicle can be provided with a combined navigation system, which can output a positioning result and a confidence level of the positioning result. The combined navigation system is a system that combines the output of navigation devices with different characteristics to obtain an optimized positioning result. For example, the output of an inertial navigation device can be combined with the output of other navigation devices.

[0045] Specifically, the confidence level of the positioning result can be used to represent the accuracy of the positioning result. For example, the confidence level can include two values, one representing a valid positioning result and the other representing an invalid positioning result. For another example, the confidence level can include multiple values, and a confidence level less than a preset value represents an invalid positioning result, and a confidence level greater than the preset value represents a valid positioning result.

[0046] Further, when the vehicle terminal uses the positioning result output by the combined navigation system, it can also obtain the confidence level of the positioning result, and determine whether the positioning result is valid based on the confidence level.

[0047] In actual application, if the confidence level represents an invalid positioning result, it means that the positioning result is not accurate enough, and the vehicle cannot be considered to be at the position represented by the positioning result. In this case, the vehicle terminal can obtain the position at the previous moment, i.e., the valid position at the previous moment.

[0048] The obtained position at the previous moment can be a valid positioning result output by the combined navigation system, or a positioning result determined based on the driving trajectory. For example, the positioning result output by the combined navigation system at time 0 is valid, and the positioning result output by the combined navigation system at time 1 is invalid. At time 1, the vehicle terminal can obtain the positioning result at time 0, and determine the driving trajectory of the vehicle based on the accurate positioning result. At time 2, if the positioning result output by the combined navigation system is still invalid, the vehicle terminal can obtain the position of the vehicle at the previous moment, which can be a positioning result determined based on the driving trajectory at time 0.

[0049] Specifically, the vehicle terminal can also be provided with a high-definition map, so that it can obtain high-definition map data, and determine the driving trajectory of the vehicle based on the high-definition map data and the position of the vehicle at the previous moment. Furthermore, the vehicle terminal can also determine the current position of the vehicle based on the position of the vehicle at the previous moment and the driving trajectory.

[0050] At step 102, the information of the local lane line is determined based on the position at the previous moment and the high-definition map data.

[0051] Further, the vehicle terminal can obtain the map data near the position at the previous moment from the high-definition map data, so as to obtain the information of the local lane line near the position at the previous moment.

[0052] In actual application, the vehicle terminal can obtain the information of the local lane line near the last position in the high-definition map, which can include the position of the lane line, the color of the lane line, and the line type of the lane line. The position of the lane line can include the coordinates of each lane line point belonging to the lane line, the color of the lane line can include yellow, white, etc., and the line type of the lane line can include a dashed lane line, a solid lane line, etc.

[0053] In the above method, the vehicle terminal can obtain the information of the lane line within a preset distance from the last position. For example, if a lane line is less than 50 meters from the last position, the vehicle terminal can obtain the information of the lane line.

[0054] Specifically, the lane line stored in the high-definition map can be a segment of line, and the vehicle terminal can obtain the information of a complete segment of lane line or a part of the lane line. For example, the vehicle terminal can obtain the information of a part of a lane line within a preset distance from the last position.

[0055] In step 103, the real-time speed of the vehicle is obtained, and the driving information of the vehicle is determined according to the local lane line information and the real-time speed. The driving trajectory of the vehicle is determined according to the driving information, and the driving trajectory is used to determine the position of the vehicle.

[0056] Further, the vehicle terminal can also obtain the real-time speed of the vehicle, and determine the driving trajectory of the vehicle according to the real-time speed of the vehicle and the local lane line information near the vehicle.

[0057] In actual application, the displacement of the vehicle within the same time will be different at different speeds, and therefore, the vehicle terminal can determine the displacement of the vehicle according to the real-time speed of the vehicle.

[0058] In the above method, the local lane line information can also include the curve equation of each local lane line, and the vehicle terminal can obtain the driving information of the vehicle by integrating the curve equation of the local lane line. In this way, the driving information of the vehicle can be accurately determined based on the lane line equation.

[0059] Specifically, the vehicle terminal can obtain the real-time speed of each frame, and can also determine the displacement value between the two obtained real-time speeds according to the time difference between the frames. The vehicle terminal can also obtain the equation of the lane line closest to the vehicle, and integrate the equation of the lane line to obtain the driving information of the vehicle when the integral distance length is equal to the displacement value. The driving information of the vehicle can specifically include the longitudinal displacement, the lateral displacement, and the heading angle increment of the vehicle.

[0060] Further, the accumulated lateral displacement of the vehicle within the preset time period can also be determined. If the accumulated lateral displacement is large, it can be considered that the driving direction of the vehicle deviates from the direction of the lane line itself. In this case, the driving trajectory of the vehicle can be determined based on the driving direction of the vehicle and the driving information. If the accumulated lateral displacement is not large, it can be considered that the driving direction of the vehicle does not deviate from the direction of the lane line itself. At this time, the vehicle terminal can determine the driving trajectory of the vehicle from the last moment to the current moment according to the last moment position of the vehicle and the current driving information.

[0061] The vehicle heading angle generally refers to the angle between the vehicle mass center speed and the vehicle transverse axis in the ground coordinate system.

[0062] Figure 2 A schematic diagram for determining the driving trajectory of the vehicle is shown for an exemplary embodiment of the present disclosure.

[0063] As shown in Figure 2 , the last moment position of the vehicle is P. The driving information of the vehicle from the last moment to the current moment can be determined according to the current real-time speed of the vehicle, and then the driving trajectory L from the last moment to the current moment can be generated.

[0064] Thereafter, the vehicle terminal can also determine the current position P1 of the vehicle according to the last moment position P and the driving trajectory L.

[0065] The method for determining the driving trajectory provided by the present disclosure comprises: acquiring the confidence of the positioning result output by the combined navigation system arranged in the vehicle. If the confidence indicates that the positioning result is invalid, the last moment position of the vehicle and the high-precision map data are acquired. The information of the local lane line is determined according to the last moment position and the high-precision map data. The real-time speed of the vehicle is acquired, and the driving information of the vehicle is determined according to the information of the local lane line and the real-time speed. The driving trajectory of the vehicle is determined according to the driving information. The method for determining the driving trajectory provided by the present disclosure can deduce the driving trajectory of the vehicle for a long time in combination with the vehicle speed and the lane line in the high-precision map when the positioning result output by the combined navigation system is invalid, so that the current position of the vehicle can be inferred according to the driving trajectory.

[0066] Figure 3 A flowchart of the method for determining the driving trajectory is shown for another exemplary embodiment of the present disclosure.

[0067] As shown in Figure 3 , the method for determining the driving trajectory provided by the present disclosure comprises:

[0068] In step 301, the confidence of the positioning result output by the combined navigation system arranged in the vehicle is acquired.

[0069] The implementation mode of the related content in step 301 is similar to that in step 101, and will not be described again.

[0070] If the confidence level indicates that the positioning result is invalid, step 302 is performed, and if the confidence level indicates that the positioning result is valid, step 317 is performed.

[0071] In step 302, if the confidence level indicates that the positioning result is invalid, the last position of the vehicle and the high-definition map data are obtained.

[0072] The implementation of step 302 is similar to that of the related content in step 101, and thus is not described herein.

[0073] In step 303, the lane line information within a preset distance from the last position of the vehicle is obtained from the high-definition map data.

[0074] The vehicle terminal can obtain the information of the lane line near the last position of the vehicle from the high-definition map data. Since the positioning result output by the combined navigation system at the current time is not accurate enough, the lane line information can be obtained based on the last position of the vehicle.

[0075] Specifically, the preset value can be set in advance. If the distance between the lane line and the last position of the vehicle is less than the preset value, the lane line can be considered to be near the vehicle, and the information of the lane line can be obtained.

[0076] In step 304, a local lane line map is generated based on the obtained information of the lane line.

[0077] Further, the vehicle terminal can also generate a local lane line map, which can include the position information of each local lane line. The local lane line map can also include the information such as the line type and color of each local lane line.

[0078] In actual application, the position information of each local lane line includes the coordinates of each lane line point on the lane line.

[0079] In step 305, the curve equation of each lane line in the local lane line map is determined based on the position information of each lane line in the local lane line map and the last position of the vehicle.

[0080] The vehicle terminal can process each lane line in the local lane line map to obtain the curve equation of each lane line.

[0081] Specifically, the local lane line map can include the first coordinates of each lane line, which are the coordinates of the coordinate system in the high-definition map. The vehicle terminal can also construct a vehicle body coordinate system based on the last position of the vehicle, and convert each first coordinate into a second coordinate in the vehicle body coordinate system based on the relative position of each lane line point to the last position.

[0082] The vehicle terminal can also fit each lane line point belonging to the same lane line based on the second coordinates of the lane line points to obtain a curve equation of each lane line in the local lane line map

[0083] In actual application, the vehicle terminal can construct a vehicle body coordinate system according to the position of the vehicle at the previous moment, and obtain the coordinates of the lane line points in each lane line in the local lane line, and can also convert the obtained coordinates of the lane line points to the vehicle body coordinate system.

[0084] The vehicle terminal can fit the curve equation of each lane line in the local lane line map according to the coordinates of each lane line point after coordinate conversion. For example, the lane line can be fitted into a cubic curve x = a0 + a1 * y + a2 * y 2 +a3*y 3 where x represents eastward and y represents northward, that is, the lane line equation is obtained. Since a0 is the distance between the vehicle and the lane line in the vehicle body coordinate system, the index of the lane line closest to the vehicle can be obtained according to the absolute value, and the equation coefficient of the lane line closest to the vehicle can also be obtained, that is, the values of a0, a1, a2, and a3.

[0085] In the scheme provided by the embodiment, the information of the lane line can include the equation of the lane line, and can also include the color and line type of the lane line in the local lane line map.

[0086] Specifically, the curve equation of the constructed lane line can include a distance parameter for representing the distance between the vehicle and the lane line, such as a0 in the above equation. For example, at time t, the curve equation of a plurality of local lane lines can be determined according to the position of the vehicle at the previous moment and the high-precision map data, and each curve equation has a distance parameter for representing the distance between the vehicle and the lane line. Therefore, the distance between the vehicle and each local lane line can be determined based on the distance parameter.

[0087] Step 306, determining the lane line closest to the vehicle according to the distance parameter included in the curve equation of each lane line.

[0088] Further, after the vehicle terminal determines the curve equation of each lane line, the distance parameter included in each equation can be used to determine the lane line closest to the vehicle. Thus, the driving trajectory of the vehicle can be deduced according to the lane line.

[0089] Step 307, determining the displacement of the vehicle according to the real-time speed, the time difference between the time when the previous position is obtained and the current time.

[0090] In actual application, the vehicle terminal can determine the position of the vehicle at each moment. For example, if the time of obtaining the last position is t, the time difference can be determined based on the time t and the current time. For example, if the current time is t1, the time difference is t-t1.

[0091] In the formula, the vehicle terminal can determine the displacement of the vehicle from the last moment to the current time based on the real-time speed of the vehicle at the current time and the determined time difference. For example, if the time difference of obtaining two continuous positions is△t, and the real-time speed of the vehicle at the current time is v, the displacement of the vehicle from the last moment to the current time is△t*v.

[0092] In step 308, the driving information of the vehicle is determined based on the displacement of the vehicle and the curve equation of the lane line closest to the vehicle.

[0093] Specifically, the vehicle terminal can determine the curve equation of the lane line closest to the vehicle based on the curve equation of the lane line constructed based on the vehicle body coordinate system, so as to determine the driving information of the vehicle based on the lane line closest to the vehicle and the displacement of the vehicle from the last moment to the current time.

[0094] Further, the vehicle terminal can integrate the curve equation of the lane line closest to the vehicle based on the displacement to obtain the lateral movement distance, the longitudinal movement distance and the heading angle increment of the vehicle. Specifically, the lane line equation can be integrated, the integral distance length is consistent with the displacement value of the vehicle from the last moment to the current time, so as to obtain the lateral movement distance, the longitudinal movement distance and the heading angle increment of the vehicle.

[0095] In step 309, the lateral movement distance, the longitudinal movement distance and the heading angle increment are superimposed on the last moment position of the vehicle to obtain the position and posture of the vehicle at the current time, wherein the driving trajectory includes the continuous position and posture of the vehicle, and the driving information includes the lateral movement distance, the longitudinal movement distance and the heading angle increment of the vehicle.

[0096] In actual application, after the driving information of the vehicle is determined, the vehicle terminal can superimpose the lateral movement distance, the longitudinal movement distance and the heading angle increment on the last moment position of the vehicle to obtain the position and posture of the vehicle at the current time.

[0097] In the formula, the lateral movement distance, the longitudinal movement distance and the heading angle increment are superimposed on the last moment position of the vehicle to obtain the position of the vehicle at the current time. When the position of the vehicle at the next moment is determined, the superposition can be performed on the current moment position, and based on this, the driving trajectory of the vehicle at continuous moments can be obtained.

[0098] In an optional embodiment, the position of the vehicle at the current time can be determined according to the driving track of the vehicle, and the position can be converted into a coordinate system in the high-definition map, so that the vehicle terminal can specify the control strategy of the vehicle based on the converted position.

[0099] Figure 4 A schematic diagram of superimposing driving information on the position at the previous time is shown for an exemplary embodiment of the present disclosure.

[0100] As shown in Figure 4 , the position of the vehicle at the previous time is P, and the driving information of the vehicle from the previous time to the current time can include longitudinal displacement y1, lateral displacement x1, and navigation angle increment a. Then, y1, x1, and a can be superimposed on the position P to determine the driving track L of the vehicle from the previous time to the current time.

[0101] After step 308, steps 310-312 can also be included.

[0102] In step 310, the lateral deviation of the vehicle within the preset time period is determined according to the navigation angle increments included in the driving information within the preset time period.

[0103] In the embodiment, the vehicle terminal can store the driving information of the vehicle, and specifically, the navigation angle increments of the vehicle. When the lateral deviation of the vehicle needs to be determined, the navigation angle increments of the vehicle within the preset time period before the current time are obtained.

[0104] For example, a time window can be set, and the length of the time window is the same as the preset time period. The vehicle terminal can obtain the navigation angle increments within the time window before the current time, and determine the lateral displacement of the vehicle within the time window.

[0105] Specifically, the vehicle terminal can determine the navigation angles of the vehicle within the preset time period according to the navigation angle increments included in the driving information within the preset time period. For example, the navigation angle of the vehicle at the current time can be determined according to the navigation angle of the vehicle at the previous time and the navigation angle increment of the vehicle from the previous time to the current time.

[0106] Further, the vehicle terminal can also store the vehicle speed of the vehicle at each time, and the vehicle terminal can obtain the vehicle speeds of the vehicle within the preset time period.

[0107] In actual application, the vehicle can determine the lateral deviation of the vehicle within the preset time period according to the navigation angles and the vehicle speeds. Specifically, the displacement of the vehicle can be determined according to the speed of the vehicle and the time difference between adjacent times, and the lateral deviation of the vehicle between each adjacent two times can be determined in combination with the navigation angles of the vehicle, and then the total lateral deviation of the vehicle within the preset time period can be obtained.

[0108] The lateral and longitudinal directions can be determined based on the vehicle's position and attitude at the beginning of a preset time period. For example, the vehicle's orientation at the beginning of the preset time period can be taken as the longitudinal direction, and the direction perpendicular to that orientation can be taken as the lateral direction.

[0109] The lateral offset refers to the lateral offset of the vehicle's position at the end of the preset time period compared to its position at the beginning of the preset time period. Specifically, the lateral offset of the vehicle can be determined based on the lateral and longitudinal dimensions of the vehicle's position and attitude at the beginning of the preset time period.

[0110] Figure 5 This is a schematic diagram illustrating the determination of lateral offset as an exemplary embodiment of the present disclosure.

[0111] like Figure 5 As shown, at the beginning time ts within the preset time period, the vehicle's position and attitude are as shown in p1. Therefore, direction A can be considered as the lateral direction, and direction B as the longitudinal direction. At the end time te within the preset time period, the vehicle's position and attitude are as shown in p2. Therefore, the offset of p1 and p2 in direction A can be determined and taken as the lateral offset of the vehicle within the preset time period.

[0112] Step 311: If the lateral offset is greater than the detection threshold, determine whether the vehicle has changed lanes based on the vehicle's heading angles.

[0113] If the determined lateral offset is greater than the detection threshold, it can be considered that the vehicle may have changed lanes. In this case, the vehicle terminal can determine whether the vehicle has changed lanes based on the vehicle's heading angles.

[0114] Specifically, if the lateral offset is less than the detection threshold, the vehicle can be considered to be traveling straight, and there is no need to perform the step of determining whether the vehicle has changed lanes.

[0115] Furthermore, the on-board terminal can determine whether any of the following conditions exist based on the vehicle's heading angles:

[0116] Performance on curves, vehicle straightening, and any abnormal heading angles;

[0117] If neither of these conditions is met, then the vehicle is confirmed to be changing lanes.

[0118] If the vehicle's lateral deviation exceeds the detection threshold within a preset time period, it could be due to the vehicle changing lanes, driving on a curve, or straightening its body. An abnormal heading angle could also lead to a large lateral deviation within the preset time period. Therefore, it is necessary to differentiate between these situations so that the onboard terminal can accurately identify lane-changing situations.

[0119] In practical applications, if the angle difference between the lane line closest to the vehicle and the vehicle's direction is greater than the curve angle threshold, and the angle difference between the heading angles of the vehicle at adjacent moments is less than the curve angle threshold, then the vehicle is determined to be driving on a curve.

[0120] The vehicle's direction is determined based on various heading angles.

[0121] Figure 6 This is a schematic diagram illustrating vehicle movement as an exemplary embodiment of the present disclosure.

[0122] like Figure 6 As shown, when a vehicle is traveling on the road, the nearest lane line to the vehicle from position P1 to position P2 is L. When the vehicle is at position P2, the first angle 61 between the vehicle's current direction and the tangent direction of the starting point of lane line L can be determined, and the second angle 62 between the vehicle's current direction and the tangent direction of the ending point of lane line L can also be determined.

[0123] Specifically, if the difference between the first angle 61 and the second angle 62 is greater than the curve angle threshold, then lane line L can be considered a curve line. Simultaneously, if the angle difference between adjacent heading angles within a preset time period is less than the curve angle threshold, then the vehicle is considered to be slowly changing its heading angle; therefore, the vehicle can be determined to be traveling on a curve.

[0124] Specifically, if the angle difference between adjacent heading angles within a preset time period is greater than the curve angle threshold, then an abnormal heading angle is identified. For example, if the angle difference between any two adjacent heading angles is too large, then an abnormal heading angle can be considered to exist.

[0125] Furthermore, if a vehicle is detected to have changed lanes twice in succession, and the directions of these two suspected lane changes are opposite, and the time interval between these two suspected lane changes is less than the vehicle body straightening window time, then the vehicle is determined to be in a straightening state.

[0126] If two consecutive lane change situations are determined based on the vehicle's heading angles, these two lane change situations can be marked as suspected lane changes. Therefore, these two lane change situations can be further determined to determine whether they are lane changes or vehicle straightening situations.

[0127] In practical applications, if the two suspected lane changes are in opposite directions and the time interval between the two suspected lane changes is less than the window time for the vehicle to straighten, then the vehicle is confirmed to be in a straightening state.

[0128] For example, the lane changing direction of the vehicle can be determined according to the change of the heading angle of the vehicle, and then it is determined whether the directions of the two suspected lane changes are opposite. A body return window time can be set in advance, and if the directions of the two suspected lane changes are opposite and the time interval is short, it can be considered that the vehicle is returning the body and not changing lanes.

[0129] In step 312, if it is determined that the vehicle changes lanes, the lane line closest to the vehicle is changed according to the lane changing condition.

[0130] If it is determined that the vehicle is actually changing lanes, the vehicle terminal can determine the lane line closest to the vehicle according to the lane changing direction of the vehicle.

[0131] Specifically, the lane line determined in step 306 can be updated.

[0132] Thereafter, the vehicle terminal can continue to determine the position of the vehicle according to the updated lane line. For example, step 308 can be performed based on the updated lane line. Thus, the driving trajectory of the vehicle is determined based on the updated lane line to obtain a more accurate driving trajectory.

[0133] If not, the vehicle terminal can continue to determine the driving trajectory of the vehicle according to the currently determined lane line closest to the vehicle.

[0134] Optionally, the scheme provided by the present disclosure can further include:

[0135] In step 313, an image output by a visual device arranged in the vehicle is obtained, and a lane line is identified in the image.

[0136] In an optional embodiment, the vehicle terminal can also obtain an image output by a visual device of the vehicle. For example, a camera can be arranged in the vehicle, and then the environment image in front of the vehicle can be collected through the camera.

[0137] If a relatively clear image can be captured through the camera, the vehicle terminal can process the image to correct the lateral movement distance in the driving information, thereby more accurately determining the driving trajectory of the vehicle.

[0138] The vehicle terminal can determine whether the image output by the visual device is valid, and if the image is valid, step 313 can be performed.

[0139] Specifically, the vehicle terminal can identify the lane line in the image collected at the current time. For example, a lane line identification algorithm can be arranged in the vehicle terminal, and the vehicle terminal can process the image output by the visual device based on the identification algorithm to determine the lane line included in the image.

[0140] In step 314, lane line information is obtained from high-precision map data in the perspective of the vehicle according to the driving information.

[0141] Further, the vehicle terminal can determine the position of the vehicle according to the determined driving information of the vehicle, and can further acquire lane line information from the high-definition map in the perspective of the position of the vehicle. For example, the vehicle terminal determines that the vehicle is located at position P, and the vehicle terminal can acquire lane line information from the high-definition map in the perspective of position P.

[0142] At step 315, the actual position of the vehicle is determined according to the information of the lane line in the image and the information of the lane line acquired from the high-definition map data.

[0143] In actual application, the vehicle terminal can compare the lane line in the image with the lane line information acquired from the high-definition map, so as to correct the determined lateral displacement distance based on the comparison result. The comparison result may, for example, include a line type comparison result, a color comparison result of the lane line, etc.

[0144] In the actual application, the vehicle terminal can further determine the actual position of the vehicle based on the comparison result of the lane line.

[0145] In an embodiment, the lateral displacement of the vehicle can be adjusted, and the lane line information is re-acquired from the high-definition map based on the updated displacement, so that the lane line information in the image is consistent with the acquired lane line information.

[0146] In another embodiment, the vehicle terminal can determine a candidate position in each lane according to the position of the vehicle at the previous moment. For example, the candidate position in each lane can be determined according to the distance between the position at the previous moment and the lane lines on both sides of the lane to which the position at the previous moment belongs; the ratio of the distance between the position at the previous moment and the lane lines on both sides of the lane to which the position at the previous moment belongs is the same as the ratio of the distance between the candidate position and the lane lines on both sides of the lane to which the candidate position belongs. For example, if the distance ratio between the position at the previous moment and the left lane line and the right lane line is 2:3, then a position candidate point can be determined for each lane, and the distance ratio between each position candidate point and the left lane line and the right lane line of the lane to which the position candidate point belongs is 2:3.

[0147] In actual application, the vehicle terminal can further determine the probability of the vehicle being at each candidate position according to the lane line in the image and the lane line in the high-definition map data; and determine the actual position of the vehicle according to the probabilities.

[0148] The probability of each candidate position can be determined based on the following formula:

[0149] p(P candidate |obs)=η·p(obs|P candidate )·p(P candidate )

[0150] =η·p(Obs type ,Obs colorHD type HD color )·p(P candidate )

[0151] =η·p(Obs) type HD type )·p(Obs color HD color )·p(P candidate )

[0152] p(P candidate |obs) is used to represent the lane line information in the image when obs is the candidate location P. candidate Let P(obs|P) be the probability of the actual location, and η be the normalization coefficient. candidate ) is used to characterize the vehicle's location at P candidate At that time, the probability that the lane line information in the image output by the vehicle vision device is obs is p(P candidate This is used to characterize the location P of the vehicle-mounted terminal. candidate The probability of being identified as a candidate position, p(Obs) type Obs color HD type HD color The lane line information acquired is represented by HD in the high-precision map. type HD color At that time, the lane line information in the image was Obs. type Obs color The probability of p(Obs). type HD type The type of lane lines acquired is HD in the high-precision map. type At that time, the lane line type in the image was Obs. type The probability, p(Obs) color HD color The color of the lane lines acquired is represented by HD in the high-precision map. color At that time, the lane line information in the image was Obs. color The probability of.

[0153] Step 316: Update the lateral movement distance based on the actual location.

[0154] The candidate position with the highest probability value can be taken as the actual position of the vehicle. The lateral movement distance of the vehicle can be updated based on the actual position, so as to obtain a more accurate lateral movement distance of the vehicle from the previous moment to the current moment.

[0155] Specifically, after updating the lateral movement distance, the on-board terminal can also update the vehicle's current position and attitude based on the updated lateral movement distance, thereby obtaining a more accurate positioning result.

[0156] In step 317, if the confidence level indicates that the positioning result is valid, preset vehicle speed compensation information and heading angle change rate compensation information are obtained.

[0157] Further, if the confidence level of the positioning result obtained by the vehicle terminal indicates that the positioning result is valid, the vehicle terminal can correct the positioning result based on the preset compensation information. Specifically, the vehicle terminal can obtain preset vehicle speed compensation information and heading angle change rate compensation information.

[0158] In actual application, the correspondence between the vehicle speed and the vehicle speed compensation information can be preset, and the correspondence between the vehicle speed and the heading angle change rate compensation information can also be preset.

[0159] Due to various reasons, the vehicle body sensor of the autonomous vehicle can output vehicle speed data and heading angle change rate data with noise. Under the condition of ignoring the influence of random error, the fixed error of the sensor data can be calculated through analysis. Therefore, the correspondence between the vehicle speed and the vehicle speed compensation information can be preset, and the correspondence between the vehicle speed and the heading angle change rate compensation information can also be preset.

[0160] In step 318, the real-time speed of the vehicle is obtained, and the real-time speed is compensated using the preset vehicle speed compensation information to obtain the compensated vehicle speed.

[0161] Specifically, the vehicle terminal can obtain the real-time speed of the vehicle, obtain a speed compensation value corresponding to the real-time speed based on the preset vehicle speed compensation information, and then compensate the obtained real-time speed using the speed compensation value to obtain the compensated vehicle speed.

[0162] In step 319, the heading angle change rate of the vehicle is obtained, and the heading angle change rate is compensated using the preset heading angle change rate compensation information to obtain the compensated heading angle change rate.

[0163] Specifically, the preset heading angle change rate compensation information can include corresponding information between the speed and the heading angle change rate compensation value. Therefore, the vehicle terminal can obtain the corresponding heading angle change rate compensation value based on the real-time speed, and then compensate the heading angle change rate of the vehicle using the heading angle change rate compensation value.

[0164] In step 320, the driving trajectory of the vehicle is determined based on the compensated vehicle speed and the compensated heading angle change rate.

[0165] Further, the vehicle terminal can acquire the last position of the vehicle, and determine the driving track of the vehicle according to the compensated vehicle speed and the compensated change rate of the heading angle. Specifically, the displacement of the vehicle from the last position to the current time can be determined according to the compensated vehicle speed and the compensated change rate of the heading angle, and then the driving track of the vehicle can be obtained by superimposing the displacement of the vehicle on the last position.

[0166] Figure 7 A structural diagram of a device for determining a driving track according to an example embodiment of the present application is shown.

[0167] As shown in Figure 7 , the device 700 for determining a driving track according to the embodiment comprises:

[0168] An acquisition unit 710 is configured to acquire the confidence of the positioning result output by the combined navigation system arranged in the vehicle;

[0169] The acquisition unit 710 is further configured to acquire the last position of the vehicle and high-definition map data if the confidence indicates that the positioning result is invalid.

[0170] A local lane determination unit 720 is configured to determine the information of the local lane line according to the last position and the high-definition map data.

[0171] The acquisition unit 710 is further configured to acquire the real-time speed of the vehicle.

[0172] A track determination unit 730 is configured to determine the driving information of the vehicle according to the information of the local lane line and the real-time speed, and determine the driving track of the vehicle according to the driving information, wherein the driving track is used to determine the position of the vehicle.

[0173] The device for determining a driving track according to the present application is similar to the embodiment shown in Figure 1 , and will not be described here.

[0174] Figure 8 A structural diagram of a device for determining a driving track according to another example embodiment of the present application is shown.

[0175] As shown in Figure 8 , based on the above-mentioned embodiment, the device for determining a driving track according to the embodiment comprises:

[0176] A lane line acquisition module 721 is configured to acquire the lane line information with a distance less than a preset value from the last position of the vehicle from the high-definition map data according to the last position of the vehicle.

[0177] The local map generation module 722 is configured to generate a local lane line map according to the acquired lane line information.

[0178] The equation construction module 723 is configured to determine a curve equation of each lane line in the local lane line map according to position information of each lane line in the local lane line map and the last time position of the vehicle.

[0179] Optionally, the equation construction module 723 is specifically configured to:

[0180] convert the first coordinates of each lane line point included in each lane line in the local lane line map into second coordinates in a vehicle body coordinate system according to the first coordinates of each lane line point and the last time position of the vehicle, wherein the first coordinates are coordinates in a coordinate system in the high-definition map;

[0181] fit each lane line point belonging to the same lane line based on the second coordinates of each lane line point to obtain the curve equation of each lane line in the local lane line map.

[0182] Optionally, the curve equation of the lane line includes a distance parameter for representing a distance between the vehicle and the lane line.

[0183] The local lane determination unit 720 is further configured to:

[0184] determine the nearest lane line of the vehicle according to the distance parameter included in the curve equation of each lane line.

[0185] Optionally, the lane line information of the local lane line includes the curve equation of the lane line.

[0186] The trajectory determination unit 730 includes:

[0187] The displacement determination module 731 is configured to determine a displacement of the vehicle according to the real-time speed and a time difference between the time when the last time position is acquired and a current time.

[0188] The driving information determination module 732 is configured to determine driving information of the vehicle according to the displacement of the vehicle and the curve equation of the nearest lane line of the vehicle.

[0189] Optionally, the driving information determination module 732 is specifically configured to:

[0190] integrate the curve equation of the nearest lane line of the vehicle according to the displacement to obtain a lateral movement distance, a longitudinal movement distance and a heading angle increment of the vehicle.

[0191] Optionally, the trajectory determination unit 730 is specifically configured to:

[0192] Superimpose the lateral movement distance, the longitudinal movement distance, the heading angle increment on the last time position of the vehicle to obtain a position and posture of the vehicle at a current time, wherein the driving track comprises the position and posture of the vehicle in succession.

[0193] Optionally, the driving information comprises a heading angle increment of the vehicle.

[0194] The device further comprises a lane line updating unit 740, configured to:

[0195] Determine a lateral deviation of the vehicle within a preset time length according to each heading angle increment comprised in the driving information within the preset time length.

[0196] If the lateral deviation is greater than a detection threshold, determine whether the vehicle changes lane according to each heading angle of the vehicle.

[0197] If it is determined that the vehicle changes lane, change a lane line closest to the vehicle according to a lane changing condition.

[0198] Optionally, the lane line updating unit 740 is specifically configured to:

[0199] Determine each heading angle of the vehicle within a preset time length according to each heading angle increment comprised in the driving information within the preset time length.

[0200] Obtain each vehicle speed of the vehicle within a preset time length.

[0201] Determine a lateral deviation of the vehicle within a preset time length according to each heading angle and each vehicle speed.

[0202] Optionally, the lane line updating unit 740 is specifically configured to:

[0203] Determine whether any of the following conditions exists according to each heading angle of the vehicle.

[0204] A curve driving condition, a vehicle body back-to-normal condition, and an abnormal heading angle.

[0205] If none of the conditions exists, determine that the vehicle is changing lane.

[0206] Optionally, if a first angle between a direction of the vehicle body of the vehicle and a tangent direction of a starting point of a lane line closest to the vehicle and a second angle between the direction of the vehicle body of the vehicle and a tangent direction of an ending point of the lane line closest to the vehicle is greater than a curve angle threshold, and an angle difference between adjacent heading angles within the preset time length is less than the curve angle threshold, it is determined that the vehicle is in the curve driving condition.

[0207] The direction of the vehicle body is determined according to each heading angle.

[0208] Optionally, if the angle difference between the first angle between the vehicle body direction and the tangent direction of the starting point of the lane line closest to the vehicle and the second angle between the vehicle body direction and the tangent direction of the ending point of the lane line closest to the vehicle is greater than a curve angle threshold, and the angle difference between adjacent heading angles in the preset time length is greater than the curve angle threshold, it is determined that there is an abnormal heading angle.

[0209] The vehicle body direction is determined according to each of the heading angles.

[0210] Optionally, if it is detected that the vehicle continuously changes lanes twice, and the directions of the two times of lane change are opposite, and the time interval between the two times of lane change is less than a vehicle body return window time, it is determined that the vehicle is in a vehicle body return state.

[0211] Optionally, the acquisition unit 710 is further configured to:

[0212] acquire an image output by a visual device arranged in the vehicle, and identify a lane line in the image;

[0213] acquire lane line information from the high-definition map data according to the driving information and a visual angle of the vehicle;

[0214] The trajectory determination unit 730 includes:

[0215] a comparison module 733 configured to compare information of the lane line in the image with information of the lane line acquired from the high-definition map data to obtain a comparison result, and determine an actual position of the vehicle according to the comparison result;

[0216] an updating module 734 configured to update the lateral movement distance according to the actual position.

[0217] Correspondingly, the trajectory determination unit 730 is further configured to update the position and posture of the vehicle at the current time according to the updated lateral movement distance.

[0218] Optionally, the comparison module 733 is specifically configured to:

[0219] determine a candidate position in each lane according to the last position;

[0220] determine a probability that the vehicle is at each candidate position according to the lane line in the image and the lane line in the high-definition map data;

[0221] determine the actual position of the vehicle according to each of the probabilities.

[0222] Optionally, the comparison module 733 is specifically configured to determine the candidate position in each lane according to the distance of the previous time position from the lane lines on both sides of the lane to which the previous time position belongs.

[0223] The proportion of the distance of the previous time position from the lane lines on both sides of the lane to which the previous time position belongs is the same as the proportion of the distance of the candidate position from the lane lines on both sides of the lane to which the candidate position belongs.

[0224] Optionally, the acquisition unit 710 is further configured to acquire preset vehicle speed compensation information and heading angle change rate compensation information if the confidence degree indicates that the positioning result is valid.

[0225] The device further includes a compensation unit 750 configured to:

[0226] acquire a real-time speed of the vehicle, and compensate the real-time speed by using the preset vehicle speed compensation information to obtain a compensated vehicle speed;

[0227] acquire a heading angle change rate of the vehicle, and compensate the heading angle change rate by using the preset heading angle change rate compensation information to obtain a compensated heading angle change rate;

[0228] The trajectory determination unit 730 is further configured to:

[0229] determine the driving trajectory of the vehicle according to the compensated vehicle speed and the compensated heading angle change rate.

[0230] The specific principles and implementation manners of the device provided in the embodiment are similar to those of the embodiment shown in Figure 3 and will not be described here.

[0231] Figure 9 A structural diagram of a vehicle-mounted device according to an exemplary embodiment of the present application.

[0232] As shown in Figure 9 , the vehicle-mounted device provided in the embodiment includes:

[0233] a memory 91;

[0234] a processor 92; and

[0235] a computer program;

[0236] The computer program is stored in the memory 91 and configured to be executed by the processor 92 to implement any one of the methods for determining a driving trajectory as described above.

[0237] The embodiment further provides a computer readable storage medium having a computer program stored thereon,

[0238] The computer program is executed by a processor to implement any one of the above methods for determining a driving trajectory.

[0239] The embodiment also provides a computer program including program codes for executing any one of the above methods for determining a driving trajectory when a computer runs the computer program.

[0240] Those skilled in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction related hardware. The foregoing program can be stored in a computer readable storage medium. The program executes the steps of the above-mentioned method embodiments when executed; and the foregoing storage medium includes ROM, RAM, magnetic disk or optical disk and various media that can store program codes.

[0241] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of determining a travel trajectory, characterized by, The method comprises the following steps: acquiring a confidence degree of a positioning result output by a combined navigation system arranged in a vehicle, and acquiring a last position of the vehicle and high-definition map data if the confidence degree indicates that the positioning result is invalid; determining information of a local lane based on the last position and the high-definition map data; acquiring a real-time speed of the vehicle, determining driving information of the vehicle based on the information of the local lane and the real-time speed, and determining a driving track of the vehicle based on the driving information, the driving track being used to determine a position of the vehicle; acquiring preset vehicle speed compensation information and heading angle change rate compensation information if the confidence degree indicates that the positioning result is valid; acquiring a real-time speed of the vehicle, and compensating the real-time speed by using the preset vehicle speed compensation information to obtain a compensated vehicle speed; acquiring a heading angle change rate of the vehicle, and compensating the heading angle change rate by using the preset heading angle change rate compensation information to obtain a compensated heading angle change rate; determining the driving track of the vehicle based on the compensated vehicle speed and the compensated heading angle change rate; the information of the local lane comprises a curve equation of a lane line; the step of determining the driving information of the vehicle based on the information of the local lane and the real-time speed comprises the following steps: determining a displacement of the vehicle based on the real-time speed and a time difference between a time when the last position is acquired and a current time; integrating a curve equation of a lane line closest to the vehicle to obtain a lateral movement distance, a longitudinal movement distance and a heading angle increment of the vehicle; the step of determining the driving track of the vehicle based on the driving information comprises the following step: superimposing the lateral movement distance, the longitudinal movement distance and the heading angle increment on the last position of the vehicle to obtain a position and posture of the vehicle at a current time, wherein the driving track comprises continuous position and postures of the vehicle.

2. The method of claim 1, wherein, the step of determining the information of the local lane based on the last position and the high-definition map data comprises the following steps: acquiring lane line information with a distance less than a preset value from the last position of the vehicle from the high-definition map data; generating a local lane line map based on the acquired lane line information; determining a curve equation of each lane line in the local lane line map based on position information of each lane line in the local lane line map and the last position of the vehicle.

3. The method of claim 2, wherein, the step of determining a curve equation of each lane line in the local lane line map based on position information of each lane line in the local lane line map and the last position of the vehicle comprises the following steps: converting a first coordinate of each lane line point included in each lane line in the local lane line map into a second coordinate in a vehicle body coordinate system based on the first coordinate of each lane line point and the last position of the vehicle, wherein the first coordinate is a coordinate in a coordinate system in the high-definition map; fitting each lane line point belonging to the same lane line based on the second coordinate of each lane line point to obtain the curve equation of each lane line in the local lane line map.

4. The method of claim 3, wherein, ​ The distance parameter for representing the distance between the vehicle and the lane line is included in the curve equation of the lane line; The method further comprises: According to the distance parameter included in the curve equation of each lane line, the distance between the vehicle and the nearest lane line is determined.

5. The method of claim 1, wherein, The driving information includes the heading angle increment of the vehicle; The method further comprises: According to each heading angle increment included in the driving information within the preset time length, the lateral offset of the vehicle within the preset time length is determined; If the lateral offset is greater than the detection threshold, whether the vehicle changes lanes is determined according to each heading angle of the vehicle; If it is determined that the vehicle changes lanes, the lane line closest to the vehicle is changed according to the lane changing situation.

6. The method of claim 5, wherein, Determining whether the vehicle changes lanes according to each heading angle of the vehicle comprises: According to each heading angle of the vehicle, whether any of the following situations exists is determined: The curve driving situation, the vehicle body back to normal situation, and the existence of an abnormal heading angle; If none of the above exists, it is determined that the vehicle is changing lanes; If the first angle between the direction of the vehicle body and the tangent direction of the starting point of the lane line closest to the vehicle at the current time and the second angle between the direction of the vehicle body and the tangent direction of the ending point of the lane line closest to the vehicle are greater than the curve angle threshold, and the angle difference between adjacent heading angles within the preset time length is less than the curve angle threshold, it is determined that the vehicle is in the curve driving situation; if the first angle between the direction of the vehicle body and the tangent direction of the starting point of the lane line closest to the vehicle at the current time and the second angle between the direction of the vehicle body and the tangent direction of the ending point of the lane line closest to the vehicle are greater than the curve angle threshold, and the angle difference between adjacent heading angles within the preset time length is greater than the curve angle threshold, it is determined that there is an abnormal heading angle; The direction of the vehicle body is determined according to each heading angle; If it is detected that the vehicle has changed lanes twice in succession, and the directions of the two suspected lane changes are opposite, and the time interval between the two suspected lane changes is less than the vehicle body back to normal window time, it is determined that the vehicle is in the vehicle body back to normal situation.

7. The method of claim 1, wherein, The method further comprises: Obtaining the image output by the visual device arranged in the vehicle, and identifying the lane line in the image; According to the last position, the lane line information is obtained from the high-precision map data in the perspective of the vehicle; According to the information of the lane line in the image and the information of the lane line obtained from the high-precision map data, the actual position of the vehicle is determined; The lateral movement distance is updated according to the actual position; Correspondingly, the position and posture of the vehicle at the current time are updated according to the updated lateral movement distance.

Images