A method, device, equipment and storage medium for determining a target vehicle distance

Abstract

The present invention discloses a method, apparatus, device and storage medium for determining a target vehicle distance. The method includes: obtaining the drag reduction percentages and driving information of at least three vehicles on the same route; wherein the drag reduction percentage is used to represent the contribution of the vehicle on the same route to reducing wind resistance during platooning; if the driving information meets the preset platooning condition, determining a target vehicle distance range according to the drag reduction percentage and the vehicle distance range solving model; and determining the target vehicle distance according to the driving information and the target vehicle distance range. This technical solution solves the problem that it is difficult to control the economy of platooning. By determining the target vehicle distance, it is beneficial to achieve maximum drag reduction, effectively save energy, and improve the efficiency of platooning.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and particularly to a method, device, equipment and storage medium for determining a target vehicle distance. Background Art

[0002] With the development of the freight market and the increasing improvement of highway facilities, the formation driving condition is becoming more and more important in the field of multi-vehicle intelligent networking. Formation driving refers to the condition that three or more vehicles on the same route maintain a constant distance or time interval and drive at a uniform high speed.

[0003] For the formation driving condition, the existing technology usually calculates the air resistance of each vehicle on the same route and the vehicle fleet according to the driving states of the vehicles on the same route in the fleet, and then determines the equivalent fuel economy of the vehicle fleet. However, currently, the vehicle distance control of each vehicle on the same route is usually adjusted by the driver based on driving experience, and it is difficult to achieve the maximum reduction of resistance during the formation driving process, and thus it is impossible to maximize energy conservation. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for determining a target vehicle distance to solve the problem that the economy of formation driving is difficult to control. By determining the target vehicle distance, it is beneficial to achieve the maximum reduction of resistance, improve the efficiency of formation driving while effectively saving energy.

[0005] According to one aspect of the present invention, there is provided a method for determining a target vehicle distance, the method comprising:

[0006] Obtaining the resistance reduction percentage and driving information of at least three vehicles on the same route; wherein, the resistance reduction percentage is used to represent the contribution of the vehicle on the same route to reducing wind resistance during formation driving;

[0007] If the driving information meets the preset formation driving condition, determining a target vehicle distance range according to the resistance reduction percentage and the vehicle distance range solving model;

[0008] Determining the target vehicle distance according to the driving information and the target vehicle distance range.

[0009] According to another aspect of the present invention, there is provided a device for determining a target vehicle distance, the device comprising:

[0010] An information acquisition module, configured to obtain the resistance reduction percentage and driving information of at least three vehicles on the same route; wherein, the resistance reduction percentage is used to represent the contribution of the vehicle on the same route to reducing wind resistance during formation driving;

[0011] A target vehicle distance range determination module, configured to determine a target vehicle distance range according to the resistance reduction percentage and the vehicle distance range solving model if the driving information meets the preset formation driving condition;

[0012] A target vehicle distance determination module, configured to determine a target vehicle distance according to the driving information and the target vehicle distance range.

[0013] According to another aspect of the present invention, there is provided an electronic device, including:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the method for determining the target vehicle distance according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the method for determining the target vehicle distance according to any embodiment of the present invention when executed.

[0018] The technical solution of the embodiment of the present invention obtains the drag reduction percentages and driving information of at least three same-route vehicles. When the driving information meets the preset formation driving conditions, the target vehicle distance range is determined according to the drag reduction percentage and the vehicle distance range solution model, and then the target vehicle distance is determined according to the driving information and the target vehicle distance range. This solution can solve the problem that it is difficult to control the economy of formation driving. By determining the target vehicle distance, it is beneficial to achieve maximum drag reduction, effectively saving energy while improving the efficiency of formation driving.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0021] Figure 1 is a flowchart of a method for determining a target vehicle distance according to Embodiment 1 of the present invention;

[0022] Figure 2 is a schematic structural diagram of a device for determining a target vehicle distance according to Embodiment 2 of the present invention;

[0023] Figure 3 It is a schematic structural diagram of an electronic device for implementing the method for determining the target vehicle distance in the embodiments of the present invention. Specific embodiments

[0024] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0026] Embodiment 1

[0027] Figure 1 For Embodiment 1 of the present invention, a flowchart of a method for determining a target vehicle distance is provided. This embodiment is applicable to the situation of determining the target vehicle distance. This method can be executed by a device for determining the target vehicle distance. The device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device. As Figure 1 shown, the method includes:

[0028] S110. Obtain the drag reduction percentages and driving information of at least three same-route vehicles.

[0029] This solution can be executed by a vehicle management platform. The vehicle management platform can obtain the driving information such as the position, speed, vehicle distance, load, and driving road conditions of each same-route vehicle through an in-vehicle system. Among them, the same-route vehicle can be any one of light, medium, or heavy type vehicles. The vehicle management platform can set the drag reduction percentage according to the fuel-saving target of each same-route vehicle. Among them, the drag reduction percentage can represent the contribution of the same-route vehicle to reducing wind resistance during formation driving.

[0030] The vehicle management platform can determine whether each co - traveling vehicle meets the conditions for platooning according to the driving information of each co - traveling vehicle. For example, the vehicle management platform can obtain road condition information through the on - vehicle system or vehicle - to - everything (V2X) navigation of each co - traveling vehicle, and determine whether to conduct platooning according to the road condition information. It can be understood that platooning is more suitable on flat and open roads, and it is difficult to reflect the advantage of reducing wind resistance of platooning on congested and rough roads.

[0031] Optionally, after obtaining the wind resistance reduction percentages and driving information of at least three co - traveling vehicles, the method further includes:

[0032] If the driving information does not meet the preset platooning conditions, then take the minimum safe distance between each co - traveling vehicle and its adjacent co - traveling vehicle as the target vehicle distance of each co - traveling vehicle.

[0033] Among them, the platooning conditions may include at least one of evaluation criteria such as vehicle speed, road conditions, and vehicle spacing. The platooning conditions may include that the vehicle speeds of each co - traveling vehicle are all greater than the vehicle speed threshold, such as 60 km / h, may also include that the road conditions are open and flat, and may also include that the vehicle spacing is within the preset vehicle spacing range, such as [6 m, 12 m].

[0034] If, based on the driving information, the vehicle management platform evaluates that each co - traveling vehicle does not meet the platooning conditions, then the minimum safe distance between adjacent vehicles can be taken as the target vehicle distance to minimize wind resistance while ensuring driving safety.

[0035] S120: If the driving information meets the preset platooning conditions, then determine the target vehicle distance range according to the wind resistance reduction percentage and the vehicle distance range solving model.

[0036] If the driving information meets the platooning conditions, the vehicle management platform can send matching driving instructions to each co - traveling vehicle to adjust the vehicle spacing between co - traveling vehicles in the platoon, thereby realizing platooning. The vehicle management platform can input the wind resistance reduction percentage into the vehicle distance range solving model to obtain the target vehicle distance range. Among them, the vehicle distance range solving model can be the correlation between vehicle distance and wind resistance reduction percentage constructed based on historical platooning data.

[0037] Exemplarily, the step of if the driving information meets the preset platooning conditions, then determine the target vehicle distance range according to the wind resistance reduction percentage and the vehicle distance range solving model includes:

[0038] If the road condition recognition result is normal, the vehicle speeds of each co - traveling vehicle are all greater than or equal to the preset speed threshold, and each vehicle distance is within the preset vehicle distance range, then determine the target vehicle distance range according to the wind resistance reduction percentage and the vehicle distance range solving model.

[0039] In this solution, the driving information may include road condition recognition results, vehicle distance information, and vehicle speed information. Among them, the vehicle distance information may include the vehicle distances between the same-route vehicles in formation driving and adjacent same-route vehicles. The vehicle speed information may include the vehicle speeds of the same-route vehicles in formation driving.

[0040] It is easy to understand that the vehicle management platform can obtain the driving road condition information of each same-route vehicle based on vehicle networking navigation, in-vehicle vision sensors, radar sensors, etc. According to the driving road condition information of each same-route vehicle, the vehicle management platform can determine the road condition recognition result. If the driving road is open and flat, it can be determined that the road condition recognition result is normal. If the driving road has rough or congested conditions, it can be determined that the road condition recognition result is abnormal.

[0041] If the road condition recognition result is normal, the vehicle speeds of all same-route vehicles are greater than or equal to the preset speed threshold, and all vehicle distances are within the preset vehicle distance range, it indicates that the driving environment of each same-route vehicle is suitable for formation driving. For example, 5 same-route vehicles maintain a distance of 10 meters and are all driving at a speed of 80 km / h uniformly on a flat and open highway. The vehicle management platform can determine that these 5 same-route vehicles can perform formation driving, and determine the target vehicle distance range according to the drag reduction percentage and vehicle distance range solution model to achieve maximum drag reduction.

[0042] This solution comprehensively considers the evaluation conditions for formation driving and can accurately judge whether each same-route vehicle is suitable for formation driving.

[0043] In this solution, optionally, the vehicle distance range solution model includes the correlation between the drag reduction percentage and the vehicle distance; the correlation between the drag reduction percentage and the vehicle distance is:

[0044] y = ax 2 + bx + c, x ∈ (l, 3L);

[0045] where y represents the drag reduction percentage, x represents the vehicle distance, l represents the minimum safety distance between adjacent same-route vehicles, and L represents the vehicle length.

[0046] This solution uses a quadratic function to fit the correlation between the drag reduction percentage and the vehicle distance, selects matching coefficient values, accurately calculates the target vehicle distance, and thus is conducive to maximizing energy loss reduction.

[0047] Based on the above solution, optionally, the vehicle distance range solution model further includes at least one of a leading vehicle coefficient group, a middle vehicle coefficient group, a trailing vehicle coefficient group, and a queue coefficient group; where the coefficient group includes a quadratic term coefficient range, a linear term coefficient range, and a constant term coefficient range.

[0048] Specifically, the vehicle distance range solution model can be as shown in Table 1 below:

[0049] Table 1:

[0050]

[0051] Among them, the leading vehicle can be a vehicle on the same route at the head of a formation driving in a queue, the trailing vehicle can be a vehicle on the same route at the end of the queue, and the middle vehicles can be all the vehicles between the leading vehicle and the trailing vehicle in the queue. The middle vehicles can include one vehicle on the same route or multiple vehicles on the same route.

[0052] The vehicle management platform can calculate the target vehicle distance range according to the coefficient ranges in each coefficient group according to the correlation between the drag reduction percentage and the vehicle distance. Each vehicle on the same route can adjust the vehicle distance according to the target vehicle distance range.

[0053] Regarding the correlation between the drag reduction percentage and the vehicle distance, this solution can configure different coefficient ranges for vehicles on the same route at different positions in the queue, and can also configure a coefficient range for the entire queue, which is beneficial to setting the drag reduction percentage from multiple dimensions, thereby improving the economy of a single vehicle on the same route or the entire queue.

[0054] S130. Determine the target vehicle distance according to the driving information and the target vehicle distance range.

[0055] According to the current vehicle distance between each vehicle on the same route and the adjacent vehicle on the same route and the target vehicle distance range, the vehicle management platform can adjust the driving speed of each vehicle on the same route to adjust the vehicle distance between each vehicle on the same route and the adjacent vehicle on the same route to within the target vehicle distance range. The vehicle management platform can also use the central vehicle distance and the boundary vehicle distance of the target vehicle distance range as the target vehicle distance to adjust the vehicle distance between each vehicle on the same route and the adjacent vehicle on the same route.

[0056] In this solution, optionally, the determining the target vehicle distance according to the driving information and the target vehicle distance range includes:

[0057] Determine the target vehicle distance of each vehicle on the same route in the target vehicle distance range between each vehicle on the same route and the adjacent vehicle on the same route according to the driving information of each vehicle on the same route.

[0058] The vehicle management platform can randomly select a vehicle distance in the target vehicle distance range as the target vehicle distance of each vehicle on the same route, or can also select a fixed-position vehicle distance in the target vehicle distance range as the target vehicle distance of each vehicle on the same route. For example, select the value at the central position of the target vehicle distance range as the target vehicle distance.

[0059] This solution can determine the target vehicle distance in the target vehicle distance range so that each vehicle on the same route drives in formation according to the target vehicle distance, which is beneficial to determining the optimal vehicle distance in the target vehicle distance range.

[0060] In a feasible solution, the drag reduction percentage includes at least one of the leading vehicle drag reduction percentage, the middle vehicle drag reduction percentage, the trailing vehicle drag reduction percentage, and the platoon drag reduction percentage;

[0061] Determining the target vehicle distance range according to the drag reduction percentage and the vehicle distance range solving model includes:

[0062] Inputting the drag reduction percentage into the vehicle distance range solving model to determine at least one reference vehicle distance range;

[0063] According to the at least one reference vehicle distance range and the pre-acquired drag reduction ratio of platoon driving, determine the target vehicle distance range between each co-routed vehicle and the adjacent co-routed vehicle during platoon driving.

[0064] The vehicle management platform can set at least one of the leading vehicle drag reduction percentage, the middle vehicle drag reduction percentage, the trailing vehicle drag reduction percentage, and the platoon drag reduction percentage. If the vehicle management platform does not set all 4 drag reduction percentages, taking the example that the vehicle management platform only sets the platoon drag reduction percentage, the vehicle management platform can obtain the reference vehicle distance range of the platoon after inputting the platoon drag reduction percentage into the vehicle distance range solving model.

[0065] The vehicle management platform can determine the leading vehicle drag reduction percentage, the middle vehicle drag reduction percentage, and the trailing vehicle drag reduction percentage according to the drag reduction ratio of platoon driving. Among them, the drag reduction ratio of platoon driving can be the ratio of the drag reduction percentages of the leading vehicle, the middle vehicle, the trailing vehicle, and the platoon. Assuming that the vehicle management platform sets the platoon drag reduction percentage to 25%, and assuming that the drag reduction ratio of platoon driving is 2:8:6:5, the middle vehicle drag reduction percentage can be obtained as 40%, the leading vehicle drag reduction percentage is 10%, and the trailing vehicle drag reduction percentage is 30%. The vehicle management platform can respectively determine the reference vehicle distance ranges of the leading vehicle, the middle vehicle, and the trailing vehicle in the platoon according to each drag reduction percentage, and then can determine the target vehicle distance range between each co-routed vehicle and the adjacent co-routed vehicle during platoon driving according to the reference vehicle distance ranges of the platoon, the leading vehicle, the middle vehicle, and the trailing vehicle. For example, the vehicle management platform can calculate the intersection of the reference vehicle distance ranges of the platoon, the leading vehicle, the middle vehicle, and the trailing vehicle to further narrow the reference vehicle distance ranges of the co-routed vehicles at each position.

[0066] If the vehicle management platform sets each drag reduction percentage, the vehicle management platform can calculate the reference vehicle distance ranges of the platoon, the leading vehicle, the middle vehicle, and the trailing vehicle respectively through the vehicle distance range solving model. The vehicle management platform can directly determine the target vehicle distance range between each co-routed vehicle and the adjacent co-routed vehicle during platoon driving according to the reference vehicle distance ranges of the platoon, the leading vehicle, the middle vehicle, and the trailing vehicle. For example, calculate the intersection of the reference vehicle distance ranges of the platoon, the leading vehicle, the middle vehicle, and the trailing vehicle as the target vehicle distance range.

[0067] The vehicle management platform can also assign weights to each reference vehicle distance range according to the drag reduction ratio of platoon driving, and obtain the target vehicle distance range between each same-route vehicle and the adjacent same-route vehicle in platoon driving through weighted calculation.

[0068] This solution can meet the drag reduction requirements of same-route vehicles at each position in platoon driving, which is conducive to achieving the optimal drag reduction of the queue and realizing global energy conservation.

[0069] This technical solution obtains the drag reduction percentages and driving information of at least three same-route vehicles. When the driving information meets the preset platoon driving conditions, it determines the target vehicle distance range according to the drag reduction percentage and the vehicle distance range solution model, and then determines the target vehicle distance according to the driving information and the target vehicle distance range. This solution can solve the problem that it is difficult to control the economy of platoon driving. By determining the target vehicle distance, it is conducive to achieving maximum drag reduction, improving the efficiency of platoon driving while effectively saving energy.

[0070] Embodiment 2

[0071] Figure 2 It is a schematic structural diagram of a device for determining a target vehicle distance provided in Embodiment 2 of the present invention. As Figure 2 shown, the device includes:

[0072] An information acquisition module 210, configured to acquire the drag reduction percentages and driving information of at least three same-route vehicles; wherein, the drag reduction percentage is used to represent the contribution of the same-route vehicle to reducing wind resistance during platoon driving;

[0073] A target vehicle distance range determination module 220, configured to determine the target vehicle distance range according to the drag reduction percentage and the vehicle distance range solution model if the driving information meets the preset platoon driving conditions;

[0074] A target vehicle distance determination module 230, configured to determine the target vehicle distance according to the driving information and the target vehicle distance range.

[0075] In this solution, optionally, the vehicle distance range solution model includes the correlation between the drag reduction percentage and the vehicle distance; the correlation between the drag reduction percentage and the vehicle distance is:

[0076] y = ax 2 + bx + c, x ∈ (l, 3L);

[0077] wherein, y represents the drag reduction percentage, x represents the vehicle distance, l represents the minimum safety distance between adjacent same-route vehicles, and L represents the vehicle length.

[0078] Based on the above solution, optionally, the vehicle distance range solving model further includes at least one of a leading vehicle coefficient group, a middle vehicle coefficient group, a trailing vehicle coefficient group, and a queue coefficient group; wherein, each coefficient group includes a quadratic term coefficient range, a linear term coefficient range, and a constant term coefficient range.

[0079] In a feasible solution, the drag reduction percentage includes at least one of a leading vehicle drag reduction percentage, a middle vehicle drag reduction percentage, a trailing vehicle drag reduction percentage, and a queue drag reduction percentage;

[0080] The target vehicle distance range determining module 220 is specifically configured to:

[0081] Input the drag reduction percentage into the vehicle distance range solving model to determine at least one reference vehicle distance range;

[0082] According to the at least one reference vehicle distance range and the pre-acquired drag reduction ratio of formation driving, determine the target vehicle distance range between each vehicle in the formation driving and the adjacent vehicle in the same route.

[0083] Based on the above solution, optionally, the target vehicle distance determining module 230 is specifically configured to:

[0084] According to the driving information of each vehicle in the same route, determine the target vehicle distance of each vehicle in the target vehicle distance range between each vehicle in the same route and the adjacent vehicle in the same route.

[0085] In a preferred solution, the driving information includes a road condition recognition result, a vehicle distance information, and a vehicle speed information; wherein, the vehicle distance information includes the vehicle distances between each vehicle in the formation driving and the adjacent vehicle in the same route; the vehicle speed information includes the vehicle speeds of each vehicle in the formation driving.

[0086] The target vehicle distance range determining module 220 is specifically configured to:

[0087] If the road condition recognition result is normal, the vehicle speeds of all vehicles in the same route are greater than or equal to the preset speed threshold, and all vehicle distances are within the preset vehicle distance range, then determine the target vehicle distance range according to the drag reduction percentage and the vehicle distance range solving model.

[0088] In another feasible solution, the information acquisition module 210 is further configured to:

[0089] If the driving information does not meet the preset formation driving conditions, then use the minimum safety distance between each vehicle in the same route and the adjacent vehicle in the same route as the target vehicle distance of each vehicle in the same route.

[0090] The target vehicle distance determining device provided by the embodiments of the present invention can execute the target vehicle distance determining method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0091] Embodiment 3

[0092] Figure 3 FIG. shows a schematic structural diagram of an electronic device 310 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described herein and / or claimed.

[0093] As Figure 3 shown, the electronic device 310 includes at least one processor 311, and a memory communicatively connected to the at least one processor 311, such as a read-only memory (ROM) 312, a random access memory (RAM) 313, etc. The memory stores a computer program executable by the at least one processor. The processor 311 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 312 or the computer program loaded from the storage unit 318 into the random access memory (RAM) 313. In the RAM 313, various programs and data required for the operation of the electronic device 310 can also be stored. The processor 311, the ROM 312, and the RAM 313 are connected to each other through a bus 314. An input / output (I / O) interface 315 is also connected to the bus 314.

[0094] A plurality of components in the electronic device 310 are connected to the I / O interface 315, including: an input unit 316, such as a keyboard, a mouse, etc.; an output unit 317, such as various types of displays, speakers, etc.; a storage unit 318, such as a magnetic disk, an optical disk, etc.; and a communication unit 319, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 319 allows the electronic device 310 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0095] The processor 311 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 311 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 311 executes the various methods and processes described above, such as the method for determining the target vehicle distance.

[0096] In some embodiments, the method for determining the target vehicle distance can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 318. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 310 via the ROM 312 and / or the communication unit 319. When the computer program is loaded into the RAM 313 and executed by the processor 311, one or more steps of the method for determining the target vehicle distance described above can be performed. Alternatively, in other embodiments, the processor 311 can be configured to perform the method for determining the target vehicle distance by any other suitable means (e.g., by means of firmware).

[0097] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0098] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer programs are executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0099] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0100] In order to provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0101] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0102] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is created by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0103] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0104] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining a target vehicle distance, characterized in that, the method includes: Obtaining the drag reduction percentage and driving information of at least three same-route vehicles; wherein, the drag reduction percentage is used to represent the contribution of the same-route vehicles to reducing wind resistance during platoon driving; the driving information includes a road condition recognition result, vehicle distance information, and vehicle speed information; the vehicle distance information includes the vehicle distances between each same-route vehicle and the adjacent same-route vehicle during platoon driving; the vehicle speed information includes the vehicle speeds of each same-route vehicle during platoon driving; If the road condition recognition result is normal, the vehicle speeds of all same-route vehicles are greater than or equal to a preset speed threshold, and all vehicle distances are within a preset vehicle distance range, then a target vehicle distance range is determined according to the drag reduction percentage and the vehicle distance range solving model; the vehicle distance range solving model is a correlation between the drag reduction percentage and the vehicle distance constructed based on historical platoon driving data; Determining the target vehicle distance according to the driving information and the target vehicle distance range; wherein, the correlation between the drag reduction percentage and the vehicle distance is: y = ax 2 + bx + c, x ∈ (l, 3L); wherein, y represents the drag reduction percentage, x represents the vehicle distance, l represents the minimum safety distance between adjacent same-route vehicles, and L represents the vehicle length.

2. The method according to claim 1, characterized in that, The vehicle distance range solving model further includes at least one of a leading vehicle coefficient group, a middle vehicle coefficient group, a trailing vehicle coefficient group, and a queue coefficient group; wherein, the coefficient group includes a quadratic term coefficient range, a linear term coefficient range, and a constant term coefficient range.

3. The method according to claim 2, characterized in that, The drag reduction percentage includes at least one of a leading vehicle drag reduction percentage, a middle vehicle drag reduction percentage, a trailing vehicle drag reduction percentage, and a queue drag reduction percentage; The determining the target vehicle distance range according to the drag reduction percentage and the vehicle distance range solving model includes: Inputting the drag reduction percentage into the vehicle distance range solving model to determine at least one reference vehicle distance range; Determining the target vehicle distance range between each same-route vehicle and the adjacent same-route vehicle during platoon driving according to the at least one reference vehicle distance range and the pre-obtained platoon driving drag reduction ratio.

4. The method according to claim 3, characterized in that, The determining the target vehicle distance according to the driving information and the target vehicle distance range includes: Determining the target vehicle distance of each same-route vehicle within the target vehicle distance range between each same-route vehicle and the adjacent same-route vehicle according to the driving information of each same-route vehicle.

5. The method according to claim 1, characterized in that, After obtaining the drag reduction percentage and driving information of at least three same-route vehicles, the method further includes: If the driving information does not meet the preset platoon driving conditions, then taking the minimum safety distance between each same-route vehicle and the adjacent same-route vehicle as the target vehicle distance of each same-route vehicle.

6. A device for determining a target vehicle distance, characterized in that, the device includes: An information acquisition module, configured to acquire the drag reduction percentages and driving information of at least three same-route vehicles; wherein, the drag reduction percentage is used to represent the contribution of the same-route vehicle to reducing wind resistance during platooning; the driving information includes a road condition recognition result, a vehicle distance information, and a vehicle speed information; the vehicle distance information includes the vehicle distances between each same-route vehicle and its adjacent same-route vehicle during platooning; the vehicle speed information includes the vehicle speeds of each same-route vehicle during platooning; A target vehicle distance range determination module, configured to, if the road condition recognition result is normal, the vehicle speeds of all same-route vehicles are greater than or equal to a preset speed threshold, and all vehicle distances are within a preset vehicle distance range, then determine a target vehicle distance range according to the drag reduction percentage and the vehicle distance range solution model; the vehicle distance range solution model is a correlation between the drag reduction percentage and the vehicle distance constructed based on historical platooning data; A target vehicle distance determination module, configured to determine a target vehicle distance according to the driving information and the target vehicle distance range; wherein, the correlation between the drag reduction percentage and the vehicle distance is: y = ax 2 + bx + c, x ∈ (l, 3L); wherein, y represents the drag reduction percentage, x represents the vehicle distance, l represents the minimum safe distance between adjacent same-route vehicles, and L represents the vehicle length.

7. An electronic device, characterized in that, the electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the target vehicle distance according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the method for determining the target vehicle distance according to any one of claims 1-5 when executed by a processor.

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