Automatic driving control method and device, vehicle, storage medium and chip

Abstract

The present disclosure relates to the technical field of automatic driving, and particularly relates to an automatic driving control method and device, a vehicle, a storage medium and a chip. The method comprises the following steps: obtaining an adhesion coefficient of a target road position; determining a maximum braking force of a first vehicle at the target road position according to the adhesion coefficient; determining a safe braking distance of the first vehicle according to a road condition where the first vehicle is located; obtaining a vehicle speed limit value of the first vehicle according to the maximum braking force and the safe braking distance; and controlling an automatic driving speed of the first vehicle, so that a speed of the first vehicle when reaching the target road position does not exceed the vehicle speed limit value. The technical scheme provided by the present disclosure can avoid the first vehicle from slipping at the target road position, so that the first vehicle can not exit the automatic driving mode at the target road position where it is easy to slip, the experience satisfaction of a driver to automatic / intelligent driving is improved, and the confidence of the driver to automatic / intelligent driving is increased.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of automatic driving, and in particular to an automatic driving control method and device, a vehicle, a storage medium and a chip. BACKGROUND

[0002] In related technologies, when the automatic driving / smart driving function is used, if the phenomenon of skidding occurs, the automatic driving / smart driving function is automatically exited, and the driver is required to take over. Requiring the driver to take over affects the experience of the automatic driving / smart driving function and reduces the confidence of the driver in the automatic driving / smart driving function. SUMMARY

[0003] To overcome the problems in related technologies, the present disclosure provides an automatic driving control method and device, a vehicle, a storage medium and a chip.

[0004] According to a first aspect of an embodiment of the present disclosure, an automatic driving control method is provided, and the method comprises:

[0005] obtaining an adhesion coefficient of a target road surface position, the target road surface position being less than or equal to a first preset distance from the first vehicle on a travel route of the first vehicle;

[0006] determining a maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient;

[0007] determining a safe braking distance of the first vehicle according to a road condition in which the first vehicle is located;

[0008] obtaining a speed limit value of the first vehicle according to the maximum braking force and the safe braking distance;

[0009] controlling an automatic driving speed of the first vehicle, so that a speed of the first vehicle when reaching the target road surface position does not exceed the speed limit value.

[0010] Optionally, the obtaining of the adhesion coefficient of the target road surface position comprises:

[0011] receiving adhesion coefficient information generated and broadcast by a second vehicle, wherein the second vehicle is a vehicle less than or equal to a second preset distance from the first vehicle, and the adhesion coefficient information comprises an adhesion coefficient and a road surface position corresponding to the adhesion coefficient;

[0012] obtaining the adhesion coefficient of the target road surface position according to the travel route of the first vehicle and the received adhesion coefficient information.

[0013] Optionally, the obtaining of the adhesion coefficient of the target road surface position comprises:

[0014] receiving the adhesion coefficient information broadcast by the roadside device, wherein the adhesion coefficient information broadcast by the roadside device is the adhesion coefficient information generated and broadcast by a second vehicle, the roadside device is a roadside device with a distance to the first vehicle less than or equal to a third preset distance, the second vehicle is a vehicle with a distance to the roadside device less than or equal to a fourth preset distance, and the adhesion coefficient information includes an adhesion coefficient and a road surface position corresponding to the adhesion coefficient;

[0015] obtaining the adhesion coefficient of the target road surface position according to the travel route of the first vehicle and the received adhesion coefficient information.

[0016] Optionally, the obtaining of the adhesion coefficient of the target road surface position according to the travel route of the first vehicle and the received adhesion coefficient information includes:

[0017] obtaining a plurality of adhesion coefficient information of a target road section according to the travel route of the first vehicle, the target road section being a road section with a distance to the first vehicle less than or equal to a first preset distance in the travel route of the first vehicle;

[0018] in a case where a plurality of adhesion coefficients less than a first threshold are included in the plurality of adhesion coefficient information, and the distances between the road surface positions corresponding to the plurality of adhesion coefficients less than the first threshold are less than a fifth preset distance, determining a minimum adhesion coefficient in the plurality of adhesion coefficients less than the first threshold, and taking the road surface position corresponding to the minimum adhesion coefficient as a target road surface position, the minimum adhesion coefficient being the adhesion coefficient of the target road surface position.

[0019] Optionally, the determining of the maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient includes: obtaining a product of the adhesion coefficient and the gravity of the first vehicle, and taking a difference between the product and a ramp resistance as the maximum braking force.

[0020] the obtaining of the speed limit of the first vehicle according to the maximum braking force and the safe braking distance includes:

[0021] obtaining a deceleration of the first vehicle according to a quotient of the maximum braking force and the mass of the first vehicle;

[0022] obtaining a product of twice the safe braking distance and the deceleration, and taking a square root of the product as the speed limit.

[0023] Optionally, the obtaining of the adhesion coefficient of the target road surface position includes:

[0024] obtaining the adhesion coefficient of the target road surface position according to an adhesion coefficient map, the adhesion coefficient map including an adhesion coefficient and a road surface position corresponding to the adhesion coefficient.

[0025] Optionally, the method further comprises establishing the adhesion coefficient map by:

[0026] For each road surface position in the adhesion coefficient map, within a first preset time period, obtaining adhesion coefficients of the road surface position uploaded by at least one vehicle, and determining a minimum value of the adhesion coefficients as the adhesion coefficient corresponding to the road surface position;

[0027] Within a second preset time period after determining the adhesion coefficient corresponding to the road surface position, if no adhesion coefficient of the road surface position uploaded by a vehicle is received, gradually increasing the adhesion coefficient of the road surface position to a maximum historical adhesion coefficient of the road surface position within a third time period.

[0028] According to a second aspect of the embodiments of the present disclosure, an automatic driving control device is provided, comprising:

[0029] An adhesion coefficient obtaining module configured to obtain an adhesion coefficient of a target road surface position, the target road surface position being less than or equal to a first preset distance from a first vehicle on a travel route of the first vehicle;

[0030] A maximum braking force determining module configured to determine a maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient;

[0031] A safe braking distance determining module configured to determine a safe braking distance of the first vehicle according to a road condition in which the first vehicle is located;

[0032] A vehicle speed limit value obtaining module configured to obtain a vehicle speed limit value of the first vehicle according to the maximum braking force and the safe braking distance;

[0033] An automatic driving control module configured to control an automatic driving speed of the first vehicle, so that a speed of the first vehicle when reaching the target road surface position does not exceed the vehicle speed limit value.

[0034] According to a third aspect of the embodiments of the present disclosure, a vehicle is provided, comprising:

[0035] A first processor;

[0036] A first memory for storing first processor executable instructions;

[0037] The first processor is configured to:

[0038] Obtain an adhesion coefficient of a target road surface position, the target road surface position being less than or equal to a first preset distance from a first vehicle on a travel route of the first vehicle;

[0039] Determine a maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient;

[0040] determine a safety braking distance of the first vehicle according to a road condition where the first vehicle is located;

[0041] obtain a vehicle speed limit of the first vehicle according to the maximum braking force and the safety braking distance;

[0042] control an automatic driving speed of the first vehicle, so that a speed of the first vehicle when reaching the target road surface position is not more than the vehicle speed limit.

[0043] According to a fourth aspect of the embodiments of the present disclosure, a computer readable storage medium is provided, and program instructions are executed by a processor to implement the steps of the automatic driving control method provided in the first aspect of the present disclosure.

[0044] According to a fifth aspect of the embodiments of the present disclosure, a chip is provided, comprising a second processor and an interface; the second processor is configured to read instructions to execute the steps of the automatic driving control method provided in the first aspect of the present disclosure.

[0045] The technical solutions provided by the embodiments of the present disclosure can include the following beneficial effects:

[0046] When the adhesion coefficient of the target road surface position is small, the vehicle is prone to slip at the target road surface position when the vehicle speed is too fast. Through the technical solutions provided in the present disclosure, the first vehicle can obtain the adhesion coefficient of the target road surface position in advance, and calculate and obtain the vehicle speed limit of the target road surface position, and control the automatic driving speed of the first vehicle in advance, so that the vehicle speed of the first vehicle when reaching the target road surface position is not more than the vehicle speed limit, thereby avoiding the first vehicle from slipping at the target road surface position, and making the first vehicle not to exit the automatic driving mode at the target road surface position which is prone to slip, improving the experience satisfaction of the driver to the automatic / intelligent driving, and increasing the confidence of the driver to the automatic / intelligent driving.

[0047] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0048] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure.

[0049] Figure 1 is a flowchart of an automatic driving control method according to an exemplary embodiment.

[0050] Figure 2 is a scene schematic diagram of receiving adhesion coefficient information generated and broadcasted by a second vehicle according to an exemplary embodiment.

[0051] Figure 3 is a scenario diagram illustrating a case of receiving attachment coefficient information broadcast by a roadside device according to an example embodiment.

[0052] Figure 4 is a block diagram of an automatic driving control device according to an example embodiment.

[0053] Figure 5 is a block diagram of a vehicle according to an example embodiment. DETAILED DESCRIPTION

[0054] The example embodiments will be described in detail below with reference to the accompanying drawings. In the following description, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following example embodiments do not represent all implementations consistent with the present disclosure. Instead, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0055] Figure 1 is a flowchart of an automatic driving control method according to an example embodiment. As shown in Figure 1 the automatic driving control method includes the following steps:

[0056] In step S11, an attachment coefficient of a target road surface position is acquired, the target road surface position being less than or equal to a first preset distance from the first vehicle on a travel route of the first vehicle.

[0057] By step S11, the attachment coefficient of the target road surface position of the road surface (travel route) in front of the first vehicle is acquired in advance, which is less than or equal to the first preset distance from the vehicle.

[0058] In step S12, a maximum braking force of the first vehicle at the target road surface position is determined according to the attachment coefficient.

[0059] In step S13, a safe braking distance of the first vehicle is determined according to the road condition in which the first vehicle is located.

[0060] For example, when the road condition is a parking lot, the safe braking distance is determined to be 5 meters; when the road condition is a highway, the safe braking distance is determined to be 50 meters. The safe braking distance is the distance traveled by the first vehicle from the speed limit to the complete stop of the vehicle.

[0061] In step S14, a speed limit of the first vehicle is acquired according to the maximum braking force and the safe braking distance.

[0062] According to the maximum braking force, a corresponding deceleration of the maximum braking force is obtained, and in combination with the safety braking distance, a vehicle speed limit value is obtained.

[0063] In step S15, the automatic driving speed of the first vehicle is controlled so that the speed of the first vehicle when reaching the target road surface position does not exceed the vehicle speed limit value.

[0064] Since the vehicle speed limit value is determined according to the maximum braking force and the safety braking distance, when the speed of the first vehicle does not exceed the vehicle speed limit value, the first vehicle does not slip.

[0065] When the adhesion coefficient of the target road surface position is small, the vehicle is easy to slip at the target road surface position when the vehicle speed is too high. Through the technical solution provided by the present disclosure, the first vehicle obtains the adhesion coefficient of the target road surface position in advance, and calculates and obtains the vehicle speed limit value of the target road surface position, and controls the automatic driving speed of the first vehicle in advance so that the vehicle speed of the first vehicle when reaching the target road surface position does not exceed the vehicle speed limit value, thereby avoiding the first vehicle from slipping at the target road surface position, and enabling the first vehicle to not exit the automatic driving mode at the target road surface position which is easy to slip, improving the experience satisfaction of the driver on automatic / intelligent driving, and increasing the confidence of the driver on automatic / intelligent driving.

[0066] Optionally, step S11 comprises:

[0067] Receiving adhesion coefficient information generated and broadcasted by a second vehicle.

[0068] The second vehicle is a vehicle with a distance from the first vehicle less than or equal to a second preset distance, and the adhesion coefficient information includes an adhesion coefficient and a road surface position corresponding to the adhesion coefficient. The second preset distance is less than the maximum broadcast distance of the second vehicle and less than the maximum receiving distance of the first vehicle. Figure 2 As shown in the figure, the second vehicle can calculate and obtain the adhesion coefficient of the road surface on which the second vehicle is currently driving according to vehicle dynamics principle. After obtaining the adhesion coefficient of the road surface on which the second vehicle is currently driving, the second vehicle can broadcast the adhesion coefficient and the road surface position (the road surface position corresponding to the adhesion coefficient) on which the second vehicle is currently driving through an on-board communication device (OBU). When the second vehicle broadcasts the adhesion coefficient information through the on-board communication device, the maximum broadcast distance thereof can be about 200 meters in square, and the maximum receiving distance of the first vehicle can also be about 200 meters in square, therefore, the second preset distance can be less than or equal to 200 meters. It should be noted that the adhesion coefficient information generated and broadcasted by the second vehicle can be calculated and broadcasted in real time during the driving of the second vehicle, or can be calculated and broadcasted only when the second vehicle slips.

[0069] Based on the travel route of the first vehicle and the received adhesion coefficient information, the adhesion coefficient of the target road surface is obtained.

[0070] Since the adhesion coefficient information received by the first vehicle may be broadcast by a second vehicle within a second preset distance, it includes adhesion coefficient information unrelated to the first vehicle's travel route (such as the adhesion coefficient of roads the first vehicle has already traveled and the adhesion coefficient of roads that will not be traveled on for a long time). Therefore, the received adhesion coefficient information can be filtered according to the travel route to obtain the adhesion coefficient of the target road surface location.

[0071] Through the above technical solution, based on vehicle-to-vehicle (V2V) communication, the second vehicle generates and broadcasts the adhesion coefficient to the first vehicle, so that the first vehicle can obtain the adhesion coefficient of the target position on the travel route in advance.

[0072] Optionally, step S11 includes:

[0073] Receive adhesion coefficient information broadcast by roadside equipment.

[0074] The adhesion coefficient information broadcast by the roadside equipment is the adhesion coefficient information received from the second vehicle and broadcast accordingly. The roadside equipment is located at a distance less than or equal to a third preset distance from the first vehicle. The second vehicle is located at a distance less than or equal to a fourth preset distance from the roadside equipment. The adhesion coefficient information includes the adhesion coefficient and the corresponding road surface position.

[0075] The third preset distance is less than the maximum broadcast distance of the roadside device and less than the maximum receiving distance of the first vehicle. The fourth preset distance is less than the maximum broadcast distance of the second vehicle and less than the maximum receiving distance of the roadside device. Figure 3As shown, the second vehicle can calculate the adhesion coefficient of the road surface on which the second vehicle is running according to the principle of vehicle dynamics. After obtaining the adhesion coefficient of the road surface on which the second vehicle is running, the second vehicle can broadcast the adhesion coefficient and the position of the road surface (the position of the road surface corresponding to the adhesion coefficient) to the roadside equipment through the on-board communication device (On Board Unit, OBU), and the roadside equipment broadcasts the adhesion coefficient to the first vehicle. When the second vehicle broadcasts the adhesion coefficient information through the on-board communication device, the maximum broadcast distance thereof can be about 200 meters in all directions, and the maximum receiving distance of the roadside equipment is greater than or equal to the maximum broadcast distance; when the first vehicle receives the adhesion coefficient, the maximum receiving distance thereof can be about 200 meters in all directions, and the maximum broadcast distance of the roadside equipment is greater than or equal to the maximum receiving distance, therefore, the fourth preset distance and the third distance can be less than or equal to 200 meters. It should be noted that the adhesion coefficient information generated and broadcast by the second vehicle can be calculated and broadcast in real time during the running of the second vehicle, or can be calculated and broadcast only when the second vehicle slips.

[0076] According to the travel route of the first vehicle and the received adhesion coefficient information, the adhesion coefficient of the target road surface position is obtained.

[0077] Since the adhesion coefficient information received by the first vehicle can be broadcast by the roadside equipment within the third preset distance, it includes adhesion coefficient information irrelevant to the travel route of the first vehicle (such as the adhesion coefficient of the road that the first vehicle has passed through and the adhesion coefficient information of the road that will not be traveled for a long time). Therefore, the received adhesion coefficient information can be screened according to the travel route to obtain the adhesion coefficient of the target road surface position.

[0078] Through the above technical solution, the Vehicle to Infrastructure (V2I) mode is used to make the second vehicle generate and broadcast the adhesion coefficient to the roadside equipment, and the roadside equipment broadcasts the adhesion coefficient to the first vehicle, so that the first vehicle can obtain the adhesion coefficient of the target position on the travel route in advance. The Vehicle to Infrastructure mode can expand the maximum broadcast distance of the adhesion coefficient, and store the adhesion coefficient so that the first vehicle can receive the adhesion coefficient sent by the first vehicle a long time ago.

[0079] Optionally, the adhesion coefficient of the target road surface position is obtained according to the travel route of the first vehicle and the received adhesion coefficient information, and includes:

[0080] According to the travel route of the first vehicle, a plurality of adhesion coefficient information of a target road section is obtained, and the target road section is a road section in the travel route of the first vehicle, the distance of which from the first vehicle is less than or equal to a first preset distance.

[0081] The target road position is in a target road section, the target road section includes a plurality of road positions, and the target road position is one of the road positions in the target road section. The plurality of adhesion coefficient information of the target road section can be generated by the plurality of second vehicles.

[0082] In a case where the plurality of adhesion coefficients less than the first threshold value are included in the plurality of adhesion coefficient information, and distances between road positions corresponding to the plurality of adhesion coefficients less than the first threshold value are less than a fifth preset distance, a minimum adhesion coefficient in the plurality of adhesion coefficients less than the first threshold value is determined, a road position corresponding to the minimum adhesion coefficient is taken as the target road position, and the minimum adhesion coefficient is taken as the adhesion coefficient of the target road position.

[0083] The first threshold value is flexibly set according to a situation, for example, when the adhesion coefficient is less than the first threshold value, the vehicle is easy to slip or exists slip when the vehicle is driven at a normal speed. The fifth preset distance can be flexibly set according to a situation, for example, when the distance between a plurality of road positions is less than the fifth preset distance, the plurality of road positions are considered to be close to each other, and can be considered to be the same road position. Through this step, when a plurality of road positions close to each other correspond to a plurality of adhesion coefficients less than the first threshold value, a road position corresponding to a minimum adhesion coefficient in the plurality of adhesion coefficients less than the first threshold value is taken as the target road position, and the minimum adhesion coefficient is taken as the adhesion coefficient of the target road position.

[0084] Therefore, through the above scheme, the adhesion coefficient of the target road position is limited to be less than the first threshold value (that is, the target road position is limited to be easy to slip or the second vehicle has already slipped), and is the minimum value of the plurality of adhesion coefficients less than the first threshold value sent by the plurality of second vehicles, so that the maximum braking force calculated according to the minimum adhesion coefficient is minimum, and then the speed limit value calculated is minimum, to ensure the safety of automatic driving speed control according to the minimum speed limit value.

[0085] Optionally, the step S12 includes: obtaining a product of the adhesion coefficient and the gravity of the first vehicle, and taking a difference between the product and the ramp resistance as the maximum braking force.

[0086] That is, the maximum braking force can be calculated by the following formula:

[0087] F BrkMax= μ*W-F Slope

[0088] In the formula, F BrkMax represents the maximum braking force; μ represents the adhesion coefficient of the target road position; W represents the gravity of the first vehicle; F Slope represents the ramp resistance, and the ramp resistance is 0 when the target road position is not a ramp.

[0089] The step S14 includes:

[0090] According to a quotient of the maximum braking force and a mass of the first vehicle, obtain a deceleration of the first vehicle caused by the maximum braking force.

[0091] That is, the deceleration can be calculated by the following formula:

[0092] a = F BrkMax / M

[0093] In the formula, a represents the deceleration; and M represents the mass of the first vehicle.

[0094] Obtain a product of twice the safe braking distance and the deceleration, and take a square root of the product as the speed limit.

[0095] That is, the speed limit can be calculated by the following formula:

[0096] v max = (2aL) 1 / 2

[0097] In the formula, v max represents the speed limit; and L represents the safe braking distance.

[0098] Optionally, the step S11 comprises:

[0099] According to an adhesion coefficient map, obtain an adhesion coefficient of a target road surface position, the adhesion coefficient map comprising adhesion coefficients and road surface positions corresponding to the adhesion coefficients.

[0100] The adhesion coefficient map can be stored in the cloud and distributed to the first vehicle by a server. Since the adhesion coefficient map stores adhesion coefficients and road surface positions corresponding to the adhesion coefficients, the adhesion coefficient corresponding to the target road surface position in the adhesion coefficient map can be obtained according to the target road surface position.

[0101] By the above technical solution, the first vehicle can obtain the adhesion coefficient of the target road surface position in advance by using the adhesion coefficient map.

[0102] Optionally, the method further comprises establishing the adhesion coefficient map by the following way:

[0103] For each road surface position in the adhesion coefficient map, obtain adhesion coefficients of the road surface position uploaded by at least one vehicle within a first preset time length, and determine a minimum value of the adhesion coefficients as the adhesion coefficient corresponding to the road surface position.

[0104] The first preset time period can be preset, for example, can be set to 1 hour. Within 1 hour, there can be multiple vehicles (second vehicles) passing through the road surface position, and each determined adhesion coefficient is uploaded to the server side. In order to ensure that a road surface position corresponds to an adhesion coefficient, it is necessary to screen the uploaded multiple adhesion coefficients. Through this step, the minimum value of the multiple adhesion coefficients is determined as the adhesion coefficient corresponding to the road surface position, which ensures that the speed limit value determined by the minimum adhesion coefficient is relatively small, and ensures the safety of automatic driving speed control according to the minimum speed limit value.

[0105] Within the second preset time period after determining the adhesion coefficient corresponding to the road surface position, if no adhesion coefficient of the road surface position uploaded by the vehicle is received, the adhesion coefficient of the road surface position is gradually increased to the maximum historical adhesion coefficient of the road surface position within a third time period.

[0106] Exemplarily, after determining the adhesion coefficient, the adhesion coefficient can be maintained unchanged until a new adhesion coefficient is determined due to the change of the adhesion coefficient of the road surface needing a certain time. However, if no adhesion coefficient of the road surface position uploaded by the vehicle is received for a long time (within the second time period), if the adhesion coefficient is not updated, it can cause the subsequent passing vehicles to take unnecessary measures (such as speed control) to prevent slipping. Therefore, the second preset time period can be set, for example, can be set to 1 hour. If no adhesion coefficient of the road surface position uploaded by the vehicle is received within the second preset time period, the previously determined adhesion coefficient can be affected by other factors and is no longer applicable, and the adhesion coefficient of the road surface position can be increased to the maximum historical adhesion coefficient of the road surface position within a third preset time period, so as to avoid the subsequent passing vehicles taking unnecessary measures (such as speed control) to prevent slipping.

[0107] Optionally, the method further comprises: determining the third preset time period according to at least one of the following information:

[0108] The region where the road surface position is currently located, the current weather information, and the current seasonal information.

[0109] Exemplarily, the third preset time length can be determined according to current weather information. If the temperature of the current weather is high, the road surface needs a shorter time to reach its maximum historical adhesion coefficient (i.e., the road surface needs a shorter time to become dry), and the third preset time length can be set to a smaller value. If the temperature of the current weather is low, the road surface needs a longer time to reach its maximum historical adhesion coefficient, and the third preset time length can be set to a larger value. For another example, the third preset time length can also be determined according to current seasonal information or the region where the road surface position currently locates. For example, if the current season is winter or the region where the road surface position currently locates is a cold region, the road surface needs a longer time to reach its maximum historical adhesion coefficient, and the third preset time length can be set to a larger value. It should be noted that the third preset time length can be determined by one of the above information, or can be determined according to multiple of them.

[0110] Optionally, gradually increasing the adhesion coefficient of the road surface position to the maximum historical adhesion coefficient of the road surface position within the third time length comprises:

[0111] Determining a difference between the maximum historical adhesion coefficient and the current adhesion coefficient.

[0112] Determining a change rate of the adhesion coefficient according to the third preset time length and the difference.

[0113] Gradually increasing the adhesion coefficient to the maximum historical adhesion coefficient according to the change rate.

[0114] By the above technical solution, the adhesion coefficient is gradually increased according to the determined change rate, which can ensure the stability of the change of the adhesion coefficient of the road surface position.

[0115] It should be noted that the first vehicle can perform all the steps of the second vehicle.

[0116] Based on the above technical concept, the embodiment of the present disclosure further provides an automatic driving control device. Figure 4 is a block diagram of an automatic driving control device according to an exemplary embodiment. Referring to Figure 4 The device comprises:

[0117] An adhesion coefficient acquisition module 11 is configured to acquire an adhesion coefficient of a target road surface position, the target road surface position being on a travel route of a first vehicle and being less than or equal to a first preset distance from the first vehicle.

[0118] A maximum braking force determination module 12 is configured to determine a maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient.

[0119] A safe braking distance determination module 13 is configured to determine a safe braking distance of the first vehicle according to a road condition where the first vehicle is located.

[0120] The vehicle speed limit obtaining module 14 is configured to obtain a vehicle speed limit of the first vehicle according to the maximum braking force and the safety braking distance.

[0121] The automatic driving control module 15 is configured to control an automatic driving speed of the first vehicle, so that a speed of the first vehicle when reaching the target road position does not exceed the vehicle speed limit.

[0122] When the adhesion coefficient of the target road position is small, the vehicle is prone to slip at the target road position when the vehicle speed is too fast. Through the technical solution provided by the present disclosure, the first vehicle obtains the adhesion coefficient of the target road position in advance, and calculates and obtains the vehicle speed limit of the target road position, and controls the automatic driving speed of the first vehicle in advance, so that the speed of the first vehicle when reaching the target road position does not exceed the vehicle speed limit, thereby avoiding the first vehicle from slipping at the target road position, and enabling the first vehicle to not exit the automatic driving mode at the target road position prone to slipping, improving the experience satisfaction of the driver on automatic / intelligent driving, and increasing the confidence of the driver on automatic / intelligent driving.

[0123] Optionally, the adhesion coefficient obtaining module 11 comprises:

[0124] The vehicle-to-vehicle communication submodule is configured to receive adhesion coefficient information generated and broadcasted by a second vehicle.

[0125] The second vehicle is a vehicle with a distance from the first vehicle less than or equal to a second preset distance, and the adhesion coefficient information comprises an adhesion coefficient and a road position corresponding to the adhesion coefficient. The second preset distance is less than a maximum broadcast distance of the second vehicle and less than a maximum receiving distance of the first vehicle.

[0126] The first screening submodule is configured to obtain the adhesion coefficient of the target road position according to the travel route of the first vehicle and the received adhesion coefficient information.

[0127] Through the above technical solution, in a vehicle-to-vehicle (V2V) manner, the second vehicle generates and broadcasts the adhesion coefficient to the first vehicle, so that the first vehicle obtains the adhesion coefficient of the target position on the travel route in advance.

[0128] Optionally, the adhesion coefficient obtaining module 11 comprises:

[0129] The vehicle-to-roadside device communication submodule is configured to receive adhesion coefficient information broadcasted by a roadside device.

[0130] The adhesion coefficient information broadcast by the roadside device is adhesion coefficient information generated and broadcast by a second vehicle. The roadside device is a roadside device with a distance to the first vehicle less than or equal to a third preset distance. The second vehicle is a vehicle with a distance to the roadside device less than or equal to a fourth preset distance. The adhesion coefficient information includes an adhesion coefficient and a road surface position corresponding to the adhesion coefficient.

[0131] The first screening submodule is configured to obtain an adhesion coefficient of a target road surface position according to the travel route of the first vehicle and the received adhesion coefficient information.

[0132] Through the above technical solution, the second vehicle generates and broadcasts the adhesion coefficient to the roadside device in a vehicle to infrastructure (V2I) manner, and the roadside device broadcasts the adhesion coefficient to the first vehicle, so that the first vehicle can obtain the adhesion coefficient of the target position on the travel route in advance. The V2I manner can expand the maximum broadcast distance of the adhesion coefficient and store the adhesion coefficient, so that the first vehicle can receive the adhesion coefficient sent by the first vehicle a long time ago.

[0133] Optionally, the first screening submodule is specifically configured to:

[0134] According to the travel route of the first vehicle, a plurality of adhesion coefficient information of a target road section is obtained, and the target road section is a road section with a distance to the first vehicle less than or equal to a first preset distance in the travel route of the first vehicle.

[0135] In a case where a plurality of adhesion coefficients less than the first threshold value are included in the plurality of adhesion coefficient information, and the distance between the road surface positions corresponding to the plurality of adhesion coefficients less than the first threshold value is less than a fifth preset distance, a minimum adhesion coefficient in the plurality of adhesion coefficients less than the first threshold value is determined, a road surface position corresponding to the minimum adhesion coefficient is taken as a target road surface position, and the minimum adhesion coefficient is the adhesion coefficient of the target road surface position.

[0136] Through the above scheme, the adhesion coefficient of the target road surface position is limited to be less than the first threshold value (i.e., the target road surface position can be easily slippery or the second vehicle has already slipped), and is the minimum value of a plurality of adhesion coefficients less than the first threshold value sent by a plurality of second vehicles, so that the maximum braking force calculated according to the minimum adhesion coefficient is minimum, and then the vehicle speed limit calculated is minimum, to ensure the safety of automatic driving speed control according to the minimum vehicle speed limit.

[0137] Optionally, the maximum braking force determination module 12 is specifically configured to:

[0138] An integral of the adhesion coefficient and the gravity of the first vehicle is obtained, and a difference between the integral and a ramp resistance is taken as the maximum braking force.

[0139] The vehicle speed limit obtaining module 14 is specifically configured to:

[0140] obtain a deceleration of the first vehicle according to a quotient of the maximum braking force and a mass of the first vehicle.

[0141] obtain a product of twice the safe braking distance and the deceleration, and take a square root of the product as the vehicle speed limit.

[0142] Optionally, the adhesion coefficient obtaining module 11 is specifically configured to:

[0143] obtain an adhesion coefficient of a target road position according to an adhesion coefficient map, the adhesion coefficient map comprising adhesion coefficients and road positions corresponding to the adhesion coefficients.

[0144] By the above technical solution, the first vehicle can obtain the adhesion coefficient of the target road position in advance by using the adhesion coefficient map.

[0145] Optionally, the device further comprises:

[0146] an adhesion coefficient map establishing module configured to, for each road position in the adhesion coefficient map, obtain adhesion coefficients of the road position uploaded by at least one vehicle within a first preset time length, and determine a minimum value of the adhesion coefficients as an adhesion coefficient corresponding to the road position.

[0147] an adhesion coefficient map updating module configured to, in a second preset time length after the adhesion coefficient corresponding to the road position is determined, gradually increase the adhesion coefficient of the road position to a maximum historical adhesion coefficient of the road position within a third time length in a case where no adhesion coefficient of the road position uploaded by a vehicle is received.

[0148] As to the device in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments of the method, and will not be described in detail here.

[0149] The present disclosure also provides a computer readable storage medium having computer program instructions stored thereon, the program instructions being executed by a processor to implement the steps of the automatic driving control method provided by the present disclosure.

[0150] The apparatus described above can be a part of an independent electronic device, for example, in an embodiment, the apparatus can be an integrated circuit (IC) or a chip, wherein the integrated circuit can be an IC or a collection of multiple ICs; the chip can include but is not limited to the following types: GPU (Graphics Processing Unit), CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), SOC (System on Chip, SoC, System on a Chip or System on Chip), etc. The integrated circuit or chip described above can be used to execute executable instructions (or code) to implement the automatic driving control method described above. Among them, the executable instructions can be stored in the integrated circuit or chip, or obtained from other devices or equipment, for example, the integrated circuit or chip includes a second processor, a second memory, and an interface for communicating with other devices. The executable instructions can be stored in the second memory, and when the executable instructions are executed by the second processor, the automatic driving control method described above is implemented; or the integrated circuit or chip can receive executable instructions through the interface and transmit them to the second processor for execution to implement the automatic driving control method described above.

[0151] Referring to Figure 5 , Figure 5 is a functional block diagram of a vehicle 600 according to an example embodiment. The vehicle 600 can be configured to operate in a fully or partially autonomous driving mode. For example, the vehicle 600 can obtain surrounding environment information through a perception system 620, and based on analysis of the surrounding environment information, obtain an autonomous driving strategy to implement full autonomous driving, or present the analysis results to a user to implement partial autonomous driving.

[0152] The vehicle 600 can include various subsystems, such as an infotainment system 610, a perception system 620, a decision control system 630, a drive system 640, and a computing platform 650. Optionally, the vehicle 600 can include more or fewer subsystems, and each subsystem can include multiple components. In addition, each subsystem and component of the vehicle 600 can be interconnected by wired or wireless means.

[0153] In some embodiments, the infotainment system 610 can include a communication system 611, an entertainment system 612, and a navigation system 613.

[0154] The communication system 611 can include a wireless communication system that can wirelessly communicate with one or more devices directly or via a communication network. For example, the wireless communication system can use 3G cellular communication, such as CDMA, EVDO, GSM / GPRS, or 4G cellular communication, such as LTE. Or 5G cellular communication. The wireless communication system can communicate with a wireless local area network (WLAN) using WiFi. In some embodiments, the wireless communication system can communicate directly with a device using an infrared link, Bluetooth, or ZigBee. Other wireless protocols, such as various vehicle communication systems, for example, the wireless communication system can include one or more dedicated short range communications (DSRC) devices that can include public and / or private data communication between vehicles and / or roadside stations.

[0155] The entertainment system 612 can include a display device, a microphone, and a sound system, based on which a user can listen to the radio, play music in the vehicle, or connect a mobile phone to the vehicle and realize mobile phone projection on the display device. The display device can be touch-enabled, and the user can operate it by touching the screen.

[0156] In some cases, the user's voice signal can be obtained through the microphone, and some control of the vehicle 600 by the user can be realized according to the analysis of the user's voice signal, such as adjusting the temperature in the vehicle. In other cases, music can be played to the user through the sound system.

[0157] The navigation system 613 can include a map service provided by a map provider, thereby providing the vehicle 600 with navigation of the driving route. The navigation system 613 can be used in cooperation with the global positioning system 621 and the inertial measurement unit 622 of the vehicle. The map service provided by the map provider can be a two-dimensional map or a high-definition map.

[0158] The perception system 620 can include several types of sensors that sense information about the environment surrounding the vehicle 600. For example, the perception system 620 can include a global positioning system 621 (which can be a GPS system, a Beidou system, or other positioning system), an inertial measurement unit (IMU) 622, a lidar 623, a millimeter wave radar 624, an ultrasonic radar 625, and a camera 626. The perception system 620 can also include sensors that monitor internal systems of the vehicle 600 (e.g., in-vehicle air quality monitors, fuel gauges, oil temperature gauges, etc.). Sensor data from one or more of these sensors can be used to detect objects and their respective characteristics (location, shape, orientation, velocity, etc.). Such detection and identification are key functions for the safe operation of the vehicle 600.

[0159] The global positioning system 621 is used to estimate the geographic position of the vehicle 600.

[0160] The inertial measurement unit 622 is used to sense changes in the pose of the vehicle 600 based on inertial acceleration. In some embodiments, the inertial measurement unit 622 can be a combination of an accelerometer and a gyroscope.

[0161] The lidar 623 uses laser light to sense objects in the environment in which the vehicle 600 is located. In some embodiments, the lidar 623 can include one or more laser sources, a laser scanner, and one or more detectors, as well as other system components.

[0162] The millimeter wave radar 624 uses radio signals to sense objects within the surrounding environment of the vehicle 600. In some embodiments, in addition to sensing objects, the millimeter wave radar 624 can also be used to sense the speed and / or heading of the objects.

[0163] The ultrasonic radar 625 can use ultrasonic signals to sense objects around the vehicle 600.

[0164] The camera 626 is used to capture image information of the surrounding environment of the vehicle 600. The camera 626 can include monocular cameras, binocular cameras, structured light cameras, and panoramic cameras, etc., and the image information acquired by the camera 626 can include still images and video stream information.

[0165] The decision control system 630 includes a computing system 631 that makes analytical decisions based on the information acquired by the perception system 620, and also includes a vehicle controller 632 that controls the power system of the vehicle 600, as well as a steering system 633, a throttle 634, and a braking system 635 for controlling the vehicle 600.

[0166] The computing system 631 can operate to process and analyze various information acquired by the perception system 620 in order to identify targets, objects, and / or features in the environment surrounding the vehicle 600. Targets can include pedestrians or animals, and objects and / or features can include traffic signals, road boundaries, and obstacles. The computing system 631 can use object recognition algorithms, Structure from Motion (SFM) algorithms, video tracking, and / or the like. In some embodiments, the computing system 631 can be used to map the environment, track objects, estimate the velocity of objects, and / or the like. The computing system 631 can analyze the acquired information and derive a control strategy for the vehicle.

[0167] The vehicle controller 632 can be used to coordinate the control of the power battery and the engine 641 of the vehicle in order to improve the power performance of the vehicle 600.

[0168] The steering system 633 can be used to adjust the heading direction of the vehicle 600. For example, the steering system 633 can be a steering wheel system in one embodiment.

[0169] The accelerator 634 can be used to control the operating speed of the engine 641 and, in turn, the speed of the vehicle 600.

[0170] The braking system 635 can be used to control the deceleration of the vehicle 600. The braking system 635 can use friction to slow the wheels 644. In some embodiments, the braking system 635 can convert the kinetic energy of the wheels 644 into electrical current. The braking system 635 can also take other forms to slow the wheels 644 and, in turn, control the speed of the vehicle 600.

[0171] The drive system 640 can include components that provide motive power for the vehicle 600. In one embodiment, the drive system 640 can include the engine 641, the energy source 642, the transmission system 643, and the wheels 644. The engine 641 can be an internal combustion engine, an electric motor, an air compression engine, or other types of engines in combination, such as a hybrid engine that includes a gasoline engine and an electric motor, a hybrid engine that includes an internal combustion engine and an air compression engine. The engine 641 converts the energy source 642 into mechanical energy.

[0172] Examples of the energy source 642 include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electrical power. The energy source 642 can also provide energy for other systems of the vehicle 600.

[0173] The drivetrain 643 can transmit mechanical power from the engine 641 to the wheels 644. The drivetrain 643 can include a transmission, a differential, and drive shafts. In one embodiment, the drivetrain 643 can also include other devices, such as a clutch. The drive shafts can include one or more shafts that can be coupled to one or more wheels 644.

[0174] Some or all of the functionality of the vehicle 600 is controlled by a computing platform 650. The computing platform 650 can include at least one first processor 651 that can execute instructions 653 stored in a non-transitory computer readable medium, such as a first memory 652. In some embodiments, the computing platform 650 can also be a plurality of computing devices that control individual components or subsystems of the vehicle 600 in a distributed manner.

[0175] The first processor 651 can be any conventional processor, such as commercially available CPUs. Alternatively, the first processor 651 can include a Graphics Process Unit (GPU), a Field Programmable Gate Array (FPGA), a System on Chip (SOC), an Application Specific Integrated Circuit (ASIC), or a combination thereof. Although Figure 5 Although functionally illustrated as a single processor, memory, and other elements of a computer in the same block, one of ordinary skill in the art will appreciate that the processor, computer, or memory can actually include multiple processors, computers, or memories that can or can not be stored in the same physical housing. For example, the memory can be a hard drive or other storage medium located in a different housing than the computer. Accordingly, references to a processor or computer will be understood to include references to a collection of processors or computers or memories that can or can not operate in parallel. Rather than using a single processor to perform the steps described herein, some components, such as the steering assembly and the deceleration assembly, can each have their own processor that only performs calculations related to the functionality specific to the component.

[0176] In the embodiments of the present disclosure, the first processor 651 can perform the automatic driving control method described above.

[0177] In various aspects described herein, the first processor 651 can be located remotely from the vehicle and in wireless communication with the vehicle. In other aspects, some of the processes described herein are performed on a processor disposed within the vehicle while others are performed by a remote processor, including taking the necessary steps to perform a single maneuver.

[0178] In some embodiments, the first memory 652 can include instructions 653 (e.g., program logic) that can be executed by the first processor 651 to perform various functions of the vehicle 600. The first memory 652 can also include additional instructions, including instructions to send data to, receive data from, interact with, and / or control one or more of the infotainment system 610, the perception system 620, the decision control system 630, the drive system 640.

[0179] In addition to the instructions 653, the first memory 652 can store data, such as road maps, route information, the vehicle's location, direction, speed, and other such vehicle data, and other information. Such information can be used by the vehicle 600 and the computing platform 650 during operation of the vehicle 600 in autonomous, semi-autonomous, and / or manual modes.

[0180] The computing platform 650 can control the functions of the vehicle 600 based on inputs received from various subsystems (e.g., the drive system 640, the perception system 620, and the decision control system 630). For example, the computing platform 650 can utilize inputs from the decision control system 630 in order to control the steering system 633 to avoid obstacles detected by the perception system 620. In some embodiments, the computing platform 650 can be operable to provide control over many aspects of the vehicle 600 and its subsystems.

[0181] Optionally, one or more of the above-described components can be installed separately from or associated with the vehicle 600. For example, the first memory 652 can exist partially or entirely separately from the vehicle 600. The above-described components can be communicatively coupled together in a wired and / or wireless manner.

[0182] Optionally, the above-described components are just one example, and in actual applications, components in each of the above-described modules can be added or deleted according to actual needs, Figure 5 It should not be understood as a limitation to the embodiments of the present disclosure.

[0183] An autonomous vehicle traveling on a roadway, such as the vehicle 600 above, can identify objects within its surroundings to determine an adjustment to a current speed. The objects can be other vehicles, traffic control devices, or other types of objects. In some examples, each identified object can be considered independently, and based on respective characteristics of the object, such as its current speed, acceleration, spacing from the vehicle, etc., can be used to determine a speed at which the autonomous vehicle is to adjust.

[0184] Optionally, the vehicle 600 or a perception and computing device (e.g., the computing system 631, the computing platform 650) associated with the vehicle 600 can predict the behavior of the identified object based on the characteristics of the identified object and the state of the surrounding environment (e.g., traffic, rain, ice on the road, etc.). Optionally, each of the identified objects depends on the behavior of the others, so the behavior of a single identified object can also be predicted by considering all of the identified objects together. The vehicle 600 can adjust its speed based on the predicted behavior of the identified object. In other words, the autonomous vehicle can determine what steady state the vehicle will need to adjust to (e.g., accelerate, decelerate, or stop) based on the predicted behavior of the object. Other factors can also be considered in determining the speed of the vehicle 600 during this process, such as the lateral position of the vehicle 600 in the road, the curvature of the road, the proximity of static and dynamic objects, etc.

[0185] In addition to providing instructions to adjust the speed of the autonomous vehicle, the computing device can also provide instructions to modify the steering angle of the vehicle 600 to cause the autonomous vehicle to follow a given trajectory and / or maintain a safe lateral and longitudinal distance from objects (e.g., vehicles in adjacent lanes on the road) near the autonomous vehicle.

[0186] The vehicle 600 described above can be various types of travel tools, such as a car, a truck, a motorcycle, a bus, a ship, an airplane, a helicopter, an amusement vehicle, a train, etc., and the embodiments of the present disclosure are not particularly limited.

[0187] In another exemplary embodiment, a computer program product is also provided, which contains a computer program capable of being executed by a programmable device, the computer program having code portions for performing the above-described autonomous driving control method when executed by the programmable device.

[0188] Other embodiments of the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the present disclosure. It is intended that the present disclosure cover any and all variations of the present disclosure including combinations of features falling within the general scope of the disclosure. The specification and examples given are intended as illustrative only and not restrictive of the true scope and spirit of the present disclosure, which is set forth in the following claims.

[0189] It should be understood that the present disclosure is not limited to the precise construction that has been described above and shown in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the present disclosure. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An automatic driving control method characterized by comprising: The method comprises: acquiring an adhesion coefficient of a target road surface position, the target road surface position being less than or equal to a first preset distance from the first vehicle on a travel route of the first vehicle; determining a maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient; determining a safe braking distance of the first vehicle according to a road condition in which the first vehicle is located; acquiring a speed limit of the first vehicle according to the maximum braking force and the safe braking distance; controlling an automatic driving speed of the first vehicle, so that a speed of the first vehicle when reaching the target road surface position does not exceed the speed limit; The acquiring of the adhesion coefficient of the target road surface position comprises: acquiring an adhesion coefficient of a target road surface position according to an adhesion coefficient map, the adhesion coefficient map comprising adhesion coefficient information, the adhesion coefficient information comprising an adhesion coefficient and a road surface position corresponding to the adhesion coefficient, the adhesion coefficient information being uploaded by at least one second vehicle, the adhesion coefficient information uploaded by the second vehicle being calculated and uploaded when the second vehicle is slipping; The method further comprises establishing the adhesion coefficient map by: for each road surface position in the adhesion coefficient map, acquiring adhesion coefficients of the road surface position uploaded by at least one second vehicle within a first preset time period, and determining a minimum value of the adhesion coefficients as the adhesion coefficient corresponding to the road surface position; in a second preset time period after the adhesion coefficient corresponding to the road surface position is determined, if no adhesion coefficient of the road surface position uploaded by the remaining vehicles is received, gradually increasing the adhesion coefficient of the road surface position to a maximum historical adhesion coefficient of the road surface position within a third time period.

2. An automatic driving control device characterized by comprising: comprise: an adhesion coefficient acquisition module configured to acquire an adhesion coefficient of a target road surface position, the target road surface position being less than or equal to a first preset distance from the first vehicle on a travel route of the first vehicle; a maximum braking force determination module configured to determine a maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient; a safe braking distance determination module configured to determine a safe braking distance of the first vehicle according to a road condition in which the first vehicle is located; a speed limit acquisition module configured to acquire a speed limit of the first vehicle according to the maximum braking force and the safe braking distance; an automatic driving control module configured to control an automatic driving speed of the first vehicle, so that a speed of the first vehicle when reaching the target road surface position does not exceed the speed limit; The adhesion coefficient acquisition module is specifically configured to: acquire an adhesion coefficient of a target road surface position according to an adhesion coefficient map, the adhesion coefficient map comprising adhesion coefficient information, the adhesion coefficient information comprising an adhesion coefficient and a road surface position corresponding to the adhesion coefficient; By the above technical solution, the first vehicle can acquire the adhesion coefficient of the target road surface position in advance by using the adhesion coefficient map; The device further comprises: The attachment coefficient map establishing module is configured to, for each road surface position in the attachment coefficient map, obtain attachment coefficients of the road surface position uploaded by at least one vehicle within a first preset time length, and determine a minimum value of the attachment coefficients as the attachment coefficient corresponding to the road surface position; The attachment coefficient map updating module is configured to, in a case where no attachment coefficient of the road surface position uploaded by a vehicle is received within a second preset time length after the attachment coefficient corresponding to the road surface position is determined, gradually increase the attachment coefficient of the road surface position to a maximum historical attachment coefficient of the road surface position within a third time length.

3. A vehicle characterized by comprising: Comprise: A first processor; A first memory for storing first processor executable instructions; Wherein the first processor is configured to: Obtain an attachment coefficient of a target road surface position, the target road surface position being less than or equal to a first preset distance from the first vehicle on a first vehicle travel route; Determine a maximum braking force of the first vehicle at the target road surface position according to the attachment coefficient; Determine a safe braking distance of the first vehicle according to a road condition in which the first vehicle is located; Obtain a vehicle speed limit value of the first vehicle according to the maximum braking force and the safe braking distance; Control an automatic driving speed of the first vehicle so that a speed of the first vehicle when reaching the target road surface position does not exceed the vehicle speed limit value; The attachment coefficient of the target road surface position comprises: Obtain an attachment coefficient of a target road surface position according to an attachment coefficient map, the attachment coefficient map comprising attachment coefficient information, the attachment coefficient information comprising an attachment coefficient and a road surface position corresponding to the attachment coefficient, the attachment coefficient information being uploaded by at least one second vehicle, the attachment coefficient information uploaded by the second vehicle being calculated and uploaded when the second vehicle slips; Further comprising establishing the attachment coefficient map by: For each road surface position in the attachment coefficient map, obtain attachment coefficients of the road surface position uploaded by at least one second vehicle within a first preset time length, and determine a minimum value of the attachment coefficients as the attachment coefficient corresponding to the road surface position; In a case where no attachment coefficient of the road surface position uploaded by a vehicle is received within a second preset time length after the attachment coefficient corresponding to the road surface position is determined, gradually increase the attachment coefficient of the road surface position to a maximum historical attachment coefficient of the road surface position within a third time length.

4. A computer-readable storage medium having stored thereon computer program instructions, wherein, The program instructions are executed by the processor to implement the steps of the method of claim 1.

5. A chip, characterized by Comprise a second processor and an interface; the second processor is used to read instructions to execute the method of claim 1. The program instructions are executed by the processor to implement the steps of the method of claim 1.

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