CN-122029574-A - Method and processor for identifying stationary traffic signs

Abstract

The present disclosure relates to a method for identifying stationary traffic signs (30), wherein a point cloud (32) of an environment (22) is obtained by a LiDAR sensor (10) included in a vehicle (20), the stationary traffic signs (30) are identified within the point cloud (32), and visual information (34) of the traffic signs (30) is extracted using contrast of intensity information, wherein the intensity information has been obtained by the LiDAR sensor (10). The disclosure also relates to a processor, a LiDAR sensor (10), a computing unit (24), a vehicle (20), and a computer program product.

Inventors

• A. Renard
• U. Nasir
• B. Amalendra

Assignees

• 法雷奥开关和传感器有限责任公司

Dates

Publication Date

20260512

Application Date

20240919

Priority Date

20231011

Claims (15)

1. 1. A method for identifying stationary traffic signs (30), wherein, A point cloud (32) of an environment (22) is obtained by a LiDAR sensor (10) included in a vehicle (20), Identifying the stationary traffic sign (30) within the point cloud (32), Visual information (34) of the traffic sign (30) is extracted using contrast of intensity information, wherein the intensity information has been obtained by the LiDAR sensor (10).
2. 2. The method of claim 1, wherein the traffic sign (30) is identified within the point cloud (32) using depth information included in the point cloud (32).
3. 3. The method according to claim 1 or 2, wherein the identification of the stationary traffic sign (30) comprises: tracking the location of the traffic sign (30) over a plurality of frames captured by the LiDAR sensor (10), and -Confirming a stationary characteristic of the traffic sign (30) based on the plurality of captured frames.
4. 4. The method according to any of the preceding claims, wherein the identifying of the traffic sign (30) comprises identifying an area within the point cloud comprising the traffic sign (30) and extracting a shape of the traffic sign (30).
5. 5. The method according to claim 4, wherein the identification of the traffic sign (30) is performed using the extracted shape of the traffic sign (30).
6. 6. The method according to any of the preceding claims, wherein the visual information (34) is extracted using a contrast of intensity information, wherein the intensity information is comprised in the point cloud (32).
7. 7. The method according to any one of the preceding claims, wherein the extracted visual information (34) comprises characters, letters and/or symbols.
8. 8. The method according to any of the preceding claims, wherein the visual information (34) of the traffic sign (30) is identified using image recognition based on the extracted visual information (34), and wherein the identified visual information (34) is output.
9. 9. The method according to claim 8, wherein the extraction and/or identification of visual information (34) is performed using the extracted shape of the traffic sign (30).
10. 10. The method of any of the preceding claims, wherein the method is performed at least partially while a vehicle (20) comprising the LiDAR sensor (10) is in motion.
11. 11. A processor for identifying stationary traffic signs (30), the processor being configured to perform the steps of the method according to any one of claims 1 to 10.
12. 12. A LiDAR sensor (10) comprised in a vehicle (20), the LiDAR sensor (10) comprising a control unit (18), the control unit (18) comprising the processor according to claim 11.
13. 13. A computing unit (24) comprised in a vehicle (20), the computing unit (24) comprising a processor according to claim 11.
14. 14. A vehicle (20) comprising the LiDAR sensor (10) according to claim 12 and/or the computing unit according to claim 13.
15. 15. A computer program product comprising instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 10.

Description

Method and processor for identifying stationary traffic signs Technical Field The present disclosure relates to a method and processor for identifying stationary traffic signs. The invention also relates to a LiDAR sensor, a computing unit, a vehicle and a computer program product. Background Modern vehicles (e.g., automobiles, vans, trucks, motorcycles, etc.) may include sensor systems whose data is used for driver information and/or by driver assistance systems. Sensor systems are continually being developed for various functions, such as for acquiring environmental information in the short-range and long-range of a vehicle (e.g., a passenger car or commercial car). Based on the acquired data, a model of the environment of the vehicle may be generated and a change in the environment of the vehicle may be responded to. The sensor system may also be used as a sensor for a driver assistance system, in particular for autonomous or semi-autonomous vehicle control. They may be used, for example, to detect obstacles and/or other road users in front of, behind, or in blind spot areas of the vehicle. The sensor system may be based on different sensor principles, such as radar, ultrasound, optics. An important optical sensor principle for example for environmental detection of vehicles is the LiDAR technology (LiDAR: light detection and ranging). The LiDAR sensor includes an optical transmitting device and an optical receiving device. The transmitting device emits an optical signal, which may be continuous or pulsed. In addition, the optical signal may be modulated. Electromagnetic waves in the form of laser beams in the ultraviolet, visible or infrared range can be used as optical signals in LiDAR sensors. The light of the optical signal is received by the optical receiving device after being reflected from an object in the detection area of the LiDAR sensor. For example, the optical signal may be evaluated according to a time-of-flight method, and the spatial position and distance of the object at which the reflection occurs may be determined. In addition, the relative speed may be determined. Reflected or reflected light is understood to mean any light that is reflected back and shall also include in particular light that is reflected back by scattering or absorption of the emission. The scanning LiDAR sensor emits an optical signal that moves in a scanning direction. The scanning movement may be achieved by steering the beam of the optical signal using a beam steering device. In CN108009474a, a method and apparatus for extracting text written on a vehicle are described. The extraction is based on the use of a fixed laser ranging device. Disclosure of Invention A method for identifying stationary traffic signs, comprising: LiDAR sensors included in a vehicle obtain a point cloud of the environment of the vehicle. Identifying stationary traffic signs within the point cloud. The contrast of the intensity information, which has been obtained by the LiDAR sensor, is used to extract visual information of the traffic sign. LiDAR sensors may provide raw data including a point cloud that includes measured values, particularly depth values, of the environment of a vehicle. To create a point cloud, a LiDAR sensor includes a light delivery device that emits an optical signal. The optical signal is reflected in the environment of the LiDAR sensor. The optical receiving device of the LiDAR sensor receives the reflection of the optical signal. The transmitted and received optical signals may be evaluated to obtain a measurement value. The measurements including transmitting, receiving and evaluating may be repeated. The collection of measurements for the various points of the environment forms a point cloud. A pulsed LiDAR sensor will emit an optical signal in pulses. Each pulse of the optical signal may provide a measurement of a point. Scanning the LiDAR sensor will cause the optical signal to perform a scanning motion, thereby continuously scanning points of the environment. A point cloud may be understood as a set of points, where each point comprises a respective coordinate in a two-dimensional or three-dimensional coordinate system. In the case of a three-dimensional point cloud, the three-dimensional coordinates may be determined, for example, by the direction of incidence of the reflected optical signal and the corresponding time of flight or radial distance measured for that respective point. In other words, the three-dimensional coordinate system may be a three-dimensional polar coordinate system. However, for each point, the information may also be given in cartesian coordinates. In addition to spatial information (i.e., two-dimensional or three-dimensional coordinates), the point cloud may also store additional information or measurements of individual points, such as the intensity of the corresponding received optical signal. The method provides reliable traffic sign recognition and identification of visual infor