Vehicle driving assistance system, control unit and method thereof

Abstract

A vehicle driving assistance system, a control unit, and a method thereof are provided. The control unit includes a base difference determination module configured to calculate a base difference based on a current position of a vehicle in an autonomous driving mode and a corresponding biased position, the current position being a position determined based on satellite signals, the corresponding biased position being the current position after biasing the current position via a deflection plug-in; a deflection difference determination module configured to calculate a deflection difference based on a position difference between an unbiased point of the vehicle and a biased point after biasing the vehicle via a deflection plug-in, the deflection difference being the value obtained by subtracting the base difference from the position difference; and a decision module configured to determine an autonomous driving strategy for the vehicle based on the deflection difference.

Description

Technical Field

[0001] The present application generally relates to the technical field of driving assistance for vehicles, and in particular to a control unit for a driving assistance system and a vehicle driving assistance system including the control unit, and also to a vehicle driving assistance method and a corresponding machine-readable storage medium. Background Art

[0002] Positioning technology provides location-based services and is essential for autonomous driving. For example, vision-based positioning, satellite-based positioning, and high-precision map-based positioning can be used. Each of these positioning technologies has its own advantages and disadvantages. For example, extreme weather conditions can cause visual impairments, and occlusions can cause GPS signal fluctuations. Consequently, a single positioning solution is often insufficient for a vehicle to locate itself in complex environments and under varying road conditions. Therefore, existing technologies have proposed the use of multiple, mutually redundant positioning solutions to provide positioning services for autonomous vehicles.

[0003] Regarding positioning technology used in autonomous driving, more research has focused on how to compensate for visual deficiencies and how to eliminate unstable GPS signals. However, there is still no better solution to another type of problem, namely, how to deal with the positioning challenges caused by the nonlinear deformation of location data after deflection and encryption. Summary of the Invention

[0004] In view of the above problems in the prior art, the present invention aims to provide an improved driving assistance solution.

[0005] According to an embodiment of the first aspect of the present invention, a control unit for a driving assistance system is provided, comprising: a basic difference determination module, configured to calculate a basic difference based on a current position of a vehicle in an automatic driving mode and a corresponding biased position, wherein the current position is a position determined based on a satellite signal, and the corresponding biased position is the position of the current position after being biased by a deflection plug-in; a deflection difference determination module, configured to calculate a deflection difference based on a position difference between a position of an unbiased point of the vehicle and a position of a biased point after being biased by a deflection plug-in, wherein the deflection difference is a value obtained by subtracting the basic difference from the position difference; and a decision module, configured to determine an automatic driving strategy for the vehicle based on the deflection difference.

[0006] According to an embodiment of the second aspect of the present invention, a driving assistance system is provided, comprising: a positioning device for determining the position of a vehicle based on satellite signals; and a control device, comprising a deflection plug-in and a control unit as described above, connected to the positioning device, for determining a deflection difference based on a position difference between a position of an unbiased point and a position of a biased point after being biased by the deflection plug-in, and determining an automatic driving strategy based on the deflection difference.

[0007] According to an embodiment of the third aspect of the present invention, a driving assistance method is provided. Optionally, the method is executed by the control unit as described above and / or the system as described above, and the method includes: calculating a deflection difference based on the position difference between the unbiased point position of the vehicle in the automatic driving mode and the biased point position after being biased by the deflection plug-in; and determining an automatic driving strategy for the vehicle based on the deflection difference.

[0008] According to an embodiment of a fourth aspect of the present invention, a machine-readable storage medium is provided, which stores executable instructions. When the instructions are executed, one or more processors are caused to perform the method described above.

[0009] It can be seen that according to an embodiment of the present invention, it is possible to monitor the nonlinear deviation (i.e., deflection difference) caused by the deflection and encryption of position data of the vehicle in the automatic driving mode, and it is also possible to make appropriate automatic driving strategies based on the monitored deviations, thereby improving the safety of the vehicle's automatic driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A vehicle having a driving assistance system according to an embodiment of the present invention is schematically shown.

[0011] Figure 2 yes Figure 1 Schematic block diagram of the driver assistance system in .

[0012] Figure 3 yes Figure 1 Schematic block diagram of the control unit of the driver assistance system in FIG.

[0013] Figure 4 The figure schematically shows a driving assistance process according to an embodiment of the present invention.

[0014] Figure 5 FIG. 4 is a schematic diagram of a deflection difference determination process according to an embodiment of the present invention.

[0015] Figure 6 is a flowchart of a driving assistance method according to one embodiment of the present invention. DETAILED DESCRIPTION

[0016] Digital maps used for autonomous driving can assist vehicles in perceiving their environment, providing road and road condition information and helping them develop autonomous driving strategies. However, digital maps used for autonomous driving must be processed using a deflection encryption algorithm. Consequently, when a vehicle uses a deflected map to perform autonomous driving, the positioning of objects on the deflected map deviates from their true position. This deviation includes a base error (described below as the "base error," e.g., approximately several hundred meters) and a random error (also referred to as a "nonlinear error," i.e., the "deflection error" described below).

[0017] Considering that such random deviations can cause errors in the vehicle's positioning of objects in the surrounding environment relative to the actual road, potentially leading to dangerous accidents. For example, errors in the vehicle's positioning of the preceding vehicle can lead to an incorrect judgment of the preceding vehicle's lane. The inventors of the present invention have designed a control strategy for driver assistance that calculates and monitors random deviations and determines the appropriate autonomous driving strategy based on these deviations, thereby improving the safety of autonomous driving.

[0018] Furthermore, the inventors also created a system error model based on the random difference to determine the error of the object position perceived by the vehicle relative to the real road, thereby achieving quantitative calculation of the error.

[0019] The specific embodiments of the present invention are described below with reference to the accompanying drawings.

[0020] Figure 1 A vehicle having a driving assistance system according to an embodiment of the present invention is schematically shown. Figure 2 yes Figure 1 Schematic block diagram of the driver assistance system in . Figure 1 and Figure 2 The driving assistance system 100 is arranged in the vehicle 1 and mainly includes a positioning device 10 and a control device 20.

[0021] The positioning device 10 is used to determine the position of the vehicle 1 (ie, the vehicle itself). The positioning device 10 may be implemented as a vehicle-mounted GPS locator that receives satellite signals and determines the position of the vehicle itself based on the received satellite signals.

[0022] The control device 30 mainly comprises a deflection plug-in 21 and a control unit 22 .

[0023] The deflection plug-in 21 is also called a security plug-in and can be set in the controller of the driving assistance system. The deflection plug-in 21 can convert the coordinates of the position determined by the positioning device 10 into deflected encrypted coordinates, which can be matched with the deflected digital map.

[0024] Control unit 22 includes a control strategy that calculates and monitors the nonlinear deviations introduced by the deflection encryption algorithm and determines an appropriate autonomous driving strategy based on these nonlinear deviations. Furthermore, this control strategy provides a system error model to determine the error between the perceived objects and the actual road surface. The operating principles of control unit 22 are described in detail below.

[0025] The control unit 22 can be implemented in hardware, software, or a combination of software and hardware. For hardware-implemented portions, these can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic units designed to perform their functions, or combinations thereof. For software-implemented portions, these can be implemented with the aid of microcode, program code, or code segments, and can also be stored in a machine-readable storage medium such as a storage component.

[0026] In one implementation, the control unit 22 is implemented as including a memory and a processor. The memory contains instructions that, when executed by the processor, enable the processor to perform a control strategy / control method according to an embodiment of the present invention.

[0027] The driving assistance system 100 may further include a sensing device 30 and a digital map 40 .

[0028] The sensing device 30 is used to sense the surrounding environment of the vehicle 1 and output environmental information. The sensing device 30 is implemented as an environmental sensor. The environmental sensor can be set inside the vehicle 1 or on one or more sides of the vehicle 1, that is, implemented as a vehicle-mounted sensor. For example, the environmental sensor can be one or more of the following: a vehicle-mounted camera (single target or multi-target), a laser radar, an ultrasonic radar (such as a millimeter wave radar), a vehicle-mounted receiver, etc. The vehicle-mounted camera can capture images or videos containing environmental information; the radar can sense the relative distance between the vehicle and surrounding objects; the vehicle-mounted receiver can determine the relative position relationship between the objects around the vehicle and the vehicle by the time delay of the received signal or according to the timestamp information in the received signal.

[0029] Sensing device 30 can also be implemented as a sensor external to vehicle 1, capable of transmitting sensed environmental information to the vehicle via wireless communication. For example, cameras, radar, or wireless transceivers can be installed on the roadside. Roadside intelligent devices analyze the collected information and transmit the analysis results to the vehicle, where further calculations can be performed based on the analysis results. In other words, in the present invention, environmental information can come from onboard environmental sensors, external environmental sensors, or both, with the environmental information from both sources being fused and processed.

[0030] The digital map 40 can assist in the autonomous driving of the vehicle 1. For example, the digital map 40 can provide road information and traffic condition information, and help the vehicle 1 formulate an autonomous driving strategy. The digital map 40 is, for example, a high-definition map (HD MAP). The digital map 40 can be stored on the vehicle, for example, in a memory (not shown) of the driving assistance system 100. The digital map 40 can also be stored on an edge server or a cloud server and retrieved from the edge server or cloud server via a communication interface on the vehicle. The map data in the digital map 40 used for autonomous driving is deflected and encrypted. That is, the coordinates displayed in the digital map 40 are deflected coordinates that have been deflected and encrypted from the real coordinates.

[0031] Next, the structure and working principle of the control unit 22 are introduced.

[0032] See also Figure 3 The control unit 22 primarily includes a base difference determination module 221, a deflection difference determination module 222, a decision module 223, and a creation module 224. It should be understood that the naming of the modules of the control unit 22 should be understood as a logical description, and should not be construed as limiting their physical form or configuration. In other words, one or more of the determination module 221, the deflection difference determination module 222, the decision module 223, and the creation module 224 can be implemented in the same chip or circuit, or they can be separately configured in different chips or circuits, and this is not a limitation of the present invention.

[0033] Figure 4 A driving assistance process 400 according to an embodiment of the present invention is schematically shown. Figure 5 The principle of the deflection difference determination process according to one embodiment of the present invention is schematically illustrated.

[0034] In block 402, the base delta determination module 221 calculates a base delta based on the vehicle's current position and a corresponding offset position. The current position is the position determined based on satellite signals, i.e., the position without offset. The corresponding offset position is the current position after offsetting via the deflection plug-in.

[0035] See also Figure 5 In one embodiment, the basic difference determination module 221 obtains the current position P1 of the vehicle and the corresponding offset position P1' from the positioning device 10. The offset position P1' is the position of the current position P1 after the deflection plug-in is applied. Then, the position difference between the current position P1 and the offset position P1' is calculated as the basic difference Δd base .

[0036] In block 404, the deflection difference determination module determines the unbiased preset trajectory L starting from the current position. lane-pre And sample multiple unbiased points on the preset trajectory (for example, Figure 5 The plurality of unbiased points are a plurality of locations sampled on the preset trajectory (e.g., represented by a plurality of position coordinates) that are not biased by the deflection plug-in. The preset trajectory can be a straight path, a curved path, or a combination of straight paths and curved paths. The preset trajectory can have a predetermined length L. The length L can be represented by the straight-line distance between the starting point and the end point of the preset trajectory.

[0037] An embodiment of determining a preset trajectory and a plurality of sampling points (ie, a plurality of sampled unbiased points) is described below by way of example.

[0038] In one embodiment, the current position of the vehicle (based on the current position of the satellite signal) is used as the starting point, and a path is selected from the path planned by the automatic driving system for the vehicle as the preset trajectory L. lane-pre That is, the preset trajectory is obtained by using the planned path of the autonomous driving system. A plurality of position points are sampled on the selected path as a plurality of unbiased points.

[0039] In another embodiment, the current position of the vehicle (based on the current position of the satellite signal) is taken as the starting point, and a straight line path is taken along the forward direction of the vehicle as the preset trajectory L lane-pre .Sampling multiple position points on the straight line path as multiple unbiased points.

[0040] In another embodiment, the current position of the vehicle (based on the current position of the satellite signal) is used as the starting point, and multiple straight paths are taken in multiple directions that deviate from the vehicle's forward direction, and these straight paths are used as the preset trajectory L lane-pre . Sampling multiple position points on multiple straight line paths as multiple unbiased points

[0041] In another embodiment, one or more concentric circular paths are determined with the current position of the vehicle (based on the current position of the satellite signal) as the center of the circle, and the one or more concentric circular paths are used as the preset trajectory L lane-pre .Sampling a plurality of position points on one or more concentric circle paths as the plurality of unbiased points.

[0042] It is understandable that the preset trajectory may also be determined by combining multiple sampling methods in the above embodiments.

[0043] It is understandable that after the preset trajectory is determined, the present invention does not limit how to sample unbiased position points on the preset path.

[0044] In block 406 , the deflection difference determination module 222 obtains a corresponding plurality of biased points based on the plurality of unbiased points.

[0045] In one embodiment, multiple unbiased points are used as inputs and substituted into the deflection plug-in to obtain multiple outputs after being biased by the deflection plug-in, that is, multiple biased points. Figure 5 The coordinates of the unbiased points P2-P6 are input into the deflection plug-in as output to obtain the coordinates of the biased points P2'-P6' (ie, biased coordinates).

[0046] In block 408, the deflection difference determination module 222 calculates a deflection difference Δd based on the position difference between the unbiased point and the biased point. The deflection difference Δd is obtained by removing the base difference Δd from the position difference. base It can be understood that the deflection difference Δd and the basic difference Δd base Both are vectors. Difference between them is to subtract two vectors. The result of subtraction is also a vector, and the value of the vector obtained after subtraction is the modulus.

[0047] Hereinafter, embodiments of the deflection difference Δd will be described by way of example.

[0048] In one embodiment, the deflection difference determination module 222 uses the position difference between the last unbiased point and the corresponding biased point minus the basic difference as the deflection difference Δd. Figure 5 The position difference Δd6 between the last unbiased point P6 sampled and the corresponding biased point P6' is subtracted from the basic difference Δd base The value after this is used as the deflection difference Δd. It is understood that, similar to the above vector subtraction, the position difference Δd6 and the base difference Δdbase are both vectors, and subtracting them is like subtracting two vectors. The result of the subtraction is also a vector, and the value of the vector obtained after the subtraction is the modulus.

[0049] In another embodiment, the deflection difference determination module 222 calculates the position difference between each unbiased point and the corresponding biased point, and subtracts the base difference Δd from the maximum of these position differences (i.e., the maximum position difference). base The subsequent value is taken as the deflection difference Δd.

[0050] In another embodiment, the deflection difference determination module 222 determines the deflection difference Δd based on the ratio of the position difference between each unbiased point and the corresponding biased point to the distance between the unbiased point and the starting point. For example, the deflection difference determination module 222 can calculate the deflection difference Δd based on the following formula:

[0051] Δd=R(max)*L, R(max) is the maximum value among Ri=Δdi / Li,

[0052] Where Li is the straight-line distance from an unbiased point to the starting point (L3 is the straight-line distance from unbiased point P3 to starting point P1), L is the straight-line distance from the last unbiased point to the starting point (for example, the straight-line distance between P1 and P6), Δdi is the position difference between the i-th unbiased point and the i-th biased point minus the base error, and Δd is the deflection error. i is a natural number from 1 to n, and n is the number of unbiased points sampled.

[0053] In yet another embodiment, the deflection difference determination module 222 decomposes the determined deflection difference along the vehicle's travel direction and in a direction perpendicular to it, and uses the component in the perpendicular direction as the deflection difference for determining the autonomous driving strategy. In other words, in this embodiment, the lateral deflection (i.e., the deflection in a direction perpendicular to the vehicle's travel direction) is given greater attention than the longitudinal deflection (i.e., the deflection in the vehicle's travel direction).

[0054] In block 410 , the decision module 223 determines a corresponding autonomous driving strategy based on the determined deflection difference. For example, the decision module 223 compares the deflection difference with a deflection difference threshold and determines the autonomous driving strategy based on the comparison result.

[0055] It is understood that the deflection difference threshold is predetermined and can be determined based on factors such as the autonomous driving level, road level, and road conditions. The deflection difference threshold can also be calculated using a model and combined with actual vehicle testing. The present invention does not limit the method for determining this threshold.

[0056] In block 412 , when the deflection difference is less than the deflection difference threshold, the decision module 223 causes the host vehicle to continue in the automatic driving mode.

[0057] In block 414 , when the deflection difference is less than the deflection difference threshold, the decision module 223 creates an error model including the deflection difference, and uses the error model to determine the error of the object perceived by the vehicle relative to the real road.

[0058] In one embodiment, the error model created by the decision module 223 is:

[0059]

[0060] Among them, δ A_to_real_road is the error of object A perceived by the vehicle relative to the real road, δ per is the error generated when the perception device of the autonomous driving system of the vehicle perceives object A (for example, the error generated when the camera or radar senses the front vehicle A), δ loc@L is the positioning error of the vehicle on the digital map, δ map is the error of the map data of the digital map (for example, the error generated when describing the position using the map data), and Δd is the deflection difference.

[0061] In this embodiment, δ loc@L It can be obtained by the following formula:

[0062] δ loc@L =L·δ loc-rot +δ loc-t

[0063] Where L is the straight-line distance between the first unbiased point and the last unbiased point, δ loc-t is the translation error of the vehicle’s positioning of its own position on the digital map, δ loc-rot It is the rotation error of the vehicle’s positioning of its own position on the digital map.

[0064] In block 416, when the deflection difference is greater than or equal to the deflection difference threshold, the decision module 223 disables the digital map used for autonomous driving and generates a warning message. The warning message may be transmitted to the driver in the vehicle via one or more of the following methods: an audible or visual alarm, seat vibration, or a warning signal on the HUD.

[0065] In block 418, if autonomous driving is not possible after disabling the digital map, the decision module 223 causes the vehicle to exit autonomous driving mode and report the vehicle's current location and related diagnostic information to the server. At this point, the vehicle can pull over or be handed over to a human driver.

[0066] The present invention further provides a driving assistance method 600. This method can be executed in the control unit 22 or in the driving assistance system 100. Therefore, the above description is also applicable here and will not be repeated.

[0067] See also Figure 6 In step S610, the deflection difference is calculated based on the position difference between the unbiased point position of the vehicle in the automatic driving mode and the biased point position after being biased by the deflection plug-in.

[0068] In step S620, an automatic driving strategy is determined for the vehicle based on the calculated deflection difference.

[0069] The present invention also provides a machine-readable storage medium storing executable instructions, which, when executed, enable one or more processors to perform the above-mentioned driving assistance method 600.

[0070] It is to be understood that all modules described above can be implemented in various ways. These modules can be implemented as hardware, software, or a combination thereof. In addition, any module in these modules can be further divided into submodules or combined together functionally.

[0071] It will be appreciated that processor can be implemented using electronic hardware, computer software or its any combination.Whether these processors are implemented as hardware or software will depend on specific application and the overall design constraint imposed on the system.As an example, the processor provided in the present invention, any part of processor or any combination of processors can be implemented as microprocessor, microcontroller, digital signal processor (DSP), field programmable gate array (FPGA), programmable logic device (PLD), state machine, gate logic, discrete hardware circuit and other suitable processing components configured for performing the various functions described in this disclosure.The function of the processor provided in the present invention, any part of processor or any combination of processors can be implemented as software performed by microprocessor, microcontroller, DSP or other suitable platforms.

[0072] It is understood that software should be broadly considered to mean instructions, instruction sets, codes, code segments, program codes, programs, subroutines, software modules, applications, software applications, software packages, routines, subroutines, objects, running threads, processes, functions, etc. Software can reside in a computer-readable medium. A computer-readable medium can include, for example, a memory, which can be, for example, a magnetic storage device (e.g., a hard disk, a floppy disk, a magnetic stripe), an optical disk, a smart card, a flash memory device, a random access memory (RAM), a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), a register, or a removable disk. Although the memory is shown as being separated from the processor in the various aspects provided in the present disclosure, the memory can also be located inside the processor (e.g., a cache or register).

[0073] Although some embodiments have been described above, these embodiments are given by way of example only and are not intended to limit the scope of the invention. The appended claims and their equivalents are intended to cover all modifications, substitutions and changes made within the scope and spirit of the invention.

Claims

1. A control unit for a driving assistance system, comprising: a base difference determination module configured to calculate a base difference based on a current position of the vehicle in the automatic driving mode and a corresponding offset position, wherein the current position is a position determined based on a satellite signal and the corresponding offset position is a position of the current position after being offset by the deflection plug-in; a deflection difference determination module configured to calculate a deflection difference based on a position difference between a position of an unbiased point of the vehicle and a position of a biased point after biasing by the deflection plug-in, wherein the deflection difference is a value obtained by subtracting the basic difference from the position difference; as well as A decision module is configured to determine an automatic driving strategy for the vehicle based on the deflection difference.

2. The control unit according to claim 1, wherein: The deflection difference determination module is further configured to: The deflection difference calculated based on the position difference is decomposed along the vehicle's travel direction and its perpendicular direction, and the component in the vertical direction is used as the deflection difference for deciding the autonomous driving strategy.

3. The control unit according to claim 1, wherein: The deflection difference determination module is configured to: Determining an unbiased preset trajectory with the current position as a starting point and sampling a plurality of unbiased points on the preset trajectory; Determining a plurality of biased points corresponding one-to-one to the plurality of unbiased points, each biased point being obtained by biasing the corresponding unbiased point via a deflection plug-in; and The position difference is calculated based on all or part of the plurality of unbiased points and the plurality of biased points.

4. The control unit according to claim 3, wherein: The deflection difference determination module is configured to calculate the deflection difference by means of one or more of the following: (1) The value obtained by subtracting the basic difference from the position difference between the last unbiased point sampled and the corresponding biased point; (2) the value obtained by subtracting the basic difference from the maximum position difference among the position differences between the positions of the sampled unbiased points and the positions of the corresponding biased points; (3) The ratio of the position difference between the position of each unbiased point and the position of the corresponding biased point to the distance of the unbiased point from the starting point.

5. The control unit according to claim 1, wherein: The decision module is configured to: comparing the deflection difference with a deflection difference threshold; When the deflection difference is less than the deflection difference threshold, the vehicle continues to be in the automatic driving mode; and When the deflection difference is greater than or equal to the deflection difference threshold, a digital map for automatic driving is disabled and a warning message is generated.

6. The control unit according to claim 5, wherein: The decision module is further configured to, when automatic driving cannot be achieved after disabling the digital map, cause the vehicle to exit the automatic driving mode and report the current position of the vehicle and related diagnostic information to the server.

7. The control unit according to claim 1, wherein: The control unit further includes a creation module, wherein the creation module is configured to: When the decision module determines that the deflection difference is less than the deflection difference threshold, an error model including the deflection difference is created, where the error model is used to determine an error of an object perceived by the vehicle relative to a real road.

8. The control unit according to claim 7, wherein: The error model is: Among them, δ A_to_real_road is the error of object A perceived by the vehicle relative to the real road, δ per is the error generated when the perception device of the autonomous driving system of the vehicle perceives object A, δ loc@L is the positioning error of the vehicle on the digital map, δ map is the error of the map data of the digital map, Δd is the deflection difference, Among them, δ loc@L Obtained by the following formula: d loc@L =L·δ loc-rot +d loc-t Where L is the straight-line distance between the first unbiased point and the last unbiased point, δ loc-t is the translation error of the vehicle’s positioning of its own position on the digital map, δ loc-rot It is the rotation error of the vehicle’s positioning of its own position on the digital map.

9. The control unit according to claim 1, wherein: The deflection difference determination module is configured to calculate the deflection difference based on the following formula: Δd=R(max)*L, where R(max) is the maximum value among Ri=Δdi / Li, where Li is the straight-line distance from the i-th unbiased point to the starting point, L is the straight-line distance from the last unbiased point to the starting point, Δdi is the position difference between the i-th unbiased point and the i-th biased point minus the base difference, and Δd is the deflection difference.

10. The control unit according to claim 3, wherein: The deflection difference determination module is configured to determine the preset trajectory and the plurality of unbiased points by means of one or more of the following: (1) Taking the current position as a starting point, selecting a path from the path planned by the autonomous driving system for the vehicle as the preset trajectory, and sampling a plurality of position points on the selected path as the plurality of unbiased points; (2) Taking the current position as the starting point, taking a straight path along the vehicle's forward direction as the preset trajectory, and sampling multiple position points on the straight path as the multiple unbiased points; (3) taking the current position as a starting point, taking a plurality of straight paths in a plurality of directions deviating from the vehicle's forward direction as the preset trajectories, and sampling a plurality of position points in the plurality of straight paths as the plurality of unbiased points; (4) With the current position as the center, one or more concentric circular paths are determined, and a plurality of position points are sampled on the one or more concentric circular paths as the plurality of unbiased points.

11. A driving assistance system comprising: A positioning device for determining the vehicle's position based on satellite signals; as well as A control device, including a deflection plug-in and a control unit as described in any one of claims 1 to 10, is connected to the positioning device and is used to determine a deflection difference based on a position difference between a position of an unbiased point and a position of a biased point after being biased by the deflection plug-in, and to determine an automatic driving strategy based on the deflection difference.

12. A driving assistance method, the method being executed by the control unit according to any one of claims 1 to 10 and / or the system according to claim 11, the method comprising: Calculating a deflection difference based on a position difference between an unbiased position of the vehicle in the automatic driving mode and a biased position of the vehicle after being biased by the deflection plug-in; as well as An autonomous driving strategy is determined for the vehicle based on the deflection difference.

13. A machine-readable storage medium storing executable instructions that, when executed, cause one or more processors to perform the method of claim 12.

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