Vehicle control method and device, electronic equipment, vehicle and readable storage medium

Abstract

The invention provides a vehicle control method and device, electronic equipment, a vehicle and a readable storage medium. The method comprises the following steps: under the condition that a map of a vehicle cabin system used by a user is received, receiving a satellite positioning result obtained by a positioning module and data obtained by a motion state sensor, and fusing the satellite positioning result and the data to obtain positioning data; obtaining the position of the vehicle according to the positioning data; under the condition that navigation activated by the user is received, path planning is carried out according to the position of the vehicle and the starting position of a matched map, and a navigation path is obtained; and sending the position of the vehicle and the navigation path to an intelligent driving system, so that the intelligent driving system controls the vehicle to run according to the navigation path according to the position of the vehicle and the navigation path. Therefore, more accurate positioning data can be obtained. And navigation is carried out based on the positioning data, so that the navigation accuracy can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, and in particular to a vehicle control method and device, electronic equipment, a vehicle and a readable storage medium. BACKGROUND

[0002] With the development of high-order intelligent driving technology, in the navigation method of the related technology, the positioning of the cockpit system traditional GPS (Global Positioning System) is used, the navigation path of the cockpit system is sent to the intelligent driving system for positioning to correct the path. However, the accuracy of the cockpit system positioning is relatively low. SUMMARY

[0003] The present application provides an improved vehicle control method, device, electronic equipment, vehicle and readable storage medium.

[0004] In a first aspect, the present application provides a vehicle control method, comprising:

[0005] In the case of receiving a map used by a user using a vehicle cockpit system, satellite positioning results obtained by a positioning module and data obtained by a motion state sensor are fused to obtain positioning data;

[0006] According to the positioning data, the self-vehicle position of the vehicle is obtained;

[0007] In the case of receiving user activation of navigation, the starting position of the map is matched according to the self-vehicle position to plan a path and obtain a navigation path;

[0008] The self-vehicle position and the navigation path are sent to an intelligent driving system, so that the intelligent driving system controls the vehicle to travel according to the navigation path according to the self-vehicle position and the navigation path.

[0009] Further, the positioning accuracy of the positioning module includes centimeter-level positioning or less than centimeter-level positioning; the positioning data obtained by fusing the satellite positioning results obtained by the positioning module and the data obtained by the motion state sensor includes:

[0010] The positioning data obtained by fusing the satellite positioning results obtained by real-time kinematic differential positioning RTK and the data obtained by a three-axis or more inertial measurement unit IMU.

[0011] Further, the positioning data obtained by fusing the satellite positioning results obtained by real-time kinematic differential positioning RTK and the data obtained by the inertial measurement unit IMU includes:

[0012] Receiving satellite positioning results obtained by RTK of the cabin system and data obtained by IMU of the cabin system to obtain positioning data.

[0013] Further, the satellite positioning results obtained by real-time dynamic difference positioning RTK and the data obtained by inertial measurement unit IMU are fused to obtain positioning data.

[0014] Receiving satellite positioning results obtained by RTK of the intelligent driving system and data obtained by IMU of the intelligent driving system to obtain positioning data.

[0015] According to the positioning data, the self-position of the vehicle is obtained.

[0016] According to the signal delay duration, the speed of the vehicle and the driving direction of the vehicle, the delay displacement of the vehicle within the signal delay duration is determined; the signal delay duration is used to represent that the receiving timestamp and the sending timestamp of the same signal are different, and the clock of the cabin system and the clock of the intelligent driving system are synchronized or use the same clock.

[0017] On the basis of the positioning data, the delay displacement is compensated to obtain corrected positioning data as the self-position of the vehicle.

[0018] Further, the positioning data includes a sending timestamp and position data of the vehicle at the sending timestamp.

[0019] In the case of receiving the map of the vehicle cabin system used by the user, the positioning data of the intelligent driving system and the navigation path input by the user and containing the starting position are received respectively.

[0020] In the case of receiving the map of the vehicle cabin system used by the user, the position data of the vehicle is received, and the navigation path input by the user and containing the starting position is received, and the receiving timestamp of the position data of the vehicle being received is recorded.

[0021] Correspondingly, the method further comprises:

[0022] According to the sending timestamp and the receiving timestamp, the signal delay duration is determined.

[0023] Further, the method further comprises:

[0024] The signal delay duration is determined in the following way:

[0025] Test signals are sent by the intelligent driving system multiple times; the test signals include sending timestamps.

[0026] receive each time a test signal is transmitted and record a reception timestamp of each time a test signal is received;

[0027] obtain a signal delay duration according to the reception timestamp and the transmission timestamp.

[0028] Further, the determining of a delay displacement of the vehicle within the signal delay duration according to the signal delay duration, the vehicle speed and the driving direction of the vehicle comprises:

[0029] obtaining a real-time driving direction of the vehicle according to a six-axis inertial measurement unit (IMU);

[0030] multiplying the signal delay duration and the vehicle speed by the real-time driving direction of the vehicle as the delay displacement of the vehicle within the signal delay duration.

[0031] In a second aspect, an embodiment of the present application provides a vehicle control method, comprising:

[0032] obtaining positioning data by fusing satellite positioning results obtained by a positioning module of an intelligent driving system and data obtained by a motion state sensor;

[0033] fusing the satellite positioning results and the obtained data to obtain positioning data of the intelligent driving system;

[0034] sending the positioning data marked with a transmission timestamp to the cockpit system; the clock of the cockpit system is synchronized with the clock of the intelligent driving system or uses the same clock; so that the cockpit system is used to implement the vehicle control method as described in the first aspect above.

[0035] Further, the obtaining of the positioning data by fusing the satellite positioning results obtained by the positioning module of the intelligent driving system and the data obtained by the motion state sensor comprises:

[0036] obtaining satellite positioning results obtained by a real-time kinematic (RTK) of the intelligent driving system and data obtained by an inertial measurement unit (IMU).

[0037] In a third aspect, an embodiment of the present application provides a vehicle control device, comprising:

[0038] a receiving module configured to, in a case where a map of a vehicle cockpit system is received by a user, receive positioning data obtained by fusing satellite positioning results obtained by a positioning module and data obtained by a motion state sensor;

[0039] a self-vehicle position module configured to obtain a self-vehicle position of the vehicle according to the positioning data;

[0040] The matching module is configured to, in response to receiving user activation of the navigation, match a map starting position with the self-vehicle position to perform path planning, and obtain a navigation path.

[0041] The first sending module is configured to send the self-vehicle position and the navigation path to the intelligent driving system, so that the intelligent driving system controls the vehicle to travel along the navigation path according to the self-vehicle position and the navigation path.

[0042] In a fourth aspect, an embodiment of the present application provides a vehicle control device, comprising:

[0043] The acquisition module is configured to acquire positioning data obtained by fusing satellite positioning results obtained by a positioning module of an intelligent driving system and data obtained by a motion state sensor.

[0044] The fusion module is configured to fuse the satellite positioning results and the obtained data to obtain positioning data of the intelligent driving system.

[0045] The second sending module is configured to send the positioning data marked with a sending time stamp to the cockpit system; a clock of the cockpit system is synchronized with a clock of the intelligent driving system or uses the same clock; so that the cockpit system is configured to implement the vehicle control method of the first aspect.

[0046] In a fifth aspect, an embodiment of the present application provides an electronic device comprising one or more processors configured to implement the vehicle control method of the first aspect or the vehicle control method of the second aspect.

[0047] In a sixth aspect, an embodiment of the present application provides a vehicle comprising one or more processors configured to implement the vehicle control method of the first aspect or the vehicle control method of the second aspect.

[0048] In a seventh aspect, an embodiment of the present application provides a computer-readable storage medium having a program stored thereon, the program being executed by a processor to implement the vehicle control method of the first aspect or the vehicle control method of the second aspect.

[0049] The present application provides a computer program product comprising computer programs / instructions, which are executed by a processor to implement the vehicle control method of the first aspect or the vehicle control method of the second aspect.

[0050] In some embodiments, the vehicle control method of the present application receives satellite positioning results obtained by the positioning module and data obtained by the motion state sensor for fusion, obtains positioning data, and further obtains the self-vehicle position of the vehicle. In this way, due to the fusion of the satellite positioning results obtained by the positioning module and the data obtained by the motion state sensor, the fused data is more comprehensive, and more accurate positioning data can be obtained. Moreover, based on the positioning data, navigation can be improved in accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 An application structure schematic diagram of a navigation method of the related art is shown;

[0052] Figure 2 A first aspect flow schematic diagram of the vehicle control method of the embodiment of the present application is shown;

[0053] Figure 3 A second aspect flow schematic diagram of the vehicle control method of the embodiment of the present application is shown;

[0054] Figure 4 A structure schematic diagram of the vehicle control device provided by the embodiment of the present application is shown;

[0055] Figure 5 Another structure schematic diagram of the vehicle control device provided by the embodiment of the present application is shown;

[0056] Figure 6 A structure schematic diagram of the electronic device provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0057] The exemplary embodiments will be described in detail herein with reference to the attached drawings. In the following description, the same numbers are used to designate the same elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all the embodiments consistent with one or more embodiments of the present description. Rather, they are merely examples of devices and methods consistent with some aspects of one or more embodiments of the present description, as detailed in the appended claims.

[0058] It should be noted that the steps of the corresponding method in other embodiments are not necessarily performed in the order shown and described in the present description. In some other embodiments, the steps included in the method can be more or less than described in the present description. In addition, a single step described in the present description can be divided into multiple steps for description in other embodiments, and multiple steps described in the present description can be combined into a single step for description in other embodiments.

[0059] To solve the technical problem of relatively low positioning accuracy of the positioning system, the embodiment of the application provides a vehicle control method, which fuses satellite positioning results obtained by a positioning module and data obtained by a motion state sensor to obtain positioning data, and then obtains a self-position of the vehicle. In this way, due to the fusion of the satellite positioning results obtained by the positioning module and the data obtained by the motion state sensor, the fused data is more comprehensive, and more accurate positioning data can be obtained. Moreover, navigation based on the positioning data can improve the accuracy of navigation.

[0060] Figure 1 Fig. 1 shows an application structure diagram of a navigation method of the related art.

[0061] As shown in Fig. 1, in the navigation method of the related art, when a user starts navigation in an intelligent cockpit system, the intelligent cockpit system obtains a relevant predetermined route and road topology, and delivers the route and the road topology to an intelligent driving system after matching. The intelligent driving system completes positioning based on a positioning system of the intelligent driving system, and controls the vehicle to travel according to the predetermined route. Figure 1

[0062] Among them, the above-mentioned intelligent cockpit system is mainly used to realize the entertainment navigation function of the vehicle. The intelligent cockpit system can include but is not limited to the positioning system of the intelligent cockpit. The positioning system of the intelligent cockpit is a combination of GPS and a three-axis IMU (Inertial Measurement Unit).

[0063] The above-mentioned intelligent driving system can be referred to as a driving system. The driving system is mainly used to realize the intelligent driving function. The above-mentioned driving system can include but is not limited to the positioning system of the intelligent driving, which is mainly used to realize the intelligent driving positioning function. The positioning system of the intelligent driving can include RTK (Real-Time Kinematic) and a six-axis IMU combination.

[0064] However, since the two positioning systems independently realize positioning, and the above-mentioned GPS single antenna has low positioning accuracy, the positioning accuracy is meter level, and the positioning accuracy of the above-mentioned RTK is centimeter level. In this way, the two positioning systems have large accuracy difference, which may cause positioning deviation, so that the driving system cannot be activated, the function is exited or re-planned to miss the intersection.

[0065] ​In order to solve the possible positioning deviation, thereby causing the intelligent driving system to fail to activate, the function to quit or the re-planning to miss the intersection, etc., the vehicle control method provided in the embodiment of the application can use one positioning system, and the positioning data obtained by fusing the satellite positioning result obtained by the positioning module and the data obtained by the motion state sensor, so that the two positioning systems share the same positioning signal, and the positioning deviation problem is fundamentally solved.

[0066] In the first optional implementation, the satellite positioning result obtained by the positioning module and the data obtained by the motion state sensor in the positioning system of the intelligent driving (also referred to as the intelligent driving system in the embodiment of the application) are fused to obtain the positioning data, so as to obtain the high-precision positioning signal, which is then transmitted to the positioning system of the intelligent cabin to position the vehicle position and perform navigation.

[0067] In the above-mentioned first optional implementation of the application, the positioning of the positioning system of the intelligent cabin itself can be removed, the high-precision positioning signal is obtained from the positioning system of the intelligent cabin to position the vehicle position and perform navigation, and the positioning system of the intelligent cabin uses the data of the intelligent driving system. In this way, not only the software and hardware of the positioning module and the related wire harness in the intelligent cabin can be removed to reduce the system cost, but also the two systems use the same positioning system to fundamentally solve the positioning deviation problem.

[0068] In the second optional implementation, the positioning system of the intelligent cabin is upgraded, the GPS of the intelligent cabin is upgraded to RTK, and the three-axis IMU of the intelligent cabin is upgraded to six-axis IMU, so as to improve the accuracy of the hardware and the accuracy of the system.

[0069] In the above-mentioned second optional implementation of the application, the intelligent driving positioning system can be removed, and the positioning system of the intelligent cabin (also referred to as the cabin system in the embodiment of the application) after the upgrade can receive the positioning data obtained by fusing the satellite positioning result obtained by the positioning module and the data obtained by the motion state sensor to obtain the high-precision positioning signal, which is then transmitted to the intelligent driving system to perform navigation. In this way, not only the software and hardware of the positioning module and the related wire harness in the intelligent driving system can be removed to reduce the system cost, but also the two systems use the same positioning system to fundamentally solve the positioning deviation problem. For details, please refer to the following.

[0070] The first aspect, Figure 2 The first aspect of the vehicle control method of the embodiment of the application is shown in the flowchart.

[0071] As Figure 2As shown, the vehicle control method of the embodiments of the present application can include steps 110 to 140 as follows:

[0072] Step 110, in the case of receiving a map used by a user using a vehicle cabin system, the satellite positioning result obtained by the positioning module and the data obtained by the motion state sensor are fused to obtain positioning data.

[0073] The positioning module herein is used to achieve positioning less than or equal to centimeter level. The positioning module can include at least one of a centimeter level positioning module and a sub-centimeter level positioning module. In this way, as the positioning technology develops, the positioning becomes more accurate.

[0074] The specific accuracy of the above-mentioned "centimeter level positioning" is not fixed to a certain centimeter value, which is used to represent that the centimeter level positioning error is controlled within a range of several centimeters to several tens of centimeters, such as (1-100 cm).

[0075] Specifically, the centimeter level positioning accuracy generally covers the following ranges:

[0076] The relatively higher accuracy of the centimeter level positioning range can be, for example, 1-5 centimeters.

[0077] The relatively lower accuracy of the centimeter level positioning range can be, for example, 5-50 centimeters.

[0078] The sub-centimeter level positioning module is used to represent that the positioning accuracy is higher than that of the centimeter level positioning module. The sub-centimeter level positioning module can include but is not limited to a millimeter level positioning module.

[0079] The accuracy range of the above-mentioned millimeter level positioning module is that the millimeter level positioning error is between 1 millimeter and several tens of millimeters (1-100 mm).

[0080] Specifically, the relatively higher accuracy of the millimeter level positioning range can be, for example, 1-10 mm.

[0081] The relatively lower accuracy of the millimeter level positioning range can be, for example, 10-100 mm.

[0082] The positioning accuracy of the above-mentioned positioning module includes centimeter level positioning or sub-centimeter level positioning. The positioning module can include but is not limited to at least one of a GNSS (Global Navigation Satellite System Chip) chip and a real-time kinematic differential positioning RTK. In this way, due to the fusion of the positioning accuracy of the positioning module belonging to the centimeter level positioning or the sub-centimeter level positioning and the data obtained by the motion state sensor, the fused data is more comprehensive, and more accurate positioning data can be obtained. Moreover, based on the positioning data for navigation, the accuracy of the navigation can be improved.

[0083] The sub-centimeter positioning module, but not limited to, includes a millimeter positioning module composed of an Ultra-Wideband (UWB) positioning technology and an inertial measurement unit (IMU).

[0084] The motion state sensor is used to measure acceleration, angular velocity, attitude change, etc. The motion state sensor can include, but is not limited to, at least one of an inertial sensor and an attitude sensor.

[0085] In step 110, the positioning data obtained by fusing the satellite positioning result obtained by the positioning module and the data obtained by the motion state sensor is more accurate.

[0086] In addition, for step 110, when the user is ready to open the map, the user inputs an opening instruction for opening the map. The system can receive the opening instruction for opening the map from the user, and in response to the opening instruction, receive the map used by the user through the vehicle cabin system. The opening instruction can include a voice instruction and / or a touch instruction, which will not be listed one by one. In this way, when using the map, the positioning data obtained by the positioning module and the motion state sensor is received in real time.

[0087] In step 120, the ego position of the vehicle is obtained according to the positioning data.

[0088] In step 130, when the user activates the navigation, the starting position of the map is matched according to the ego position to plan the navigation path.

[0089] For step 130, when the user navigates, the user inputs a trigger instruction for triggering the navigation of the map. The system can receive the trigger instruction for triggering the navigation of the map from the user, and in response to the trigger instruction, receive the map used by the user through the vehicle cabin system.

[0090] In step 140, the ego position and the navigation path are sent to the intelligent driving system, so that the intelligent driving system controls the vehicle to travel according to the navigation path according to the ego position and the navigation path.

[0091] Further, in step 140, the ego position, the navigation path, and the matching road topology information are sent to the intelligent driving system. In this way, the intelligent driving system can determine that the vehicle deviates from the navigation route continuously by using the road topology information, and then re-plan the navigation path. Details are not described here.

[0092] In combination Figure 2As shown, the step 110 can include, but is not limited to, receiving satellite positioning results obtained by real-time kinematic positioning (RTK) and data obtained by an inertial measurement unit (IMU) with three or more axes, and fusing the obtained positioning data.

[0093] Since the satellite returns a coordinate value, and the transmission link has a time, the returned coordinate value is not completely accurate. The present specification needs to be combined with vehicle speed and / or acceleration multiplied by signal delay time to correct the positioning data to obtain corrected positioning data. Preferably, the vehicle speed, especially the vehicle speed with direction, and the acceleration need to be obtained with high-precision IMU assistance. In this way, by fusing RTK and IMU, the positioning deviation between the two systems can be reduced. At the same time, by RTK and IMU, the positioning can be accurately performed to the centimeter level, and the scenes such as the main and auxiliary roads in the plane, the elevated roads in the three-dimensional space, etc. can be improved. The positioning accuracy and the sensitivity of navigation. The above-mentioned inertial measurement unit (IMU) with three or more axes can not include a three-axis IMU, and can include at least one of a six-axis IMU, a nine-axis IMU, and an IMU with nine or more axes.

[0094] The above-mentioned six-axis IMU can be composed of a three-axis accelerometer and a three-axis gyroscope. The accelerometer is used to measure the linear acceleration of the object in three orthogonal axes, and the gyroscope is used to measure the angular velocity of the three orthogonal axes, which can provide six degrees of freedom measurement.

[0095] The above-mentioned nine-axis IMU can be a three-axis magnetometer added to the six-axis IMU, also known as an attitude sensor or AHRS. Among them, the magnetometer measures the magnetic field strength in three dimensions, and by using the earth's magnetic field, it can help determine the heading of the object and the roll and pitch, and correct the integrated error of the yaw gyroscope in the sensor fusion algorithm.

[0096] It should be noted that the above-mentioned receiving satellite positioning results obtained by real-time kinematic positioning (RTK) and data obtained by an inertial measurement unit (IMU) for fusion can be realized by at least one of the following optional embodiments:

[0097] In the first optional embodiment, the satellite positioning results obtained by the RTK of the cockpit system and the data obtained by the IMU of the cockpit system are fused to obtain the positioning data.

[0098] Since the data of RTK and IMU are directly used inside the cockpit system, only one system is used, and there is no need to synchronize the frequency with RTK and IMU. In this way, the positioning hardware of the cockpit system is improved, and the cockpit system can directly obtain the data using the data of RTK and IMU, which not only reduces the positioning module of the intelligent driving system, but also reduces the cost. Moreover, using the data of RTK and IMU can reduce the positioning deviation between the two systems to achieve high-precision navigation. In this way, the positioning signal synchronization between the intelligent driving domain and the cockpit domain is continuously completed, which fundamentally solves the positioning deviation.

[0099] In a second optional embodiment, in the first step, the satellite positioning result obtained by the RTK of the intelligent driving system and the data obtained by the IMU of the intelligent driving system are fused to obtain the positioning data. Correspondingly, the above-mentioned step 120 can further include a second step and a third step:

[0100] In the second step, according to the signal delay duration, the vehicle speed and the driving direction of the vehicle, the delay displacement of the vehicle within the signal delay duration is determined. The signal delay duration is used to represent that the receiving timestamp and the sending timestamp of the same signal are different, and the clock of the cockpit system is synchronized with the clock of the intelligent driving system or uses the same clock. Among them, the synchronization of the clock of the cockpit system and the clock of the intelligent driving system can include but is not limited to that the cockpit is the master clock and the intelligent driving is the slave clock.

[0101] The above-mentioned receiving timestamp can refer to the current time when the vehicle receives the positioning data.

[0102] In some examples, the determination of the driving direction of the vehicle can be determined by the linear acceleration and the rotational angular velocity in the three orthogonal axial directions of the X-axis, the Y-axis and the Z-axis obtained by the six-axis inertial measurement unit IMU.

[0103] In yet some examples, the determination of the driving direction of the vehicle can be determined by the linear acceleration, the rotational angular velocity and the components of the geomagnetic field in the X-axis, the Y-axis and the Z-axis at the position of the vehicle obtained by the nine-axis inertial measurement unit IMU.

[0104] Correspondingly, the above-mentioned second step can further include a first step of obtaining the real-time driving direction of the vehicle according to the six-axis inertial measurement unit IMU or the nine-axis inertial measurement unit IMU. The second step is to multiply the signal delay duration and the vehicle speed in the real-time driving direction of the vehicle as the delay displacement of the vehicle within the signal delay duration.

[0105] The second step can further include (1) determining whether the signal delay duration meets a compensation duration condition; (2) if the signal delay duration meets the compensation duration condition, determining a delay displacement of the vehicle within the signal delay duration according to the signal delay duration, the vehicle speed and the driving direction of the vehicle; and (2) if the signal delay duration does not meet the compensation duration condition, returning to step 110 for continuous execution. In this way, when the signal delay duration is relatively short, the corresponding delay displacement is relatively small, indicating that the synchronization frequency of the RTK and the IMU of the intelligent driving system is high, and this step can be omitted. The delay can be ignored, reducing the computing burden of the system. In this way, without increasing the cost of a single vehicle, the positioning signals in the two fields are synchronized or shared according to the above logical flow, and the problem caused by the deviation of the positioning signals is fundamentally solved.

[0106] The compensation duration condition can be adjusted and set variably. The compensation duration condition is related to the positioning accuracy of the positioning module. The greater the positioning accuracy, the smaller the compensation duration. The smaller the positioning accuracy, the greater the compensation duration. For example, for a centimeter-level positioning module, the corresponding compensation duration condition is greater than or equal to 0.3 ms (milliseconds). For example, for a millimeter-level positioning module, the corresponding compensation duration condition is greater than or equal to 0.03 ms.

[0107] The third step is to compensate for the delay displacement on the basis of the positioning data to obtain corrected positioning data as the ego position of the vehicle.

[0108] For example, the intelligent driving system sends positioning data at 12:00 on A / B / C day. The receiving time stamp of the positioning data received by the system is 12:01 on A / B / C day. Within this 1 second, the system determines the delay displacement distance according to the vehicle speed and the driving direction. The positioning data plus the delay displacement distance gives the ego position of the vehicle.

[0109] In the second optional embodiment, the high-precision positioning signal in the intelligent driving domain controller is transmitted to the cockpit system for positioning and navigation. Further, the cockpit system can indirectly obtain data through the intelligent driving domain controller to achieve high-precision navigation. At the same time, the integration of the embodiments of the present application is higher, reducing the repeated development work, and the problem link is shorter.

[0110] Based on the second optional embodiment, the signal delay duration is determined in at least one of the following optional examples:

[0111] In an optional example, the positioning data comprises a sending time stamp and position data of the vehicle at the sending time stamp. Correspondingly, in the above-mentioned case of receiving the map used by the user through the vehicle cabin system, receiving the positioning data of the intelligent driving system and the navigation path input by the user and containing the starting position respectively comprises: in the case of receiving the map used by the user through the vehicle cabin system, receiving the position data of the vehicle, and receiving the navigation path input by the user and containing the starting position, and recording the receiving time stamp of the position data of the vehicle being received;

[0112] Correspondingly, the above-mentioned method further comprises determining the signal delay duration according to the sending time stamp and the receiving time stamp. Wherein, the receiving time stamp is subtracted from the sending time stamp to obtain the signal delay duration.

[0113] In an optional example of the present application, the signal delay duration can be determined in real time to obtain real-time delay displacement, which is more in line with the actual vehicle driving situation, and thus the navigation conforming to the actual situation is completed.

[0114] In an optional example, in the first step, the test signal is sent by the intelligent driving system multiple times; the test signal comprises a sending time stamp. In the second step, each time the test signal is received, the receiving time stamp of each test signal being received is recorded. In the third step, the signal delay duration is obtained according to the receiving time stamp and the sending time stamp.

[0115] In this paper, the above-mentioned first step to the third step can be used to test the signal delay duration between the intelligent driving system and the cabin system when each test vehicle is driving.

[0116] In an optional example of the present application, due to the fixed configuration of the hardware, the signal delay duration can be determined through multiple tests as a preset value, so as to obtain the accurate value of the ego position of the vehicle, and thus more accurate navigation is realized.

[0117] In this specification, the signal delay duration is determined according to the sending time stamp and the receiving time stamp in the following way:

[0118] In an optional way, the current time difference is obtained by subtracting the sending time stamp from the receiving time stamp as the signal delay duration.

[0119] In another optional way, the current time difference is obtained by subtracting the average of the sending time stamp from the receiving time stamp as the signal delay duration.

[0120] The above-mentioned vehicle control method is applied to an electronic device. The electronic device can but not limited to include at least any one of the vehicle body processor, the vehicle body controller, the cabin domain controller, for realizing the vehicle control method as in the above-mentioned first aspect.

[0121] In a second aspect, based on the same inventive concept as the above method, the embodiments of the present application also provide an electronic device to which the above vehicle control method is applied. The electronic device may, but is not limited to, include at least any one of a body processor, a body controller, and a cockpit domain controller, and is configured to implement the vehicle control method of the first aspect as described above, such as Figure 3 As shown in the method, the method may, for example, include the following steps 210 and 220.

[0122] In step 210, satellite positioning results obtained by a positioning module of the intelligent driving system and data obtained by a motion state sensor are fused to obtain positioning data.

[0123] In step 220, the satellite positioning results and the obtained data are fused to obtain positioning data of the intelligent driving system.

[0124] In step 230, the positioning data with a sending timestamp is sent to a cockpit system. The clock of the cockpit system is synchronized with the clock of the intelligent driving system or uses the same clock. The cockpit system is configured to implement the vehicle control method of the first aspect as described above.

[0125] In the present specification, the above positioning data of the cockpit system may, for example, be sent at a sending frequency of 10 times per second. The intelligent driving domain and the cockpit domain naturally interact with signals, and the communication protocol of the communication mode uses the following: 1. CAN (Controller Area Network) protocol. 2. Ethernet protocol. Both channels can transmit positioning signals, so there is no need to add a communication protocol at the hardware level.

[0126] For this purpose, in the present specification, the positioning data with a sending timestamp is sent to the cockpit system through a vehicle-mounted Ethernet cable. Alternatively, the positioning data with a sending timestamp is sent to the cockpit system through a CAN line.

[0127] As an embodiment, the satellite positioning results obtained by the positioning module of the intelligent driving system and the data obtained by the motion state sensor are fused to obtain the positioning data, which includes:

[0128] The satellite positioning results obtained by the real-time kinematic differential positioning RTK of the intelligent driving system and the data obtained by the inertial measurement unit IMU.

[0129] The above vehicle control method is applied to an electronic device. The electronic device may, but is not limited to, include at least any one of a body processor, a body controller, and an intelligent driving domain controller, and is configured to implement the vehicle control method of the second aspect as described above.

[0130] In a third aspect, based on the same inventive concept as the above method, the embodiments of the present application also provide a vehicle control device, which is configured to implement the vehicle control method of the first aspect as described above, such asFigure 4 As shown in the figure, the apparatus can include the following modules.

[0131] The receiving module 31 is configured to fuse the satellite positioning result obtained by the positioning module and the data obtained by the motion state sensor to obtain positioning data when receiving a map used by the user in the vehicle cabin system.

[0132] The ego vehicle position module 32 is configured to obtain the ego vehicle position of the vehicle according to the positioning data.

[0133] The matching module 33 is configured to match the starting position of the map according to the ego vehicle position to plan a path when receiving the user-activated navigation, to obtain a navigation path.

[0134] The first sending module 34 is configured to send the ego vehicle position and the navigation path to the intelligent driving system, so that the intelligent driving system controls the vehicle to travel according to the navigation path according to the ego vehicle position and the navigation path.

[0135] As an embodiment, the apparatus further includes a delay determination module configured to determine the signal delay duration in the following manner:

[0136] The sending sub-module is configured to send the test signal multiple times by the intelligent driving system; the test signal includes a sending timestamp.

[0137] The processing sub-module is configured to receive each sent test signal and record a receiving timestamp of each test signal.

[0138] The delay determination sub-module is configured to obtain the signal delay duration according to the receiving timestamp and the sending timestamp.

[0139] In a fourth aspect, based on the same inventive concept as the above method, the embodiments of the present application further provide a vehicle control apparatus, such as Figure 5 As shown in the figure, the apparatus can include the following modules.

[0140] The acquisition module 41 is configured to acquire the positioning data obtained by fusing the satellite positioning result obtained by the positioning module of the intelligent driving system and the data obtained by the motion state sensor.

[0141] The fusion module 42 is configured to fuse the satellite positioning result and the obtained data to obtain the positioning data of the intelligent driving system.

[0142] The second sending module 43 is configured to send the positioning data marked with a sending timestamp to the cabin system; the clock of the cabin system is synchronized with or uses the same clock as the clock of the intelligent driving system; so that the cabin system is configured to implement the vehicle control method of the second aspect.

[0143] Correspondingly, the functions and effects of the modules / sub-modules of the device are the same as those of the steps of the method, and thus are not described here.

[0144] In a fifth aspect, an embodiment of the present application provides an electronic device, including the vehicle control device in the third aspect or the vehicle control device in the fourth aspect.

[0145] In a sixth aspect, an embodiment of the present application provides a vehicle control system, including:

[0146] a smart driving domain controller, configured to implement the vehicle control method in the second aspect;

[0147] a cockpit domain controller, configured to implement the vehicle control method in the first aspect.

[0148] In this way, the synchronization of positioning signals between the smart driving domain and the two domains is continuously completed, and the deviation of positioning is fundamentally solved.

[0149] In a seventh aspect, an embodiment of the present application provides a vehicle, including the electronic device or the vehicle control device.

[0150] Figure 6 As shown in FIG. 5, an embodiment of the present application provides a structure schematic diagram of an electronic device 50.

[0151] As shown in FIG. 5, an embodiment of the present application provides a structure schematic diagram of an electronic device 50. Figure 6 As shown in FIG. 5, an embodiment of the present application provides a structure schematic diagram of an electronic device 50.

[0152] In some embodiments, the electronic device 50 can include a storage medium 59. For example, the computer readable storage medium can store a program that can be invoked by the processor 51, and can include a non-volatile storage medium. In some embodiments, the electronic device 50 can include a memory 58 and an interface 57. In some embodiments, the electronic device 50 can further include other hardware according to actual application.

[0153] The computer readable storage medium of the embodiment of the present application has a program stored thereon, and the program is executed by the processor 51 to implement the vehicle control method as described above.

[0154] In a seventh aspect, an embodiment of the present application provides a vehicle, including one or more processors, configured to implement the vehicle control method in the first aspect or the vehicle control method in the second aspect.

[0155] In an eighth aspect, the present application provides a computer program product comprising computer programs / instructions which, when executed by a processor, implement the method of any of the above.

[0156] In a ninth aspect, the embodiments of the present application also provide a computer program stored in a computer readable storage medium, for example, Figure 6 a storage medium 59, and when the processor executes the computer program, causes the processor 51 to execute the method described above.

[0157] The present application can take the form of a computer program product implemented on one or more computer readable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage media, etc.) having computer code thereon. Computer readable storage media include permanent and non-permanent, movable and non-movable media, which can implement information storage in any method or technology. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer readable storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0158] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0159] It should also be noted that the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusion, so that processes, methods, articles or devices including a series of elements not only include those elements, but also include other elements not explicitly listed, or inherent to such processes, methods, articles or devices. Without more limitations, the statement "including a……" limited element does not exclude the presence of other identical elements in the process, method, article or device including the element.

Claims

1. A vehicle control method characterized by, The method comprises the following steps: In the case of receiving a map used by a user in a vehicle cabin system, satellite positioning results obtained by a positioning module and data obtained by a motion state sensor are fused to obtain positioning data; and a self-vehicle position of the vehicle is obtained according to the positioning data; In the case of receiving a user-activated navigation, a navigation path is planned according to the self-vehicle position and a map starting position to obtain the navigation path; The self-vehicle position and the navigation path are sent to an intelligent driving system, so that the intelligent driving system controls the vehicle to travel according to the navigation path according to the self-vehicle position and the navigation path.

2. The vehicle control method according to claim 1, characterized by, The positioning accuracy of the positioning module comprises centimeter-level positioning or less than centimeter-level positioning; The positioning data obtained by fusing the satellite positioning results obtained by the positioning module and the data obtained by the motion state sensor comprises: The positioning data obtained by fusing satellite positioning results obtained by a real-time kinematic differential positioning (RTK) and data obtained by an inertial measurement unit (IMU) with more than three axes.

3. The vehicle control method according to claim 2, characterized by, The positioning data obtained by fusing the satellite positioning results obtained by the RTK and the data obtained by the IMU comprises: The positioning data obtained by fusing satellite positioning results obtained by an RTK of the cabin system and data obtained by an IMU of the cabin system.

4. The vehicle control method according to claim 2, characterized by, The positioning data obtained by fusing the satellite positioning results obtained by the RTK and the data obtained by the IMU comprises: The positioning data obtained by fusing satellite positioning results obtained by an RTK of the intelligent driving system and data obtained by an IMU of the intelligent driving system; The self-vehicle position of the vehicle obtained according to the positioning data comprises: According to a signal delay duration, a vehicle speed of the vehicle and a travel direction of the vehicle, a delay displacement of the vehicle within the signal delay duration is determined; the signal delay duration is used to represent that a receiving timestamp and a sending timestamp of a same signal are different, and a clock of the cabin system and a clock of the intelligent driving system are synchronized or use a same clock; On the basis of the positioning data, the delay displacement is compensated to obtain corrected positioning data as the self-vehicle position of the vehicle.

5. The vehicle control method according to claim 4, characterized by The positioning data comprises a sending timestamp and position data of the vehicle at the sending timestamp; In the case of receiving a map used by a user in a vehicle cabin system, positioning data of the intelligent driving system and a navigation path containing a starting position input by the user are received respectively, which comprises: In the case of receiving a map used by a user in a vehicle cabin system, position data of the vehicle is received, and a navigation path containing a starting position input by the user is received, and a receiving timestamp at which the position data of the vehicle is received is recorded; Correspondingly, the method further comprises: According to the sending timestamp and the receiving timestamp, a signal delay duration is determined.

6. The vehicle control method according to claim 4, characterized by The method further comprises: The signal delay duration is determined in the following manner: Test signals are sent by the intelligent driving system multiple times; the test signals comprise sending timestamps; receive each time a test signal is transmitted and record a receiving time stamp of each time a test signal is received; obtain a signal delay duration according to the receiving time stamp and the transmitting time stamp.

7. The vehicle control method according to claim 4, characterized by determine a delay displacement of the vehicle within the signal delay duration according to the signal delay duration, the vehicle speed and the driving direction of the vehicle, including: obtain a real-time driving direction of the vehicle according to a six-axis inertial measurement unit (IMU); multiply the signal delay duration and the vehicle speed in the real-time driving direction of the vehicle as the delay displacement of the vehicle within the signal delay duration.

8. A vehicle control method characterized by, including: obtain positioning data by fusing satellite positioning results obtained by a positioning module of an intelligent driving system and data obtained by a motion state sensor; fuse the satellite positioning results and the obtained data to obtain positioning data of the intelligent driving system; send the positioning data with a transmitting time stamp to the cockpit system; the clock of the cockpit system is synchronized with the clock of the intelligent driving system or uses the same clock; so that the cockpit system is used to implement the vehicle control method in any one of claims 1 to 6.

9. The vehicle control method according to claim 8, characterized by, the obtaining positioning data by fusing satellite positioning results obtained by a positioning module of an intelligent driving system and data obtained by a motion state sensor, including: obtain satellite positioning results obtained by a real-time kinematic (RTK) of the intelligent driving system and data obtained by an inertial measurement unit (IMU).

10. A vehicle control device characterized by comprising: including: a receiving module, configured to receive positioning data obtained by fusing satellite positioning results obtained by a positioning module and data obtained by a motion state sensor when a user uses a map of a vehicle cockpit system; a self-vehicle position module, configured to obtain a self-vehicle position of the vehicle according to the positioning data; a matching module, configured to match a starting position of the map according to the self-vehicle position to plan a path when a user activates navigation, to obtain a navigation path; a first sending module, configured to send the self-vehicle position and the navigation path to the intelligent driving system, so that the intelligent driving system controls the vehicle to travel according to the navigation path according to the self-vehicle position and the navigation path.

11. A vehicle control device characterized by comprising: including: an obtaining module, configured to obtain positioning data by fusing satellite positioning results obtained by a positioning module of an intelligent driving system and data obtained by a motion state sensor; a fusion module, configured to fuse the satellite positioning results and the obtained data to obtain positioning data of the intelligent driving system; a second sending module, configured to send the positioning data with a transmitting time stamp to the cockpit system; the clock of the cockpit system is synchronized with the clock of the intelligent driving system or uses the same clock; so that the cockpit system is used to implement the vehicle control method in any one of claims 1 to 7.

12. An electronic device, comprising: including one or more processors configured to implement the vehicle control method in any one of claims 1 to 7 or the vehicle control method in any one of claims 8 to 9.

13. A vehicle characterized by comprising: A vehicle control method as claimed in any one of claims 1 to 7 or a vehicle control method as claimed in any one of claims 8-9.

14. A computer-readable storage medium, characterized in that, A vehicle control method as claimed in any one of claims 1 to 7 or a vehicle control method as claimed in any one of claims 8-9.

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