Vehicle driving control method and device, vehicle machine and vehicle

Abstract

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. Whether the vehicle can be parked comfortably before the next intersection needing to pass can be determined; when the vehicle cannot be parked comfortably before the next intersection needing to pass, the road condition information and the geometric information of the next intersection needing to pass are obtained, so that the theoretical risk degree of the vehicle entering the intersection can be determined, and whether the vehicle needs to be parked or not is determined according to the theoretical risk degree. Therefore, the driving strategy of the vehicle at the next intersection needing to pass can be determined more reasonably, and the safety is 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 rules, you should stop at a red light, go at a green light, and you can drive when it is safe at a yellow light, but most of the time you need to slow down and stop. 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 deceleration required for parking. If the required deceleration is lower than the maximum deceleration, the parking decision is made. This method takes into account only a few factors, and often results in cancellation of parking or crossing the line after parking due to deceleration following delay. This solution is lacking in both safety and rationality. 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: before the yellow light goes out, obtaining the current speed and current position of the vehicle; 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 can determine whether the vehicle can stop comfortably before the next intersection that needs to be passed by obtaining the current speed and current position of the vehicle; when the vehicle cannot stop 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 obtained, so that the theoretical risk of the vehicle entering the intersection can be determined, and whether the vehicle needs to stop can be determined based on the theoretical risk. In this way, 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.

[0008] In an optional embodiment, determining whether the vehicle can park 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 parking 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 parking distance based on the vehicle's current speed and the comfortable parking deceleration; when the theoretical parking distance is greater than the actual parking distance, determining that the vehicle cannot park comfortably before the next intersection to be passed; when the theoretical parking distance is less than or equal to the actual parking distance, determining that the vehicle can park 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, and determining the road risk for 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 for 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 condition when entering the intersection.

[0016] In an optional implementation, 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 implementation, 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 further 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 vehicle driving control method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0022] In a fourth aspect, the present invention further provides a vehicle, comprising the vehicle computer of 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, wherein the computer instructions are used to enable 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 current speed and current position of the vehicle, it can be determined whether the vehicle can stop comfortably before the next intersection that needs to be passed; when the vehicle cannot stop 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 obtained, so that the theoretical risk of the vehicle entering the intersection can be determined, and whether the vehicle needs to stop can be determined based on the theoretical risk. In this way, 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying 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 It is the conceptual block diagram of fuzzy controller;

[0029] Figure 3 It is the logic block diagram of the 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] Fig. 9 is a risk degree rule calculated based on a rule according to an embodiment of the present invention;

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

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

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

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

[0040] Fig.14 is a risk degree rule calculated based on rules in an embodiment of the present invention;

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

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

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

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

[0045] Fig.19 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the 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 creative work are within the scope of protection of the present invention.

[0047] According to an embodiment of the present invention, a vehicle driving control method embodiment 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 into yellow light, and the yellow light flashes for 3 seconds before turning into red light.

[0051] Specifically, 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, and can be obtained from the CANbus. The current position of the vehicle is obtained in the positioning module of the vehicle.

[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, the road condition information can be obtained through perception sensors, laser radars, cameras, etc. The geometric information of the intersection can be obtained from the map.

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

[0057] Fuzzy logic control (Fuzzy Logic Control) is a computer digital control technology based on fuzzy set theory, fuzzy language variables and fuzzy logic reasoning. Fuzzy control is essentially a nonlinear control and belongs to the category of intelligent control.

[0058] Figure 2 is the conceptual block diagram of the fuzzy controller. Figure 3 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 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. Scale transformation usually involves normalization and standardization;

[0062] Third, determine the fuzzy language value of each input quantity and the corresponding membership function. The membership function is 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, usually represented by a value between 0 and 1. The membership function provides a way to quantify fuzziness, allowing us to be more flexible and natural when dealing with 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 fuzzy controllers.

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

[0065] (4) Defuzzification: Its main function is to convert the control quantity obtained by inference 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 that needs to be passed by obtaining the current speed and current position of the vehicle before the yellow light goes out; when the vehicle cannot stop 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 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 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. 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. The vehicle driving control method provided in this embodiment can be used to safely and reasonably determine the driving strategy.

[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 the 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 according to geometric information using a preset first fuzzy control algorithm includes the following steps SA1 to SA3.

[0075] Step SA1: Fuzzify 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, 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, 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 width, the lower the risk; the smaller the width, the higher the risk; thus, nine control rules can be obtained based on the two fuzzy subsets of intersection length and width, such as Fig. 9 shown.

[0082] (4) Fuzzy reasoning: The total output is calculated according to the Mamdani algorithm based on the membership degree, such as Fig.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 current speed and road condition information of the vehicle after fuzzification 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 according to the current speed of the vehicle and the road condition information includes the following steps:

[0093] (1) Set the triangle membership function, such as Fig.11 As shown in , the fuzzy subsets of vehicle speed are defined as [fast (SF), medium (SM), slow (SS)]; Fig.12 As shown in , the fuzzy subsets defining the road conditions are [good (FG), medium (FM), bad (FB)]; Fig.13 As shown, 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 degree of membership 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 condition, the higher the risk; the better the road condition, the higher the risk; thus, based on these two fuzzy subsets, 9 control rules can be obtained, such as Fig.14 shown.

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

[0097] For example, the risk threshold can be set as T, the road risk weight coefficient as α, and the vehicle condition risk weight coefficient as β. By comparing the result of α*u1+β*u2>T, the decision information of whether to continue to pass the intersection in this scenario is output. When it is applied in a real car, different weight coefficients can be adjusted to meet the driver's risk assessment ratio, making it more in line 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 according to 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 driving strategy of the vehicle at the next intersection that needs to be passed, but also perform weighted calculations on the road risk and the vehicle condition risk, which can make the determined theoretical risk more reasonable. Furthermore, the weight coefficients of the road risk and the 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. Fig.16 FIG. 1 is a flow chart of another vehicle driving control method according to an embodiment of the present invention. Fig.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, and can be obtained from the CANbus. The current position of the vehicle is obtained in the positioning module of the vehicle. For example, Fig.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 parking distance according to 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 park comfortably before the next intersection that needs to be passed, and the process goes to step S1607; otherwise, the vehicle can park comfortably before the next intersection that needs to be passed, and the process goes to step S1610.

[0113] That is, when the theoretical parking distance is greater than the actual parking 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 implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0120] This embodiment provides a vehicle driving control device, such as Fig.18 As 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 that needs 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] 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 according to the theoretical risk.

[0126] In some optional embodiments, the first judgment module 1802 is specifically used to: obtain map information; determine the actual parking 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 be comfortably parked 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 be comfortably parked 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 implementations, 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 used to: fuzzify the intersection length and the 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 used 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 also provides a vehicle computer having the above Fig.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 Fig.19 , Fig.19 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Fig.19As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, 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 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. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig.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 a dedicated 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 executable by at least one processor 10, so that at least one processor 10 executes 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, an application required for at least one function; the data storage area may store data created according to 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 arranged 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 also 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. Fig.19 The example of connecting through bus is taken in the following.

[0141] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. 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 method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, 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 hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. 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 part 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 existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and 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 accessible to the computer.

[0144] Although the embodiments of the present invention have been described in conjunction with 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, and 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 the next intersection where the vehicle needs to pass according to 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; Determine the theoretical risk of the vehicle entering the intersection using a fuzzy control method according to the geometric information and the road condition information; Whether the vehicle needs to stop is determined according to the theoretical risk.

2. The method according to claim 1, characterized in that: Determining whether the vehicle can stop comfortably before the next intersection where the vehicle needs to pass 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 according to the current position of the vehicle and the map information; Obtaining a comfortable parking deceleration of the vehicle; determining a theoretical stopping distance according to a current speed of the vehicle and the comfort parking deceleration; When the theoretical parking distance is greater than the actual parking distance, it is determined that the vehicle cannot be parked 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, it is determined that the vehicle can be parked 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 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 includes: Determine 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 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.

4. The method according to claim 3, characterized in that The geometric information includes the length and width of the intersection, and the determining the road risk of the vehicle entering the intersection by using a preset first fuzzy control algorithm according to the geometric information of the intersection includes: Performing fuzzy processing on the intersection length and the intersection width; The fuzzy processed intersection length and intersection width are processed using a preset first fuzzy rule to obtain a first output value; Defuzzifying the first output value to obtain the road risk of the vehicle entering the intersection; 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 includes: Fuzzy processing is performed 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 the vehicle condition risk of the vehicle entering the intersection.

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

6. 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 that needs 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, used to determine the theoretical risk of the vehicle entering the intersection using a fuzzy control method according to the geometric information and the road condition information; The second judgment module is used to determine whether the vehicle needs to stop according to the theoretical risk.

7. 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 5 by executing the computer instructions.

8. A vehicle, characterized in that: Including the vehicle computer as described in claim 7.

9. 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 5.

10. 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 5.

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