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EP-4095007-B1 - METHOD FOR DETERMINING PASSING BY SELF-DRIVING VEHICLE AND RELATED DEVICE

EP4095007B1EP 4095007 B1EP4095007 B1EP 4095007B1EP-4095007-B1

Inventors

  • LIU, JIANGJIANG

Dates

Publication Date
20260506
Application Date
20201231

Claims (12)

  1. A method for determining passage of an autonomous vehicle, comprising: acquiring (S310) information about an intersection on a driving route of the autonomous vehicle, wherein the information about the intersection comprises lane data and traffic light corresponding to the lane data; acquiring (S320) a historical trajectory of an obstacle in the intersection within a specific time, wherein the obstacle is a vehicle or a pedestrian; acquiring (S330), by matching the historical trajectory of the obstacle with center lines of respective lanes in the lane data, a lane with smallest matching error; determining (S340) that a state of the traffic light corresponding to the lane with the smallest matching error is in a passable state, wherein the lane with the smallest matching error is a lane where the obstacle is located; determining that there are multiple obstacles and that there is a logical contradiction between the state of the traffic lights at the intersection; and determining that the state of the traffic light corresponding to the lane with the largest number of obstacles is in the passable state.
  2. The method according to claim 1, further comprising: acquiring a state of a traffic light on the driving route of the autonomous vehicle; verifying, when the traffic light corresponding to the lane with the smallest matching error is the traffic light on the driving route of the autonomous vehicle, whether the traffic light on the driving route of the autonomous vehicle is in the passable state; or verifying, when the traffic light corresponding to the lane with the smallest matching error is not the traffic light on the driving route of the autonomous vehicle, whether the traffic light on the driving route of the autonomous vehicle is in the passable state according to logical relationship between traffic lights at the intersection.
  3. The method according to claim 1, wherein the acquiring (S320) the historical trajectory of the obstacle in the intersection within the specific time comprises: tracking historical trajectory points of the obstacle through a control algorithm, and determining an obtained tracking trajectory as the historical trajectory of the obstacle; wherein an interpolation is performed on the historical trajectory, and the historical trajectory comprises coordinates and orientations of respective interpolated points, and an orientation of an interpolated point is a moving direction of the obstacle.
  4. The method according to claim 3, wherein the acquiring (S330), by matching the historical trajectory of the obstacle with center lines of respective lanes in the lane data, the lane with smallest matching error comprises: acquiring, by matching a shape and an orientation of the historical trajectory of the obstacle with a shape and an extension direction of the center lines of respective lanes in the lane data, the lane with the smallest matching error; wherein an interpolation is performed on the center lines of respective lanes, and a center line of a lane comprises coordinates and orientations of respective interpolated points.
  5. The method according to claim 1, wherein the acquiring (S330), by matching the historical trajectory of the obstacle with center lines of respective lanes in the lane data, the lane with smallest matching error comprises: acquiring, by matching the historical trajectory of the obstacle with the center lines of respective lanes in the lane data through a curve similarity matching algorithm, the lane with the smallest matching error.
  6. The method according to claim 5, wherein an interpolation is performed on the historical trajectory, and the historical trajectory comprises coordinates and orientations of respective interpolated points, and an orientation of an interpolated point is a moving direction of the obstacle; another interpolation is performed on the center lines of respective lanes, and a center line of a lane comprises coordinates and orientations of respective interpolated points; and the acquiring, by matching the historical trajectory of the obstacle with the center lines of respective lanes in the lane data through the curve similarity matching algorithm, the lane with the smallest matching error comprises: calculating a distance from each interpolated point of the historical trajectory to a nearest interpolated point on the center lines of respective lanes in the lane data, and calculating an orientation difference between each interpolated point of the historical trajectory and the nearest interpolated point on the center lines of respective lanes in the lane data; calculating a sum of absolute values of the distance and the orientation difference between the historical trajectory and the center lines of respective lanes in the lane data; and determining a lane with a smallest sum of the absolute values in the lane data as the lane with the smallest matching error; wherein, the orientation difference is an angle between an orientation of an interpolated point of the historical trajectory and an orientation of an interpolated point of a center line of a lane.
  7. The method according to claim 1, wherein the information about the intersection further comprises a polygon formed by sequentially connecting cut-off lines of respective lanes, and the acquiring (S320) the historical trajectory of the obstacle in the intersection within the specific time comprises: acquiring the historical trajectory of the obstacle in the intersection within the specific time and within the polygon.
  8. An apparatus for determining passage of an autonomous vehicle, comprising: an acquiring module (510), configured to acquire information about an intersection on a driving route of the autonomous vehicle and a historical trajectory of an obstacle in the intersection within a specific time, wherein the information about the intersection comprises lane data and traffic light corresponding to the lane data, and the obstacle is a vehicle or a pedestrian; a matching module (520), configured to acquire, by matching the historical trajectory of the obstacle with center lines of respective lanes in the lane data, a lane with smallest matching error; and a determining module (530), configured to determine that a state of the traffic light corresponding to the lane with the smallest matching error is in a passable state; wherein the lane with the smallest matching error is a lane where the obstacle is located, wherein the determining module (530) is further configured to: determine that there are multiple obstacles and that there is a logical contradiction between the state of the traffic lights at the intersection; and determine that the state of the traffic light corresponding to the lane with the largest number of obstacles is in the passable state.
  9. The apparatus according to claim 8, wherein the acquiring module (510) is further configured to acquire a state of a traffic light on the driving route of the autonomous vehicle; the matching module (520) is further configured to verify, when the traffic light corresponding to the lane with the smallest matching error is the traffic light on the driving route of the autonomous vehicle, whether the traffic light on the driving route of the autonomous vehicle is in the passable state; or verify, when the traffic light corresponding to the lane with the smallest matching error is not the traffic light on the driving route of the autonomous vehicle, whether the traffic light on the driving route of the autonomous vehicle is in the passable state according to logical relationship between traffic lights at the intersection.
  10. The apparatus according to claim 8, wherein the acquiring module (510) is specifically configured to: track historical trajectory points of the obstacle through a control algorithm, and determine an obtained tracking trajectory as the historical trajectory of the obstacle; wherein an interpolation is performed on the historical trajectory, and the historical trajectory comprises coordinates and orientations of respective interpolated points, and an orientation of an interpolated point is a moving direction of the obstacle.
  11. The apparatus according to claim 8, wherein the matching module (520) is specifically configured to: acquire, by matching the historical trajectory of the obstacle with the center lines of respective lanes in the lane data through a curve similarity matching algorithm, the lane with the smallest matching error.
  12. A computer-readable storage medium storing a computer program, wherein the computer program is used for, when being executed by a processor, implementing the method according to any one of claims 1 to 7.

Description

TECHNICAL FIELD The disclosure relates to the field of computer and communication technologies, and in particular, to a method and an apparatus for determining the passage of an autonomous vehicle, a computer-readable storage medium, and an electronic device. BACKGROUND Typically, when an autonomous vehicle determines the state of the traffic light in its travel direction, it needs to collect the state of multiple traffic lights at the intersection, and then determines the state of the traffic light in its travel direction based on the logical relationship between the multiple traffic lights and the perception results. It should be noted that the information disclosed in the background section is only used to enhance the understanding of the background of the disclosure, and therefore may include information that does not constitute the prior art known to those of ordinary skill in the art. Related technologies are known from patent documents CN110660256A and US 2019/197902 A1. SUMMARY The invention is specified by the independent claims. Preferred embodiments are defined in the dependent claims. Embodiments of the invention provide a method, an apparatus for determining passage of an autonomous vehicle, and a computer-readable storage medium, thereby determining passage condition of the autonomous vehicle on its driving route. Other characteristics and advantages of the invention will become apparent through the following detailed description, or partly learned through implementation of the disclosure. According to an aspect of the invention there is provided a method for determining passage of an autonomous vehicle as defined by the independent claim 1. According to another aspect of the invention, there is provided an apparatus for determining passage of an autonomous vehicle as defined by the independent claim 8. According to still another aspect of the invention, there is provided a computer-readable storage medium storing a computer program as defined by the independent claim 12. It should be understood that the following detailed description are only exemplary and explanatory without limiting the scope of the invention which is defined by the appended claims. BRIEF DESCRIPTION OF THE DRAWINGS The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the disclosure, and are used together with the specification to explain the principle of the disclosure. Obviously, the drawings in the following description are only some embodiments of the disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings: FIG. 1 shows a schematic diagram of an exemplary system architecture in which the method or apparatus for determining passage of the autonomous vehicle according to some embodiments of the disclosure can be applied;FIG. 2 shows a block diagram of a computer system suitable for implementing the electronic device according to some embodiments of the disclosure;FIG. 3 schematically shows a flowchart of the method for determining passage of the autonomous vehicle according to some embodiments of the disclosure;FIG. 4 is a schematic diagram of an intersection according to some embodiments of the disclosure;FIG. 5 schematically shows a block diagram of the apparatus for determining passage of the autonomous vehicle according to some embodiments of the disclosure;FIG. 6 schematically shows a block diagram of the apparatus for determining passage of the autonomous vehicle according to some other embodiments of the disclosure; andFIG. 7 schematically shows a block diagram of the apparatus for determining passage of the autonomous vehicle according to some other embodiments of the disclosure. DETAILED DESCRIPTION Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in various forms, and should not be construed as being limited to the examples set forth herein. Rather, these embodiments are provided so that the disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art. In addition, the described features, structures, or characteristics can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to give a sufficient understanding of the embodiments of the disclosure. However, those skilled in the art will realize that the technical solutions of the disclosure can be practiced without one or more of the specific details. Alternatively, other methods, components, devices, steps, and the like can be used. In other cases, well-known methods, devices, implementations or operations are not shown or described in detail in order to avoid obscuring various aspects of the disclosure. The block diagrams sho