CN119705456B - Vehicle driving control method, device, vehicle computer and vehicle - Google Patents

Abstract

The invention relates to the technical field of automatic driving or auxiliary driving, in particular to a vehicle driving control method, a device, a vehicle machine and a vehicle, wherein before a yellow lamp is extinguished, whether the vehicle can park comfortably or not before the next crossing needing to pass can be determined by acquiring the current speed and the current position of the vehicle; when the vehicle cannot park comfortably before the next crossing needing to pass, road condition information and geometric information of the next crossing needing to pass are obtained, so that the theoretical risk degree of the vehicle entering the crossing can be determined, and whether the vehicle needs to park or not is determined according to the theoretical risk degree. Therefore, the driving strategy of the vehicle at the next crossing needing to pass can be more reasonably determined, and the safety is higher.

Description

Vehicle driving control method and device, vehicle machine and vehicle

Technical Field

The invention relates to the technical field of automatic driving or auxiliary driving, in particular to a vehicle driving control method and device, a vehicle machine and a vehicle.

Background

At present, in the automatic driving of SAE-L3 and above, various traffic lights often appear in the process of passing through the intersection, such as color, combination and the like.

According to the requirements of traffic regulations, traffic can be passed under the conditions of red light stop, green light running and yellow light safety, but most of traffic needs to be decelerated and stopped. In general, the yellow light needs to last for 3s, i.e. the green light changes to yellow light, and the yellow light changes to red light after flashing for 3 s.

A common technique in automatic driving is to calculate the required deceleration for stopping, and if the required deceleration is lower than the maximum deceleration, a stopping decision is performed. This approach is considered single and often results in a cancellation of the stop or a line crossing after the stop due to a delay in deceleration following. This solution is lacking in both safety and rationality.

Disclosure of Invention

In view of the above, the present invention provides a vehicle driving control method, device, machine and vehicle, so as to solve the problem that the current vehicle control method is deficient in safety and rationality when the traffic light crossing passes through.

According to the first aspect, the invention provides a vehicle driving control method, which comprises the steps of obtaining the current speed and the current position of a vehicle before a yellow light is turned off, determining whether the vehicle can park comfortably before the next crossing needing to pass according to the current speed and the current position of the vehicle, obtaining road condition information and geometric information of the next crossing needing to pass when the vehicle cannot park comfortably before the next crossing needing to pass, determining the theoretical risk degree of the vehicle entering the crossing according to the geometric information and the road condition information by using a fuzzy control method, and determining whether the vehicle needs to park according to the theoretical risk degree.

The vehicle driving control method provided by the invention can determine whether the vehicle can park comfortably before the next crossing needing to pass or not by acquiring the current speed and the current position of the vehicle, and can determine the theoretical risk degree of the vehicle entering the crossing and determine whether the vehicle needs to park according to the theoretical risk degree when the vehicle cannot park comfortably before the next crossing needing to pass and the road condition information and the geometric information of the next crossing needing to pass. Therefore, the driving strategy of the vehicle at the next crossing needing to pass can be more reasonably determined, and the safety is higher.

In an alternative embodiment, determining whether the vehicle can park comfortably before the next intersection to be travelled according to the current speed and the current position of the vehicle comprises obtaining map information, determining the actual parking distance from the current position to the intersection according to the current position of the vehicle and the map information, obtaining comfortable parking deceleration of the vehicle, determining a theoretical parking distance according to the current speed and the comfortable parking deceleration of the vehicle, determining that the vehicle cannot park comfortably before the next intersection to be travelled when the theoretical parking distance is greater than the actual parking distance, and determining that the vehicle can park comfortably before the next intersection to be travelled when the theoretical parking distance is less than or equal to the actual parking distance, and controlling the vehicle to park.

Therefore, whether the vehicle can park comfortably or not before the next crossing needing to pass can be quickly and accurately determined.

In an alternative embodiment, determining the risk of the vehicle entering the intersection by using a fuzzy control method according to the geometric information and the road condition information comprises determining the road risk of the vehicle entering the intersection by using a preset first fuzzy control algorithm according to the geometric information, determining the vehicle condition risk of the vehicle entering the intersection by using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information, and weighting the road risk and the vehicle condition risk to obtain the theoretical risk of the vehicle entering the intersection.

The road risk degree and the vehicle condition risk degree are weighted and calculated, so that the determined theoretical risk degree is more reasonable, and further, the driving habits of different people can be met by adjusting the weight coefficients of the road risk degree and the vehicle condition risk degree.

In an alternative embodiment, the geometric information comprises an intersection length and an intersection width, and determining the road risk degree of the vehicle entering the intersection by utilizing a preset first fuzzy control algorithm according to the geometric information of the intersection comprises the steps of carrying out fuzzy processing on the intersection length and the intersection width, processing the intersection length and the intersection width after the fuzzy processing by utilizing a preset first fuzzy rule to obtain a first output value, and deblurring the first output value to obtain the road risk degree of the vehicle entering the intersection.

The first fuzzy control algorithm can be used for determining the road risk degree of the vehicle entering the intersection.

In an alternative embodiment, determining the risk of the vehicle entering the intersection by using a preset second fuzzy control algorithm according to the current speed and the road condition information of the vehicle comprises the steps of carrying out fuzzification on the current speed and the road condition information of the vehicle, processing the current speed and the road condition information of the vehicle after the fuzzification by using a preset second fuzzy rule to obtain a second output value, and defuzzifying the second output value to obtain the risk of the vehicle entering the intersection.

Therefore, the risk of the vehicle entering the intersection can be determined by using the second fuzzy control algorithm.

In an alternative embodiment, determining whether the vehicle needs to be parked according to the theoretical risk degree comprises obtaining a preset risk degree threshold value, and judging that the vehicle needs to be parked when the theoretical risk degree is greater than the risk degree threshold value.

Thus, the vehicle driving control method can be safer.

In an alternative embodiment, the vehicle driving control method further comprises the step of controlling the vehicle to stop when the vehicle can be parked comfortably before the next intersection requiring passage.

Therefore, when the vehicle can park comfortably before the next crossing needing to pass, the vehicle is controlled to park, so that the vehicle driving control method is safer.

The invention further provides a vehicle driving control device, which comprises a first acquisition module, a first judgment module, a second acquisition module, a theoretical risk degree determination module and a second judgment module, wherein the first acquisition module is used for acquiring the current speed and the current position of a vehicle before a yellow light is extinguished, the first judgment module is used for determining whether the vehicle can park comfortably before the next crossing needing to pass according to the current speed and the current position of the vehicle, the second acquisition module is used for acquiring road condition information and geometric information of the next crossing needing to pass when the vehicle cannot park comfortably before the next crossing needing to pass, the theoretical risk degree determination module is used for determining the theoretical risk degree of the vehicle entering the crossing according to the geometric information and the road condition information by using a fuzzy control method, and the second judgment module is used for determining whether the vehicle needs to park according to the theoretical risk degree.

In a third aspect, the present invention further provides a vehicle machine, including a memory and a processor, where the memory and the processor are communicatively connected to each other, and the memory stores computer instructions, and the processor executes the computer instructions, so as to execute the vehicle driving control method according to the first aspect or any embodiment corresponding to the first aspect.

In a fourth aspect, the present invention also provides a vehicle, including the vehicle machine of the third aspect.

In a fifth aspect, the present invention also provides a computer-readable storage medium having stored thereon computer instructions for causing a computer to execute the vehicle driving control method of the first aspect or any one of the embodiments corresponding thereto.

In a sixth aspect, the present invention also provides a computer program product comprising computer instructions for causing a computer to perform the vehicle driving control method of the first aspect or any of its corresponding embodiments.

The vehicle driving control method, the device, the vehicle machine and the vehicle have the advantages that before the yellow light is extinguished, whether the vehicle can park comfortably before the next crossing needing to pass or not can be determined by acquiring the current speed and the current position of the vehicle, and when the vehicle cannot park comfortably before the next crossing needing to pass, road condition information and geometric information of the next crossing needing to pass are acquired, so that the theoretical risk degree of the vehicle entering the crossing can be determined, and whether the vehicle needs to park or not is determined according to the theoretical risk degree. Therefore, the driving strategy of the vehicle at the next crossing needing to pass can be more reasonably determined, and the safety is higher.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a vehicle drive control method according to an embodiment of the present invention;

FIG. 2 is a conceptual block diagram of a fuzzy controller;

FIG. 3 is a logic block diagram of a fuzzy controller;

FIG. 4 is a flow chart of another vehicle drive control method according to an embodiment of the invention;

FIG. 5 is a schematic illustration of an intersection length and intersection width in accordance with an embodiment of the present invention;

FIG. 6 is a graph of a fuzzy subset of intersection lengths in accordance with an embodiment of the present invention;

FIG. 7 is a graph of a fuzzy subset of intersection widths, according to an embodiment of the present invention;

FIG. 8 is a map of a fuzzy subset of road risk according to an embodiment of the present invention;

FIG. 9 is a rule-based calculation of risk rules according to an embodiment of the invention;

FIG. 10 is a schematic diagram of mapping membership to risk according to a first fuzzy rule in accordance with an embodiment of the present invention;

FIG. 11 is a fuzzy subset map of vehicle speed in accordance with an embodiment of the present invention;

FIG. 12 is a fuzzy subset map of road conditions in accordance with an embodiment of the present invention;

FIG. 13 is a graph of a fuzzy subset of vehicle condition risk levels in accordance with an embodiment of the present invention;

FIG. 14 is a rule-based calculation of risk rules in accordance with an embodiment of the present invention;

FIG. 15 is a diagram of mapping membership to risk according to a second fuzzy rule in accordance with an embodiment of the present invention;

FIG. 16 is a flowchart of yet another vehicle driving control method according to an embodiment of the invention;

FIG. 17 is a vehicle chassis information traffic block diagram according to an embodiment of the present invention;

fig. 18 is a block diagram of a structure of a vehicle driving control apparatus according to an embodiment of the invention;

Fig. 19 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

According to an embodiment of the present invention, there is provided a vehicle driving control method embodiment, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order other than that shown or described herein.

In the present embodiment, a vehicle driving control method is provided, which can be used for a computer device, such as a vehicle machine. Fig. 1 is a flowchart of a vehicle driving control method according to an embodiment of the present invention, as shown in fig. 1, the flowchart including the steps of:

step S101, before the yellow lamp is extinguished, the current speed and the current position of the vehicle are obtained.

According to the requirements of traffic regulations, the traffic light can pass under the condition of safety when the traffic light is yellow, and the traffic light needs to last for 3s, namely, the green light turns into the traffic light, and the traffic light turns into the red light after flashing for 3 s.

Specifically, the current speed of the vehicle is mainly used for determining the time required for passing through the intersection, so that the risk of passing through the intersection is estimated, and the risk can be obtained from CANbus. The current position of the vehicle is obtained in a positioning module of the vehicle.

Step S102, determining whether the vehicle can park comfortably before the next crossing needing to pass according to the current speed and the current position of the vehicle.

In the present embodiment, the comfortable parking may be understood as parking in accordance with a comfortable parking deceleration set in the vehicle.

Step S103, when the vehicle cannot park comfortably before the next crossing needing to pass, road condition information and geometric information of the next crossing needing to pass are obtained.

Specifically, the road condition information can be obtained through a perception sensor, a laser radar, a camera and the like. Geometric information of the intersection can be acquired in the map.

And step S104, determining the theoretical risk degree of the vehicle entering the intersection by utilizing a fuzzy control method according to the geometric information and the road condition information.

Fuzzy logic Control (Fuzzy Logic Control) is abbreviated as Fuzzy Control (Fuzzy Control), which is a computer numerical Control technology based on Fuzzy set theory, fuzzy linguistic variables and Fuzzy logic reasoning. Fuzzy control is essentially a nonlinear control, belonging to the category of intelligent control.

Fig. 2 is a conceptual block diagram of a fuzzy controller, and fig. 3 is a logical block diagram of the fuzzy controller, as shown in fig. 2 and 3, the fuzzy controller includes four parts:

(1) Blurring. The method mainly aims at selecting the input quantity of the fuzzy controller and converting the input quantity into the identifiable fuzzy quantity of the system, and specifically comprises the following three steps:

First, the input amount is processed to satisfy the fuzzy control demand.

Second, the input is scaled. In fuzzy control, scaling of the input is an important preprocessing step. This process is mainly used for converting the actual input variables into a range suitable for fuzzy logic processing, thereby improving the accuracy and efficiency of the system. Scaling generally involves normalization and normalization;

Thirdly, determining the fuzzy language value and the corresponding membership function of each input quantity. Membership functions are a core concept in fuzzy logic and fuzzy set theory. It is used to describe the degree to which an element belongs to a fuzzy set and is typically represented by a value between 0 and 1. Membership functions provide a way to quantify ambiguity, making it more flexible and natural in handling uncertainty and imprecise information.

(2) Rule base. And establishing a fuzzy rule base according to the experience of human expert. The fuzzy rule base contains a plurality of control rules, and is a key step for transitioning from actual control experience to a fuzzy controller.

(3) Fuzzy reasoning. Mainly realizes the reasoning decision based on knowledge.

(4) And (5) deblurring. The main function is to convert the control quantity obtained by reasoning into control output.

And step 105, determining whether the vehicle needs to be parked according to the theoretical risk degree.

According to the vehicle driving control method, before the yellow light is extinguished, whether the vehicle can park comfortably before the next crossing needing to pass or not can be determined by acquiring the current speed and the current position of the vehicle, and when the vehicle cannot park comfortably before the next crossing needing to pass, road condition information and geometric information of the next crossing needing to pass are acquired, so that theoretical risk degree of the vehicle entering the crossing can be determined, and whether the vehicle needs to park or not is determined according to the theoretical risk degree. Therefore, the driving strategy of the vehicle at the next crossing needing to pass can be more reasonably determined, and the safety is higher. In automatic driving or assisted driving, one scene which is difficult to process is that a vehicle does not enter an intersection, but the traffic light color corresponding to the current traffic is changed from a green light to a yellow light, and the driving strategy can be safely and reasonably determined by adopting the vehicle driving control method provided by the embodiment.

In the present embodiment, a vehicle driving control method is provided, which can be used for a computer device, such as a vehicle machine. Fig. 4 is a flowchart of another vehicle driving control method according to an embodiment of the present invention, as shown in fig. 4, the flowchart including the steps of:

step S401, before the yellow lamp is extinguished, the current speed and the current position of the vehicle are obtained.

Step S402, determining whether the vehicle can park comfortably before the next crossing needing to pass according to the current speed and the current position of the vehicle.

And S403, determining the theoretical risk degree of the vehicle entering the intersection by using a fuzzy control method according to the geometric information and the road condition information.

In an alternative embodiment, determining the theoretical risk of the vehicle entering the intersection by using the fuzzy control method according to the geometric information and the road condition information includes the following steps S4031 to S4033.

And step S4031, determining the road risk degree of the vehicle entering the intersection by using a preset first fuzzy control algorithm according to the geometric information.

Specifically, determining the road risk degree of the vehicle entering the intersection by using a preset first fuzzy control algorithm according to the geometric information includes the following steps SA 1-SA 3.

And step SA1, blurring the intersection length and the intersection width.

And step SA2, processing the intersection length and the intersection width after the blurring processing by using a preset first blurring rule to obtain a first output value.

And step SA3, deblurring the first output value to obtain the road risk degree of the vehicle entering the intersection.

For example, as shown in fig. 5, assuming that the intersection length l=65 and the width w=45, the road risk degree is calculated as follows:

(1) Setting triangle membership functions, wherein the fuzzy subsets defining the intersection length are [ long (LL), medium (LM) and short (LS) ] as shown in figure 6, the fuzzy subsets defining the intersection width are [ far (WF), medium (WM) and near (WN) ] as shown in figure 7, and the fuzzy subsets of the road risk degree are Very High (VH), high (H), medium (M), low (L) and Very Low (VL) as shown in figure 8, and the input and output distribution rules are defined according to the triangle membership function method.

(2) And calculating membership according to the length and width values. For example, LS (65) =0, lm (65) =0.7, ll (65) =0.3, wf (45) =0.1, wm (45) =0.9, and wn (45) =0.

(3) The fuzzy rules are set, namely the longer the crossing, the higher the passing risk, the shorter the crossing, the lower the passing risk, the larger the width, the lower the risk, the smaller the width and the higher the risk, so that 9 control rules can be obtained according to the two fuzzy subsets of the crossing length and width, as shown in fig. 9.

(4) Fuzzy reasoning, namely calculating the total output according to the membership degree and the Mamdani algorithm, as shown in fig. 10.

U_w=30, u_l=45, where u_w represents the risk degree of the intersection width, and u_l represents the risk degree of the intersection length.

(5) And (4) sharpening, namely sharpening the total output into road risk degree according to a mean value method.

u1=(30+45)/2=37.5。

And step S4032, determining the vehicle condition risk degree of the vehicle entering the intersection by utilizing a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information.

Specifically, determining the risk of the vehicle entering the intersection by using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information comprises the following steps SB 1-SB 3.

Step SB1, blurring the current speed of the vehicle and road condition information;

step SB2, processing the current speed of the vehicle after the blurring processing and road condition information by using a preset second blurring rule to obtain a second output value;

and step SB3, deblurring the second output value to obtain the risk degree of the vehicle condition of the vehicle entering the intersection.

For example, determining the risk of the vehicle entering the intersection by using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information comprises the following steps:

(1) Setting a triangle membership function, wherein the fuzzy subset of the vehicle speed is defined as [ fast (SF), medium (SM) and slow (SS) ] as shown in fig. 11, the fuzzy subset of the road condition is defined as [ good (FG), medium (FM) and poor (FB) ] as shown in fig. 12, and the fuzzy subset of the vehicle condition risk degree is defined as [ Very High (VH), high (H), medium (M), low (L) and Very Low (VL) ] as shown in fig. 13, and the distribution rules of input and output are defined according to the membership function method of the triangle.

(2) And calculating the membership degree according to the vehicle speed and the quantity value of the front vehicle.

(3) The fuzzy rules are set, namely, the higher the vehicle speed is, the lower the passing risk is, the higher the passing risk is, the worse the road condition is, the higher the risk is, the better the road condition is, and the higher the risk is, so that 9 control rules can be obtained according to the two fuzzy subsets, as shown in fig. 14.

(4) Similarly to the road risk degree, the vehicle condition risk degree u2 may be calculated as shown in fig. 15.

For example, the risk threshold may be set to be T, the road risk weight coefficient is α, the vehicle condition risk weight coefficient is β, and the decision information of whether the scene continues to pass through the intersection is output by comparing the result of αxu1+βxu2 > T. In the application process of the real vehicle, the specific gravity of the driver to the risk assessment can be met by adjusting different weight coefficients. So that it is more suitable for human driving habit.

And step S4033, weighting the road risk degree and the vehicle condition risk degree to obtain the theoretical risk degree of the vehicle entering the intersection.

And step S404, determining whether the vehicle needs to stop according to the theoretical risk degree.

In an alternative embodiment, determining whether the vehicle needs to be parked according to the theoretical risk level includes the following steps S4041 to S4042.

Step S4041, acquiring a preset risk threshold;

And step S4042, when the theoretical risk degree is greater than the risk degree threshold, judging that the vehicle needs to be parked.

Specifically, when the theoretical risk degree is less than or equal to the risk degree threshold, judging that the vehicle can pass through.

The vehicle driving control method provided by the embodiment not only can reasonably determine the driving strategy of the vehicle at the next crossing needing to pass, but also can carry out weighted calculation on the road risk degree and the vehicle condition risk degree, so that the determined theoretical risk degree is more reasonable, and further, the driving habit of different crowds can be more met by adjusting the weight coefficient of the road risk degree and the vehicle condition risk degree.

In the present embodiment, a vehicle driving control method is provided, which can be used for a computer device, such as a vehicle machine. Fig. 16 is a flowchart of still another vehicle driving control method according to an embodiment of the present invention, as shown in fig. 16, the flowchart including the steps of:

Step S1601, before the yellow light is turned off, the current speed and the current position of the vehicle are acquired.

As above, the current speed of the vehicle is mainly used to determine the time required to pass through an intersection, so as to evaluate the risk of passing through the intersection, and can be obtained from CANbus. The current position of the vehicle is obtained in a positioning module of the vehicle. For example, as shown in FIG. 17, the current speed of the vehicle may also be obtained in the positioning module.

Step S1602, obtaining map information.

Step S1603, determining the actual parking distance from the current position to the intersection according to the current position of the vehicle and the map information.

Step S1604, obtaining a comfortable parking deceleration of the vehicle.

Step S1605, determining a theoretical stopping distance according to the current speed of the vehicle and the comfortable stopping deceleration.

Step S1606, judging whether the theoretical parking distance is larger than the actual parking distance, when the theoretical parking distance is larger than the actual parking distance, judging that the vehicle cannot park comfortably before the next crossing needing to pass, and turning to step S1607, otherwise, the vehicle can park comfortably before the next crossing needing to pass, and turning to step S1610.

That is, when the theoretical parking distance is greater than the actual parking distance, parking is performed.

Step S1607, obtaining road condition information and geometric information of the next crossing to be passed.

And step S1608, determining the theoretical risk degree of the vehicle entering the intersection by utilizing a fuzzy control method according to the geometric information and the road condition information.

Step S1609, determining whether the vehicle needs to stop according to the theoretical risk degree.

Step S1610, controlling the vehicle to stop.

The vehicle driving control method provided by the embodiment can reasonably determine the driving strategy of the vehicle at the next crossing needing to pass.

In this embodiment, a vehicle driving control device is further provided, and the device is used to implement the foregoing embodiments and preferred embodiments, and will not be described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

The present embodiment provides a vehicle driving control apparatus, as shown in fig. 18, including:

The first acquiring module 1801 is configured to acquire a current speed and a current position of the vehicle before the yellow light is turned off.

A first determining module 1802 is configured to determine whether the vehicle can park comfortably before the next intersection to be passed according to the current speed and the current position of the vehicle.

The second obtaining module 1803 is configured to obtain road condition information and geometric information of the next intersection to be passed when the vehicle cannot be parked comfortably before the next intersection to be passed.

The theoretical risk degree determining module 1804 is configured to determine a theoretical risk degree of the vehicle entering the intersection according to the geometric information and the road condition information by using a fuzzy control method.

A second determining module 1805 is configured to determine whether the vehicle needs to be parked according to the theoretical risk.

In some alternative embodiments, the first determining module 1802 is specifically configured to obtain map information, determine an actual parking distance from a current position to an intersection of the vehicle according to the current position of the vehicle and the map information, obtain a comfortable parking deceleration of the vehicle, determine a theoretical parking distance according to a current speed and the comfortable parking deceleration of the vehicle, determine that the vehicle cannot park comfortably before the intersection that needs to be passed next when the theoretical parking distance is greater than the actual parking distance, determine that the vehicle can park comfortably before the intersection that needs to be passed next when the theoretical parking distance is less than or equal to the actual parking distance, and control the vehicle to park.

In some alternative embodiments, the theoretical risk level determination module 1804 is specifically configured to determine a road risk level of the vehicle entering the intersection according to the geometric information by using a preset first fuzzy control algorithm, determine a vehicle condition risk level of the vehicle entering the intersection according to the current speed of the vehicle and the road condition information by using a preset second fuzzy control algorithm, and weight the road risk level and the vehicle condition risk level to obtain the theoretical risk level of the vehicle entering the intersection.

In some alternative embodiments, the theoretical risk level determination module 1804 includes a road risk level determination unit, a vehicle condition risk level determination unit, and a weighting unit. The road risk degree determining unit is used for carrying out fuzzification on the intersection length and the intersection width, processing the intersection length and the intersection width after the fuzzification by using a preset first fuzzy rule to obtain a first output value, and defuzzifying the first output value to obtain the road risk degree of the vehicle entering the intersection.

In some optional embodiments, the vehicle condition risk degree determining unit is configured to perform a blurring process on the current speed of the vehicle and the road condition information, process the current speed of the vehicle and the road condition information after the blurring process by using a preset second blurring rule to obtain a second output value, and deblur the second output value to obtain a vehicle condition risk degree of the vehicle entering the intersection.

In some optional embodiments, the second determining module 1805 is specifically configured to obtain a preset risk threshold, and determine that the vehicle needs to stop when the theoretical risk is greater than the risk threshold.

Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.

The vehicle driving control apparatus in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application SPECIFIC INTEGRATED Circuit) Circuit, a processor and a memory that execute one or more software or a fixed program, and/or other devices that can provide the above functions.

The embodiment of the invention also provides a vehicle machine, which is provided with the vehicle driving control device shown in the figure 18.

The embodiment of the invention also provides a vehicle, which comprises the vehicle machine.

Referring to fig. 19, fig. 19 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, and as shown in fig. 19, the computer device includes one or more processors 10, a memory 20, and interfaces for connecting the components, including a high-speed interface and a low-speed interface. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 19.

The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.

Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform a method for implementing the embodiments described above.

The memory 20 may include a storage program area that may store an operating system, application programs required for at least one function, and a storage data area that may store data created according to the use of the computer device, etc. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The memory 20 may comprise volatile memory, such as random access memory, or nonvolatile memory, such as flash memory, hard disk or solid state disk, or the memory 20 may comprise a combination of the above types of memory.

The computer device further comprises input means 30 and output means 40. The processor 10, memory 20, input device 30, and output device 40 may be connected by a bus or other means, for example in fig. 19.

The input device 30 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the computer apparatus, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointer stick, one or more mouse buttons, a trackball, a joystick, and the like. The output means 40 may include a display device, auxiliary lighting means (e.g., LEDs), tactile feedback means (e.g., vibration motors), and the like. Such display devices include, but are not limited to, liquid crystal displays, light emitting diodes, displays and plasma displays. In some alternative implementations, the display device may be a touch screen.

The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium may be a magnetic disk, an optical disk, a read-only memory, a random-access memory, a flash memory, a hard disk, a solid state disk, or the like, and further, the storage medium may further include a combination of the above types of memories. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.

Portions of the present invention may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or aspects in accordance with the present invention by way of operation of the computer. Those skilled in the art will appreciate that the existence of computer program instructions in a computer-readable medium includes, but is not limited to, source files, executable files, installation package files, and the like, and accordingly, the manner in which computer program instructions are executed by a computer includes, but is not limited to, the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled programs, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed programs. Herein, a computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by a computer.

Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.

Claims (9)

1. A vehicle driving control method, characterized by comprising:

before the yellow lamp is extinguished, the current speed and the current position of the vehicle are obtained;

Determining whether the vehicle can park comfortably before the next crossing needing to pass according to the current speed and the current position of the vehicle;

When the vehicle cannot park comfortably before the next crossing needing to pass, acquiring road condition information and geometric information of the next crossing needing to pass;

Determining the theoretical risk degree of the vehicle entering the intersection by using a fuzzy control method according to the geometric information and the road condition information;

determining whether the vehicle needs to be parked according to the theoretical risk degree;

The determining the theoretical risk degree of the vehicle entering the intersection by using the fuzzy control method according to the geometric information and the road condition information comprises the following steps:

Determining the road risk degree of the vehicle entering the intersection by using a preset first fuzzy control algorithm according to the geometric information;

Determining the risk degree of the vehicle entering the intersection by using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information;

and weighting the road risk degree and the vehicle condition risk degree to obtain the theoretical risk degree of the vehicle entering the intersection.

2. The method of claim 1, wherein determining whether the vehicle can park comfortably before the next intersection to be travelled based on the current speed and current location of the vehicle comprises:

map information is acquired;

determining an actual parking distance from the current position of the vehicle to the intersection according to the current position of the vehicle and the map information;

Acquiring a comfortable parking deceleration of the vehicle;

Determining a theoretical stopping distance based on the current speed of the vehicle and the comfortable stopping deceleration;

When the theoretical parking distance is larger than the actual parking distance, judging that the vehicle cannot park comfortably before the next crossing needing to pass;

And when the theoretical parking distance is smaller than or equal to the actual parking distance, judging that the vehicle can park comfortably before the next crossing needing to pass, and controlling the vehicle to park.

3. The method of claim 1, wherein the geometric information includes an intersection length and an intersection width, and wherein determining the road risk of the vehicle entering the intersection using a preset first fuzzy control algorithm based on the geometric information of the intersection includes:

blurring the intersection length and the intersection width;

processing the length of the crossing and the width of the crossing after the blurring processing by using a preset first blurring rule to obtain a first output value;

deblurring the first output value to obtain a road risk degree of the vehicle entering the intersection;

the determining the risk of the vehicle entering the intersection by using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information comprises the following steps:

blurring the current speed of the vehicle and the road condition information;

processing the current speed of the vehicle after the blurring processing and the road condition information by using a preset second blurring rule to obtain a second output value;

and deblurring the second output value to obtain the vehicle condition risk degree of the vehicle entering the intersection.

4. The method of claim 1, wherein determining whether the vehicle is in need of parking based on the theoretical risk level comprises:

acquiring a preset risk threshold;

and when the theoretical risk degree is greater than the risk degree threshold, judging that the vehicle needs to be parked.

5. A vehicle driving control apparatus, characterized by comprising:

The first acquisition module is used for acquiring the current speed and the current position of the vehicle before the yellow lamp is extinguished;

the first judging module is used for determining whether the vehicle can park comfortably before the next crossing needing to pass according to the current speed and the current position of the vehicle;

The second acquisition module is used for acquiring road condition information and geometric information of the next crossing needing to pass when the vehicle cannot park comfortably before the next crossing needing to pass;

the theoretical risk degree determining module is used for determining the theoretical risk degree of the vehicle entering the intersection by utilizing a fuzzy control method according to the geometric information and the road condition information;

The second judging module is used for determining whether the vehicle needs to be parked or not according to the theoretical risk degree;

the theoretical risk degree determining module is specifically configured to determine a road risk degree of the vehicle entering the intersection by using a preset first fuzzy control algorithm according to the geometric information, determine a vehicle condition risk degree of the vehicle entering the intersection by using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information, and weight the road risk degree and the vehicle condition risk degree to obtain the theoretical risk degree of the vehicle entering the intersection.

6. A vehicle machine, comprising:

a memory and a processor communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the vehicle drive control method of any one of claims 1 to 4.

7. A vehicle comprising the vehicle machine of claim 6.

8. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon computer instructions for causing a computer to execute the vehicle driving control method according to any one of claims 1 to 4.

9. A computer program product comprising computer instructions for causing a computer to execute the vehicle driving control method according to any one of claims 1 to 4.