CN-116198532-B - Vehicle control method, device and medium based on laser radar life prediction

CN116198532BCN 116198532 BCN116198532 BCN 116198532BCN-116198532-B

Abstract

The embodiment of the disclosure discloses a vehicle control method, device, equipment and medium based on laser radar life prediction, wherein the method comprises the steps of determining working parameters of a vehicle-mounted laser radar through a sensor data acquisition and processing module when the vehicle-mounted laser radar is in a working state, sending the working parameters to a preset server through the sensor data acquisition and processing module to predict the current failure rate of the vehicle-mounted laser radar through the preset server based on the working parameters or the working parameters and factory data of the vehicle-mounted laser radar, receiving the current failure rate of the vehicle-mounted laser radar issued by the preset server through an automatic driving decision planning module, and determining a vehicle control strategy through the automatic driving decision planning module based on the current failure rate and a plurality of preset thresholds matched with the working scene of the vehicle-mounted laser radar so as to control a vehicle based on the vehicle control strategy. The present disclosure improves the safety of a vehicle.

Inventors

WU KE
LIU YANAN
LUO SAI
YUAN JINTAO
LIU YOULIANG
XIE CAIXIA
WANG ZHIXIN

Assignees

驭势科技（北京）有限公司

Dates

Publication Date: 20260512
Application Date: 20211130

Claims (13)

1. A method of controlling a vehicle based on lidar life prediction, the method comprising: when the vehicle-mounted laser radar is in a working state, determining working parameters of the vehicle-mounted laser radar through a sensor data acquisition and processing module; The working parameters are sent to a preset server through the sensor data acquisition and processing module, so that the current failure rate of the vehicle-mounted laser radar is predicted through the preset server based on the working parameters or the working parameters and factory data of the vehicle-mounted laser radar; Receiving the current failure rate of the vehicle-mounted laser radar issued by the preset server through an automatic driving decision-making planning module; And determining a vehicle control strategy based on the current fault rate and a plurality of preset thresholds matched with the working scene of the vehicle-mounted laser radar through the automatic driving decision planning module so as to control the vehicle based on the vehicle control strategy.
2. The method of claim 1, wherein the automated driving decision planning module determining a vehicle control strategy based on the current failure rate and a preset plurality of thresholds matching an operating scenario of the on-board lidar comprises: if the current failure rate reaches a first-level threshold value matched with the working scene of the vehicle-mounted laser radar but does not reach a second-level threshold value matched with the working scene of the vehicle-mounted laser radar, determining that the vehicle control strategy sends prompt information for controlling a vehicle; if the current failure rate reaches the second-level threshold value but does not reach a third-level threshold value matched with the working scene of the vehicle-mounted laser radar, determining that the vehicle control strategy is to control the vehicle to run at a reduced speed, and turning on a double flashing lamp; if the current failure rate reaches the third-level threshold value but does not reach a fourth-level threshold value matched with the working scene of the vehicle-mounted laser radar, determining the vehicle control strategy to control the vehicle to run to a set maintenance position so as to maintain the vehicle; and if the current failure rate reaches the fourth-level threshold, determining the vehicle control strategy to control the vehicle to run to a set parking position for parking.
3. The method of claim 2, wherein prior to controlling the vehicle based on the vehicle control strategy, further comprising: Receiving the vehicle perception positioning information sent by the automatic driving perception positioning module through the automatic driving decision planning module; The automatic driving perception positioning module determines the vehicle perception positioning information based on the vehicle-mounted sensor data sent by the sensor data acquisition and processing module.
4. The method of claim 3, wherein the controlling the vehicle based on the vehicle control strategy comprises: Determining a planned driving path of the vehicle according to the vehicle perceived positioning information and the vehicle control strategy by the automatic driving decision planning module, and determining an automatic driving control instruction according to the planned driving path; The automatic driving control instruction is sent to an automatic driving chassis control module through the automatic driving decision planning module; and controlling the vehicle according to the automatic driving control instruction through the automatic driving chassis control module.
5. The method of claim 4, wherein the controlling the vehicle by the autopilot chassis control module in accordance with the autopilot control instructions comprises at least one of: transmitting a brake control command to a brake-by-wire system of the vehicle; transmitting a steering control command to an electronic power steering system of the vehicle; Sending a lamp off control instruction to a double flashing lamp of the vehicle; And sending a driving control instruction to a whole vehicle controller of the vehicle.
6. The method of any one of claims 1-5, wherein the determining, by a sensor data acquisition and processing module, an operating parameter of the vehicle-mounted lidar comprises: Acquiring the current temperature and the current humidity based on a vehicle-mounted temperature and humidity sensor; Acquiring a current acceleration and a current angular velocity of a vehicle based on an inertial measurement unit of the vehicle, wherein the current acceleration and the current angular velocity are used for determining a current vibration intensity; the operating parameters include the current temperature, the current humidity, the current acceleration, and the current angular velocity.
7. The method of claim 6, wherein the pre-set server predicts a current failure rate of the vehicle-mounted lidar based on the operating parameters and factory data of the vehicle-mounted lidar, comprising: determining an environmental coefficient based on a ratio between the current temperature and a preset reference temperature, a ratio between the current humidity and a preset reference humidity, a ratio between the current vibration intensity and a preset reference vibration intensity, and a preset coefficient; predicting the current failure rate of the vehicle-mounted laser radar according to the environmental coefficient and the factory data of the vehicle-mounted laser radar.
8. The method of claim 7, wherein if the sensor data acquisition and processing module cannot determine the operating parameters of the vehicle-mounted lidar, the environmental coefficients are obtained by table look-up: determining the weather proportion of each preset weather type, the weather proportion of each preset weather type and the road surface proportion of each preset road condition type in the working scene of the vehicle-mounted laser radar; Determining weights corresponding to the preset weather types respectively through table lookup, weights corresponding to the preset weather types respectively and weights corresponding to the preset road condition types respectively; According to the climate duty ratio of each preset climate type in the working scene of the vehicle-mounted laser radar and the weight corresponding to each preset climate type, weighting and summing are carried out, so that a first numerical value is obtained; weighting and summing according to weather duty ratios of all preset weather types in the working scene of the vehicle-mounted laser radar and weights corresponding to all the preset weather types respectively to obtain a second numerical value; weighting and summing according to the road surface duty ratio of each preset road condition type and the weights respectively corresponding to each preset road condition type in the working scene of the vehicle-mounted laser radar to obtain a third numerical value; and determining the sum of the first value, the second value and the third value as the environment coefficient.
9. The method of claim 6, wherein the operating parameters further comprise at least one of an operating voltage, an operating current, an operating temperature, and a motor speed of the vehicle lidar when in operation.
10. The method of claim 9, wherein the predicting, by the preset server, a current failure rate of the vehicle-mounted lidar based on the operating parameter, comprises: and inputting the working parameters into a trained machine learning model to obtain the current failure rate of the vehicle-mounted laser radar.
11. A laser radar life prediction-based vehicle control device, comprising: The sensor data acquisition and processing module is used for determining working parameters of the vehicle-mounted laser radar when the vehicle-mounted laser radar is in a working state, and sending the working parameters to a preset server so as to predict the current failure rate of the vehicle-mounted laser radar through the preset server based on the working parameters or the working parameters and factory data of the vehicle-mounted laser radar; and the automatic driving decision planning module is used for receiving the current failure rate of the vehicle-mounted laser radar issued by the preset server, and determining a vehicle control strategy based on the current failure rate and a plurality of preset thresholds matched with the working scene of the vehicle-mounted laser radar so as to control the vehicle based on the vehicle control strategy.
12. An electronic device, the electronic device comprising: one or more processors; a storage means for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-10.
13. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any one of claims 1-10.

Description

Vehicle control method, device and medium based on laser radar life prediction Technical Field The disclosure relates to the technical field of automatic driving, in particular to a laser radar life prediction-based vehicle control method, a laser radar life prediction-based vehicle control device, electronic equipment and a storage medium. Background In the unmanned field, how to ensure the running safety of a vehicle is a primary problem. Aging of each part of the vehicle can have a certain influence on the running safety of the vehicle. For example, the vehicle-mounted lidar has a very large influence on the running safety of the vehicle if it ages. However, there is currently no relevant solution for monitoring the aging of vehicle-mounted lidar. Disclosure of Invention In order to solve the technical problems or at least partially solve the technical problems, embodiments of the present disclosure provide a vehicle control method, device, electronic device and storage medium based on laser radar life prediction, so as to achieve the purpose of improving vehicle driving safety. In a first aspect, an embodiment of the present disclosure provides a vehicle control method based on lidar lifetime prediction, the method comprising: when the vehicle-mounted laser radar is in a working state, determining working parameters of the vehicle-mounted laser radar through a sensor data acquisition and processing module; The working parameters are sent to a preset server through the sensor data acquisition and processing module, so that the current failure rate of the vehicle-mounted laser radar is predicted through the preset server based on the working parameters or the working parameters and factory data of the vehicle-mounted laser radar; Receiving the current failure rate of the vehicle-mounted laser radar issued by the preset server through an automatic driving decision-making planning module; And determining a vehicle control strategy based on the current fault rate and a plurality of preset thresholds matched with the working scene of the vehicle-mounted laser radar through the automatic driving decision planning module so as to control the vehicle based on the vehicle control strategy. In a second aspect, embodiments of the present disclosure further provide a vehicle control apparatus based on lidar lifetime prediction, the apparatus comprising: The sensor data acquisition and processing module is used for determining working parameters of the vehicle-mounted laser radar when the vehicle-mounted laser radar is in a working state, and sending the working parameters to a preset server so as to predict the current failure rate of the vehicle-mounted laser radar through the preset server based on the working parameters or the working parameters and factory data of the vehicle-mounted laser radar; and the automatic driving decision planning module is used for receiving the current failure rate of the vehicle-mounted laser radar issued by the preset server, and determining a vehicle control strategy based on the current failure rate and a plurality of preset thresholds matched with the working scene of the vehicle-mounted laser radar so as to control the vehicle based on the vehicle control strategy. In a third aspect, the disclosed embodiments also provide an electronic device including one or more processors, a storage device for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the lidar lifetime prediction-based vehicle control method as described above. In a fourth aspect, the presently disclosed embodiments also provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a laser radar life prediction based vehicle control method as described above. According to the vehicle control method based on the laser radar life prediction, when the vehicle-mounted laser radar is in a working state, working parameters of the vehicle-mounted laser radar are determined through the sensor data acquisition and processing module, the working parameters are sent to the preset server through the sensor data acquisition and processing module, so that the current failure rate of the vehicle-mounted laser radar is predicted through the preset server based on the working parameters or the working parameters and factory data of the vehicle-mounted laser radar, the current failure rate of the vehicle-mounted laser radar issued by the preset server is received through the automatic driving decision planning module, a vehicle control strategy is determined through the automatic driving decision planning module based on the current failure rate and a plurality of preset thresholds matched with the working scene of the vehicle-mounted laser radar, and therefore safety of a vehicle is improved through technical means of controlling the vehicle based on the vehicle control strategy. Specifica