CN115140100A

CN115140100A - Automatic driving control method, device, vehicle, storage medium and chip

Info

Publication number: CN115140100A
Application number: CN202210982020.8A
Authority: CN
Inventors: 杨亚娟; 李璇
Original assignee: Xiaomi Automobile Technology Co Ltd
Current assignee: Xiaomi Automobile Technology Co Ltd
Priority date: 2022-08-16
Filing date: 2022-08-16
Publication date: 2022-10-04

Abstract

The present disclosure relates to the field of automatic driving technologies, and in particular, to an automatic driving control method and apparatus, a vehicle, a storage medium, and a chip. The method comprises the following steps: acquiring an adhesion coefficient of a target road surface position; determining the maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient; determining the safe braking distance of the first vehicle according to the road condition of the first vehicle; acquiring a vehicle speed limit value of the first vehicle according to the maximum braking force and the safe braking distance; and controlling the automatic driving speed of the first vehicle so that the speed of the first vehicle when the first vehicle reaches the target road surface position does not exceed the vehicle speed limit value. The technical scheme provided by the disclosure can avoid the first vehicle from skidding at the target road surface position, so that the first vehicle can not exit from the automatic driving mode at the target road surface position which is easy to skid, the experience satisfaction degree of a driver on automatic/intelligent driving is improved, and the confidence of the driver on automatic/intelligent driving is increased.

Description

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

Technical Field

The present disclosure relates to the field of automatic driving technologies, and in particular, to an automatic driving control method and apparatus, a vehicle, a storage medium, and a chip.

Background

In the related art, when the automatic driving/smart driving function is used, if a slip phenomenon occurs, the automatic driving/smart driving is automatically exited and the driver is required to take his/her hold. And the driver is required to take over, the experience of the automatic driving/intelligent driving function is influenced, and the confidence of the driver on the automatic driving/intelligent driving is also reduced.

Disclosure of Invention

To overcome the problems in the related art, the present disclosure provides an automatic driving control method, apparatus, vehicle, storage medium, and chip.

According to a first aspect of an embodiment of the present disclosure, there is provided an automatic driving control method, the method including:

acquiring an adhesion coefficient of a target road surface position, wherein the distance between the target road surface position and a first vehicle on a first vehicle travelling route is smaller than or equal to a first preset distance;

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

determining the safe braking distance of the first vehicle according to the road condition of the first vehicle;

acquiring a speed limit value of the first vehicle according to the maximum braking force and the safe braking distance;

and controlling the automatic driving speed of the first vehicle to enable the speed of the first vehicle when the first vehicle reaches the target road surface position not to exceed the vehicle speed limit value.

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

receiving adhesion coefficient information generated and broadcasted by a second vehicle, wherein the second vehicle is a vehicle with a distance from the first vehicle being smaller than or equal to a second preset distance, and the adhesion coefficient information comprises an adhesion coefficient and a road surface position corresponding to the adhesion coefficient;

and acquiring the adhesion coefficient of the target road position according to the travelling route of the first vehicle and the received adhesion coefficient information.

receiving adhesion coefficient information broadcasted by road side equipment, wherein the adhesion coefficient information broadcasted by the road side equipment is the adhesion coefficient information generated and broadcasted by a second received vehicle, the road side equipment is the road side equipment with the distance from the first vehicle being smaller than or equal to a third preset distance, the second vehicle is the vehicle with the distance from the road side equipment being smaller than or equal to a fourth preset distance, and the adhesion coefficient information comprises an adhesion coefficient and a road surface position corresponding to the adhesion coefficient;

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

acquiring a plurality of pieces of adhesion coefficient information of a target road section according to the traveling route of the first vehicle, wherein the target road section is a road section which is in the traveling route of the first vehicle and has a distance to the first vehicle smaller than or equal to a first preset distance;

and determining the minimum adhesion coefficient of the adhesion coefficients smaller than the first threshold value when the plurality of pieces of adhesion coefficient information include a plurality of adhesion coefficients smaller than the first threshold value, and the distance between the road surface positions corresponding to the plurality of adhesion coefficients smaller than the first threshold value is smaller than a fifth preset distance, and taking the road surface position corresponding to the minimum adhesion coefficient as a target road surface position, wherein the minimum adhesion coefficient is the adhesion coefficient of the target road surface position.

Optionally, the determining the maximum braking force of the first vehicle at the target road surface position according to the adhesion coefficient comprises: acquiring a product of the adhesion coefficient and the gravity of the first vehicle, and taking the difference of the product minus the ramp resistance as a maximum braking force;

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

acquiring deceleration of the maximum braking force to the first vehicle according to the quotient of the maximum braking force and the mass of the first vehicle;

and acquiring a quotient of two times of the safe braking distance divided by the deceleration, and taking the derivation of the quotient as the vehicle speed limit value.

and acquiring an adhesion coefficient of the target road surface position according to the adhesion coefficient map, wherein the adhesion coefficient map comprises the adhesion coefficient and the road surface position corresponding to the adhesion coefficient.

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

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

and in a second preset time period after the adhesion coefficient corresponding to the road surface position is determined, under the condition that the adhesion coefficient of the road surface position uploaded by a vehicle is not received, gradually increasing the adhesion coefficient of the road surface position to the maximum historical adhesion coefficient of the road surface position in a third time period.

According to a second aspect of an embodiment of the present disclosure, there is provided an automatic driving control apparatus including:

the adhesion coefficient acquisition module is configured to acquire an adhesion coefficient of a target road surface position, wherein the distance between the target road surface position and a first vehicle on a first vehicle travelling route is smaller than or equal to a first preset distance;

a maximum braking force determination module configured to determine a maximum braking force of the first vehicle at a target road surface position according to the adhesion coefficient;

the safety braking distance determining module is configured to determine the safety braking distance of the first vehicle according to the road condition of the first vehicle;

a vehicle speed limit acquisition module configured to acquire a vehicle speed limit of the first vehicle according to the maximum braking force and the safe braking distance;

an autonomous driving control module configured to control an autonomous driving speed of the first vehicle such that a speed of the first vehicle when reaching a target road surface position does not exceed the vehicle speed limit.

According to a third aspect of an embodiment of the present disclosure, there is provided a vehicle including:

a first processor;

a first memory for storing first processor-executable instructions;

wherein the first processor is configured to:

acquiring an adhesion coefficient of a target road surface position, wherein the distance between the target road surface position and a first vehicle on a first vehicle traveling route is smaller than or equal to a first preset distance;

and controlling the automatic driving speed of the first vehicle so that the speed of the first vehicle when the first vehicle reaches the target road surface position does not exceed the vehicle speed limit value.

According to a fourth aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium, the program instructions when executed by a processor implementing the steps of the automatic driving control method provided by the first aspect of the present disclosure.

According to a fifth aspect of embodiments of the present disclosure, there is provided a chip comprising a second processor and an interface; the second processor is used for reading instructions to execute the steps of the automatic driving control method provided by the first aspect of the disclosure.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

when the adhesion coefficient at the target road surface position is small, the vehicle is likely to slip at the target road surface position when the vehicle speed is excessively high. According to the technical scheme provided by the disclosure, the first vehicle obtains the adhesion coefficient of the target road position in advance, the vehicle speed limit value of the target road position is calculated, the automatic driving speed of the first vehicle is controlled in advance, and the vehicle speed of the first vehicle reaching the target road position is not more than the vehicle speed limit value, so that the first vehicle is prevented from slipping at the target road position, the first vehicle can not exit from an automatic driving mode at the target road position which is easy to slip, the experience satisfaction degree of a driver on automatic/intelligent driving is improved, and the confidence of the driver on automatic/intelligent driving is increased.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1 is a flow chart illustrating a method of automatic driving control according to an exemplary embodiment.

Fig. 2 is a schematic diagram illustrating a scenario for receiving adhesion coefficient information generated and broadcast by a second vehicle according to an exemplary embodiment.

Fig. 3 is a schematic diagram illustrating a scenario of receiving attachment coefficient information broadcast by a roadside device according to an example embodiment.

FIG. 4 is a block diagram illustrating an automatic drive control apparatus according to an exemplary embodiment.

FIG. 5 is a block diagram of a vehicle shown in accordance with an exemplary embodiment.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the disclosure, as detailed in the appended claims.

FIG. 1 is a flow chart illustrating a method of automatic driving control according to an exemplary embodiment. As shown in fig. 1, the automatic driving control method includes the steps of:

in step S11, an adhesion coefficient of a target road surface position is obtained, where a distance between the target road surface position and a first vehicle on a first vehicle travel route is less than or equal to a first preset distance.

By step S11, the adhesion coefficient of the road surface (traveling route) ahead of the first vehicle from the target road surface position where the vehicle is less than or equal to the first preset distance is acquired in advance.

In step S12, a maximum braking force of the first vehicle at a target road surface position is determined based on the adhesion coefficient.

In step S13, a safe braking distance of the first vehicle is determined according to a road condition where the first vehicle is located.

For example, when the road condition is a parking lot, the safe braking distance is determined to be 5 meters; and when the road condition is the expressway, determining that the safe braking distance is 50 meters. The safe braking distance is the distance traveled by the first vehicle from the vehicle speed limit value to the complete stop of the vehicle.

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

And obtaining the deceleration corresponding to the maximum braking force according to the maximum braking force, and obtaining the vehicle speed limit value by combining the safe braking distance.

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

Since the vehicle speed limit is determined based on the maximum braking force and the safety braking distance, the first vehicle does not slip when the speed of the first vehicle does not exceed the vehicle speed limit.

According to the technical scheme provided by the disclosure, the first vehicle obtains the adhesion coefficient of the target road position in advance, calculates the vehicle speed limit value of the target road position, controls the automatic driving speed of the first vehicle in advance, and makes the vehicle speed of the first vehicle reaching the target road position not exceed the vehicle speed limit value, so that the first vehicle is prevented from slipping at the target road position, the first vehicle does not exit from an automatic driving mode at the easy-to-slip target road position, the experience satisfaction degree of the driver on automatic/intelligent driving is improved, and the confidence of the driver on automatic/intelligent driving is increased.

Optionally, step S11 includes:

and receiving the adhesion coefficient information generated and broadcasted by the second vehicle.

The second vehicle is a vehicle with a distance from the first vehicle being smaller 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 smaller than the maximum broadcast distance of the second vehicle and smaller than the maximum receiving distance of the first vehicle. As shown in fig. 2, during the running process of the second vehicle, the adhesion coefficient of the road surface on which the second vehicle is running can be calculated and obtained according to the vehicle dynamics principle. After obtaining the adhesion coefficient of the road surface On which the second vehicle is traveling, the second vehicle may broadcast the adhesion coefficient through an On Board Unit (OBU), and the position of the road surface On which the second vehicle is traveling (the position of the road surface to which the adhesion coefficient corresponds). When the second vehicle broadcasts the adhesion coefficient information through the on-vehicle communication device, the maximum broadcast distance thereof may be about 200 meters in a square circle, and the maximum reception distance of the first vehicle may also be about 200 meters in a square circle, and thus, the second preset distance may be less than or equal to 200 meters. The adhesion coefficient information generated and broadcast by the second vehicle may be calculated and broadcast in real time during the traveling of the second vehicle, or may be calculated and broadcast only when the second vehicle slips.

And acquiring the adhesion coefficient of the target road surface position according to the travelling route of the first vehicle and the received adhesion coefficient information.

Since the adhesion coefficient information received by the first vehicle may be broadcast by a second vehicle within a second predetermined distance of the square circle, it includes the adhesion coefficient information (e.g., the adhesion coefficient of the road that the first vehicle has traveled and the adhesion coefficient of the road that the first vehicle will not travel for a long period of time) independent of the route traveled by the first vehicle. Therefore, the received adhesion coefficient information can be screened according to the traveling route to obtain the adhesion coefficient of the target road surface position.

Through the technical scheme, the second Vehicle generates and broadcasts the adhesion coefficient to the first Vehicle based on a Vehicle-to-Vehicle (V2V) mode, so that the first Vehicle acquires the adhesion coefficient of the target position on the travel route in advance.

Optionally, step S11 includes:

and receiving the attachment coefficient information broadcasted by the road side equipment.

Wherein the adhesion coefficient information broadcast by the roadside device is adhesion coefficient information generated and broadcast by the second vehicle received. The roadside apparatus is a roadside apparatus whose distance from the first vehicle is less than or equal to a third preset distance. The second vehicle is a vehicle which is away from the roadside equipment by a distance smaller than or equal to a fourth preset distance. The adhesion coefficient information comprises an adhesion coefficient and a road surface position corresponding to the adhesion coefficient.

The third preset distance is smaller than the maximum broadcasting distance of the roadside device and smaller than the maximum receiving distance of the first vehicle. The fourth preset distance is smaller than the maximum broadcasting distance of the second vehicle and smaller than the maximum receiving distance of the road side equipment. As shown in fig. 3, during the traveling of the second vehicle, the adhesion coefficient of the road surface on which the second vehicle is traveling can be calculated and obtained according to the vehicle dynamics principle. After obtaining the adhesion coefficient of the road surface On which the second vehicle is traveling, the second vehicle may broadcast the adhesion coefficient and the position of the road surface On which the second vehicle is traveling (the position of the road surface corresponding to the adhesion coefficient) to the road side device, and the road side device may broadcast the adhesion coefficient to the first vehicle. When the second vehicle broadcasts the adhesion coefficient information through the vehicle-mounted communication equipment, the maximum broadcasting distance of the second vehicle is probably about 200 meters of a square circle, and the maximum receiving distance of the road-side equipment is larger than or equal to the maximum broadcasting distance; when the first vehicle receives the adhesion coefficient, the maximum receiving distance of the first vehicle may be about 200 meters square, and the maximum broadcasting distance of the roadside device is greater than or equal to the maximum receiving distance, so that the fourth preset distance and the third distance may be less than or equal to 200 meters. It should be noted that the adhesion coefficient information generated and broadcast by the second vehicle may be calculated and broadcast in real time during the running of the second vehicle, or may be calculated and broadcast only when the second vehicle slips.

Since the adhesion coefficient information received by the first vehicle may be broadcast by roadside devices within a third predetermined distance of the square circle, it includes adhesion coefficient information that is independent of the route traveled by the first vehicle (e.g., the adhesion coefficient of the road that the first vehicle has traveled and the adhesion coefficient of the road that the first vehicle will not travel for a long period of time). Therefore, the received adhesion coefficient information can be screened according to the traveling route to obtain the adhesion coefficient of the target road surface position.

Through the technical scheme, the second Vehicle generates and broadcasts the adhesion coefficient to the road-side equipment based on the mode of the Vehicle and the road-side equipment (V2I), and the road-side equipment broadcasts the adhesion coefficient to the first Vehicle so that the first Vehicle can acquire the adhesion coefficient of the target position on the traveling route in advance. Based on the manner of the vehicle and the road side device, the maximum broadcast distance of the adhesion coefficient can be expanded, and the adhesion coefficient can be stored so that the first vehicle can receive the adhesion coefficient sent by the first vehicle before a long time.

and acquiring a plurality of pieces of adhesion coefficient information of a target road section according to the traveling route of the first vehicle, wherein the target road section is a road section which is in the traveling route of the first vehicle and has a distance to the first vehicle smaller than or equal to a first preset distance.

The target road surface position is in the target road section, the target road section comprises a plurality of road surface positions, and the target road surface position is one road surface position in the target road section. The plurality of adhesion coefficient information for the target road segment may be generated by a plurality of second vehicles.

And under the condition that the plurality of pieces of adhesion coefficient information comprise a plurality of adhesion coefficients smaller than a first threshold value, and the distance between the road surface positions corresponding to the plurality of adhesion coefficients smaller than the first threshold value is smaller than a fifth preset distance, determining a minimum adhesion coefficient in the plurality of adhesion coefficients smaller than the first threshold value, and taking the road surface position corresponding to the minimum adhesion coefficient as a target road surface position, wherein the minimum adhesion coefficient is the adhesion coefficient of the target road surface position.

The first threshold value is flexibly set according to conditions, such as easy slippage or slippage when the vehicle runs at a normal speed when the adhesion coefficient is smaller than the first threshold value. The fifth preset distance may be flexibly set according to a situation, for example, when the distance between the multiple road positions is smaller than the fifth preset distance, the multiple road positions are considered to be close to each other, and may be considered to be the same road position. With this step, when a plurality of adhesion coefficients smaller than the first threshold value correspond to a plurality of adjacent road surface positions, a road surface position corresponding to a minimum adhesion coefficient of the plurality of adhesion coefficients smaller than the first threshold value is set as the target road surface position, and the minimum adhesion coefficient is set as the adhesion coefficient of the target road surface position.

Therefore, with the above-described aspect, the adhesion coefficient defining the target road surface position is smaller than the first threshold value (i.e., the target road surface position may be defined as being easy to slip or the second vehicle has slipped), and is the minimum value of the adhesion coefficients smaller than the first threshold value transmitted by the plurality of second vehicles, so that the maximum braking force calculated from the minimum adhesion coefficient is minimum, and then the calculated vehicle speed limit is minimum, to ensure the safety of the automatic driving speed control according to the minimum vehicle speed limit.

Optionally, step S12 includes: and acquiring the product of the adhesion coefficient and the gravity of the first vehicle, and taking the difference of the product and the slope resistance as the maximum braking force.

That is, the maximum braking force can be calculated by the following equation:

F _BrkMax＝ μ*W-F _Slope

in the formula, F _BrkMax Represents the maximum braking force; μ represents an adhesion coefficient of the target road surface position; w represents the weight of the first vehicle; f _Slope Represents a ramp resistance, and when the target road surface position is not a ramp, the ramp resistance is 0.

Step S14 includes:

and acquiring the deceleration of the maximum braking force to the first vehicle according to the quotient of the maximum braking force and the mass of the first vehicle.

I.e. deceleration can be calculated by the following formula:

a＝F _BrkMax /M

in the formula, a represents deceleration; m represents the mass of the first vehicle.

That is, the vehicle speed limit may be calculated by the following equation:

v _max ＝(2*L/a) ^1/2

in the formula, v _max Represents a vehicle speed limit; l represents a safety braking distance.

Optionally, step S11 includes:

The attachment coefficient map can be stored in a cloud end and issued to the first vehicle by a server. Since the adhesion coefficient map stores the adhesion coefficient and the road surface position corresponding to the adhesion coefficient, the adhesion coefficient corresponding to the target road surface position stored in the adhesion coefficient map can be obtained from the target road surface position.

Through the technical scheme, the first vehicle can acquire the adhesion coefficient of the target road surface position in advance by adopting the mode of the adhesion coefficient map.

and aiming at each road surface position in the adhesion coefficient map, acquiring the adhesion coefficient of the road surface position uploaded by at least one vehicle within a first preset time period, and determining the minimum value in the adhesion coefficients as the adhesion coefficient corresponding to the road surface position.

The first preset time period may be preset, for example, may be set to 1 hour. Within 1 hour, there may be a plurality of vehicles (second vehicles) passing the road surface position, and the respective determined adhesion coefficients are uploaded to the server side. In order to ensure that a road surface position corresponds to one adhesion coefficient, a plurality of uploaded adhesion coefficients need to be screened. By this step, the minimum value of the plurality of adhesion coefficients is determined as the adhesion coefficient corresponding to the road surface position, the vehicle speed limit determined by the minimum adhesion coefficient is relatively minimum, and the safety of the automatic driving speed control based on the minimum vehicle speed limit is ensured.

And increasing the adhesion coefficient of the road surface position to the maximum historical adhesion coefficient of the road surface position gradually within a third time period under the condition that the adhesion coefficient of the road surface position uploaded by a vehicle is not received within a second preset time period after the adhesion coefficient corresponding to the road surface position is determined.

For example, after the adhesion coefficient is determined, since it takes a certain time for the adhesion coefficient of the road surface to change, the adhesion coefficient may be maintained until a new adhesion coefficient is determined. However, if the adhesion coefficient of the road surface position uploaded by the vehicle is not received for a long time (within the second time period), the subsequent passing vehicle may perform unnecessary measures (such as speed control) for skid prevention if the adhesion coefficient is not updated. Therefore, the second preset time period may be set, for example, to 1 hour. If the adhesion coefficient of the road surface position uploaded by the vehicle is not received within the second preset time period, the previously determined adhesion coefficient may be influenced by other factors and is not applicable any more, and the adhesion coefficient of the road surface position may be increased to the maximum historical adhesion coefficient of the road surface position within the third preset time period, so as to avoid unnecessary measures (such as speed control) of the following passing vehicles for skid prevention.

Optionally, the method further comprises: determining the third preset duration according to at least one of the following information:

the current area of the road surface position, the current weather information and the current season information.

For example, the third preset time period may be determined according to the current weather information. If the temperature of the current weather is high, the time required for the road surface to reach the maximum historical adhesion coefficient is short (namely the time required for the road surface to become dry is short), and the third set time length can be set to be a small value; if the temperature of the current weather is low and the time required for the road surface to reach the maximum historical adhesion coefficient is long, the third set time length can be set to be a large value. For another example, the third preset time period may also be determined according to current season information or a current region of the road position. For example, if the current season is winter or the area where the road surface is currently located is a cold area, and the time required for the road surface to reach its maximum historical adhesion coefficient is long, the third preset time period may be set to a large value. It should be noted that the third preset time period may be determined by one of the above information, or may be determined according to a plurality of the above information.

Optionally, the step of increasing the adhesion coefficient of the road surface position to the maximum historical adhesion coefficient of the road surface position within the third period of time includes:

a difference between the maximum historical adhesion coefficient and the current adhesion coefficient is determined.

And determining the change rate of the attachment coefficient according to the third preset time length and the difference value.

Gradually increasing the adhesion coefficient to the maximum historical adhesion coefficient according to the rate of change.

Through the technical scheme, the adhesion coefficient is gradually increased according to the determined change rate, and the stability of the change of the adhesion coefficient of the road surface position can be ensured.

It should be noted that the first vehicle may perform all the steps of the second vehicle.

Based on the technical concept, the embodiment of the disclosure further provides an automatic driving control device. FIG. 4 is a block diagram illustrating an automatic driving control apparatus according to an exemplary embodiment. Referring to fig. 4, the apparatus includes:

the adhesion coefficient acquiring module 11 is configured to acquire an adhesion coefficient of a target road surface position, where a distance between the target road surface position and the first vehicle on a first vehicle traveling route is smaller than or equal to a first preset distance.

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

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

A vehicle speed limit acquisition module 14 configured to acquire a vehicle speed limit of the first vehicle according to the maximum braking force and the safe braking distance.

An automatic driving control module 15 configured to control an automatic driving speed of the first vehicle such that a speed of the first vehicle when reaching a target road surface position does not exceed the vehicle speed limit.

When the adhesion coefficient of the target road surface position is smaller, the vehicle is easy to slip at the target road surface position when the vehicle speed is too high, through the technical scheme provided by the disclosure, the first vehicle obtains the adhesion coefficient of the target road surface position in advance, the vehicle speed limit value of the target road surface position is obtained through calculation, the automatic driving speed of the first vehicle is controlled in advance, the vehicle speed of the first vehicle reaching the target road surface position is not more than the vehicle speed limit value, so that the first vehicle is prevented from slipping at the target road surface position, the first vehicle can not exit from the automatic driving mode at the easy-to-slip target road surface position, the experience satisfaction degree of the driver on automatic/intelligent driving is improved, and the confidence of the driver on automatic driving/intelligent driving is increased.

Optionally, the adhesion coefficient obtaining module 11 includes:

a vehicle-to-vehicle communication sub-module configured to receive adhesion coefficient information generated and broadcast by a second vehicle.

The second vehicle is a vehicle with a distance from the first vehicle being smaller 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 smaller than the maximum broadcast distance of the second vehicle and smaller than the maximum receiving distance of the first vehicle.

And the first screening submodule is configured to acquire the adhesion coefficient of the target road surface position according to the travelling route of the first vehicle and the received adhesion coefficient information.

Through the technical scheme, the second Vehicle generates and broadcasts the adhesion coefficient to the first Vehicle based on a Vehicle-to-Vehicle (V2V) mode, so that the first Vehicle acquires the adhesion coefficient of the target position on the travelling route in advance.

Optionally, the adhesion coefficient obtaining module 11 includes:

and the vehicle-road side device communication sub-module is configured to receive the attachment coefficient information broadcast by the road side device.

And the first screening submodule is configured to acquire the adhesion coefficient of the target road position according to the travelling route of the first vehicle and the received adhesion coefficient information.

Optionally, the first filtering submodule is specifically configured to:

and acquiring a plurality of pieces of attachment coefficient information of a target road section according to the traveling route of the first vehicle, wherein the target road section is a road section which is in the traveling route of the first vehicle and has a distance to the first vehicle smaller than or equal to a first preset distance.

With the above arrangement, the adhesion coefficient defining the target road surface position is smaller than the first threshold value (i.e., the defining target road surface position may be easy to slip or the second vehicle may have slipped), and is the minimum value of the adhesion coefficients smaller than the first threshold value transmitted by the second vehicles, so that the maximum braking force calculated from the minimum adhesion coefficient is minimized, and the calculated vehicle speed limit is then minimized, to ensure the safety of the automatic driving speed control according to the minimum vehicle speed limit.

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

and acquiring the product of the adhesion coefficient and the gravity of the first vehicle, and taking the difference of the product and the slope resistance as the maximum braking force.

The vehicle speed limit acquisition module 14 is specifically configured to:

And acquiring a quotient of twice the safe braking distance divided by the deceleration, and taking the derivation of the quotient as the vehicle speed limit value.

Optionally, the attachment coefficient obtaining module 11 is specifically configured to:

Optionally, the apparatus further comprises:

and the adhesion coefficient map building module is configured to acquire the adhesion coefficient of the road position uploaded by at least one vehicle within a first preset time period for each road position in the adhesion coefficient map, and determine the minimum value of the adhesion coefficients as the adhesion coefficient corresponding to the road position.

And the adhesion coefficient map updating module is configured to gradually increase the adhesion coefficient of the road surface position to the maximum historical adhesion coefficient of the road surface position within a third time period under the condition that the adhesion coefficient of the road surface position uploaded by a vehicle is not received within a second preset time period after the adhesion coefficient corresponding to the road surface position is determined.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

The present disclosure also provides a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the autopilot control method provided by the present disclosure.

The apparatus may be a part of a stand-alone electronic device, for example, in an embodiment, the apparatus may be an Integrated Circuit (IC) or a chip, where the IC may be one IC or a collection of multiple ICs; the chip may include, but is not limited to, the following categories: a GPU (Graphics Processing Unit), a CPU (Central Processing Unit), an FPGA (Field Programmable Gate Array), a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an SOC (System on Chip, SOC, system on Chip, or System on Chip), and the like. The integrated circuit or chip may be configured to execute executable instructions (or code) to implement the autopilot control method described above. Where the executable instructions may be stored in the integrated circuit or chip or may be retrieved from another apparatus or device, for example where the integrated circuit or chip includes a second processor, a second memory, and an interface for communicating with the other apparatus. The executable instructions may be stored in the second memory, and when executed by the second processor, implement the above-described autopilot control method; alternatively, the integrated circuit or chip may receive the executable instructions through the interface and transmit the executable instructions to the second processor for execution, so as to implement the automatic driving control method.

Referring to fig. 5, fig. 5 is a functional block diagram of a vehicle 600 according to an exemplary embodiment. The vehicle 600 may be configured in a fully or partially autonomous driving mode. For example, the vehicle 600 may acquire environmental information of its surroundings through the sensing system 620 and derive an automatic driving strategy based on an analysis of the surrounding environmental information to implement full automatic driving, or present the analysis result to the user to implement partial automatic driving.

Vehicle 600 may include various subsystems such as infotainment system 610, perception system 620, decision control system 630, drive system 640, and computing platform 650. Alternatively, vehicle 600 may include more or fewer subsystems, and each subsystem may include multiple components. In addition, each of the sub-systems and components of the vehicle 600 may be interconnected by wire or wirelessly.

In some embodiments, the infotainment system 610 may include a communication system 611, an entertainment system 612, and a navigation system 613.

The communication system 611 may comprise a wireless communication system that may wirelessly communicate with one or more devices, either directly or via a communication network. For example, the wireless communication system may use 3G cellular communication, such as CDMA, EVD0, GSM/GPRS, or 4G cellular communication, such as LTE. Or 5G cellular communication. The wireless communication system may communicate with a Wireless Local Area Network (WLAN) using WiFi. In some embodiments, the wireless communication system may communicate directly with the device using an infrared link, bluetooth, or ZigBee. Other wireless protocols, such as various vehicular communication systems, for example, a wireless communication system may include one or more Dedicated Short Range Communications (DSRC) devices that may include public and/or private data communications between vehicles and/or roadside stations.

The entertainment system 612 may include a display device, a microphone, and a sound box, and a user may listen to a broadcast in the car based on the entertainment system, playing music; or the mobile phone is communicated with the vehicle, screen projection of the mobile phone is realized on the display equipment, the display equipment can be in a touch control type, and a user can operate the display equipment by touching the screen.

In some cases, the voice signal of the user may be captured by a microphone, and certain control of the vehicle 600 by the user, such as adjusting the temperature in the vehicle, etc., may be implemented according to the analysis of the voice signal of the user. In other cases, music may be played to the user through a stereo.

The navigation system 613 may include a map service provided by a map provider to provide navigation of a route of travel for the vehicle 600, and the navigation system 613 may be used in conjunction with a global positioning system 621 and an inertial measurement unit 622 of the vehicle. The map service provided by the map provider can be a two-dimensional map or a high-precision map.

The sensing system 620 may include several types of sensors that sense information about the environment surrounding the vehicle 600. For example, the sensing system 620 may include a global positioning system 621 (the global positioning system may be a GPS system, a beidou system or other positioning system), an Inertial Measurement Unit (IMU) 622, a laser radar 623, a millimeter wave radar 624, an ultrasonic radar 625, and a camera 626. The sensing system 620 may also include sensors of internal systems of the monitored vehicle 600 (e.g., an in-vehicle air quality monitor, a fuel gauge, an oil temperature gauge, etc.). Sensor data from one or more of these sensors may be used to detect the object and its corresponding characteristics (position, shape, orientation, velocity, etc.). Such detection and identification is a critical function of the safe operation of the vehicle 600.

Global positioning system 621 is used to estimate the geographic location of vehicle 600.

The inertial measurement unit 622 is used to sense a pose change of the vehicle 600 based on the inertial acceleration. In some embodiments, inertial measurement unit 622 may be a combination of accelerometers and gyroscopes.

Lidar 623 utilizes laser light to sense objects in the environment in which vehicle 600 is located. In some embodiments, lidar 623 may include one or more laser sources, laser scanners, and one or more detectors, among other system components.

The millimeter-wave radar 624 utilizes 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 may also be used to sense the speed and/or heading of objects.

The ultrasonic radar 625 may sense objects around the vehicle 600 using ultrasonic signals.

The camera 626 is used to capture image information of the surroundings of the vehicle 600. The image capturing device 626 may include a monocular camera, a binocular camera, a structured light camera, a panoramic camera, and the like, and the image information acquired by the image capturing device 626 may include still images or video stream information.

Decision control system 630 includes a computing system 631 that makes analytical decisions based on information acquired by sensing system 620, decision control system 630 further includes a vehicle control unit 632 that controls the powertrain of vehicle 600, and a steering system 633, throttle 634, and brake system 635 for controlling vehicle 600.

The computing system 631 may operate to process and analyze the various information acquired by the perception system 620 to identify objects, and/or features in the environment surrounding the vehicle 600. The target may comprise a pedestrian or an animal and the objects and/or features may comprise traffic signals, road boundaries and obstacles. The computing system 631 may use object recognition algorithms, motion from Motion (SFM) algorithms, video tracking, and the like. In some embodiments, the computing system 631 may be used to map an environment, track objects, estimate the speed of objects, and so forth. The computing system 631 may analyze the various information obtained and derive a control strategy for the vehicle.

The vehicle controller 632 may be used to perform coordinated control on the power battery and the engine 641 of the vehicle to improve the power performance of the vehicle 600.

Steering system 633 is operable to adjust the heading of vehicle 600. For example, in one embodiment, a steering wheel system.

The throttle 634 is used to control the operating speed of the engine 641 and thus the speed of the vehicle 600.

The brake system 635 is used to control the deceleration of the vehicle 600. The braking system 635 may use friction to slow the wheel 644. In some embodiments, the braking system 635 may convert kinetic energy of the wheels 644 to electrical current. The braking system 635 may also take other forms to slow the rotational speed of the wheels 644 to control the speed of the vehicle 600.

The drive system 640 may include components that provide powered motion to the vehicle 600. In one embodiment, the drive system 640 may include an engine 641, an energy source 642, a transmission 643, and wheels 644. The engine 641 may be an internal combustion engine, an electric motor, an air compression engine, or other types of engine combinations, such as a hybrid engine consisting of a gasoline engine and an electric motor, a hybrid engine consisting of an internal combustion engine and an air compression engine. The engine 641 converts the energy source 642 into mechanical energy.

Examples of energy sources 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 may also provide energy to other systems of the vehicle 600.

The transmission 643 may transmit mechanical power from the engine 641 to the wheels 644. The transmission 643 may include a gearbox, a differential, and a drive shaft. In one embodiment, the transmission 643 may also include other devices, such as clutches. Wherein the drive shaft may include one or more axles that may be coupled to one or more wheels 644.

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

The first processor 651 may be any conventional processor, such as a commercially available CPU. Alternatively, the first processor 651 may also include a processor such as a Graphics Processor Unit (GPU), a Field Programmable Gate Array (FPGA), a System On Chip (SOC), an Application Specific Integrated Circuit (ASIC), or a combination thereof. Although fig. 5 functionally illustrates a processor, memory, and other elements of a computer in the same block, those skilled in the art will appreciate that the processor, computer, or memory may actually comprise multiple processors, computers, or memories that may or may not be stored within the same physical housing. For example, the memory may be a hard drive or other storage medium located in a different enclosure than the computer. Thus, references to a processor or computer are to be understood as including references to a collection of processors or computers or memories which may or may not operate in parallel. Rather than using a single processor to perform the steps described herein, some of the components, such as the steering and deceleration components, may each have their own processor that performs only computations related to the component-specific functions.

In the disclosed embodiment, the first processor 651 may perform the above-described automatic driving control method.

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

In some embodiments, the first memory 652 can contain instructions 653 (e.g., program logic), which instructions 653 can be executed by the first processor 651 to perform various functions of the vehicle 600. The first memory 652 may also contain 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.

In addition to instructions 653, first memory 652 may also store data such as road maps, route information, the location, direction, speed, and other such vehicle data of the vehicle, as well as other information. Such information may 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.

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

Optionally, one or more of these components described above may be mounted separately from or associated with the vehicle 600. For example, the first memory 652 may exist partially or completely separate from the vehicle 600. The aforementioned components may be communicatively coupled together in a wired and/or wireless manner.

Optionally, the above components are only an example, in an actual application, components in the above modules may be added or deleted according to an actual need, and fig. 5 should not be construed as limiting the embodiment of the present disclosure.

An autonomous automobile traveling on a roadway, such as vehicle 600 above, may identify objects within its surrounding environment to determine an adjustment to the current speed. The object may be another vehicle, a traffic control device, or another type of object. In some examples, each identified object may be considered independently, and based on the respective characteristics of the object, such as its current speed, acceleration, separation from the vehicle, etc., may be used to determine the speed at which the autonomous vehicle is to be adjusted.

Optionally, the vehicle 600 or a sensory and computing device associated with the vehicle 600 (e.g., computing system 631, computing platform 650) may predict behavior of the identified object based on characteristics of the identified object and the state of the surrounding environment (e.g., traffic, rain, ice on the road, etc.). Optionally, each identified object depends on the behavior of each other, so it is also possible to predict the behavior of a single identified object taking all identified objects together into account. The vehicle 600 is able to adjust its speed based on the predicted behavior of the identified object. In other words, the autonomous vehicle is able to 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. In this process, other factors may also be considered to determine the speed of the vehicle 600, such as the lateral position of the vehicle 600 in the road being traveled, the curvature of the road, the proximity of static and dynamic objects, and so forth.

In addition to providing instructions to adjust the speed of the autonomous vehicle, the computing device may 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 in the vicinity of the autonomous vehicle (e.g., vehicles in adjacent lanes on the road).

The vehicle 600 may be any type of vehicle, such as a car, a truck, a motorcycle, a bus, a boat, an airplane, a helicopter, a recreational vehicle, a train, etc., and the embodiment of the present disclosure is not particularly limited.

In another exemplary embodiment, a computer program product is also provided, which comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-described autopilot control method when executed by the programmable apparatus.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An automatic driving control method, characterized in that the method comprises:

2. The automatic driving control method according to claim 1, wherein the acquiring the adhesion coefficient of the target road surface position includes:

3. The automatic driving control method according to claim 1, wherein the acquiring the adhesion coefficient of the target road surface position includes:

4. The automatic driving control method according to claim 2 or 3, wherein the obtaining of the adhesion coefficient of the target road surface position based on the travel path of the first vehicle and the received adhesion coefficient information includes:

acquiring a plurality of pieces of attachment coefficient information of a target road section according to the traveling route of the first vehicle, wherein the target road section is a road section which is in the traveling route of the first vehicle and has a distance to the first vehicle smaller than or equal to a first preset distance;

5. The automatic driving control method according to claim 4, wherein the determining the maximum braking force of the first vehicle at a target road surface position according to the adhesion coefficient includes: acquiring a product of the adhesion coefficient and the gravity of the first vehicle, and taking a difference of the product minus the ramp resistance as a maximum braking force;

the step of obtaining the vehicle speed limit value of the first vehicle according to the maximum braking force and the safe braking distance comprises the following steps:

acquiring deceleration of the first vehicle by the maximum braking force according to the quotient of the maximum braking force and the mass of the first vehicle;

6. The automatic driving control method according to claim 1, wherein the acquiring the adhesion coefficient of the target road surface position includes:

7. The autonomous driving control method of claim 6, further comprising building the adhesion coefficient map by:

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

8. An automatic driving control apparatus, characterized by comprising:

an adhesion coefficient acquisition module configured to acquire an adhesion coefficient of a target road surface position, the target road surface position being a distance from a first vehicle on a first vehicle travel route that is less than or equal to a first preset distance;

9. A vehicle, characterized by comprising:

a first processor;

a first memory for storing first processor-executable instructions;

wherein the first processor is configured to:

acquiring a vehicle speed limit value of the first vehicle according to the maximum braking force and the safe braking distance;

10. A computer-readable storage medium, on which computer program instructions are stored, which program instructions, when executed by a processor, carry out the steps of the method according to any one of claims 1 to 7.

11. A chip comprising a second processor and an interface; the second processor is to read instructions to perform the method of any one of claims 1-7.