A vehicle driving control method and device, a vehicle machine, and a vehicle

Abstract

The present application relates to the technical field of automatic driving or assisted driving, in particular to a vehicle driving control method, device, car machine and vehicle, the vehicle driving control method provided by the present application can determine whether the vehicle can be parked comfortably before the next intersection that needs to be passed by acquiring the current speed and current position of the vehicle before the yellow light is turned off; when the vehicle cannot be parked comfortably before the next intersection that needs to be passed, the road condition information and the geometric information of the next intersection that needs to be passed are acquired, so that the theoretical risk degree of the vehicle entering the intersection can be determined, and whether the vehicle needs to be parked is determined according to the theoretical risk degree. Therefore, the driving strategy of the vehicle at the next intersection that needs to be passed can be determined more reasonably, and the safety is also higher.

Description

Technical Field

[0001] The present invention relates to the field of automatic driving or assisted driving technology, and in particular to a vehicle driving control method, device, vehicle computer and vehicle. Background Art

[0002] At present, in SAE-L3 and above levels of autonomous driving, there are often multiple colors and combinations of traffic lights when passing through intersections.

[0003] According to traffic regulations, you should stop at red lights and go at green lights. You can pass when the yellow light is safe, but you will need to slow down and stop in most cases. Generally, the yellow light needs to last for 3 seconds, that is, the green light turns yellow, and the yellow light flashes for 3 seconds before turning red.

[0004] A common technique used in autonomous driving is to calculate the required deceleration for a stop and, if the required deceleration is lower than the maximum deceleration, execute the stop decision. This approach, however, takes only a limited set of factors into account and often results in the vehicle being canceled or crossing the line after stopping due to deceleration tracking delays. This approach is both safety-critical and rational. Summary of the Invention

[0005] In view of this, the present invention provides a vehicle driving control method, device, vehicle computer and vehicle to solve the problem that the current vehicle control method is lacking in safety and rationality when passing through traffic light intersections.

[0006] In a first aspect, the present invention provides a vehicle driving control method, comprising the following steps: obtaining the current speed and current position of the vehicle before the yellow light goes out; determining whether the vehicle can stop comfortably before the next intersection that needs to be passed based on the current speed and current position of the vehicle; when the vehicle cannot stop comfortably before the next intersection that needs to be passed, obtaining road condition information and geometric information of the next intersection that needs to be passed; determining the theoretical risk of the vehicle entering the intersection using a fuzzy control method based on the geometric information and road condition information; and determining whether the vehicle needs to stop based on the theoretical risk.

[0007] The vehicle driving control method provided by the present invention determines whether the vehicle can stop comfortably before the next intersection by acquiring the vehicle's current speed and current position. If the vehicle cannot stop comfortably before the next intersection, it acquires road condition information and geometric information of the next intersection to determine the theoretical risk of the vehicle entering the intersection and, based on the theoretical risk, determines whether the vehicle needs to stop. This allows for a more rational driving strategy at the next intersection, resulting in greater safety.

[0008] In an optional embodiment, determining whether the vehicle can stop comfortably before the next intersection to be passed based on the vehicle's current speed and current position includes: obtaining map information; determining the actual stopping distance of the vehicle from the current position to the intersection based on the vehicle's current position and the map information; obtaining the vehicle's comfortable parking deceleration; determining a theoretical stopping distance based on the vehicle's current speed and the comfortable parking deceleration; when the theoretical stopping distance is greater than the actual stopping distance, determining that the vehicle cannot stop comfortably before the next intersection to be passed; when the theoretical stopping distance is less than or equal to the actual stopping distance, determining that the vehicle can stop comfortably before the next intersection to be passed, and controlling the vehicle to stop.

[0009] This allows for a quick and accurate determination of whether the vehicle can stop comfortably before the next intersection it needs to pass.

[0010] In an optional embodiment, determining the risk of a vehicle entering an intersection using a fuzzy control method based on geometric information and road condition information includes: determining the road risk of the vehicle entering the intersection using a preset first fuzzy control algorithm based on the geometric information; determining the vehicle condition risk of the vehicle entering the intersection using a preset second fuzzy control algorithm based on the vehicle's current speed and road condition information; and weighting the road risk and vehicle condition risk to obtain a theoretical risk of the vehicle entering the intersection.

[0011] By weighting the road risk and vehicle condition risk, the determined theoretical risk can be made more reasonable. Furthermore, the weight coefficients of the road risk and vehicle condition risk can be adjusted to make them more in line with the driving habits of different groups of people.

[0012] In an optional embodiment, the geometric information includes the length and width of the intersection. Determining the road risk of a vehicle entering the intersection based on the geometric information of the intersection using a preset first fuzzy control algorithm includes: fuzzifying the intersection length and the intersection width; processing the fuzzified intersection length and intersection width using a preset first fuzzy rule to obtain a first output value; and defuzzifying the first output value to obtain the road risk of the vehicle entering the intersection.

[0013] Therefore, the first fuzzy control algorithm can be used to determine the road risk of the vehicle entering the intersection.

[0014] In an optional embodiment, determining the vehicle condition risk of a vehicle entering an intersection based on the vehicle's current speed and road condition information using a preset second fuzzy control algorithm includes: fuzzifying the vehicle's current speed and road condition information; processing the fuzzified vehicle's current speed and road condition information using a preset second fuzzy rule to obtain a second output value; and defuzzifying the second output value to obtain the vehicle condition risk of the vehicle entering the intersection.

[0015] Therefore, the second fuzzy control algorithm can be used to determine the risk level of the vehicle entering the intersection.

[0016] In an optional embodiment, determining whether the vehicle needs to stop based on the theoretical risk includes: obtaining a preset risk threshold; and when the theoretical risk is greater than the risk threshold, determining that the vehicle needs to stop.

[0017] This can make the vehicle driving control method safer.

[0018] In an optional embodiment, the vehicle driving control method further includes the following steps: when the vehicle can stop comfortably before the next intersection where the vehicle needs to pass, controlling the vehicle to stop.

[0019] In this way, when the vehicle can stop comfortably before the next intersection where it needs to pass, the vehicle can be controlled to stop, making the vehicle driving control method safer.

[0020] In the second aspect, the present invention also provides a vehicle driving control device, which includes a first acquisition module, a first judgment module, a second acquisition module, a theoretical risk determination module and a second judgment module; the first acquisition module is used to obtain the current speed and current position of the vehicle before the yellow light goes out; the first judgment module is used to determine whether the vehicle can stop comfortably before the next intersection that needs to be passed based on the current speed and current position of the vehicle; the second acquisition module is used to obtain road condition information and geometric information of the next intersection that needs to be passed when the vehicle cannot stop comfortably before the next intersection that needs to be passed; the theoretical risk determination module is used to determine the theoretical risk of the vehicle entering the intersection using a fuzzy control method based on the geometric information and road condition information; the second judgment module is used to determine whether the vehicle needs to stop based on the theoretical risk.

[0021] In a third aspect, the present invention also provides a vehicle computer, comprising a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to execute the vehicle driving control method of the first aspect or any corresponding embodiment thereof.

[0022] In a fourth aspect, the present invention further provides a vehicle, comprising the vehicle computer according to the third aspect.

[0023] In a fifth aspect, the present invention further provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the vehicle driving control method of the first aspect or any corresponding embodiment thereof.

[0024] In a sixth aspect, the present invention further provides a computer program product, comprising computer instructions for causing a computer to execute the vehicle driving control method of the first aspect or any corresponding embodiment thereof.

[0025] The vehicle driving control method, device, vehicle computer, and vehicle provided by the present invention have the following beneficial effects: before the yellow light goes out, by obtaining the vehicle's current speed and current position, it is possible to determine whether the vehicle can stop comfortably before the next intersection to be passed. If the vehicle cannot stop comfortably before the next intersection to be passed, road condition information and geometric information of the next intersection to be passed are obtained to determine the theoretical risk of the vehicle entering the intersection, and based on the theoretical risk, determine whether the vehicle needs to stop. This allows for a more reasonable determination of the vehicle's driving strategy at the next intersection to be passed, and also improves safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 is a flow chart of a vehicle driving control method according to an embodiment of the present invention;

[0028] Figure 2 This is the conceptual block diagram of the fuzzy controller;

[0029] Figure 3 It is the logic block diagram of fuzzy controller;

[0030] Figure 4 is a flow chart of another vehicle driving control method according to an embodiment of the present invention;

[0031] Figure 5 is a schematic diagram of an intersection length and an intersection width according to an embodiment of the present invention;

[0032] Figure 6 is a fuzzy subset graph of intersection length according to an embodiment of the present invention;

[0033] Figure 7 is a fuzzy subset graph of intersection width according to an embodiment of the present invention;

[0034] Figure 8 is a road risk fuzzy subset graph according to an embodiment of the present invention;

[0035] Figure 9 is a risk rule calculated based on a rule according to an embodiment of the present invention;

[0036] Figure 10 is a schematic diagram of mapping membership degree to risk degree according to the first fuzzy rule according to an embodiment of the present invention;

[0037] Figure 11 is a fuzzy subset graph of vehicle speed according to an embodiment of the present invention;

[0038] Figure 12 is a fuzzy subset graph of the road condition according to an embodiment of the present invention;

[0039] Figure 13 is a fuzzy subset graph of vehicle condition risk according to an embodiment of the present invention;

[0040] Figure 14 The risk degree rule calculated based on the rules in the embodiment of the present invention;

[0041] Figure 15 is a schematic diagram of mapping membership degree to risk degree according to the second fuzzy rule according to an embodiment of the present invention;

[0042] Figure 16 is a flow chart of another vehicle driving control method according to an embodiment of the present invention;

[0043] Figure 17 is a block diagram of vehicle chassis information communication according to an embodiment of the present invention;

[0044] Figure 18 is a structural block diagram of a vehicle driving control device according to an embodiment of the present invention;

[0045] Figure 19 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0047] According to an embodiment of the present invention, an embodiment of a vehicle driving control method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0048] In this embodiment, a vehicle driving control method is provided, which can be used in a computer device, such as a vehicle computer. Figure 1 is a flow chart of a vehicle driving control method according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0049] Step S101: Before the yellow light goes out, obtain the current speed and current position of the vehicle.

[0050] According to traffic regulations, you can pass when the light is yellow if it is safe. The yellow light needs to last for 3 seconds, that is, the green light turns yellow, and the yellow light flashes for 3 seconds before turning red.

[0051] Specifically, the vehicle's current speed is mainly used to determine the time required to pass the intersection, thereby assessing the risk of passing the intersection. It can be obtained from the CANbus. The vehicle's current position is obtained from the vehicle's positioning module.

[0052] Step S102: Determine whether the vehicle can stop comfortably before the next intersection where the vehicle needs to pass based on the current speed and current position of the vehicle.

[0053] In this embodiment, comfort parking can be understood as parking according to a comfort parking deceleration set in the vehicle.

[0054] Step S103: When the vehicle cannot stop comfortably before the next intersection that needs to be passed, obtain road condition information and geometric information of the next intersection that needs to be passed.

[0055] Specifically, road condition information can be obtained through perception sensors, lidar, cameras, etc. Geometric information of intersections can be obtained from maps.

[0056] Step S104: Determine the theoretical risk of the vehicle entering the intersection using a fuzzy control method based on the geometric information and road condition information.

[0057] Fuzzy logic control (also known as fuzzy control) is a computer digital control technology based on fuzzy set theory, fuzzy linguistic variables, and fuzzy logic reasoning. Fuzzy control is essentially a nonlinear control method that falls under the category of intelligent control.

[0058] Figure 2 This is the conceptual diagram of the fuzzy controller. Figure 3 This is the logic block diagram of the fuzzy controller, such as Figure 2 and Figure 3 As shown in Figure 1, the fuzzy controller consists of four parts:

[0059] (1) Fuzzification. The main function is to select the input of the fuzzy controller and convert it into a fuzzy quantity that can be recognized by the system. It specifically includes the following three steps:

[0060] First, the input quantity is processed to meet the requirements of fuzzy control.

[0061] Second, scale the input. In fuzzy control, scale transformation of the input is an important preprocessing step. This process is mainly to convert the actual input variables into a range suitable for fuzzy logic processing, thereby improving the accuracy and efficiency of the system. Scaling usually involves normalization and standardization;

[0062] Third, determine the fuzzy linguistic values ​​of each input variable and the corresponding membership function. The membership function is a core concept in fuzzy logic and fuzzy set theory. It describes the degree to which an element belongs to a fuzzy set, typically expressed as a numerical value between 0 and 1. Membership functions provide a method for quantifying fuzziness, allowing for more flexibility and naturalness in handling uncertainty and imprecise information.

[0063] (2) Rule base. A fuzzy rule base is established based on the experience of human experts. The fuzzy rule base contains numerous control rules and is a key step in the transition from actual control experience to a fuzzy controller.

[0064] (3) Fuzzy reasoning. It mainly realizes reasoning and decision-making based on knowledge.

[0065] (4) Defuzzification: The main function is to convert the control quantity obtained by reasoning into control output.

[0066] Step S105: Determine whether the vehicle needs to stop based on the theoretical risk.

[0067] The vehicle driving control method provided in this embodiment can determine whether the vehicle can stop comfortably before the next intersection to be passed by obtaining the vehicle's current speed and current position before the yellow light goes out; when the vehicle cannot stop comfortably before the next intersection to be passed, the road condition information and the geometric information of the next intersection to be passed are obtained, so as to determine the theoretical risk of the vehicle entering the intersection, and determine whether the vehicle needs to stop based on the theoretical risk. In this way, the vehicle's driving strategy at the next intersection to be passed can be determined more reasonably, and safety is also improved. In automatic driving or assisted driving, a scenario that is more difficult to handle is: the vehicle has not entered the intersection, but the color of the traffic light corresponding to the current passage has changed from green to yellow. Using the vehicle driving control method provided in this embodiment, the driving strategy can be determined safely and reasonably.

[0068] In this embodiment, a vehicle driving control method is provided, which can be used in a computer device, such as a vehicle computer. Figure 4 is a flow chart of another vehicle driving control method according to an embodiment of the present invention. Figure 4 As shown, the process includes the following steps:

[0069] Step S401: Before the yellow light goes out, obtain the current speed and current position of the vehicle.

[0070] Step S402: Determine whether the vehicle can stop comfortably before the next intersection where the vehicle needs to pass based on the current speed and current position of the vehicle.

[0071] Step S403: Determine the theoretical risk of the vehicle entering the intersection using a fuzzy control method based on the geometric information and road condition information.

[0072] In an optional implementation, determining the theoretical risk of a vehicle entering an intersection using a fuzzy control method based on geometric information and road condition information includes the following steps S4031 to S4033.

[0073] Step S4031: Determine the road risk of the vehicle entering the intersection using a preset first fuzzy control algorithm based on the geometric information.

[0074] Specifically, determining the road risk of a vehicle entering an intersection using a preset first fuzzy control algorithm according to geometric information includes the following steps SA1 to SA3.

[0075] Step SA1: Fuzzy the intersection length and intersection width.

[0076] Step SA2: The fuzzy-processed intersection length and intersection width are processed using a preset first fuzzy rule to obtain a first output value.

[0077] Step SA3: Defuzzify the first output value to obtain the road risk of the vehicle entering the intersection.

[0078] For example, Figure 5 As shown in Figure 2, assuming that the intersection length l = 65 and the width w = 45, the road risk is calculated as follows:

[0079] (1) Set the triangle membership function, such as Figure 6 As shown in , the fuzzy subsets defining the intersection length are [long (LL), medium (LM), short (LS)]; Figure 7 As shown in , the fuzzy subsets defining the intersection width are [far (WF), middle (WM), near (WN)]; Figure 8 As shown in the figure, the fuzzy subsets of road risk are very high (VH), high (H), medium (M), low (L), and very low (VL), and the distribution rules of input and output are defined according to the triangular membership function method.

[0080] (2) Calculate the membership degree 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, WN(45) = 0.

[0081] (3) Set fuzzy rules: the longer the intersection, the higher the risk; the shorter the intersection, the lower the risk; the wider the intersection, the lower the risk; the smaller the intersection, the higher the risk; thus, nine control rules can be obtained based on the two fuzzy subsets of intersection length and width, such as Figure 9 shown.

[0082] (4) Fuzzy reasoning: Calculate the total output according to the Mamdani algorithm based on the membership degree, such as Figure 10 shown.

[0083]

[0084] u_w=30; u_l=45, where u_w represents the risk of the intersection width, and u_l represents the risk of the intersection length.

[0085] (5) Clarification: The total output is clarified into road risk according to the mean method.

[0086] u1=(30+45) / 2=37.5.

[0087] Step S4032: Determine the vehicle condition risk of the vehicle entering the intersection using a preset second fuzzy control algorithm based on the vehicle's current speed and road condition information.

[0088] Specifically, determining the vehicle condition risk of the vehicle entering the intersection using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information includes the following steps SB1 to SB3.

[0089] Step SB1: Fuzzy the vehicle's current speed and road condition information;

[0090] Step SB2: Processing the fuzzy processed current speed and road condition information of the vehicle using a preset second fuzzy rule to obtain a second output value;

[0091] Step SB3: Defuzzify the second output value to obtain the vehicle condition risk of the vehicle entering the intersection.

[0092] For example, determining the vehicle condition risk of a vehicle entering an intersection using a preset second fuzzy control algorithm based on the vehicle's current speed and road condition information includes the following steps:

[0093] (1) Set the triangle membership function, such as Figure 11 As shown in , the fuzzy subsets of vehicle speed are defined as [fast (SF), medium (SM), slow (SS)]; Figure 12 As shown in , the fuzzy subsets defining the road conditions are [good (FG), medium (FM), bad (FB)]; Figure 13 As shown in the figure, the fuzzy subsets of vehicle condition risk are [very high (VH), high (H), medium (M), low (L), very low (VL)], and the distribution rules of input and output are defined according to the triangular membership function method.

[0094] (2) Calculate the membership degree according to the vehicle speed and the number of vehicles ahead.

[0095] (3) Set fuzzy rules: the higher the speed, the lower the risk of passing; the lower the speed, the higher the risk of passing; the worse the road conditions, the higher the risk; the better the road conditions, the higher the risk; thus, based on these two fuzzy subsets, 9 control rules can be obtained, such as Figure 14 shown.

[0096] (4) Similar to the road risk, the vehicle condition risk u2 can be calculated, as Figure 15 shown.

[0097] For example, the risk threshold can be set to T, the road risk weight coefficient to α, and the vehicle condition risk weight coefficient to β. By comparing the result of α*u1+β*u2>T, the decision information on whether to continue passing the intersection in this scenario is output. In actual vehicle application, different weight coefficients can be adjusted to meet the driver's risk assessment weight, making it more consistent with human driving habits.

[0098] Step S4033: Weight the road risk and vehicle condition risk to obtain the theoretical risk of the vehicle entering the intersection.

[0099] Step S404: Determine whether the vehicle needs to stop based on the theoretical risk.

[0100] In an optional implementation, determining whether the vehicle needs to stop based on the theoretical risk includes the following steps S4041 to S4042.

[0101] Step S4041: Obtaining a preset risk threshold;

[0102] Step S4042: When the theoretical risk is greater than the risk threshold, it is determined that the vehicle needs to stop.

[0103] Specifically, when the theoretical risk is less than or equal to the risk threshold, it is determined that the vehicle can pass.

[0104] The vehicle driving control method provided in this embodiment can not only reasonably determine the vehicle's driving strategy at the next intersection that needs to be passed; but also perform weighted calculations on the road risk and vehicle condition risk, which can make the determined theoretical risk more reasonable. Furthermore, the weight coefficients of the road risk and vehicle condition risk can be adjusted to make it more in line with the driving habits of different groups of people.

[0105] In this embodiment, a vehicle driving control method is provided, which can be used in a computer device, such as a vehicle computer. Figure 16 FIG. 1 is a flow chart of another vehicle driving control method according to an embodiment of the present invention. Figure 16 As shown, the process includes the following steps:

[0106] Step S1601: Before the yellow light goes out, obtain the current speed and current position of the vehicle.

[0107] As mentioned above, the current speed of the vehicle is mainly used to determine the time required to pass the intersection, so as to assess the risk of passing the intersection. It can be obtained from the CANbus. The current position of the vehicle is obtained in the vehicle's positioning module. For example, Figure 17 As shown, the current speed of the vehicle can also be obtained in the positioning module.

[0108] Step S1602: Obtain map information.

[0109] Step S1603: Determine the actual stopping distance of the vehicle from the current position to the intersection based on the current position of the vehicle and map information.

[0110] Step S1604: Obtain the comfortable parking deceleration of the vehicle.

[0111] Step S1605: Determine the theoretical stopping distance based on the current speed of the vehicle and the comfortable parking deceleration.

[0112] Step S1606: Determine whether the theoretical parking distance is greater than the actual parking distance. When the theoretical parking distance is greater than the actual parking distance, it is determined that the vehicle cannot stop comfortably before the next intersection that needs to be passed, and the process proceeds to step S1607; otherwise, the vehicle can stop comfortably before the next intersection that needs to be passed, and the process proceeds to step S1610.

[0113] That is, when the theoretical stopping distance is greater than the actual stopping distance, parking is performed.

[0114] Step S1607: Obtain traffic information and geometric information of the next intersection to be passed.

[0115] Step S1608: Determine the theoretical risk of the vehicle entering the intersection using a fuzzy control method based on the geometric information and road condition information.

[0116] Step S1609: Determine whether the vehicle needs to stop based on the theoretical risk.

[0117] Step S1610: Control the vehicle to stop.

[0118] The vehicle driving control method provided in this embodiment can reasonably determine the driving strategy of the vehicle at the next intersection where it needs to pass.

[0119] In this embodiment, a vehicle driving control device is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments. Details already described will not be repeated here. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0120] This embodiment provides a vehicle driving control device, such as Figure 18 Shown, including:

[0121] The first acquisition module 1801 is used to acquire the current speed and current position of the vehicle before the yellow light goes out.

[0122] The first judgment module 1802 is used to determine whether the vehicle can stop comfortably before the next intersection to be passed according to the current speed and current position of the vehicle.

[0123] The second acquisition module 1803 is used to acquire road condition information and geometric information of the next intersection that needs to be passed when the vehicle cannot stop comfortably before the next intersection that needs to be passed.

[0124] The theoretical risk determination module 1804 is used to determine the theoretical risk of a vehicle entering an intersection using a fuzzy control method based on geometric information and road condition information.

[0125] The second judgment module 1805 is used to determine whether the vehicle needs to stop based on the theoretical risk.

[0126] In some optional embodiments, the first judgment module 1802 is specifically used to: obtain map information; determine the actual stopping distance of the vehicle from the current position to the intersection based on the current position of the vehicle and the map information; obtain the comfortable parking deceleration of the vehicle; determine the theoretical parking distance based on the current speed of the vehicle and the comfortable parking deceleration; when the theoretical parking distance is greater than the actual parking distance, determine that the vehicle cannot stop comfortably before the next intersection that needs to be passed; when the theoretical parking distance is less than or equal to the actual parking distance, determine that the vehicle can stop comfortably before the next intersection that needs to be passed, and control the vehicle to stop.

[0127] In some optional embodiments, the theoretical risk determination module 1804 is specifically used to: determine the road risk of the vehicle entering the intersection using a preset first fuzzy control algorithm based on geometric information; determine the vehicle condition risk of the vehicle entering the intersection using a preset second fuzzy control algorithm based on the vehicle's current speed and road condition information; and weight the road risk and vehicle condition risk to obtain the theoretical risk of the vehicle entering the intersection.

[0128] In some optional embodiments, the theoretical risk determination module 1804 includes a road risk determination unit, a vehicle condition risk determination unit, and a weighting unit. The road risk determination unit is configured to: fuzzify the intersection length and intersection width; process the fuzzified intersection length and intersection width using a preset first fuzzy rule to obtain a first output value; and defuzzify the first output value to obtain the road risk of the vehicle entering the intersection.

[0129] In some optional embodiments, the vehicle condition risk determination unit is used to fuzzy the vehicle's current speed and road condition information; process the fuzzyized vehicle's current speed and road condition information using a preset second fuzzy rule to obtain a second output value; and defuzzify the second output value to obtain the vehicle condition risk of the vehicle entering the intersection.

[0130] In some optional implementations, the second judgment module 1805 is specifically configured to obtain a preset risk threshold; when the theoretical risk is greater than the risk threshold, it is determined that the vehicle needs to stop.

[0131] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0132] The vehicle driving control device 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 memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0133] The embodiment of the present invention further provides a vehicle computer having the above Figure 18 Vehicle driving controls shown.

[0134] An embodiment of the present invention further provides a vehicle, comprising the above-mentioned vehicle computer.

[0135] See also Figure 19 , Figure 19 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 19As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 19 A processor 10 is taken as an example.

[0136] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. 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.

[0137] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0138] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0139] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0140] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 19 The bus connection is taken as an example.

[0141] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0142] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0143] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0144] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A vehicle driving control method, characterized in that: include: Before the yellow light goes out, obtain the current speed and current position of the vehicle; determining whether the vehicle can stop comfortably before a next intersection requiring passage based on the vehicle's current speed and current position; When the vehicle cannot stop comfortably before the next intersection to be passed, obtaining road condition information and geometric information of the next intersection to be passed; Determining the theoretical risk of the vehicle entering the intersection using a fuzzy control method based on the geometric information and the road condition information; determining whether the vehicle needs to stop according to the theoretical risk; Determining the theoretical risk of the vehicle entering the intersection using a fuzzy control method according to the geometric information and the road condition information includes: Determining the road risk of the vehicle entering the intersection using a preset first fuzzy control algorithm according to the geometric information; Determining the vehicle condition risk of the vehicle entering the intersection using a preset second fuzzy control algorithm according to the current speed of the vehicle and the road condition information; The road risk and the vehicle condition risk are weighted to obtain a theoretical risk of the vehicle entering the intersection.

2. The method according to claim 1, characterized in that Determining whether the vehicle can stop comfortably before the next intersection to be passed according to the current speed and current position of the vehicle includes: Get map information; determining an actual stopping distance of the vehicle from the current position to the intersection based on the current position of the vehicle and the map information; Obtaining a comfortable parking deceleration for the vehicle; determining a theoretical stopping distance based on a current speed of the vehicle and the comfortable parking deceleration; When the theoretical stopping distance is greater than the actual stopping distance, determining that the vehicle cannot stop comfortably before the next intersection to be passed; When the theoretical stopping distance is less than or equal to the actual stopping distance, it is determined that the vehicle can stop comfortably before the next intersection that needs to be passed, and the vehicle is controlled to stop.

3. The method according to claim 1, characterized in that The geometric information includes the length and width of the intersection, and 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: Performing fuzzy processing on the intersection length and the intersection width; Processing the fuzzy-processed intersection length and intersection width using a preset first fuzzy rule to obtain a first output value; Defuzzifying the first output value to obtain a road risk of the vehicle entering the intersection; The determining of 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 includes: Performing fuzzy processing on the current speed of the vehicle and the road condition information; Processing the current speed of the vehicle and the road condition information after fuzzification using a preset second fuzzy rule to obtain a second output value; The second output value is defuzzified to obtain a vehicle condition risk of the vehicle entering the intersection.

4. The method according to claim 1, wherein Determining whether the vehicle needs to stop according to the theoretical risk includes: Obtaining the preset risk threshold; When the theoretical risk is greater than the risk threshold, it is determined that the vehicle needs to stop.

5. A vehicle driving control device, characterized in that: The device comprises: The first acquisition module is used to obtain the current speed and current position of the vehicle before the yellow light goes out; A first judgment module is used to determine whether the vehicle can stop comfortably before the next intersection to be passed according to the current speed and current position of the vehicle; A second acquisition module is used to acquire road condition information and geometric information of the next intersection that needs to be passed when the vehicle cannot stop comfortably before the next intersection that needs to be passed; a theoretical risk determination module, configured to determine the theoretical risk of the vehicle entering the intersection using a fuzzy control method based on geometric information and the road condition information; A second judgment module is used to determine whether the vehicle needs to stop according to the theoretical risk; The theoretical risk determination module is specifically used to: determine the road risk of the vehicle entering the intersection using a preset first fuzzy control algorithm based on the geometric information; determine the vehicle condition risk of the vehicle entering the intersection using a preset second fuzzy control algorithm based on the current speed of the vehicle and the road condition information; and weight the road risk and the vehicle condition risk to obtain the theoretical risk of the vehicle entering the intersection.

6. A vehicle computer, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the vehicle driving control method according to any one of claims 1 to 4 by executing the computer instructions.

7. A vehicle, characterized in that: Including the vehicle computer according to claim 6.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the vehicle driving control method according to any one of claims 1 to 4.

9. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the vehicle driving control method according to any one of claims 1 to 4.

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