Intelligent cruise method and system based on big data

Abstract

The invention provides an intelligent cruise method and system based on big data, and relates to the technical field of vehicle intelligent control, and the method comprises the steps: obtaining the positioning information of a vehicle and a pre-stored user takeover memory point in a self-adaptive cruise function starting state; acquiring road condition information of the current road section according to the positioning information of the vehicle; judging whether the road condition information of the current road section is matched with the takeover operation corresponding to the user takeover memory point or not, and if yes, controlling the vehicle or reminding the user to take over the vehicle according to the takeover operation; wherein the user takeover memory point is generated according to the takeover operation of the user on the vehicle in the state that the self-adaptive cruise function is started, and comprises a positioning point during takeover and an attribute corresponding to the point. According to the invention, the user driving experience under adaptive cruise can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle intelligent control technology, and in particular to an intelligent cruise method and system based on big data. Background Art

[0002] With the advancement of artificial intelligence technology, vehicle autonomous driving technology and functions are developing in a diversified manner. The principle of adaptive cruise control (ACC) based on single or multi-sensor systems on the market is to dynamically adjust the vehicle speed and / or following distance in the lane according to the cruising speed and following distance set by the user, combined with the closest vehicle on the path (Closest In Path Vehicle, CIPV) identified, under the premise that the lateral intervention does not exceed the set threshold, to reduce driving fatigue.

[0003] However, the traditional ACC control method can only control the vehicle according to the set cruising speed on roads with multiple speed limits or no speed limits and in the absence of CIPV, because there is no high-fresh beyond-visual-range information and no learning of user driving habits. Overall, it is quite different from the human driving experience and it is difficult to achieve the original intention of reducing driving fatigue. Summary of the invention

[0004] In view of the shortcomings of the prior art, the embodiments of the present disclosure provide a smart cruise method and system based on big data, which can improve the user driving experience under adaptive cruise. The technical solution is as follows:

[0005] In a first aspect, a smart cruise method based on big data is provided, comprising:

[0006] When the adaptive cruise control function is turned on, the vehicle's positioning information and pre-stored user takeover memory points are obtained;

[0007] Obtaining the road condition information of the current road section according to the vehicle's positioning information;

[0008] Determine whether the road condition information of the current road section matches the takeover operation corresponding to the user's takeover memory point, and if so, control the vehicle according to the takeover operation or remind the user to take over the vehicle;

[0009] The user takeover memory point is generated according to the user's takeover operation on the vehicle when the adaptive cruise function is turned on, including the positioning point at the time of takeover and the attributes corresponding to the point.

[0010] In the second aspect, a smart cruise system based on big data is provided, including:

[0011] A positioning module is configured to obtain the positioning information of the vehicle and a pre-stored user takeover memory point when the adaptive cruise function is turned on; wherein the user takeover memory point is generated according to the user's takeover operation on the vehicle when the adaptive cruise function is turned on, including the positioning point at the time of takeover and the attribute corresponding to the point;

[0012] A road condition information acquisition module is configured to acquire road condition information of a current road section according to the vehicle's positioning information;

[0013] The control module is configured to determine whether the road condition information of the current road section matches the takeover operation corresponding to the user's takeover memory point, and if so, control the vehicle according to the takeover operation or remind the user to take over the vehicle.

[0014] In a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the above-mentioned smart cruise method based on big data.

[0015] In a fourth aspect, a computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, complete the steps of the above-mentioned intelligent cruising method based on big data.

[0016] In a fifth aspect, a computer program product is provided, comprising a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned intelligent cruise method based on big data.

[0017] The beneficial effect brought about by the technical solution provided by the embodiment of the present disclosure is: in the embodiment of the present disclosure, by memorizing the user's driving habits on a specific road section, the driving habits are matched with the road condition information to learn the human driving habits on the specific road section, and the highest freshness decision results are issued in real time, so that the adaptive cruise function is closer to human driving habits and the user driving experience under the adaptive cruise is improved.

[0018] Advantages of additional aspects of the present disclosure will be given in part in the following description and in part will become apparent from the following description or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1is a schematic diagram of a hardware system corresponding to a smart cruise method based on big data provided in an embodiment of the present disclosure;

[0021] Figure 2 It is a flow chart of a smart cruising method based on big data provided in an embodiment of the present disclosure.

[0022] The reference numerals in the accompanying drawings respectively represent: 1. Vehicle; 2. Information upload / download path; 3. Cloud; 4. Intelligent driving controller; 5. Beyond visual range accident site. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present disclosure more clear, the embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings.

[0024] The present disclosure provides a method for intelligent cruising based on big data, see Figure 1-Figure 2 ,include:

[0025] When the adaptive cruise control function is turned on, the vehicle's positioning information and pre-stored user takeover memory points are obtained;

[0026] Obtaining the road condition information of the current road section according to the vehicle's positioning information;

[0027] Determine whether the road condition information of the current road section matches the takeover operation corresponding to the user's takeover memory point, and if so, control the vehicle according to the takeover operation or remind the user to take over the vehicle;

[0028] The user takeover memory point is generated according to the user's takeover operation on the vehicle when the adaptive cruise function is turned on, including the positioning point at the time of takeover and the attributes corresponding to the point.

[0029] Traditional adaptive cruise control systems usually control the vehicle based on a preset cruising speed and the identified current road conditions. On the one hand, the cruising speed is usually set manually by the user, and it is difficult to effectively adaptively control the vehicle speed when driving on roads with multiple speed limits or no speed limits. On the other hand, in the absence of CIPV (Closest In Path Vehicle), due to the lack of high-fresh beyond-visual-range information and learning of user driving habits, the vehicle can only be controlled according to the set cruising speed, resulting in a large gap between the driving experience and the human driving experience, making it difficult to achieve the original intention of reducing driving fatigue.

[0030] Based on this, the disclosed embodiment uses the V2X (Vehicle-to-Everything, information exchange technology between vehicles and all entities that can communicate with it) on-board intelligent module and intelligent driving controller module to memorize the user's driving habits, and then uses beyond-visual-range information, vehicle-side / cloud-side training and memory of the user's driving habits on this road section to achieve a less-takeover / more intelligent anthropomorphic cruise experience. The method provided in the disclosed embodiment is mainly used to optimize the control logic of the V2X on-board intelligent module installed in vehicles with L3 and above autonomous driving levels to improve the vehicle's intelligent driving experience.

[0031] like Figure 1 As shown, the conventional self-driving vehicle 1 equipped with the intelligent driving controller 4 is difficult to identify the beyond-visual-range accident site 5 outside the field of vision in the adaptive cruise state, and thus it is difficult to take over the control of the vehicle in advance. In the disclosed embodiment, by pre-memorizing the user takeover memory point, combined with the road condition information obtained by the cloud 3 through the information upload / download path 2, if the user brakes the vehicle at the memory point, and the cloud obtains construction or temporary accident information ahead, and the information is information that cannot be recognized by the vehicle vision system, then the memory point is judged as a valid memory point and the takeover operation is performed.

[0032] Specifically, after turning on the cruise function, the intelligent driving controller ADCC needs to memorize the positioning points (GNSS coordinates) where the user steps on the brake or accelerator pedal. The positioning accuracy is lane-level positioning, which can be obtained through the RTK algorithm based on the fusion results of the vehicle's GPS positioning + visual positioning, or the intelligent driving's own high-precision positioning module. Attach attributes to the action memory points, that is, the user takes over, and upload this data to the OEM cloud after desensitization. At the same time, the intelligent driving controller also sends to the cloud the road condition information within the FOV (Field of View) range at the moment the user takes over.

[0033] The V2X on-board intelligent module carried by the vehicle sends the GNSS coordinates of the vehicle in real time. The cloud obtains the latest road condition information of the current section through the lane-level positioning results of the vehicle, including speed limit, congestion, construction, accidents and / or electronic eye photography information. Every time the user takes over the vehicle, the road condition information in the FOV when the user takes over (stepping on the brake, stepping on the accelerator, etc.) is compared with the road condition information sent by V2X. If the road conditions are consistent, the cloud compares the attributes of this GNSS point with the attributes of the corresponding pre-stored user takeover memory point. If the attributes are consistent, save the attribute value corresponding to the point: non-user habit; if the attributes are inconsistent, replace the attribute value of the point with: non-user habit; if the road conditions are inconsistent, the cloud compares the attributes of this GNSS point with the attributes of the corresponding pre-stored user takeover memory point. If the attributes are consistent, save the attribute value corresponding to the point: beyond-line-of-sight takeover point; if the attributes are inconsistent, replace the attribute value of the point with: beyond-line-of-sight takeover point.

[0034] The user takeover memory point is sent to the vehicle side, and the vehicle's on-board vision system collects real-time road condition information during driving, performs adaptive cruise control based on the real-time road condition information, and before each intelligent driving system controls acceleration and deceleration, the attribute information attached to the user takeover memory point must be compared with the latest speed limit / road condition information obtained through V2X.

[0035] If the user's operation at the memory point is to step on the brakes, and the V2X cloud sends information about construction / temporary accidents ahead, and the information is unrecognizable by the on-board vision system (beyond visual range information), the decision is to take over effectively. If you pass this section next time and do not receive updated information from the V2X cloud, a pop-up window and / or voice reminder will take over 200-500m (calibrable) before this memory point; otherwise, if the V2X cloud system sends updated information, the decision will be made based on vision and V2X cloud information.

[0036] If the user's operation at the memory point is to step on the accelerator pedal, and the V2X cloud does not send information about construction / temporary accidents ahead + no electronic eye taking photos, and the on-board visual system detects that the surrounding vehicles are passing at a speed higher than the road speed limit, then this memory point is judged to be a reasonable user habit intervention point. The next time you pass this section of road, if there is no CIPV ahead and the V2X end has not sent updated information, the cruising speed will be adjusted according to user habits within the road speed limit.

[0037] The disclosed embodiment also provides a big data-based intelligent cruise system, which includes: a positioning module, a road condition information acquisition module, and a control module.

[0038] The positioning module is configured to obtain the positioning information of the vehicle and the pre-stored user takeover memory point when the adaptive cruise function is turned on; wherein the user takeover memory point is generated according to the user's takeover operation of the vehicle when the adaptive cruise function is turned on, including the positioning point at the time of takeover and the attribute corresponding to the point;

[0039] A road condition information acquisition module is configured to acquire road condition information of a current road section according to the vehicle's positioning information;

[0040] The control module is configured to determine whether the road condition information of the current road section matches the takeover operation corresponding to the user's takeover memory point, and if so, control the vehicle according to the takeover operation or remind the user to take over the vehicle.

[0041] It should be noted that: the above embodiment provides an intelligent cruise system based on big data, when performing vehicle cruise control, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the above embodiment provides an intelligent cruise system based on big data and an embodiment of an intelligent cruise method based on big data, which belongs to the same concept. The specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0042] The embodiment of the present disclosure also provides an electronic device, which may be a vehicle-mounted computer, etc. The electronic device includes: a processor and a memory.

[0043] The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor may be implemented in at least one of the following hardware forms: DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and LA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0044] The memory may include one or more computer-readable media, which may be non-transitory. The memory may also include high-speed random access memory, and non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable medium in the memory is used to store at least one computer program, which is used to be executed by the processor to implement a smart cruise method based on big data provided in an embodiment of the present disclosure.

[0045] Those skilled in the art will appreciate that the structure of the electronic device described above may include more or fewer components, or combine certain components, or adopt different component arrangements.

[0046] The embodiment of the present disclosure also provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, the steps of a big data-based intelligent cruising method provided in the embodiment of the present disclosure can be completed.

[0047] The present disclosure also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of a big data-based intelligent cruise method provided in the present disclosure.

[0048] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A smart cruising method based on big data, characterized in that: include: When the adaptive cruise control function is turned on, the vehicle's positioning information and pre-stored user takeover memory points are obtained; Obtaining the road condition information of the current road section according to the vehicle's positioning information; Determine whether the road condition information of the current road section matches the takeover operation corresponding to the user's takeover memory point, and if so, control the vehicle according to the takeover operation or remind the user to take over the vehicle; The user takeover memory point is generated according to the user's takeover operation on the vehicle when the adaptive cruise function is turned on, including the positioning point at the time of takeover and the attributes corresponding to the point.

2. The big data-based intelligent cruising method according to claim 1, characterized in that: The positioning information of the vehicle and the positioning point at the time of takeover, the positioning accuracy is lane-level positioning.

3. The intelligent cruising method based on big data according to claim 1, characterized in that: Traffic condition information for the current road section, including speed limit, congestion, accidents and / or electronic eye camera information.

4. The intelligent cruising method based on big data according to claim 1, characterized in that: It also includes obtaining real-time traffic information during vehicle driving, performing adaptive cruise control based on the real-time traffic information, and determining whether the traffic information of the current road section matches the takeover operation corresponding to the user's takeover memory point before each acceleration or deceleration.

5. The big data-based intelligent cruising method according to claim 4, characterized in that: If the takeover operation of the user's takeover memory point corresponding to the current positioning point is stepping on the brakes, and the road condition information obtained is accident information, which is information that the vehicle cannot recognize and the information has not been updated, the user is reminded to take over the vehicle when the vehicle is at a set position before the user's takeover memory point.

6. The big data-based intelligent cruising method according to claim 4, characterized in that: If the user's takeover operation for the memory point corresponding to the current positioning point is to step on the accelerator pedal, the road condition information obtained does not contain any construction or accident information and there are no electronic eyes taking pictures, and it is monitored that the surrounding vehicles are passing at a speed higher than the road speed limit, the cruising speed is adjusted according to the user's habits within the road speed limit.

7. An intelligent cruise system based on big data, characterized in that: include: A positioning module is configured to obtain the positioning information of the vehicle and a pre-stored user takeover memory point when the adaptive cruise function is turned on; wherein the user takeover memory point is generated according to the user's takeover operation on the vehicle when the adaptive cruise function is turned on, including the positioning point at the time of takeover and the attribute corresponding to the point; A road condition information acquisition module is configured to acquire road condition information of a current road section according to the vehicle's positioning information; The control module is configured to determine whether the road condition information of the current road section matches the takeover operation corresponding to the user's takeover memory point, and if so, control the vehicle according to the takeover operation or remind the user to take over the vehicle.

8. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to complete the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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