Intelligent cruise method and system based on big data

Abstract

The present disclosure provides a big data-based intelligent cruise method and system, and relates to the technical field of vehicle intelligent control. The method comprises the following steps: in an adaptive cruise function opening state, obtaining positioning information of a vehicle and pre-stored user takeover memory points; obtaining road condition information of a current road section according to the positioning information of the vehicle; judging whether the road condition information of the current road section matches the takeover operation corresponding to the user takeover memory points, and if so, controlling the vehicle according to the takeover operation or reminding the user to take over the vehicle; wherein the user takeover memory points are generated according to the user's takeover operation on the vehicle in the adaptive cruise function opening state, and include a positioning point at the time of takeover and the attributes corresponding to the point. The present disclosure can improve the user driving experience under adaptive cruise.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of intelligent control of vehicles, in particular to an intelligent cruise method and system based on big data. BACKGROUND

[0002] With the progress of artificial intelligence technology, vehicle automatic driving technology and functions are developing in a diversified manner. At present, the principle of adaptive cruise control (ACC) based on single sensor or multi-sensor system on the market is to dynamically adjust the vehicle lane speed and / or following distance according to the user set cruise speed and following distance, combined with the closest in path vehicle (CIPV) identified on the path, under the premise that the lateral intervention does not exceed the set threshold, to meet the need to reduce driving fatigue.

[0003] However, the traditional ACC control method, in the case of no CIPV on a multi-speed limit / infinite speed section, can only control the vehicle according to the set cruise speed due to the lack of high freshness over-the-horizon information and learning of user driving habits, which overall has a large gap with human driving experience, and it is difficult to achieve the original intention of reducing driving fatigue. SUMMARY

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

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

[0006] In the adaptive cruise function enabled state, the positioning information of the vehicle and the pre-stored user takeover memory point are obtained.

[0007] The road condition information of the current section is obtained according to the positioning information of the vehicle.

[0008] It is judged whether the road condition information of the current section matches the takeover operation corresponding to the user takeover memory point, and if so, the vehicle is controlled according to the takeover operation or the user is reminded to take over the vehicle.

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

[0010] In a second aspect, an intelligent cruise system based on big data is provided, comprising:

[0011] The positioning module is configured to acquire positioning information of the vehicle and pre-stored user takeover memory points in a state where the adaptive cruise function is turned on, wherein the user takeover memory points are generated according to user takeover operations on the vehicle in the state where the adaptive cruise function is turned on, and include a positioning point at the time of takeover and attributes corresponding to the point.

[0012] The road condition information acquisition module is configured to acquire road condition information of a current road section according to the positioning information of the vehicle.

[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 takeover memory points, and control the vehicle or remind the user to take over the vehicle according to the takeover operation if the two are matched.

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

[0015] In a fourth aspect, a computer-readable storage medium is provided for storing computer instructions, and the computer instructions are executed by a processor to complete the steps of the above-described intelligent cruise method based on big data.

[0016] In a fifth aspect, a computer program product is provided, including computer programs / instructions, and the computer programs / instructions are executed by a processor to implement the steps of the above-described intelligent cruise method based on big data.

[0017] The technical scheme provided by the embodiments of the present disclosure has the beneficial effects that, in the embodiments of the present disclosure, the driving habits of the user on a specific road section are memorized, the driving habits are matched with road condition information to learn the driving habits of the user on the specific road section, and the most fresh decision result is issued in real time, so that the adaptive cruise function is closer to the driving habits of the user, and the driving experience of the user under the adaptive cruise function is improved.

[0018] The advantages of the additional aspects of the present disclosure will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical schemes in the embodiments of the present disclosure, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

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

[0021] Figure 2 is a flowchart of an intelligent cruise method based on big data provided by an embodiment of the present disclosure.

[0022] The reference signs respectively represent: 1, a vehicle; 2, an information uploading / delivering path; 3, a cloud; 4, an intelligent driving controller; and 5, an over-the-horizon accident site. DETAILED DESCRIPTION

[0023] To make the objectives, technical solutions and advantages of the present disclosure clearer, the following will further describe the embodiments of the present disclosure in detail with reference to the drawings.

[0024] An intelligent cruise method based on big data provided by an embodiment of the present disclosure, referring to Figures 1-2 , comprises:

[0025] In a state where the adaptive cruise function is turned on, the positioning information of the vehicle and the pre-stored user takeover memory point are acquired.

[0026] The road condition information of the current road section is acquired according to the positioning information of the vehicle.

[0027] It is judged whether the road condition information of the current road section matches the takeover operation corresponding to the user takeover memory point, and if so, the vehicle is controlled or the user is reminded to take over the vehicle according to the takeover operation.

[0028] The user takeover memory point is generated according to the user's takeover operation on the vehicle in the state where the adaptive cruise function is turned on, and includes the positioning point at the time of takeover and the attribute corresponding to the point.

[0029] The traditional adaptive cruise system usually controls the vehicle according to the preset cruise speed and the recognized current road condition information. On the one hand, the cruise speed is usually manually set by the user, and it is difficult to effectively adaptively control the vehicle speed when driving to a multi-speed limit / unlimited speed road section. On the other hand, in the case of no CIPV (Closest In Path Vehicle, closest vehicle on the path), due to the lack of high-freshness over-the-horizon information and the learning of the user's driving habits, the vehicle can only be controlled according to the set cruise speed, resulting in a large gap between the driving experience and the human driving experience, and it is difficult to achieve the original intention of reducing driving fatigue.

[0030] Based on this, the embodiments of the present disclosure memorize the user driving habits through the V2X (Vehicle-to-Everything, information exchange technology between vehicles and entities that can communicate with them) vehicle-mounted intelligent module and the intelligent driving controller module, and further memorize the user driving habits on this section through the over-the-horizon information, vehicle / cloud training, to achieve less takeover / more intelligent anthropomorphic cruise experience. The method provided by the embodiments of the present disclosure is mainly used for optimizing the control logic of the V2X vehicle-mounted intelligent module carried by the L3 and above automatic driving level vehicle, so as to improve the intelligent driving experience of the vehicle.

[0031] As shown in Figure 1 , the traditional ego vehicle 1 carrying the intelligent driving controller 4 is difficult to identify the over-the-horizon accident 5 outside the field of view range in the adaptive cruise state, so it is difficult to take over the control of the vehicle in advance. In the embodiments of the present disclosure, the user takeover memory point is memorized in advance, and the road condition information obtained by the cloud 3 through the information uploading / distributing path 2 is used for judgment. If the user brakes the vehicle at the memory point, and the cloud obtains that there is construction or temporary accident information in front, and the information is information that cannot be identified by the vehicle-mounted vision system, it is judged that the memory point is an effective memory point, and the takeover operation is performed.

[0032] Specifically, the intelligent driving controller ADCC needs to memorize the positioning point (GNSS coordinates) of the user stepping on the brake or accelerator pedal after starting the cruise function, and the positioning accuracy is lane-level positioning, which can be obtained by RTK algorithm according to the fusion result of vehicle GPS positioning + vision positioning or the high-precision positioning module of the intelligent driving. The attribute of the action memory point is added, that is, the user takes over, and the data is desensitized and uploaded to the OEM cloud. At the same time, the intelligent driving controller also sends the road condition information in the FOV (Field of View) range of the user takeover time to the cloud.

[0033] The V2X vehicle-mounted intelligent module carried by the vehicle sends the GNSS coordinates of the ego vehicle in real time. The cloud obtains the latest road condition information of the current section through the lane-level positioning result of the ego vehicle, including speed limit, congestion, construction, accident and / or electronic eye shooting information. When the user takes over the vehicle each time, the road condition information in the FOV when the user takes over the operation (steps on the brake, steps on the accelerator, etc.) is compared with the road condition information issued by the V2X. If the road conditions are consistent, the cloud compares the attribute of this GNSS point with the attribute of the corresponding user takeover memory point stored in advance. If the attributes are consistent, the attribute value of the point is saved: non-user habit; if the attributes are inconsistent, the attribute value of the point is replaced: non-user habit; if the road conditions are inconsistent, the cloud compares the attribute of this GNSS point with the attribute of the corresponding user takeover memory point stored in advance. If the attributes are consistent, the attribute value of the point is saved: over-the-horizon takeover point; if the attributes are inconsistent, the attribute value of the point is replaced: over-the-horizon takeover point.

[0034] The user takeover memory point is sent to the vehicle end, the vehicle-mounted vision system of the vehicle collects real-time road condition information in the driving process in real time, adaptive cruise is performed according to the real-time road condition information, and before the intelligent driving system controls acceleration and deceleration each time, the user takeover memory point is compared with the latest speed limit / road condition information obtained through V2X.

[0035] If the user's operation on the memory point is to step on the brake, and the V2X cloud end sends the information of the front construction / temporary accident type, and the information is an information (over-the-horizon information) that cannot be recognized by the vehicle-mounted vision system, the decision is to take over effectively, if the next time the vehicle passes through this section and no updated information is received from the V2X cloud end, a pop-up window and / or voice prompt is given to take over 200-500m (which can be calibrated) before the memory point; otherwise, the V2X cloud system sends updated information, and the vision and V2X cloud information are used as the main decision.

[0036] If the user's operation on the memory point is to step on the accelerator pedal, and the V2X cloud end does not send the information of the front construction / temporary accident type + no electronic eye shooting, and the vehicle-mounted vision system monitors that the surrounding vehicles all pass through at a speed higher than the road speed limit, it is determined that the memory point is a reasonable user habit intervention point, and in the next time the vehicle passes through this section, no CIPV is in front of the vehicle and no updated information is sent from the V2X end, the cruise speed is adjusted according to the user's habit within the road speed limit.

[0037] The embodiment of the present disclosure also provides an intelligent cruise system based on big data, which comprises a positioning module, a road condition information acquisition module and a control module.

[0038] The positioning module is configured to acquire the positioning information of the vehicle and the pre-stored user takeover memory point in the adaptive cruise function opening state, wherein the user takeover memory point is generated according to the takeover operation of the user on the vehicle in the adaptive cruise function opening state, and includes the positioning point at the time of takeover and the attribute corresponding to the point.

[0039] The road condition information acquisition module is configured to acquire the road condition information of the current section according to the positioning information of the vehicle.

[0040] The control module is configured to judge whether the road condition information of the current section matches the takeover operation corresponding to the user takeover memory point, and if it matches, 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 a kind of intelligent cruise system based on big data, when vehicle cruise control is carried out, only the division of above-mentioned each functional module is illustrated, in actual application, the above-mentioned function distribution can be completed by different functional module according to needs, i.e. the internal structure of equipment is divided into different functional module, to complete the above described all or part of function.In addition, the above embodiment provides a kind of intelligent cruise system based on big data and a kind of big data-based intelligent cruise method embodiment belongs to the same concept, its specific implementation process is described in detail in method embodiment, here will not be repeated.

[0042] The embodiment of the present disclosure further provides an electronic device, which can be a vehicle-mounted computer or the like.The electronic device includes a processor and a memory.

[0043] The processor can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc.The processor can be implemented in at least one hardware form of a DSP (Digital Signal Processing), a FPGA (Field-Programmable Gate Array), a LA (Programmable Logic Array).The processor can also include a main processor and a coprocessor, the main processor is a processor for processing data in the wake-up state, also known as CPU (Central Processing Unit), and the coprocessor is a low-power processor for processing data in the standby state.In some embodiments, the processor can be integrated with a GPU (Graphics Processing Unit) for rendering and drawing the content required to be displayed by the display screen.In some embodiments, the processor can further include an AI (Artificial Intelligence) processor for processing machine learning-related computing operations.

[0044] The memory can include one or more computer-readable media, which can be non-transitory.The memory can also include a high-speed random access memory and a 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 for being executed by the processor to implement the big data-based intelligent cruise method provided in the embodiment of the present disclosure.

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

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

[0047] The embodiment of the present disclosure further provides a computer program product, including computer programs / instructions, when the computer programs / instructions are executed by a processor, the steps of the intelligent cruise method based on big data provided in the embodiment of the present disclosure can be implemented.

[0048] The above only describes the preferred embodiments of the present disclosure and is not intended to limit the present disclosure. Those skilled in the art can make various modifications and changes to the present disclosure. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A big data based intelligent cruise method, characterized in that, The application comprises the following steps: In the state of starting the adaptive cruise function, the positioning information of the vehicle and the pre-stored user takeover memory point are obtained; The road condition information of the current section is obtained according to the positioning information of the vehicle; It is judged whether the road condition information of the current section matches the takeover operation corresponding to the user takeover memory point, and if so, the vehicle is controlled or the user is reminded to take over the vehicle according to the takeover operation; The user takeover memory point is generated according to the user's takeover operation on the vehicle in the state of starting the adaptive cruise function, and includes the positioning point at the time of takeover and the attributes corresponding to the point; Further comprising obtaining real-time road condition information during the driving process of the vehicle, and performing the adaptive cruise function according to the real-time road condition information, and judging whether the road condition information of the current section matches the takeover operation corresponding to the user takeover memory point before each acceleration or deceleration; If the takeover operation corresponding to the current positioning point of the user takeover memory point is to step on the brake, the obtained road condition information is accident information, the accident information is information that cannot be recognized by the vehicle, and the information is not updated, when the vehicle is at a set position before the user takeover memory point, the user is reminded to take over the vehicle; If the takeover operation corresponding to the current positioning point of the user takeover memory point is to step on the accelerator pedal, the obtained road condition information does not exist construction, accident information and no electronic eye shooting, and it is monitored that the surrounding vehicles all pass through at a speed higher than the road speed limit, and the cruise speed is adjusted within the road speed limit according to the user's habit.

2. The big data based intelligent cruise method of claim 1, wherein, The positioning accuracy of the positioning information of the vehicle and the positioning point at the time of takeover is lane-level positioning.

3. The big data based intelligent cruise method of claim 1, wherein, The road condition information of the current section includes speed limit, congestion, accident and / or electronic eye shooting information.

4. A big data based intelligent cruise system characterized in that, The application comprises the following steps: The positioning module is configured to obtain the positioning information of the vehicle and the pre-stored user takeover memory point in the state of starting the adaptive cruise function, wherein the user takeover memory point is generated according to the user's takeover operation on the vehicle in the state of starting the adaptive cruise function, and includes the positioning point at the time of takeover and the attributes corresponding to the point; The road condition information acquisition module is configured to obtain the road condition information of the current section according to the positioning information of the vehicle; The control module is configured to judge whether the road condition information of the current section matches the takeover operation corresponding to the user takeover memory point, and if so, to control the vehicle or to remind the user to take over the vehicle according to the takeover operation; Further comprising obtaining real-time road condition information during the driving process of the vehicle, and performing the adaptive cruise function according to the real-time road condition information, and judging whether the road condition information of the current section matches the takeover operation corresponding to the user takeover memory point before each acceleration or deceleration; If the takeover operation corresponding to the current positioning point of the user takeover memory point is to step on the brake, the obtained road condition information is accident information, the accident information is information that cannot be recognized by the vehicle, and the information is not updated, when the vehicle is at a set position before the user takeover memory point, the user is reminded to take over the vehicle; If the takeover operation corresponding to the current positioning point of the user takeover memory point is to step on the accelerator pedal, the obtained road condition information does not exist construction, accident information and no electronic eye shooting, and it is monitored that the surrounding vehicles all pass through at a speed higher than the road speed limit, and the cruise speed is adjusted within the road speed limit according to the user's habit.

5. An electronic device, comprising: A computer program product comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to perform the steps of the method of any of claims 1-3.

6. A computer-readable storage medium, characterized in that, A computer program product for storing computer instructions which, when executed by a processor, perform the steps of the method of any of claims 1-3.

7. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instructions, when executed by a processor, perform the steps of the method of any of claims 1-3.

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