Vehicle curve driving auxiliary device and auxiliary method

Abstract

The embodiment of the invention provides an auxiliary device and an auxiliary method for curve driving of a vehicle. The vehicle curve driving assistance apparatus includes: a curvature information module configured to obtain curvature-related information of a curve driving in front of a vehicle, and determine a plurality of curvatures of a plurality of position points on the curve based on the information; the adhesion coefficient module is configured to obtain road adhesion coefficient related information of the vehicle driving curve and determine a plurality of road adhesion coefficients of the plurality of position points based on the information; and the vehicle speed module is configured to determine a plurality of maximum allowable vehicle speeds based on the curvatures and the road adhesion coefficients, and the maximum allowable vehicle speeds represent the maximum allowable values of the vehicle speeds when the vehicle travels through each position point in the position points.

Description

Technical Field

[0001] The present invention generally relates to the technical field of vehicle control, and in particular to a vehicle control technology in a curve driving scenario. Background Art

[0002] When a vehicle is driving on a curve, especially when turning on a mountain road, an accident may occur due to excessive speed. In addition, when a vehicle is driving on a curve, if it encounters severe weather such as heavy rain or ice and snow, and the driver still turns according to his usual driving habits, the risk of an accident will increase. Therefore, it is urgent to study technical solutions for vehicle driving on curves in order to improve the safety of vehicle driving on curves. Summary of the invention

[0003] In this context, according to an embodiment of one aspect of the present invention, a curve driving assistance device for a vehicle is proposed, which includes: a curvature information module, configured to obtain information related to the curvature of a curve ahead of the vehicle, and determine multiple curvatures of multiple position points on the curve based on the information; an adhesion coefficient module, configured to obtain information related to the road adhesion coefficient of the curve on which the vehicle is traveling, and determine multiple road adhesion coefficients at the multiple position points based on the information; and a vehicle speed module, configured to determine multiple maximum allowable vehicle speeds based on the multiple curvatures and the multiple road adhesion coefficients, respectively representing the maximum allowable value of the vehicle speed when the vehicle passes through each of the multiple position points.

[0004] According to an embodiment of another aspect of the present invention, a vehicle is provided, which includes a curve driving assistance device according to an embodiment of the present invention.

[0005] According to an embodiment of yet another aspect of the present invention, a method for assisting vehicle in turning is provided, comprising: obtaining information related to the curvature of a curve ahead of the vehicle, and determining multiple curvatures of multiple position points on the curve based on the information; obtaining information related to the road adhesion coefficient of the curve on which the vehicle is traveling, and determining multiple road adhesion coefficients of the multiple position points based on the information; and determining multiple maximum allowable vehicle speeds based on the multiple curvatures and the multiple road adhesion coefficients, respectively representing the maximum allowable value of the vehicle speed when the vehicle passes through each of the multiple position points.

[0006] According to an embodiment of still another aspect of the present invention, a computer program product is provided, which includes computer executable instructions, and when the instructions are executed, one or more processors execute the curve driving assistance method according to the embodiment of the present invention.

[0007] A summary of the main aspects of the present invention is provided above so that these aspects can be basically understood. This summary is not intended to describe the key or important elements of all aspects of the present invention, nor is it intended to limit the scope of any or all aspects of the present invention. The purpose of this summary is to provide some implementations of these aspects in a simplified form as a preface to the detailed description that will be provided later. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The technical solution of the present invention will become clearer from the following detailed description in conjunction with the accompanying drawings. It is understood that these drawings are only used for exemplary description and are not intended to limit the scope of protection of the present invention.

[0009] Figure 1 is a schematic block diagram of a curve driving assistance device according to an embodiment of the present invention.

[0010] Figure 2 is a flowchart of a curve driving assistance method according to an embodiment of the present invention.

[0011] Figure 3 The figure schematically shows a curve ahead of the vehicle and a plurality of position points on the curve. DETAILED DESCRIPTION

[0012] An embodiment of the present invention relates to a technology for assisting cornering, which comprehensively considers the curvature of the corner ahead of the vehicle, the road adhesion conditions, and also takes the slope factor into consideration when there is a slope on the road, so as to calculate the maximum speed limit for the vehicle to safely pass the corner, that is, the maximum allowable vehicle speed.

[0013] According to the embodiments of the present invention, multi-dimensional data sources are integrated to obtain the curvature of the curve, the road surface adhesion condition and the slope condition, ensuring the accuracy and reliability of the information involved in the maximum speed limit calculation. In addition, in some embodiments, weather and temperature conditions are also used to correct the road surface adhesion coefficient of the curve, thereby further improving the accuracy of the road surface adhesion coefficient parameters involved in the maximum speed limit calculation. Compared with the traditional method of relying on only a single factor to determine the maximum limit of the vehicle's cornering, the maximum speed limit of the vehicle's cornering obtained according to the embodiments of the present invention is more accurate, thereby providing a safer driving experience.

[0014] The technical solution according to the embodiment of the present invention has wide applicability, and can be applied to all kinds of driving modes, including various driving assistance modes from automatic driving to semi-automatic driving. In other words, the present invention can be applied to both human driving scenarios and intelligent driving scenarios.

[0015] According to an embodiment of the present invention, after calculating the maximum allowable vehicle speed for driving on a curve, the vehicle speed information is provided to the driver or the driving assistance system to ensure that the driver or the driving assistance system has enough time and space to adjust the vehicle state so that the vehicle can be safely driven through the curve.

[0016] The specific implementation of the present invention is described below in conjunction with the accompanying drawings.

[0017] Figure 1 The schematic diagram shows a curve driving assistance device 10 according to an embodiment of the present invention, which is arranged on a vehicle and is referred to as the device 10 in some places below. The device 10 is connected to communicate and exchange information with other systems (e.g., ADAS system 20, power system 30, suspension system 40) or devices (e.g., human-machine interface 50) on the vehicle through a vehicle bus (e.g., CAN, LIN, FlexRay, MOST); on the other hand, it is connected to communicate and exchange information with external devices (e.g., cloud server 60, roadside unit 70, other vehicles 80) outside the vehicle through a communication interface (not shown).

[0018] The curve driving assistance device 10 determines the maximum permissible speed of the vehicle when passing through multiple positions of the curve according to the curvature and road adhesion coefficient of the curve ahead of the vehicle, and optionally according to the slope of the curve, and sends a speed reminder to the driver or the driving assistance system. In addition, the driving assistance device 10 can also distribute the front and rear axle driving torque when the vehicle passes through different positions during the curve according to the curve curvature condition and the road adhesion coefficient condition. In addition, the driving assistance device 10 can also adjust the suspension stiffness and / or damping coefficient when the vehicle passes through different positions during the curve according to the curve curvature condition and the road adhesion coefficient condition.

[0019] In one embodiment, the curve driving assistance device 10 is implemented to include a curvature information module 11, an adhesion coefficient module 12, a slope information module 13, a vehicle speed module 14, a reminder module 15, a torque distribution module 16 and a suspension control module 17. The naming of these modules is functional and is not intended to limit their implementation methods or physical locations. For example, these modules can be implemented on the same chip or circuit, or on different chips or circuits. In addition, some or all of these modules can be combined into one module, or further divided into multiple sub-modules.

[0020] The curve driving assistance device 10 and its various modules can be implemented in hardware or software or a combination of software and hardware. For the part implemented in hardware, it 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 a combination thereof. For the part implemented in software, it can be implemented with the help of microcodes, program codes or code segments, and they can also be stored in machine-readable storage media such as storage components.

[0021] In one embodiment, the curve driving assistance device 10 can be arranged in an electronic control unit (ECU) of the vehicle, for example, in an ECU of a braking system. The driving assistance device 10 can also be arranged in a vehicle body controller (VCU) of the vehicle, or in a domain controller of the vehicle.

[0022] In one embodiment, some of the multiple modules of the curve driving assistance device 10 are arranged in one ECU of the vehicle, and other modules are arranged in another ECU or VCU of the vehicle.

[0023] In one embodiment, the curve driving assistance device 10 is implemented as including a memory and a processor. The memory contains instructions, which, when executed by the processor, enable the processor to perform the curve driving assistance method according to the embodiment of the present invention.

[0024] Figure 2 A curve driving assistance method 200 according to an embodiment of the present invention is shown. The method 200 may be executed by the curve driving assistance device 10. The following takes the curve driving assistance device 10 executing the method 200 as an example to introduce a specific implementation of the method 200.

[0025] In box 202 , the curvature information module 11 obtains information related to the curvature of the curve ahead of the vehicle (Info_1), and determines multiple curvatures of multiple position points on the curve ahead of the vehicle based on the information.

[0026] Since the curvatures at different points on the curve may be different, the shape of the curve ahead of the vehicle can be more accurately depicted by using multiple curvatures at multiple points on the curve. Figure 3A schematic diagram of multiple position points P1, P2 and P3 on the curve ahead is shown. These position points can be distributed at predetermined intervals. One implementation is that the intervals between these position points are equal, so as to evenly cover the entire curve. For example, the vertical distance D1 between position points P1 and P2 is equal to the vertical distance D2 between position points P2 and P3. Another implementation is to adjust the intervals between the position points according to the change in the shape of the curve. In a curved road section with a complex curve shape and large changes, a denser position point can be set, that is, the interval is reduced; while in a curved road section with a relatively regular curve shape and a gentle change, the interval can be appropriately increased and a sparser position point can be set. For example, the vertical distance D1 between position points P1 and P2 is greater than the vertical distance D2 between position points P2 and P3. Such an arrangement can more effectively capture subtle changes in the shape of the curve and improve the accuracy of the description of its curvature characteristics.

[0027] Next, some embodiments of block 202 are described.

[0028] In one embodiment, the curvature information module 11 obtains multiple curvatures of multiple position points on the curve in front of the vehicle from the camera module of the driving assistance system 20. That is, in this embodiment, the multiple curvatures from the camera module are directly used as the curvature information for subsequent calculation of the maximum allowed vehicle speed. For example, the camera module of the driving assistance system 20 collects an image of the curve in front of the vehicle, analyzes the collected image, and thus obtains multiple curvatures of multiple position points on the curve.

[0029] In another embodiment, the curvature information module 11 determines multiple curvatures of multiple position points on the curve ahead based on curvature information (e.g., multiple first curvatures) from the camera module of the driving assistance system 20 and curvature information (e.g., multiple second curvatures) from the high-precision map. The curvature information of the curve may be stored in the high-precision map, and the curvature information includes the curvatures of a large number of position points that are very dense on the curve. The high-precision map may be located in the vehicle, and the curvature information module 11 obtains the curvature information from the high-precision map via the vehicle bus. The high-precision map may also be located in the cloud server 60, and the curvature information module 11 obtains the curve information from the high-precision map in the cloud via the communication interface on the vehicle.

[0030] In general, in this embodiment, the curvature information module 11 obtains curvature information from two data sources, and determines a plurality of curvatures based on the two data sources as curvature information for subsequent calculation of the maximum allowed vehicle speed.

[0031] In one implementation of this embodiment, the curvature information module 11 obtains multiple first curvatures of multiple positions on the front curve and a first curvature confidence level characterizing the credibility of the multiple first curvatures from a camera module of the driving assistance system 20; obtains multiple second curvatures of the multiple positions and a second curvature confidence level characterizing the credibility of the multiple second curvatures from a high-precision map; and determines the multiple curvatures based on the multiple first curvatures, the multiple second curvatures, and the first and second curvature confidence levels.

[0032] The first curvature confidence is related to the performance of the camera module. For example, under adverse weather conditions such as strong light or heavy fog, the performance of the camera module will be relatively reduced. Affected by this, the first curvature confidence will also be reduced accordingly in this situation.

[0033] The second curvature confidence is related to the storage time of multiple second curvature information in the high-precision map. The longer the storage time, the longer the curvature information is obtained, the more likely the road is changing, and the lower the second curvature confidence; conversely, the shorter the storage time, the newer the curvature information, and the higher the second curvature confidence.

[0034] The first curvature confidence and the second curvature confidence may be expressed in the form of percentages, or in the form of fractions within a set consistent range, so as to reflect the confidence levels and enable quantitative comparison.

[0035] When the first curvature confidence is greater than or equal to the curvature confidence threshold, and the second curvature confidence is less than the curvature confidence, it means that the credibility of the curvature information from the camera module is high and the credibility of the curvature information from the high-precision map is low. In this case, the curvature information module 11 directly uses the multiple first curves from the camera module as the multiple curvatures for subsequent calculation of the maximum allowable vehicle speed.

[0036] When the first curvature confidence is less than the confidence threshold, regardless of the size of the second curvature confidence, a weighted average method is used to calculate multiple curvatures for subsequent calculation of the maximum allowable vehicle speed based on multiple first curvatures, multiple second curvatures, and the first and second curvature confidences.

[0037] In box 204, the adhesion coefficient module 12 obtains the road adhesion coefficient related information (Info_2) of the curve ahead of the vehicle, and determines the multiple road adhesion coefficients of the multiple position points based on the information. The multiple position points involved in box 204 are completely consistent with the multiple position points involved in box 202 in position distribution and implementation, so the above description of the multiple position points is also applicable here.

[0038] Since the adhesion coefficients at different positions on a curve may vary due to different road conditions, for example, some curved sections may have uneven roads while other curved sections may be slippery, by using multiple adhesion coefficients at multiple positions on the curve, the actual adhesion conditions of the curved road surface in front of the vehicle can be more accurately reflected.

[0039] Next, some embodiments of block 204 are described.

[0040] In one embodiment, the adhesion coefficient module 12 obtains the road adhesion coefficient information from the road evaluation module (not shown) of the vehicle braking system (the road evaluation module is a functional module in the vehicle braking system for evaluating the current road adhesion condition), which includes a plurality of first road adhesion coefficients of the plurality of position points; and determines the plurality of road adhesion coefficients based on the plurality of first road adhesion coefficients and the predetermined reduction amount as the road adhesion coefficient information for subsequent calculation of the maximum allowable vehicle speed. One implementation is that the predetermined reduction amount is a predetermined value. In this implementation, the predetermined value is subtracted from each of the plurality of first road adhesion coefficients to obtain the plurality of road adhesion coefficients. Another implementation is that the predetermined reduction amount is a predetermined ratio, for example, 2% to 10%. In this implementation, each of the plurality of first road adhesion coefficients is adjusted down by a predetermined ratio (for example, if the predetermined ratio is 2%, each of the first road adhesion coefficients after the reduction is 98% of the original) to obtain the plurality of road adhesion coefficients. In this way, each road adhesion coefficient is less than the corresponding first road adhesion coefficient, so that the safety of the road adhesion coefficient can be fully considered when calculating the maximum allowable vehicle speed.

[0041] In another embodiment, the adhesion coefficient module 12 obtains a plurality of first road adhesion coefficients of the plurality of positions from a road surface evaluation module of the braking system; obtains a plurality of second road adhesion coefficients of the plurality of positions from a cloud server (information about the adhesion condition of the curved road surface is stored in the cloud server, for example, a road adhesion coefficient map containing road adhesion condition information is stored in the cloud server); obtains a plurality of third road adhesion coefficients of at least some of the plurality of positions from other vehicles that are communicatively connected to the vehicle (this vehicle) (for example, the vehicle in front of this vehicle evaluates the road adhesion coefficient when passing the curve ahead, and sends the evaluation result of the road adhesion coefficient to this vehicle through V2V communication); and determines the plurality of road adhesion coefficients based on at least two of the plurality of first road adhesion coefficients, the plurality of second road adhesion coefficients and the plurality of third road adhesion coefficients.

[0042] In general, in this embodiment, road adhesion information from multiple data sources is used to determine multiple road adhesion coefficients at multiple position points on the front curve, which is used as road adhesion information for subsequent calculation of the maximum allowed vehicle speed.

[0043] In an implementation of this embodiment, the adhesion coefficient module 12 performs weighted average calculation according to the first, second and third road adhesion coefficients and their confidence levels to obtain the plurality of road adhesion coefficients.

[0044] The first adhesion coefficient confidence level characterizing the credibility of the plurality of first road adhesion coefficients is set by the adhesion coefficient module 12 according to the wheel slipping condition of the vehicle. If at least one wheel slips or is close to slipping, the first adhesion coefficient confidence level is set to a low level or a preset low confidence value, because the estimated road adhesion coefficient in this case may have a large error; if all wheels are in a stable state and no slipping occurs, the first adhesion coefficient confidence level is set to a high level or a preset high confidence value, because the estimated road adhesion coefficient in this case should have a high accuracy.

[0045] The second adhesion coefficient confidence level characterizing the credibility of the plurality of second road adhesion coefficients is obtained from the cloud server. In other words, the second adhesion coefficient confidence level is obtained from the cloud server together with the plurality of second road adhesion coefficients. The second adhesion coefficient confidence level is related to the storage time of the plurality of adhesion coefficient information in the cloud server. The longer the storage time is, the longer the adhesion coefficient information is obtained, the possibility of road condition changes exists, and the second adhesion coefficient confidence level is lower; conversely, the shorter the storage time is, the newer the adhesion coefficient information is, and the higher the second adhesion coefficient confidence level is.

[0046] The third adhesion coefficient confidence level that characterizes the credibility of the plurality of third road adhesion coefficients is set by the adhesion coefficient module 12 according to the distance between the host vehicle and the other vehicle. The smaller the distance is, the closer the curve positions of the two vehicles are, and the higher the third adhesion coefficient confidence level is set, because at this time, the road conditions have more similar effects on the two vehicles, and the adhesion coefficient evaluation result is more credible; conversely, the larger the distance is, the farther the curve positions of the two vehicles are, and the lower the third adhesion coefficient confidence level is set, because the farther the positions are, the greater the difference in road adhesion conditions may be, and thus the uncertainty of the estimation may be caused by the greater difference in the effects on the vehicles.

[0047] In addition, in each of the above two embodiments, the adhesion coefficient module 12 can also adjust the determined multiple road adhesion coefficients according to the influence of one or both of the weather conditions and the ambient temperature on the road adhesion coefficient, and bring the adjusted multiple road adhesion coefficients into the subsequent calculation of the maximum allowable vehicle speed. For example, in the case of a rainstorm and below zero degrees Celsius, the road surface may be slippery and icy, and the adhesion coefficient module 12 determines each road adhesion coefficient by reducing the predetermined adjustment amount. For example, in dry weather conditions, the vehicle has strong grip, and the adhesion coefficient module 12 determines each road adhesion coefficient by increasing the predetermined adjustment amount.

[0048] In block 206, the vehicle speed module 14 determines a plurality of maximum allowable vehicle speeds according to the determined plurality of curvatures and the plurality of road adhesion coefficients, which respectively represent the maximum allowable value of the vehicle speed when the vehicle passes through each of the plurality of positions. For each position point, the vehicle speed module 14 determines each maximum allowable vehicle speed in a manner that is proportional to the value of the road adhesion coefficient and inversely proportional to the value of the curvature. Thus, it is possible to ensure that the vehicle can pass through the curve at a safe speed (i.e., a speed that is less than or equal to the calculated maximum uniform speed) under different road conditions on the curve.

[0049] For example, the vehicle speed module 14 uses the following formula (1) to calculate the maximum allowable vehicle speed at each location point:

[0050]

[0051] Among them, vi_i represents the maximum allowed vehicle speed at the i-th position point; μ_i represents the road adhesion coefficient determined at the i-th position point; k_i represents the curvature value determined at the i-th position point.

[0052] In block 208, after determining the maximum permissible speed of the vehicle when turning, the reminder module 15 sends a speed reminder message to the vehicle driver or the driving assistance system. The reminder to the driver can be presented through the human-machine interface 50, for example, by means of the human-machine interface 50, the driver is reminded through one or more of text, voice, image, and vibration.

[0053] In one example, the reminder module 15 determines the minimum speed among multiple maximum allowable speeds and the corresponding position of the minimum speed, and determines the vehicle cornering reminder strategy based on the speed difference between the minimum speed and the current speed and the relative distance between the corresponding position and the current vehicle position.

[0054] The larger the speed difference or the shorter the relative distance, the earlier the speed reminder message is sent, so as to ensure that the driver or the driving assistance system has enough time to make necessary adjustments to the vehicle's driving status. On the contrary, the smaller the speed difference or the longer the relative distance, the later the speed reminder message is sent. In addition, when the speed difference is large (greater than the speed difference threshold) or the relative distance is short (for example, less than the distance threshold), the more intense the reminder is, for example, a stronger vibration, voice broadcast and image presentation are used simultaneously, etc., to ensure that the driver's full attention is drawn.

[0055] In addition, according to an embodiment of the present invention, the road condition (road type) may also be considered in determining the timing of sending the speed reminder. For example, after the timing of sending the speed reminder is determined by the above method, if the current road condition is covered with ice or snow or is slippery after rain, the timing of sending the speed reminder is slightly advanced.

[0056] According to an embodiment of the present invention, after determining multiple curvatures and multiple road adhesion coefficients at multiple positions on the front curve, the torque distribution module 16 can intelligently distribute (frame 210) the driving torque of the front and rear axles of the vehicle according to the road adhesion conditions and the curve curvature conditions to reduce the risk of wheel slippage and further improve the driving stability of the vehicle.

[0057] In general, when the road adhesion coefficient is high and the curvature is large, the driving torque is allocated to the rear axle first; when the road adhesion coefficient is high and the curvature is low, the driving torque is allocated to the front axle according to the thermal management of the front and rear axle motors; when the road adhesion coefficient is low and the curvature is large, the driving torque is allocated to the front axle first; when the road adhesion coefficient is low and the curvature is low, the driving torque is allocated to the front axle first. Such allocation can make the vehicle have higher flexibility and stronger stability during cornering. Here, "high and low adhesion coefficients" and "high and low curvatures" can be determined by pre-set ranges indicating high or low. The present invention does not limit the specific setting method and values ​​of these ranges.

[0058] In one embodiment, the torque distribution module 16 compares each of the multiple determined curvatures with a first curvature threshold to obtain a first comparison result; compares each of the multiple determined road adhesion coefficients with a first road adhesion coefficient threshold to obtain a second comparison result; and distributes the front and rear axle driving torques when the vehicle passes through various positions during the cornering process according to the first and second comparison results.

[0059] For example, if the first comparison result is that more than 50% of the curvatures among the multiple curvatures are greater than the first curvature threshold and the second comparison result is that more than 50% of the road adhesion coefficients among the multiple road adhesion coefficients are greater than the first road adhesion coefficient threshold, the torque distribution module will prioritize the drive torque to the rear axle. If the first comparison result is that more than 50% of the curvatures among the multiple curvatures are less than the first curvature threshold and the second comparison result is that more than 50% of the road adhesion coefficients among the multiple road adhesion coefficients are less than the first road adhesion coefficient threshold, the torque distribution module will prioritize the drive torque to the front axle.

[0060] According to an embodiment of the present invention, after determining multiple curvatures and multiple road adhesion coefficients at multiple locations on the forward curve, the suspension control module 17 may adjust the vehicle suspension according to the road adhesion condition and the curve curvature condition (block 212).

[0061] In general, when the curvature is high and the road adhesion coefficient is high, the suspension control module 17 increases the suspension stiffness to reduce the risk of body roll and improve comfort. When the road adhesion coefficient is low, the suspension control module 17 reduces the suspension stiffness to increase the contact area between the tire and the road, increase grip, and improve driving stability. Similarly, the "high and low adhesion coefficient" and "high and low curvature" here can be determined by pre-set ranges indicating high or low. The present invention does not limit the specific setting method and values ​​of these ranges.

[0062] In one embodiment, the suspension control module 17 compares each of the multiple determined curvatures with the second curvature threshold to obtain a third comparison result; compares each of the multiple determined road adhesion coefficients with the second road adhesion coefficient threshold to obtain a fourth comparison result; and adjusts the suspension stiffness and / or damping coefficient when the vehicle passes through various positions during the cornering process according to the third and fourth comparison results.

[0063] For example, when the third comparison result is that more than 50% of the curvatures among the plurality of curvatures are greater than the second curvature threshold and the fourth comparison result is that more than 50% of the road adhesion coefficients among the plurality of road adhesion coefficients are greater than the second road adhesion coefficient threshold, the suspension control module 17 increases the suspension stiffness. When the third comparison result is that more than 50% of the curvatures among the plurality of curvatures are less than the second curvature threshold and the fourth comparison result is that more than 50% of the road adhesion coefficients among the plurality of road adhesion coefficients are less than the second road adhesion coefficient threshold, the suspension control module 17 reduces the suspension stiffness and lowers the suspension height.

[0064] In addition, according to an embodiment of the present invention, in the case where the curve is a curve with a slope, the slope information module 13 obtains (box 205) the slope related information (Info_3), and determines the multiple slope values ​​of the multiple positions based on the information. In addition, the vehicle speed module 14 also calculates the maximum allowable vehicle speed based on the slope information. The multiple position points involved here are completely consistent with the multiple position points involved in box 202 in position distribution and implementation method, so the above description of the multiple position points is also applicable here.

[0065] In one embodiment, the slope information module 13 obtains the slope value of the current position from the slope evaluation module of the braking system, or obtains multiple slope values ​​of multiple position points on the front curve from the radar module of the driving assistance system 20 (for example, radar information from the radar sensor of the driving assistance system). That is, in this embodiment, multiple slope values ​​from the slope evaluation module of the braking system are directly used as the slope information for subsequent calculation of the maximum allowed vehicle speed. For example, the slope evaluation module determines the slope of the road on which the vehicle is traveling based on the vehicle acceleration sensed by the inertial sensor.

[0066] In another embodiment, the slope information module 13 determines multiple slopes of multiple position points on the curve ahead based on the slope information (e.g., multiple first slopes) from the slope evaluation module of the braking system and the slope information (e.g., multiple second slopes) from the high-precision map. The slope information of the curve can be stored in the high-precision map, and the slope information contains the slope values ​​of a large number of position points that are very dense on the curve. The high-precision map can be located in the vehicle, and the slope information module 13 obtains the slope information from the high-precision map via the vehicle bus. The high-precision map can also be located in the cloud server 60, and the slope information module 13 obtains the slope information from the high-precision map in the cloud via the communication interface on the vehicle.

[0067] In general, in this embodiment, the slope information module 13 obtains slope information from two data sources, and determines a plurality of slopes based on the two data sources as the slope information for subsequently calculating the maximum allowed vehicle speed.

[0068] In one implementation of this embodiment, the slope information module 13 obtains a plurality of first slopes of a plurality of position points on the front curve from the slope evaluation module of the braking system; obtains a plurality of second slopes of the plurality of position points from the high-precision map; and determines the slope of each position point according to each first slope value, the difference between each first slope value and the corresponding second slope value, and the correction coefficient, thereby obtaining the plurality of slopes. For example, for each position point, the slope information module 13 uses the following formula (2) to calculate the slope value:

[0069] Slop_i=Slop_i1+c*(Slop_i1- Slop_i2) (2)

[0070] Among them, Slop_i represents the slope value of the i-th position point; Slop_i1 represents the slope value of the i-th position point from the slope assessment module of the braking system; Slop_i2 represents the slope value of the i-th position point from the high-precision map; c represents the correction coefficient. The value of the correction coefficient c is preset.

[0071] After obtaining the slope information, the speed module 14 calculates multiple maximum allowable speeds according to the determined multiple curvatures, multiple road adhesion coefficients and multiple slopes, which respectively represent the maximum allowable value of the vehicle speed when the vehicle passes through each of the multiple positions. For each position point, the speed module 14 determines each maximum allowable speed in a manner that is proportional to the value of the road adhesion coefficient, proportional to the slope value, and inversely proportional to the curvature value. In this way, it can be ensured that the vehicle can pass through the curve at a safe speed (i.e., a speed less than or equal to the calculated maximum uniform speed) under different road conditions on the curve.

[0072] For example, the vehicle speed module 14 uses the following formula (3) to calculate the maximum allowable vehicle speed at each location point:

[0073]

[0074] Among them, vi_i represents the maximum allowed vehicle speed at the i-th position point; μ_i represents the road adhesion coefficient determined at the i-th position point; k_i represents the curvature value determined at the i-th position point; tanθ_i represents the slope value at the i-th position point.

[0075] In an embodiment of the present invention, a variety of thresholds or predetermined values ​​are used, and these thresholds are all predetermined, for example, they can be predetermined based on actual vehicle test results and / or models. The present invention does not limit their specific values. Moreover, these thresholds can also be customized thresholds for vehicle users based on the preferences of vehicle users (e.g., OEM or vehicle drivers), so that the vehicle steering style meets the preferences of vehicle users. It should be understood that the customized thresholds that meet the preferences of vehicle users are determined to fully ensure the safety of vehicle driving. Therefore, these customized thresholds should be understood to meet the preferences of vehicle users to a certain extent, without following the preferences of vehicle users at the expense of vehicle safety.

[0076] According to an embodiment of the present invention, a vehicle is further provided, which includes the above-mentioned curve driving assistance unit. Therefore, the vehicle according to the embodiment of the present invention has the above-mentioned features and advantages.

[0077] According to an embodiment of the present invention, a machine-readable storage medium is further provided, which stores executable instructions, and when the instructions are executed, one or more processors execute the curve driving assistance method 200 as described above.

[0078] According to an embodiment of the present invention, a computer program product is further provided, which includes computer executable instructions. When the instructions are executed, one or more processors are enabled to perform the curve form assistance method 200 as described above.

[0079] It should be noted that all operations in the method described above are merely exemplary, and the present invention is not limited to any operation in the method or the order of these operations, but should cover all other equivalent transformations under the same or similar concept.

[0080] It should be noted that the processor may use any combination of one or more of the following: an appropriate central processing unit, CPU, multiprocessor, single-chip microcomputer, digital signal processor, DSP, application-specific integrated circuit, etc., capable of executing software instructions of a computer program stored in the memory. Therefore, the memory may be considered as part of or forming part of a computer program product. The processor may be configured to execute a computer program stored therein to cause the controller to perform the required steps.

[0081] It should be noted that software should be broadly considered to represent 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 by the present invention, the memory can also be located inside the processor (e.g., a cache or a register).

[0082] The above description is provided to enable any person skilled in the art to implement the various aspects described herein. Various modifications to these aspects are apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects. Therefore, the claims are not intended to be limited to the aspects shown herein. All structural and functional equivalents of elements of the various aspects described herein that are known or to be known to those skilled in the art will be expressly included herein by reference and are intended to be covered by the claims.

Claims

1. A curve driving assist device for a vehicle, comprising: a curvature information module configured to obtain information related to the curvature of a curve ahead of the vehicle and determine multiple curvatures of multiple position points on the curve based on the information; an adhesion coefficient module, configured to obtain information related to the road adhesion coefficient of the vehicle traveling on the curve, and determine a plurality of road adhesion coefficients at the plurality of position points based on the information; as well as The vehicle speed module is configured to determine a plurality of maximum allowable vehicle speeds based on the plurality of curvatures and the plurality of road adhesion coefficients, respectively representing a maximum allowable value of the vehicle speed when the vehicle passes through each of the plurality of position points.

2. The curve driving assistance device as described in claim 1 further includes a reminder module, which is configured to generate a vehicle speed reminder message based on the determined multiple maximum allowed vehicle speeds, and send the vehicle speed reminder message to the driver and / or the driving assistance system.

3. The curve driving assistance device according to claim 2, wherein: The reminder module is configured as follows: Determine the minimum vehicle speed among multiple maximum allowed vehicle speeds and the corresponding position point of the minimum vehicle speed, and determine the timing of sending the vehicle speed reminder message based on the vehicle speed difference between the minimum vehicle speed and the current vehicle speed and the relative distance between the corresponding position point and the current vehicle position.

4. The curve driving assistance device according to claim 1, wherein: The multiple curvatures come from a camera module of a vehicle driving assistance system.

5. The curve driving assistance device according to claim 1, wherein: The curvature information module is configured as follows: Acquire, from a camera module of the vehicle driving assistance system, a plurality of first curvatures of the plurality of position points and a first curvature confidence level representing a degree of credibility of the plurality of first curvatures; Acquire, from the high-precision map, a plurality of second curvatures of the plurality of location points and a second curvature confidence level representing a degree of credibility of the plurality of second curvatures; as well as The plurality of curvatures are determined based on the plurality of first curvatures, the plurality of second curvatures, and first and second curvature confidences.

6. The curve driving assistance device according to claim 1, wherein: The adhesion coefficient module is configured as follows: Acquire a plurality of first road surface adhesion coefficients of the plurality of position points from a road surface evaluation module of a braking system of the vehicle; and The plurality of road surface adhesion coefficients are determined based on the plurality of first road surface adhesion coefficients and a predetermined reduction amount so that each road surface adhesion coefficient is smaller than the corresponding first road surface adhesion coefficient.

7. The curve driving assistance device according to claim 1, wherein: The adhesion coefficient module is configured as follows: Acquire a plurality of first road surface adhesion coefficients of the plurality of position points from a road surface evaluation module of a braking system of the vehicle; Acquire a plurality of second road adhesion coefficients of the plurality of location points from a cloud server; Acquire a plurality of third road adhesion coefficients of at least some of the plurality of position points from other vehicles that are in communication connection with the vehicle; as well as The plurality of road surface adhesion coefficients are determined based on at least two of a plurality of first road surface adhesion coefficients, a plurality of second road surface adhesion coefficients, and a plurality of third road surface adhesion coefficients.

8. The curve driving assistance device according to claim 7, wherein: The adhesion coefficient module is configured as follows: determining the plurality of road surface adhesion coefficients based on the plurality of first, second and third road surface adhesion coefficients and first, second and third adhesion coefficient confidence levels respectively representing their credibility, The first adhesion coefficient confidence is related to whether there is a slipping wheel among the wheels; The second adhesion coefficient confidence is related to the storage duration of the plurality of second road adhesion coefficients in the cloud server; The third adhesion coefficient confidence level is related to the distance between the other vehicles and the vehicle.

9. The curve driving assistance device according to any one of claims 6 to 8, wherein: The adhesion coefficient module is configured as follows: The plurality of road adhesion coefficients are adjusted based on current weather conditions and / or ambient temperature, and the maximum permissible vehicle speed is calculated using the corrected plurality of road adhesion coefficients.

10. The curve driving assistance device according to claim 1, wherein: The vehicle speed module is configured as follows: For each position point, each maximum permissible vehicle speed is determined in a manner proportional to the value of the road adhesion coefficient and inversely proportional to the value of the curvature.

11. The curve driving assistance device according to claim 1, wherein: The greater the vehicle speed difference and / or the shorter the relative distance, the earlier the vehicle speed reminder message is issued.

12. The curve driving assist device according to claim 1, further comprising a slope information module configured to obtain slope related information and determine a plurality of slopes of the plurality of position points based on the information; The vehicle speed module further determines the plurality of maximum allowed vehicle speeds based on the plurality of slopes, wherein: For each position point, each maximum permissible vehicle speed is determined in proportion to the value of the road adhesion coefficient, in proportion to the value of the slope, and inversely proportional to the value of the curvature.

13. The curve driving assistance device according to claim 1, further comprising a torque distribution module configured to: Comparing each of the plurality of curvatures with a first curvature threshold to obtain a first comparison result; comparing each of the plurality of road adhesion coefficients with a first road adhesion coefficient threshold value to obtain a second comparison result; as well as The front and rear axle driving torques are distributed according to the first and second comparison results when the vehicle passes through various positions during the cornering process.

14. The curve driving assist device according to claim 1, further comprising a suspension control module configured to: comparing each of the plurality of curvatures with a second curvature threshold to obtain a third comparison result; comparing each of the plurality of road surface adhesion coefficients with a second road surface adhesion coefficient threshold value to obtain a fourth comparison result; and The suspension stiffness and / or damping coefficient of the vehicle when passing through various positions during the cornering process is adjusted according to the third and fourth comparison results.

15. A vehicle comprising the curve driving assistance device according to any one of claims 1 to 14.

16. A curve driving assistance method for a vehicle, comprising: Obtaining information related to the curvature of a curve ahead of the vehicle, and determining multiple curvatures of multiple position points on the curve based on the information; Acquiring information related to a road adhesion coefficient of the vehicle traveling on a curved road, and determining a plurality of road adhesion coefficients at the plurality of position points based on the information; as well as A plurality of maximum permissible vehicle speeds are determined based on the plurality of curvatures and the plurality of road adhesion coefficients, respectively representing maximum permissible values ​​of the vehicle speed when the vehicle passes through each of the plurality of position points.

17. The curve driving assistance method according to claim 16, further comprising: A vehicle speed reminder message is generated based on the determined multiple maximum allowed vehicle speeds, and the vehicle speed reminder message is sent to the driver and / or the driving assistance system.

18. The curve driving assistance method according to claim 17, wherein: Determine the minimum vehicle speed among multiple maximum allowed vehicle speeds and the corresponding position point of the minimum vehicle speed, and determine the timing of sending the vehicle speed reminder message based on the vehicle speed difference between the minimum vehicle speed and the current vehicle speed and the relative distance between the corresponding position point and the current vehicle position.

19. The curve driving assistance method according to claim 16, wherein: Determining the plurality of curvatures comprises: Acquire, from a camera module of the vehicle driving assistance system, a plurality of first curvatures of the plurality of position points and a first curvature confidence level representing a degree of credibility of the plurality of first curvatures; Acquire a plurality of second curvatures of the plurality of location points and a second curvature confidence level representing the credibility of the plurality of second curvatures from the high-precision map; and The plurality of curvatures are determined based on the plurality of first curvatures, the plurality of second curvatures, and first and second curvature confidences.

20. The curve driving assistance method according to claim 16, wherein: Determining the plurality of road adhesion coefficients includes: Acquire a plurality of first road surface adhesion coefficients of the plurality of position points from a road surface evaluation module of a braking system of the vehicle; and The plurality of road surface adhesion coefficients are determined based on the plurality of first road surface adhesion coefficients and a predetermined reduction amount so that each road surface adhesion coefficient is smaller than the corresponding first road surface adhesion coefficient.

21. The curve driving assistance method according to claim 16, wherein: Determining the plurality of road adhesion coefficients includes: Acquire a plurality of first road surface adhesion coefficients of the plurality of position points from a road surface evaluation module of a braking system of the vehicle; Acquire a plurality of second road adhesion coefficients of the plurality of location points from a cloud server; Acquiring a plurality of third road adhesion coefficients of at least some of the plurality of position points from other vehicles that are in communication connection with the vehicle; and The plurality of road surface adhesion coefficients are determined based on at least two of a plurality of first road surface adhesion coefficients, a plurality of second road surface adhesion coefficients, and a plurality of third road surface adhesion coefficients.

22. A computer program product comprising computer executable instructions, which when executed, cause one or more processors to perform the curve driving assistance method according to any one of claims 16 to 21.

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