Method, device, electronic device and storage medium for obtaining braking distance of driverless mining vehicle

Abstract

The present disclosure relates to a method, device, electronic device, and storage medium for obtaining the braking distance of an unmanned mining vehicle. The method includes: when the target unmanned mining vehicle needs to brake, obtaining the vehicle information of the target unmanned mining vehicle and the road information at the current moment; obtaining the target relationship value corresponding to the actual average deceleration and the braking performance index of the target unmanned mining vehicle at the initial speed; and determining the minimum braking distance of the target unmanned mining vehicle at the current moment based on the vehicle information, road information, and target relationship value. In this way, the minimum braking distance of the target unmanned vehicle at the current moment can be obtained, and according to the differences in the initial speed and road information of the target unmanned vehicle at different moments, the minimum braking distance of the target unmanned vehicle can be obtained in real time, which is convenient for dynamically adjusting the braking timing to avoid accidents.

Description

Technical Field

[0001] The present invention relates to the technical field of driverless mining vehicles, and particularly to a method, device, electronic device and storage medium for obtaining the braking distance of driverless mining vehicles. Background Art

[0002] For driverless mining vehicles, when an obstacle is detected ahead, braking measures need to be taken within an appropriate distance to ensure that no collision occurs and the driving safety of the vehicle is guaranteed. In related technologies, a fixed safety distance is usually set to ensure driving safety. However, due to the differences in vehicles and driving scenarios, the reserved safety distance may be insufficient, and thus a collision risk event may occur. Summary of the Invention

[0003] The present disclosure provides a method, device, electronic device and storage medium for obtaining the braking distance of driverless mining vehicles.

[0004] According to one aspect of the present disclosure, there is provided a method for obtaining the braking distance of a driverless mining vehicle, the method comprising:

[0005] When the target driverless mining vehicle needs to brake, obtaining the vehicle information of the target driverless mining vehicle and the road information at the current moment, the vehicle information including the initial speed of the target driverless mining vehicle at the current moment, and the road information including the slope and rolling resistance coefficient of the road;

[0006] Obtaining a target relationship value corresponding to the actual average deceleration of the target driverless mining vehicle at the initial speed and the braking performance index; wherein, the preset relationship values between the actual average deceleration and the braking performance index at different initial speeds are different;

[0007] Based on the vehicle information, the road information and the target relationship value, determining the minimum braking distance of the target driverless mining vehicle at the current moment.

[0008] According to a second aspect of the present disclosure, there is provided a device for obtaining the braking distance of a driverless mining vehicle, characterized in that the device comprises:

[0009] An information acquisition module, configured to obtain the vehicle information of the target driverless mining vehicle and the road information at the current moment when the target driverless mining vehicle needs to brake, the vehicle information including the initial speed of the target driverless mining vehicle at the current moment, and the road information including the slope and rolling resistance coefficient of the road;

[0010] A numerical value determination module for obtaining a target relationship value corresponding to the actual average deceleration of the target driverless mining vehicle at the initial speed and the braking performance index; wherein, the preset relationship values between the actual average deceleration and the braking performance index at different initial speeds are different;

[0011] A braking distance determination module for determining the minimum braking distance of the target driverless mining vehicle at the current moment based on the vehicle information, the road information and the target relationship value.

[0012] According to a third aspect of the present disclosure, there is provided an electronic device. The electronic device includes: a memory and a processor, a computer program is stored on the memory, and when the processor executes the program, the method as described above is implemented.

[0013] According to a fourth aspect of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above method of the present disclosure is implemented.

[0014] The method, device, electronic device and storage medium for obtaining the braking distance of a driverless mining vehicle provided by the embodiments of the present disclosure, when the target driverless mining vehicle brakes, obtain the vehicle information of the target driverless mining vehicle and the road information at the current moment, and based on the obtained vehicle information, road information and the target relationship value corresponding to the actual average deceleration at the initial speed and the braking performance index, determine the minimum braking distance of the target driverless mining vehicle at the current moment. In this way, by obtaining the road information, initial speed at the current moment and the target relationship value corresponding to the actual average deceleration of the target driverless mining vehicle at this initial speed and the braking performance index, the minimum braking distance of the target driverless vehicle at the current moment can be obtained, and according to the different initial speeds and road information of the target driverless vehicle at different moments, the minimum braking distance of the target driverless vehicle can be obtained in real time, which is convenient for dynamically adjusting the braking timing to avoid accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In the following description of the exemplary embodiments in conjunction with the drawings, more details, features and advantages of the present disclosure are disclosed. In the drawings:

[0016] Figure 1 It is a flowchart of a method for obtaining the braking distance of a driverless mining vehicle provided by an exemplary embodiment of the present disclosure;

[0017] Figure 2 It is a flowchart of a method for obtaining the braking distance of a driverless mining vehicle provided by another exemplary embodiment of the present disclosure;

[0018] Figure 3Scenario schematic diagram of an unmanned mining vehicle during driving provided by another exemplary embodiment of the present disclosure;

[0019] Figure 4 Schematic block diagram of functional modules of a braking distance acquisition device for an unmanned mining vehicle provided by an exemplary embodiment of the present disclosure;

[0020] Figure 5 Schematic block diagram of a structure of an electronic device provided by an exemplary embodiment of the present disclosure;

[0021] Figure 6 Schematic block diagram of a structure of a computer system provided by an exemplary embodiment of the present disclosure. Detailed implementation manners

[0022] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0023] It should be understood that the various steps recorded in the method embodiments of the present disclosure can be executed in different orders and / or executed in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this regard.

[0024] As used herein, the term "including" and its variants are open-ended, that is, "including but not limited to". The term "based on" is "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order of functions executed by these devices, modules or units or their interdependent relationships.

[0025] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that unless clearly stated otherwise in the context, it should be understood as "one or more".

[0026] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0027] For driverless wide-body mining trucks, when an obstacle is detected ahead, braking measures need to be taken within an appropriate distance to ensure no collision occurs and the driving safety of the vehicle. It is not possible to simply set a fixed safety distance to ensure driving safety. This not only cannot flexibly plan the speed but also reduces the road traffic efficiency. Moreover, due to the differences in vehicles and scenarios, the reserved safety distance may be insufficient, leading to the occurrence of collision risks.

[0028] For large-scale operation of driverless mining vehicles, the braking capabilities of different vehicles are different, the vehicle speeds when obstacles are detected and the terrains where the vehicles are located also vary. It is also necessary to combine this information to obtain the real-time minimum braking distance of the vehicle in order to dynamically adjust the timing and magnitude of braking intervention.

[0029] Therefore, in the embodiments provided in the present disclosure, a braking distance estimation model is proposed based on the vehicle kinematics and dynamics models, and the braking distance estimation model is corrected.

[0030] First, the braking process of the target driverless mining vehicle is regarded as a uniformly decelerated motion with a deceleration of a. Therefore, when calculating the minimum braking distance of the target driverless mining vehicle, the vehicle starts braking from the current initial speed v0 until the vehicle speed stops at 0. Therefore, the braking distance S can be expressed as

[0031]

[0032] According to the force analysis of the target driverless mining vehicle during the uniformly decelerated process, the following dynamic equation is obtained:

[0033]

[0034] Among them, m is the mass of the target driverless mining vehicle, a is the actual average deceleration of the target driverless mining vehicle, g is the acceleration due to gravity, f is the rolling resistance coefficient, is the slope of the road, μ is a preset coefficient, C d is the air resistance coefficient, A is the braking performance index of the target driverless mining vehicle, and v0 is the initial speed of the target driverless mining vehicle during braking.

[0035] In the embodiment, the target driverless mining vehicle may specifically be a driverless wide-body mining truck. For a driverless wide-body mining truck, due to its large vehicle mass and low running speed, the air resistance has a relatively small impact on the deceleration process compared with other resistances, so it can be ignored. In the embodiment, it may be the case of an even road for the driving route to abstract the deceleration of the vehicle, that is, at this time, since is small, so is approximately equal to 1, Approximately equal to

[0036] Therefore, the above formula (2) can be converted to:

[0037]

[0038] Correspondingly, the braking distance S of the above formula (1) can be converted as follows:

[0039]

[0040] Wherein, S is the braking distance of the target driverless mining vehicle at the current moment, v0 is the initial speed, f is the rolling resistance coefficient, is the slope of the road, and g is the acceleration due to gravity.

[0041] Considering that the braking performances of different vehicles are different, and the actual average braking deceleration a shown is also different, so the coefficient in the above formula can also be expressed as a parameter related to the braking consistency ability index A. Therefore, the above formula (4) can be converted as follows:

[0042]

[0043] Wherein, S is the braking distance of the target driverless mining vehicle at the current moment, v0 is the initial speed, k is the reciprocal of the rolling resistance coefficient, is the slope of the road, a is the actual average deceleration of the target driverless mining vehicle, and A is the braking performance index of the target driverless mining vehicle.

[0044] In the embodiment, the braking performance index of the vehicle can be characterized by the average deceleration fully developed by the vehicle.

[0045] As shown in Table 1, Table 1 shows the ratio relationship between the actual average deceleration and the average deceleration fully developed when the target driverless mining vehicle brakes at different initial speeds in an exemplary embodiment.

[0046] Table 1:

[0047]

[0048]

[0049] As can be seen from the actual vehicle data in the above table, a / A is related to the braking vehicle speed, and this value is different at different braking initial speeds v0. In order to cover the relationship in the full speed range, the following relationship can be fitted according to the actual vehicle data:

[0050]

[0051] It should be noted that f(v0) can be a polynomial of a / A at the initial speed of different brakings obtained after obtaining the actual measurement value. For example, a quadratic equation of v0 can be fitted, and the corresponding value can be obtained through this equation at the initial speed of different brakings. In addition, f(v0) can also obtain the corresponding value by looking up a table, such as obtaining the corresponding value in the way of Table 1.

[0052] Exemplary m and n are coefficients, and d is a constant.

[0053] The finally obtained braking distance estimation model related to the braking consistency index, the initial braking speed, and the slope is as follows:

[0054]

[0055] Among them, S is the braking distance of the target driverless mining vehicle at the current moment, v0 is the initial speed, f is the rolling resistance coefficient, is the slope of the road, and f(v0) represents the target relationship value between the actual average deceleration and the braking performance index of the target driverless mining vehicle at the initial speed, which can be obtained through the embodiments corresponding to the above formula (6). It should be noted that the calculated braking distance of the target driverless mining vehicle at the current moment in the embodiment is the minimum braking distance.

[0056] For mining wide-body trucks, there is a relatively large difference between the no-load braking distance and the heavy-load braking distance. Therefore, the above method provided by the embodiments of the present disclosure is applicable to the establishment of both the no-load and heavy-load distance estimation models.

[0057] In actual application, the comparison results and errors between the braking distances calculated by the model established by the above method at different initial braking speeds and the actual braking distances are as follows. Among them, the actual braking distance is calculated by obtaining the position coordinates of the vehicle at the initial braking and the position coordinates of the vehicle when it stops with the positioning device on the vehicle.

[0058] Four vehicle speeds 8 km / h, 15 km / h, 25 km / h, and 35 km / h in different low, medium, and high vehicle speed ranges are selected, corresponding to the braking data when going uphill at 5%, on flat road, and downhill at 5% respectively, and compared with the estimated braking distances, and the errors are all within 10%, as shown in Table 2.

[0059] Table 2:

[0060]

[0061] Based on the above embodiments, the embodiments of the present disclosure also provide a method for obtaining the braking distance of a driverless mining vehicle, as Figure 1 shown, the method may include the following steps:

[0062] In step S110, when the target driverless mining vehicle needs to brake, the vehicle information of the target driverless mining vehicle and the road information at the current moment are acquired.

[0063] Among them, the vehicle information includes the initial speed of the target driverless mining vehicle at the current moment, and the road information includes the slope of the road and the rolling resistance coefficient.

[0064] The target driverless mining vehicle in the embodiments of the present disclosure may specifically be a driverless mining wide-body vehicle. During the driving process of the target driverless mining vehicle, for example, when a braking instruction is received, braking is initiated. The road on which the target driverless mining vehicle travels during braking can be referred to as the driving route. During the braking process of the target driverless mining vehicle, the driving speed gradually decreases from the initial data at the time of braking to zero, and the driving distance generated during its braking process can be referred to as the braking distance.

[0065] The parameters such as the slope and the rolling resistance coefficient in this embodiment correspond to the parameters in the above embodiment.

[0066] In step S120, the target relationship value corresponding to the actual average deceleration of the target driverless mining vehicle at the initial speed and the braking performance index is acquired. Among them, the preset relationship values between the actual average deceleration and the braking performance index at different initial speeds are different.

[0067] During the braking process of the target driverless mining vehicle, the braking distance is not only related to the initial speed of the target driverless mining vehicle, but also related to the road information of the driving route at the current moment, such as the slope of the driving route and the rolling resistance coefficient of the target driverless mining vehicle during the braking process on the driving route, etc.

[0068] In the embodiment, the actual average deceleration and the braking performance index of the target driverless mining vehicle can be obtained by pre-conducting actual performance tests on the target driverless mining vehicle. Among them, the braking performance index can be characterized by the average deceleration fully exerted by the target driverless mining vehicle. The target relationship value corresponding to the actual average deceleration of the target driverless mining vehicle at the initial speed and the braking performance index can be obtained through the above embodiment, which will not be elaborated here.

[0069] In step S130, based on the vehicle information, the road information, and the target relationship value, the minimum braking distance of the target driverless mining vehicle at the current moment is determined.

[0070] During the braking process of the target driverless mining vehicle on the driving route, the greater its initial speed is and other conditions remain unchanged, the greater its braking distance will be. In addition, the braking distance of the target driverless mining vehicle is also related to the slope and friction coefficient of the braking speed, that is, the greater the slope of the driving route is and other conditions remain unchanged, the smaller the braking distance will be; the greater the braking resistance coefficient of the driving route is, the smaller the braking distance of the target driverless mining vehicle will be.

[0071] In addition, since the braking capabilities of different vehicles are different, the embodiments of the present disclosure can well estimate the braking distance of the target driverless mining vehicle by introducing the actual average deceleration and braking performance index of the target driverless mining vehicle and combining the road information and vehicle information of the driving route.

[0072] Specifically, the minimum braking distance of the target driverless mining vehicle at the current moment can be determined according to the corresponding embodiment of the above formula (7), which will not be elaborated here.

[0073] In this way, during the driving process of the target driverless mining vehicle, by obtaining the road information and vehicle information corresponding to each moment, the minimum braking distance of the target driverless mining vehicle at the corresponding moment can be obtained in real time, that is, the minimum braking distance of the target driverless mining vehicle at the current moment can be obtained in real time, which is convenient for flexibly adjusting the braking strategy.

[0074] The method for obtaining the braking distance of the driverless mining vehicle provided by the embodiments of the present disclosure, when the target driverless mining vehicle brakes, obtains the vehicle information of the target driverless mining vehicle and the road information at the current moment, and determines the minimum braking distance of the target driverless mining vehicle at the current moment based on the obtained vehicle information, road information and the target relationship value corresponding to the actual average deceleration and braking performance index at the initial speed. In this way, by obtaining the road information, initial speed at the current moment and the target relationship value corresponding to the actual average deceleration and braking performance index of the target driverless mining vehicle at this initial speed, the minimum braking distance of the target driverless vehicle at the current moment can be obtained, and according to the different initial speeds and road information of the target driverless vehicle at different moments, the minimum braking distance of the target driverless vehicle can be obtained in real time, which is convenient for dynamically adjusting the braking timing to avoid accidents.

[0075] Based on the above embodiments, in order to detail how to use the calculated minimum braking distance for braking when the target driverless mining vehicle encounters an obstacle on the driving route, therefore, in another embodiment provided by the present disclosure, as Figure 2 shown, the above method may further include the following steps:

[0076] In step S140, when an obstacle is detected, the target distance between the target driverless mining vehicle and the obstacle at the current moment is obtained.

[0077] In the embodiments of the present disclosure, when the target driverless vehicle is driving on the driving route and an obstacle is detected on the driving route, the minimum braking distance can be obtained based on the above method. Wherein, the driving route refers to the route along which the target driverless mining vehicle travels according to a predetermined plan.

[0078] For example, when other vehicles, large stones and other obstacles that affect the normal driving of the driverless mining vehicle appear on the driving route, the driverless mining vehicle will obtain the minimum braking distance of the target driverless mining vehicle according to the information such as the current driving speed, road information, actual average deceleration and braking performance index obtained, and based on the above method.

[0079] In step S150, when the target distance meets the first preset condition, a braking instruction is generated to make the target driverless mining vehicle start braking according to the braking instruction.

[0080] In an embodiment provided by the present disclosure, it may be determined that the target distance meets the first preset condition when the target distance is within the first preset range. Wherein, the lower limit of the first preset range is greater than the minimum braking distance of the target driverless mining vehicle. This can avoid the situation that the target distance between the target driverless mining vehicle and the obstacle is less than the minimum braking distance before starting to take braking measures, so that braking can be started in advance to avoid accidents.

[0081] In another embodiment provided by the present disclosure, it can also be judged by calculating the difference between the target distance and the minimum braking distance. That is, when the difference between the detected target distance and the minimum braking distance of the target driverless mining vehicle on the driving route is within the first target numerical interval, a braking instruction is generated to make the target driverless mining vehicle start braking according to the braking instruction.

[0082] In the embodiment, the target distance between the target driverless mining vehicle and the obstacle is represented by S1, the current minimum braking distance of the target driverless mining vehicle on the driving route is represented by S0, and the difference between the target distance and the minimum braking distance of the target driverless mining vehicle on the driving route is represented by S2. As Figure 3 shown, it is a schematic diagram of the target driverless mining vehicle 100 and other vehicles 200 on the driving route. Wherein, the obstacle in the embodiment is represented by the vehicle 200.

[0083] Combined with Figure 3As shown, when S2 is within the first target numerical range, it indicates that the distance between the target unmanned mining vehicle 100 and the vehicle 200 is relatively close to the minimum braking distance. At this time, a braking instruction can be generated so that the target unmanned mining vehicle 100 can brake in time, avoiding the situation that the minimum braking distance of the target unmanned mining vehicle 100 is affected by road information and other conditions on the driving road. For example, during the driving process of the target unmanned mining vehicle 100, due to road information, the minimum braking distance suddenly becomes larger, resulting in the inability to take braking measures in time and causing a rear-end collision.

[0084] In another embodiment provided by the present disclosure, in combination with the above embodiment, in order to enable the target unmanned mining vehicle to take more braking measures in time, before step S150, the method may further include the following steps:

[0085] S160, when the target distance is within the second preset range, reduce the speed of the target unmanned mining vehicle. Wherein, the lower limit value of the second preset range is equal to the upper limit value of the first preset range.

[0086] In the embodiment, before starting to brake, other measures may also be taken, such as reducing the vehicle speed, etc., in order to perform smooth braking and avoid directly taking braking measures. In this way, by extending the braking distance and flexibly adjusting the braking means, the purpose of smooth braking can be achieved.

[0087] In addition, in another embodiment provided by the present disclosure, it can also be judged according to the difference between the target distance and the minimum braking distance of the target unmanned mining vehicle on the driving route. For example, when the difference between the detected target distance and the minimum braking distance of the target unmanned mining vehicle on the driving route is within the second target numerical range, reduce the speed of the target unmanned mining vehicle. For example, it can be achieved by reducing the power of the engine, etc., so as to gently brake the target unmanned mining vehicle. Wherein, the upper limit value in the first target numerical range is equal to the lower limit value in the second target numerical range.

[0088] In the embodiment, when the difference between the detected target distance and the minimum braking distance of the target unmanned mining vehicle on the driving route is within the second target numerical range, since the upper limit value in the first target numerical range is equal to the lower limit value in the second target numerical range, that is, at this time, the distance between the target unmanned mining vehicle and the obstacle is relatively large. At this time, the driving speed of the target unmanned mining vehicle can be reduced first. When the difference between the target distance and the minimum braking distance of the target unmanned mining vehicle on the driving route is within the first target numerical range, then brake. In this way, the target unmanned mining vehicle can be prepared for braking in advance, avoiding the situation that the target unmanned mining vehicle performs emergency braking when the distance from the obstacle in front of the driving route is relatively close, resulting in wear of the braking system.

[0089] It should be noted that, due to the different braking performances and other conditions of each driverless mining vehicle, and the different road information of different roads, the first target numerical range and the second target numerical range can be set according to specific conditions.

[0090] In the case of dividing each functional module according to each function, the embodiments of the present disclosure provide a device for obtaining the braking distance of a driverless mining vehicle. The device for obtaining the braking distance of a driverless mining vehicle can be a server or a chip applied to the server. Figure 4 It is a schematic block diagram of the functional modules of the device for obtaining the braking distance of a driverless mining vehicle provided by an exemplary embodiment of the present disclosure. As Figure 4 shown, the device for obtaining the braking distance of a driverless mining vehicle includes:

[0091] An information acquisition module 10, configured to acquire the vehicle information of the target driverless mining vehicle and the road information at the current moment when the target driverless mining vehicle needs to brake. The vehicle information includes the initial speed of the target driverless mining vehicle at the current moment, and the road information includes the slope and rolling resistance coefficient of the road;

[0092] A numerical value determination module 20, configured to determine the minimum braking distance of the target driverless mining vehicle at the current moment based on the vehicle information, the road information, and the target relationship value;

[0093] A braking distance determination module 30, configured to determine the braking distance of the target driverless mining vehicle on the driving route based on the vehicle information, the road information, the actual average deceleration, and the braking performance index.

[0094] In another embodiment provided by the present disclosure, the braking performance index is characterized by the average deceleration fully developed by the target driverless mining vehicle.

[0095] In another embodiment provided by the present disclosure, the device further includes:

[0096] A target distance acquisition module, configured to acquire the target distance between the target driverless mining vehicle and the obstacle at the current moment when an obstacle is detected;

[0097] An instruction generation module, configured to generate a braking instruction when the target distance meets a first preset condition, so that the target driverless mining vehicle starts braking according to the braking instruction.

[0098] Since the device corresponds to the above method, the description of the device part can refer to the above method part and will not be elaborated here.

[0099] The braking distance acquisition device for driverless mining vehicles provided by the embodiments of the present disclosure, when the target driverless mining vehicle brakes, acquires the vehicle information of the target driverless mining vehicle and the road information at the current moment, and determines the minimum braking distance of the target driverless mining vehicle at the current moment based on the acquired vehicle information, road information, and the target relationship value corresponding to the actual average deceleration and braking performance index at the initial speed. In this way, by acquiring the road information, initial speed, and the target relationship value corresponding to the actual average deceleration and braking performance index of the target driverless mining vehicle at the initial speed at the current moment, the minimum braking distance of the target driverless vehicle at the current moment can be obtained, and according to the different initial speeds and road information of the target driverless vehicle at different moments, the minimum braking distance of the target driverless vehicle can be obtained in real time, which is convenient for dynamically adjusting the braking timing to avoid accidents.

[0100] The embodiments of the present disclosure also provide an electronic device, including: at least one processor; a memory for storing executable instructions of the at least one processor; wherein, the at least one processor is configured to execute the instructions to implement the above method disclosed by the embodiments of the present disclosure.

[0101] Figure 5 It is a schematic structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure. As Figure 5 shown, the electronic device 1800 includes at least one processor 1801 and a memory 1802 coupled to the processor 1801, and the processor 1801 can execute the corresponding steps in the above method disclosed by the embodiments of the present disclosure.

[0102] The above-mentioned processor 1801 can also be referred to as a central processing unit (CPU). It can be an integrated circuit chip with the ability to process signals. Each step in the above-mentioned methods disclosed in the embodiments of the present disclosure can be completed by the integrated logic circuit in the hardware of the processor 1801 or instructions in the form of software. The above-mentioned processor 1801 can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the methods disclosed in the embodiments of the present disclosure in combination can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module can be located in the memory 1802, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, and other well-known storage media in the art. The processor 1801 reads the information in the memory 1802 and completes the steps of the above-mentioned methods in combination with its hardware.

[0103] In addition, when various operations / processes according to the present disclosure are implemented by software and / or firmware, a program constituting the software can be installed from a storage medium or a network into a computer system having a dedicated hardware structure, such as Figure 4 the computer system 1900 shown. When various programs are installed in the computer system, it can execute various functions, including functions such as those described above. Figure 6 It is a block diagram of the structure of a computer system provided by an exemplary embodiment of the present disclosure.

[0104] The computer system 1900 is intended to represent various forms of digital electronic computer devices, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0105] As Figure 6As shown, computer system 1900 includes a computing unit 1901 that can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1902 or a computer program loaded from a storage unit 1908 into a random access memory (RAM) 1903. In the RAM 1903, various programs and data required for the operation of the computer system 1900 can also be stored. The computing unit 1901, the ROM 1902, and the RAM 1903 are connected to each other through a bus 1904. An input / output (I / O) interface 1905 is also connected to the bus 1904.

[0106] Multiple components in the computer system 1900 are connected to the I / O interface 1905, including: an input unit 1906, an output unit 1907, a storage unit 1908, and a communication unit 1909. The input unit 1906 can be any type of device that can input information into the computer system 1900. The input unit 1906 can receive input digital or character information and generate key signal inputs related to the user settings and / or function controls of the electronic device. The output unit 1907 can be any type of device that can present information and can include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 1908 can include, but is not limited to, a magnetic disk, an optical disk. The communication unit 1909 allows the computer system 1900 to exchange information / data with other devices through a network such as the Internet and can include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a BluetoothTM device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0107] The computing unit 1901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 1901 executes the various methods and processes described above. For example, in some embodiments, the above-described methods disclosed in the embodiments of the present disclosure can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 1908. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 1900 via the ROM 1902 and / or the communication unit 1909. In some embodiments, the computing unit 1901 can be configured to execute the above-described methods disclosed in the embodiments of the present disclosure by any other appropriate means (e.g., by means of firmware).

[0108] An embodiment of the present disclosure also provides a computer-readable storage medium. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the above methods disclosed in the embodiments of the present disclosure.

[0109] The computer-readable storage medium in the embodiments of the present disclosure may be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The above computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specifically, the above computer-readable storage medium may include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0110] The above computer-readable medium may be included in the above electronic device; or may exist separately without being assembled into the electronic device.

[0111] An embodiment of the present disclosure also provides a computer program product, including a computer program, where the computer program, when executed by a processor, implements the above methods disclosed in the embodiments of the present disclosure.

[0112] In the embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof. The above programming languages include, but are not limited to, object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network (including a local area network (LAN) or a wide area network (WAN)), or may be connected to an external computer.

[0113] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0114] The modules, components, or units involved in the embodiments described in the present disclosure may be implemented in software or in hardware. Among them, the names of the modules, components, or units do not, in some cases, constitute a limitation on the modules, components, or units themselves.

[0115] The functions described above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that may be used include: Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), Application Specific Standard Product (ASSP), System on Chip (SOC), Complex Programmable Logic Device (CPLD), and so on.

[0116] The above description is only some embodiments of the present disclosure and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present disclosure.

[0117] Although some specific embodiments of the present disclosure have been described in detail by way of examples, those skilled in the art should understand that the above examples are only for illustration and not for limiting the scope of the present disclosure. Those skilled in the art should understand that the above embodiments may be modified without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A method for obtaining the braking distance of an unmanned mining vehicle, characterized in that, The method includes: When the target driverless mining vehicle needs to brake, obtaining the vehicle information of the target driverless mining vehicle and the road information at the current moment, where the vehicle information includes the initial speed of the target driverless mining vehicle at the current moment, and the road information includes the slope and rolling resistance coefficient of the road; Obtaining the target relationship value corresponding to the actual average deceleration and the braking performance index of the target driverless mining vehicle at the initial speed; wherein, the preset relationship values between the actual average deceleration and the braking performance index at different initial speeds are different; Based on the vehicle information, the road information and the target relationship value, determining the minimum braking distance of the target driverless mining vehicle at the current moment.

2. The method according to claim 1, characterized in that, The determining the minimum braking distance of the target driverless mining vehicle at the current moment includes: Determining the minimum braking distance of the target driverless mining vehicle at the current moment through the following formula: Wherein, S is the minimum braking distance of the target driverless mining vehicle at the current moment, v0 is the initial speed, f is the rolling resistance coefficient, is the slope of the road, f(v0) represents the target relationship value between the actual average deceleration corresponding to the target driverless mining vehicle at the initial speed and the braking performance index, and A is the braking performance index of the target driverless mining vehicle.

3. The method according to claim 2, characterized in that, where a is the actual average deceleration of the target driverless mining vehicle; the target relationship value is the ratio between the actual average deceleration and the braking performance index of the target driverless mining vehicle at the initial speed, and the braking performance is used to characterize the braking ability of the target driverless mining vehicle.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: When detecting an obstacle, obtaining the target distance between the target driverless mining vehicle and the obstacle at the current moment; When the target distance meets the first preset condition, generating a braking instruction to enable the target driverless mining vehicle to start braking according to the braking instruction.

5. The method according to claim 4, characterized in that, The method further includes: When the target distance is within the first preset range, determining that the target distance meets the first preset condition; wherein, the lower limit of the first preset range is greater than the minimum braking distance.

6. The method according to claim 5, characterized in that, The method further includes: When the target distance is within the second preset range, reducing the speed of the target driverless mining vehicle; wherein, the lower limit value of the second preset range is equal to the upper limit value of the first preset range.

7. An apparatus for obtaining the braking distance of an unmanned mining vehicle, characterized in that, The device includes: An information acquisition module, configured to obtain the vehicle information of the target driverless mining vehicle and the road information at the current moment when the target driverless mining vehicle needs to brake, where the vehicle information includes the initial speed of the target driverless mining vehicle at the current moment, and the road information includes the slope and rolling resistance coefficient of the road; A numerical determination module, configured to obtain the target relationship value corresponding to the actual average deceleration and the braking performance index of the target driverless mining vehicle at the initial speed; wherein, the preset relationship values between the actual average deceleration and the braking performance index at different initial speeds are different; A braking distance determination module, configured to determine the minimum braking distance of the target driverless mining vehicle at the current moment based on the vehicle information, the road information and the target relationship value.

8. The apparatus according to claim 7, characterized in that, The device further includes: A target distance acquisition module, configured to obtain the target distance between the target driverless mining vehicle and the obstacle at the current moment when detecting an obstacle; An instruction generation module, configured to generate a braking instruction when the target distance meets a first preset condition, so that the target driverless mining vehicle starts braking according to the braking instruction.

9. An electronic device, characterized in that, Comprising: At least one processor; A memory for storing executable instructions of the at least one processor; Wherein, the at least one processor is configured to execute the instructions to implement the method according to any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method according to any one of claims 1-6.

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