Vehicle automatic driving control method and device and storage medium

Abstract

The invention discloses a vehicle automatic driving control method and device and a storage medium, and the method comprises the following steps: obtaining the traffic conditions of an unmanned vehicle from a starting point to a target point, the traffic conditions including a traffic light condition, an obstacle condition and a speed limit condition; acquiring corresponding environment information and driving information according to the traffic condition to make an automatic driving decision; and enabling the unmanned vehicle to execute an automatic driving operation based on the automatic driving decision. According to the invention, the automatic driving decision is made by acquiring the traffic light condition, the obstacle condition and the speed limit condition in the driving process of the unmanned vehicle and acquiring the corresponding environment information and driving information, so that the unmanned vehicle can perform efficient and safe automatic driving control on different traffic conditions in the driving process; the method is suitable for long-distance and complex road conditions, operation management is more flexible, control is more effective, and the method is more suitable for the requirement of automatic driving of the vehicle.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and specifically to a vehicle autonomous driving control method, device and storage medium. Background Art

[0002] Self-driving cars, also known as driverless cars, computer-driven cars, or wheeled mobile robots, are intelligent vehicles that are unmanned by computer systems. With the popularity of self-driving cars, they can be used as taxis or public transportation. When using self-driving cars, passengers need to enter their destinations. Self-driving cars generate driving routes based on their current locations and destinations, and drive according to the generated driving routes.

[0003] However, the road conditions on the driving route are not static, and there are different traffic conditions. This makes it impossible for the vehicle's autonomous driving to adapt to different traffic conditions and to deal with various complex traffic conditions safely and efficiently. Summary of the invention

[0004] In order to overcome the shortcomings of the above-mentioned background technology that the road conditions on the driving route of the autonomous driving vehicle are not static and there are different traffic conditions, which makes the vehicle autonomous driving unable to adapt to different traffic conditions and unable to safely and efficiently deal with various complex traffic conditions, the purpose of the present invention is to provide a vehicle autonomous driving control method.

[0005] In order to achieve the above purpose, the present invention adopts the following technical solution:

[0006] A first aspect of the present invention provides a vehicle automatic driving control method, comprising the following steps:

[0007] Obtaining the traffic conditions of the unmanned vehicle from the starting point to the target point, wherein the traffic conditions include traffic light conditions, obstacle conditions, and speed limit conditions;

[0008] Obtaining corresponding environmental information and driving information according to the traffic conditions to make an autonomous driving decision;

[0009] Based on the autonomous driving decision, the unmanned vehicle performs an autonomous driving operation.

[0010] Compared with the prior art, the beneficial effects of the present invention are: by obtaining the traffic light conditions, obstacle conditions and speed limit conditions of the unmanned vehicle during its driving, and obtaining corresponding environmental information and driving information to make automatic driving decisions, the unmanned vehicle can perform efficient and safe automatic driving control under different traffic conditions during driving, adapt to long-distance and complex road conditions, make operation management more flexible, control more effective, and better meet the needs of vehicle automatic driving.

[0011] In some possible implementations, when the traffic condition is a traffic light condition, the steps for executing the autonomous driving decision include the following:

[0012] Obtain the vehicle's driving path through the traffic lights, the vehicle's current actual speed, and the current traffic light status information;

[0013] Obtaining the expected time to pass the traffic light according to the traffic light status information;

[0014] The expected acceleration and expected speed of the unmanned vehicle are generated based on the expected time to pass the traffic light, the driving path and the actual speed.

[0015] In some possible implementations, when the traffic condition is an obstacle condition, the steps of executing the autonomous driving decision include the following:

[0016] Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle;

[0017] Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

[0018] In some possible implementations, when the traffic condition is a speed limit condition, the steps for executing the autonomous driving decision include the following:

[0019] Get the speed limit information and speed limit path of the speed limit section;

[0020] Get the safe distance between each speed limit path;

[0021] A safe acceleration is obtained based on the safety distances between the speed limit paths and the speed limit information.

[0022] A second aspect of the present invention provides a vehicle automatic driving control device, comprising:

[0023] Traffic condition acquisition module: used to obtain the traffic conditions of the unmanned vehicle from the starting point to the target point, including traffic light conditions, obstacle conditions and speed limit conditions;

[0024] An autonomous driving decision generation module: obtaining corresponding environmental information and driving information according to the traffic conditions to make an autonomous driving decision;

[0025] Autonomous driving module: enables the unmanned vehicle to perform autonomous driving operations based on the autonomous driving decision.

[0026] In some possible implementations, when the traffic condition is a traffic light condition, the steps for executing the autonomous driving decision include the following:

[0027] Obtain the vehicle's driving path through the traffic lights, the vehicle's current actual speed, and the current traffic light status information;

[0028] Obtaining the expected time to pass the traffic light according to the traffic light status information;

[0029] The expected acceleration and expected speed of the unmanned vehicle are generated based on the expected time to pass the traffic light, the driving path and the actual speed.

[0030] In some possible implementations, when the traffic condition is an obstacle condition, the steps of executing the autonomous driving decision include the following:

[0031] Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle;

[0032] Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

[0033] In some possible implementations, when the traffic condition is an obstacle condition, the steps of executing the autonomous driving decision include the following:

[0034] Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle;

[0035] Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

[0036] In some possible implementations, when the traffic condition is a speed limit condition, the steps for executing the autonomous driving decision include the following:

[0037] Get the speed limit information and speed limit path of the speed limit section;

[0038] Get the safe distance between each speed limit path;

[0039] A safe acceleration is obtained based on the safety distances between the speed limit paths and the speed limit information.

[0040] According to a third aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned vehicle automatic driving control method are implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flowchart of the overall steps of the vehicle automatic driving control method according to an embodiment of the present invention;

[0042] Figure 2 This is a flow chart of the execution steps of the automatic driving decision-making in the case of a traffic light condition according to an embodiment of the present invention;

[0043] Figure 3 A flowchart of the execution steps of the autonomous driving decision when there is an obstacle in the embodiment of the present invention;

[0044] Figure 4 This is a flow chart of the execution steps of autonomous driving decision-making when the speed limit is in the embodiment of the present invention.

[0045] Figure 5 Schematic diagram of the structure of an automatic driving control device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0047] See attached Figure 1 As shown, the vehicle automatic driving control method provided in this embodiment includes the following steps:

[0048] S1: Obtain the traffic conditions of the unmanned vehicle from the starting point to the target point, wherein the traffic conditions include traffic light conditions, obstacle conditions and speed limit conditions.

[0049] Specifically, when the unmanned vehicle encounters traffic lights during autonomous driving, the unmanned vehicle uses visual sensors and three-dimensional laser radars to capture or collect information about traffic lights and obstacles within a certain range, and collects speed limit information through the map navigation system.

[0050] S2: Obtain corresponding environmental information and driving information according to the traffic conditions to make an autonomous driving decision.

[0051] When the traffic situation is a traffic light situation, see the attached Figure 2 As shown, the execution steps of the autonomous driving decision include the following:

[0052] S211: Obtaining the driving path of the vehicle and the traffic light, the current actual speed of the vehicle and the current traffic light status information;

[0053] S212: Obtaining an expected time to pass the traffic light according to the traffic light status information;

[0054] S213: Generate an expected acceleration and an expected speed of the unmanned vehicle based on the expected time to pass the traffic light, the driving path and the actual speed.

[0055] By using the driving path of the vehicle and the traffic lights, the current actual speed of the vehicle and the current traffic light status information, the unmanned vehicle can not only drive economically and smoothly when passing through traffic light intersections, but also ensure the safety of autonomous driving with the expected acceleration and expected speed.

[0056] When the traffic situation is an obstacle situation, see the attached Figure 3 As shown, the execution steps of the autonomous driving decision include the following:

[0057] S221: Obtaining a current first actual speed of the unmanned vehicle and a current second actual speed of the obstacle;

[0058] S222: Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

[0059] The expected safe driving speed of the unmanned vehicle can be determined through the distance value between the human vehicle and the obstacle, the first actual speed and the second actual speed, so that the unmanned vehicle can maintain a safe distance from the obstacle at the expected safe driving speed when facing an obstacle, making autonomous driving safer.

[0060] When the traffic situation is speed limit, see the attached Figure 4 As shown, the execution steps of the autonomous driving decision include the following:

[0061] S231: Obtain speed limit information and speed limit path of the speed limit section;

[0062] S232: Obtaining the safety distance between each speed-limited path;

[0063] S233: Acquire a safe acceleration based on the safety distances between the speed limit paths and the speed limit information.

[0064] By obtaining the safe distance and speed limit information between each speed limit path in the speed limit section, the safe acceleration of the unmanned vehicle when passing through different speed limit paths can be determined, so that the unmanned vehicle can safely and efficiently adjust the driving speed in the speed limit path and prevent safety accidents caused by speeding or slowing down.

[0065] S3: Enable the unmanned vehicle to perform an autonomous driving operation based on the autonomous driving decision.

[0066] By obtaining the traffic light conditions, obstacle conditions and speed limit conditions of the unmanned vehicle during its driving process, and obtaining the corresponding environmental information and driving information to make autonomous driving decisions, the unmanned vehicle can perform efficient and safe autonomous driving control in different traffic conditions during driving, adapt to long-distance and complex road conditions, make operation management more flexible, control more effective, and better meet the needs of vehicle autonomous driving.

[0067] This embodiment also provides a vehicle automatic driving control device, which is applied to the above vehicle automatic driving control method, see the attached Figure 5 As shown, the vehicle automatic driving control device includes

[0068] Traffic condition acquisition module: used to obtain the traffic conditions of the unmanned vehicle from the starting point to the target point, including traffic light conditions, obstacle conditions and speed limit conditions;

[0069] An autonomous driving decision generation module: obtaining corresponding environmental information and driving information according to the traffic conditions to make an autonomous driving decision;

[0070] Autonomous driving module: enables the unmanned vehicle to perform autonomous driving operations based on the autonomous driving decision.

[0071] In some possible implementations, when the traffic condition is a traffic light condition, the steps for executing the autonomous driving decision include the following:

[0072] Obtain the vehicle's driving path through the traffic lights, the vehicle's current actual speed, and the current traffic light status information;

[0073] Obtaining the expected time to pass the traffic light according to the traffic light status information;

[0074] The expected acceleration and expected speed of the unmanned vehicle are generated based on the expected time to pass the traffic light, the driving path and the actual speed.

[0075] In some embodiments, when the traffic condition is an obstacle condition, the steps of executing the autonomous driving decision include the following:

[0076] Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle;

[0077] Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

[0078] In some embodiments, when the traffic condition is an obstacle condition, the steps of executing the autonomous driving decision include the following:

[0079] Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle;

[0080] Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

[0081] In some embodiments, when the traffic condition is a speed limit condition, the steps of executing the autonomous driving decision include the following:

[0082] Get the speed limit information and speed limit path of the speed limit section;

[0083] Get the safe distance between each speed limit path;

[0084] A safe acceleration is obtained based on the safety distances between the speed limit paths and the speed limit information.

[0085] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned vehicle automatic driving control method are implemented.

[0086] The storage medium stores program instructions that can implement all the above methods, wherein the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or a terminal device such as a computer, a server, a mobile phone, or a tablet.

[0087] The processor may also be referred to as a CPU (Central Processing Unit). The processor may be an integrated circuit chip with signal processing capabilities. The processor may also be:

[0088] DSP (Digital Signal Processor, digital signal processor, digital signal processor is a processor composed of large-scale or ultra-large-scale integrated circuit chips to complete certain signal processing tasks. It has gradually developed to meet the needs of high-speed real-time signal processing tasks. With the development of integrated circuit technology and digital signal processing algorithms, the implementation methods of digital signal processors are constantly changing, and the processing functions are constantly improving and expanding.)

[0089] ASIC (Application Specific Integrated Circuit) is an integrated circuit designed and manufactured to meet the needs of specific users and specific electronic systems.

[0090] FPGA (Field Programmable Gate Array) is a product further developed on the basis of programmable devices such as PAL (Programmable Array Logic) and GAL (generic array logic). It emerged as a semi-custom circuit in the field of application-specific integrated circuits (ASICs), which not only solves the shortcomings of custom circuits, but also overcomes the shortcomings of the limited number of gate circuits of the original programmable devices.

[0091] A general-purpose processor may be a microprocessor or any conventional processor.

[0092] The above implementation modes are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with this technology to understand the content of the present invention and implement it, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle automatic driving control method, characterized in that: The steps include: Obtaining the traffic conditions of the unmanned vehicle from the starting point to the target point, wherein the traffic conditions include traffic light conditions, obstacle conditions, and speed limit conditions; Obtaining corresponding environmental information and driving information according to the traffic conditions to make an autonomous driving decision; Based on the autonomous driving decision, the unmanned vehicle performs an autonomous driving operation.

2. The vehicle automatic driving control method according to claim 1, characterized in that: When the traffic condition is a traffic light condition, the execution steps of the automatic driving decision include the following: Obtain the vehicle's driving path through the traffic lights, the vehicle's current actual speed, and the current traffic light status information; Obtaining the expected time to pass the traffic light according to the traffic light status information; The expected acceleration and expected speed of the unmanned vehicle are generated based on the expected time to pass the traffic light, the driving path and the actual speed.

3. The vehicle automatic driving control method according to claim 1, characterized in that: When the traffic condition is an obstacle condition, the execution steps of the autonomous driving decision include the following: Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle; Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

4. The vehicle automatic driving control method according to claim 1, characterized in that: When the traffic condition is a speed limit condition, the execution steps of the automatic driving decision include the following: Get the speed limit information and speed limit path of the speed limit section; Get the safe distance between each speed limit path; The safety acceleration is obtained based on the safety distance and speed limit information between the speed limit paths, so that the speed limits of different road sections can complete the safe transition between the speed limit paths with the safety acceleration.

5. A vehicle automatic driving control device, characterized in that: include Traffic condition acquisition module: used to obtain the traffic conditions of the unmanned vehicle from the starting point to the target point, including traffic light conditions, obstacle conditions and speed limit conditions; An autonomous driving decision generation module: obtaining corresponding environmental information and driving information according to the traffic conditions to make an autonomous driving decision; Autonomous driving module: enables the unmanned vehicle to perform autonomous driving operations based on the autonomous driving decision.

6. The vehicle automatic driving control device according to claim 1, characterized in that: When the traffic condition is a traffic light condition, the execution steps of the automatic driving decision include the following: Obtain the vehicle's driving path through the traffic lights, the vehicle's current actual speed, and the current traffic light status information; Obtaining the expected time to pass the traffic light according to the traffic light status information; The expected acceleration and expected speed of the unmanned vehicle are generated based on the expected time to pass the traffic light, the driving path and the actual speed.

7. The vehicle automatic driving control device according to claim 1, characterized in that: When the traffic condition is an obstacle condition, the execution steps of the autonomous driving decision include the following: Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle; Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

8. The vehicle automatic driving control method according to claim 1, characterized in that: When the traffic condition is an obstacle condition, the execution steps of the autonomous driving decision include the following: Obtain the current first actual speed of the unmanned vehicle and the current second actual speed of the obstacle; Obtain a distance value between the unmanned vehicle and the obstacle; and determine an expected safe driving speed of the unmanned vehicle based on the distance value, the first actual speed, and the second actual speed.

9. The vehicle automatic driving control device according to claim 1, characterized in that: When the traffic condition is a speed limit condition, the execution steps of the automatic driving decision include the following: Get the speed limit information and speed limit path of the speed limit section; Get the safe distance between each speed limit path; A safe acceleration is obtained based on the safety distances between the speed limit paths and the speed limit information.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the vehicle automatic driving control method according to any one of claims 1 to 4 are implemented.

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