Wind resistance based two-wheeled vehicle navigation method, apparatus, device, and storage medium

Abstract

The application relates to the technical field of navigation, and provides a two-wheeled vehicle navigation method and device based on wind resistance, equipment and a storage medium. The method comprises the following steps: obtaining a departure place and a destination; planning a passable path of the two-wheeled vehicle according to the departure place and the destination; determining a grid area passed through by the passable path; obtaining meteorological data of the grid area; predicting energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area and according to a two-wheeled vehicle human riding model; wherein the two-wheeled vehicle human riding model is constructed in combination with the meteorological data; and determining an optimal path based on the energy consumption corresponding to different passable paths. The application enables a user to save the power of the two-wheeled vehicle by selecting the optimal path.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of navigation, and particularly relates to a two-wheeled vehicle navigation method and device based on wind resistance, equipment and a storage medium. BACKGROUND

[0002] The existing two-wheeled vehicle path planning method often gives all passable paths according to the starting point and destination of the user for the user to refer to, and then determines the optimal path from all passable paths according to the distance or estimated time cost.

[0003] However, the inventor finds that although the distance or time cost can reflect the power consumption to some extent, the power consumption of the two-wheeled vehicle during the driving process is affected by meteorological factors, so the power consumption of the two-wheeled vehicle cannot be accurately reflected only according to the distance or estimated time cost, that is, the optimal path determined in this way cannot truly represent the minimum power consumption of the two-wheeled vehicle. SUMMARY

[0004] In view of the above technical problems, the present application aims to provide a two-wheeled vehicle navigation method and device based on wind resistance, equipment and a storage medium, which aims to solve the technical problem that the existing optimal path cannot truly represent the minimum power consumption of the two-wheeled vehicle without considering meteorological factors.

[0005] In a first aspect, the embodiments of the present application provide a two-wheeled vehicle navigation method based on wind resistance, comprising:

[0006] obtaining a starting point and a destination;

[0007] planning a passable path of the two-wheeled vehicle according to the starting point and the destination;

[0008] determining a grid area passed by the passable path;

[0009] obtaining meteorological data of the grid area;

[0010] predicting the energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area and according to a two-wheeled vehicle human riding model, wherein the two-wheeled vehicle human riding model is constructed in combination with meteorological data;

[0011] determining an optimal path based on the energy consumption corresponding to different passable paths.

[0012] Further, the two-wheeled vehicle human riding model is:

[0013]

[0014] F m =C r Fs =C r Mgcosθ

[0015]

[0016]

[0017] F-F' f -F m -F w -F' g =Ma

[0018]

[0019]

[0020] Wherein, F f represents the wind, represents the real-time wind speed at the altitude, and φ represents the wind force F f generated by nature, and the angle between the vehicle body advancing direction, F m represents the friction between the tire of the two-wheeled vehicle and the ground, C r represents the rolling friction coefficient between the tire of the two-wheeled vehicle and the ground, F s represents the ground support force, M represents the total mass of the human-vehicle system, and g represents the gravitational acceleration, F g represents the gravity of the human-vehicle system, and θ represents the angle between the road surface and the horizontal plane, F w represents the air resistance received by the human-vehicle system, ρ represents the air density at the altitude, V c represents the speed of the two-wheeled vehicle, A represents the frontal area of the human-vehicle system calculated by using the human riding model, C w represents the wind resistance coefficient of the two-wheeled vehicle, a represents the acceleration, V2 is the speed of the two-wheeled vehicle at t2, V1 is the speed of the two-wheeled vehicle at t1, F is the motor driving force of the two-wheeled vehicle, S is the driving distance estimated by the planned route, Л is the motor conversion efficiency, and W is the energy consumption, which represents the size of the work done by the motor driving force of the two-wheeled vehicle.

[0021] Further, the human riding model is:

[0022] The frontal area of the human-vehicle system = proportional coefficient * (body surface area + area increased by clothing thickness); wherein the body surface area = first coefficient * height + second coefficient * weight + third coefficient.

[0023] Further, after the step of determining the optimal path based on the energy consumption corresponding to different passable paths, the method further comprises:

[0024] obtaining the remaining power of the two-wheeled vehicle;

[0025] comparing the remaining power with the energy consumption corresponding to the optimal path;

[0026] if the remaining power is less than the energy consumption corresponding to the optimal path, issuing a charging prompt signal or issuing a return prompt signal or issuing a destination change prompt signal.

[0027] Further, after the step of planning the passable path of the two-wheeled vehicle according to the departure place and the destination, the method further comprises:

[0028] obtaining geographical data of the passable path;

[0029] calculating a total wind force on the passable path according to the geographical data of the passable path and meteorological data of the passable path, wherein the meteorological data of the passable path is determined according to meteorological data of a grid region passed through by the passable path;

[0030] The step of determining the optimal path based on the energy consumption corresponding to different passable paths comprises:

[0031] determining the optimal path according to the total wind force on different passable paths and the energy consumption corresponding to different passable paths.

[0032] Further, after the step of determining the optimal path based on the energy consumption corresponding to different passable paths, the method further comprises:

[0033] judging whether the wind force of any grid region of the optimal path is greater than a preset level or whether the rainfall of any grid region is greater than a preset threshold;

[0034] if the wind force of any grid region of the optimal path is greater than the preset level or the rainfall of any grid region is greater than the preset threshold, issuing a signal of driving danger.

[0035] Further, after the step of planning the passable path of the two-wheeled vehicle according to the departure place and the destination, the method further comprises:

[0036] obtaining geographical data of the passable path;

[0037] obtaining the height of a tree on the passable path according to the geographical data of the passable path;

[0038] evaluating a falling risk coefficient of the tree according to the height of the tree and meteorological data of the grid region;

[0039] calculating a proportion of a tree falling risk section to total sections according to the falling risk coefficient of the tree;

[0040] The step of determining the optimal path based on the energy consumption corresponding to different passable paths comprises:

[0041] The optimal path is determined based on the proportion of tree falling danger sections corresponding to different passable paths in total sections and the energy consumption corresponding to different passable paths.

[0042] In a second aspect, an embodiment of the present application provides a two-wheeled vehicle navigation device based on wind resistance, comprising:

[0043] An acquisition module is configured to acquire a departure location and a destination;

[0044] A passable path planning module is configured to plan a passable path of the two-wheeled vehicle according to the departure location and the destination;

[0045] A determination module is configured to determine a grid area passed through by the passable path;

[0046] A meteorological data acquisition module is configured to acquire meteorological data of the grid area;

[0047] An energy consumption calculation module is configured to predict energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area and according to a two-wheeled vehicle human riding model; the two-wheeled vehicle human riding model is constructed in combination with the meteorological data;

[0048] An optimal path determination module is configured to determine an optimal path based on the energy consumption corresponding to different passable paths.

[0049] In a third aspect, an embodiment of the present application provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the two-wheeled vehicle navigation method based on wind resistance when executing the computer program.

[0050] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the two-wheeled vehicle navigation method based on wind resistance when executed by a processor.

[0051] The embodiment of the present application provides a two-wheeled vehicle navigation method based on wind resistance, which comprises the following steps: planning a passable path of the two-wheeled vehicle according to a starting place and a destination; determining a grid area passed by the passable path; obtaining meteorological data of the grid area; predicting energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area and a two-wheeled vehicle human riding model; wherein the two-wheeled vehicle human riding model is constructed in combination with the meteorological data; and determining an optimal path based on the energy consumption corresponding to different passable paths. In this way, the meteorological data of each area on the passable path is considered in detail for energy consumption of the two-wheeled vehicle, and the optimal path is determined according to the energy consumption of the two-wheeled vehicle on each passable path, so that the user can save the power of the two-wheeled vehicle by selecting the optimal path. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0053] Figure 1 is a flowchart of the two-wheeled vehicle navigation method based on wind resistance provided by the embodiment of the present application;

[0054] Figure 2 is a flowchart of the two-wheeled vehicle navigation method based on wind resistance provided by another embodiment of the present application;

[0055] Figure 3 is a structural schematic diagram of the two-wheeled vehicle navigation device based on wind resistance provided by the embodiment of the present application;

[0056] Figure 4 is a structural schematic block diagram of the computer device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0058] Those skilled in the art can understand that the singular forms "a", "an", "the" and "said" used herein also include the plural forms unless specifically stated otherwise. It should be further understood that the use of the phrase "comprising" in the specification of the present application means that the features, integers, steps, operations, elements, modules and / or components exist, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, modules, components and / or groups thereof. It should be understood that when we say an element is "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or there can be an intermediate element. In addition, "connected" or "coupled" used herein can include wireless connection or wireless coupling. The phrase "and / or" used herein includes all or any module of the associated list and all combinations thereof.

[0059] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as that generally understood by those skilled in the art to which the present application belongs. It should also be understood that terms such as those defined in a general dictionary should be understood to have meanings consistent with those in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as such.

[0060] Before implementing the embodiments of the present application, first, the entire area needs to be divided into several areas according to the chessboard net format distribution mode, an area is composed of M grids (it can be M k*k areas), and each area is distributed with an meteorological element collection point, which can finely reflect the meteorological elements such as air, precipitation, relative humidity, etc. of each grid of the city for local meteorological service and weather forecast.

[0061] Please refer to Figure 1 The embodiments of the present application provide a two-wheeled vehicle navigation method based on wind resistance, comprising steps S1-S6

[0062] S1, obtaining a departure place and a destination;

[0063] S2, planning a passable path of the two-wheeled vehicle according to the departure place and the destination;

[0064] S3, determining a grid area passed by the passable path;

[0065] S4, obtaining meteorological data of the grid area;

[0066] S5, predicting energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area according to a two-wheeled vehicle human riding model; wherein the two-wheeled vehicle human riding model is constructed in combination with the meteorological data;

[0067] S6, determining an optimal path based on energy consumption corresponding to different passable paths.

[0068] In the embodiments of the present application, the wind resistance based two-wheeled vehicle navigation method is applied to a navigation software, which can be installed on a smart system of the two-wheeled vehicle or a mobile terminal such as a mobile phone. The two-wheeled vehicle can be an electric bicycle, a motorcycle, etc. The departure location can be obtained by GPS positioning, and the destination can be obtained by user input. The number of passable paths of the two-wheeled vehicle planned according to the departure location and the destination is determined according to actual conditions, such as one, two, three, etc. If the passable paths include two or more, the energy consumption of the two-wheeled vehicle on each passable path needs to be calculated. The energy consumption of the two-wheeled vehicle on a passable path is calculated according to the following manner:

[0069] Suppose a passable path is path A, the grid areas passed by path A need to be determined, for example, path A passes through grid area 1, grid area 2 and grid area 3. Then, the meteorological data of each grid area is obtained. For example, the meteorological data of grid area 1, the meteorological data of grid area 2 and the meteorological data of grid area 3 are obtained. Next, based on the meteorological data of grid area 1, the energy consumption of the two-wheeled vehicle in grid area 1 is predicted according to the two-wheeled vehicle human riding model; based on the meteorological data of grid area 2, the energy consumption of the two-wheeled vehicle in grid area 2 is predicted according to the two-wheeled vehicle human riding model; based on the meteorological data of grid area 3, the energy consumption of the two-wheeled vehicle in grid area 3 is predicted according to the two-wheeled vehicle human riding model. Finally, the energy consumptions of the two-wheeled vehicle in grid area 1, grid area 2 and grid area 3 are added to obtain the energy consumption of the two-wheeled vehicle on path A.

[0070] In one embodiment, if the planned passable paths include path A, path B and path C, after the energy consumptions of the two-wheeled vehicle on path A, path B and path C are calculated respectively, the energy consumptions of the three paths are compared, and the path corresponding to the minimum energy consumption is taken as the optimal path.

[0071] The embodiments of the present application consider in detail the meteorological conditions of each area on the passable path and the energy consumption of the two-wheeled vehicle, and determine the optimal path according to the energy consumption of the two-wheeled vehicle on each passable path, so that the user can save the power of the two-wheeled vehicle by selecting the optimal path.

[0072] In one embodiment, the two-wheeled vehicle human riding model is as follows:

[0073]

[0074] Fm =C r F s =C r Mgcosθ

[0075] F′ g =F g sinθ

[0076]

[0077] F-F′ f -F m -F w -F′ g =Ma

[0078]

[0079]

[0080] Wherein, F f represents the wind force, represents the real-time wind speed at the altitude, and φ represents the angle between the wind force F f generated by nature and the forward direction of the vehicle body, F m represents the friction between the tires of the two-wheeled vehicle and the ground, C r represents the rolling friction coefficient between the tires of the two-wheeled vehicle and the ground, F s represents the ground support force, M represents the total mass of the human-vehicle system, and g represents the acceleration of gravity, F g represents the gravity of the human-vehicle system, and θ represents the angle between the road surface and the horizontal plane, F w represents the air resistance received by the human-vehicle system, ρ represents the air density at the altitude, V c represents the speed of the two-wheeled vehicle, A represents the frontal area of the human-vehicle system calculated by using the human riding model, C w represents the wind resistance coefficient of the two-wheeled vehicle, a represents the acceleration, V2 is the speed of the two-wheeled vehicle at t2, V1 is the speed of the two-wheeled vehicle at t1, F is the motor driving force of the two-wheeled vehicle, S is the driving distance estimated by the planned route, Л is the motor conversion efficiency, and W is the energy consumption, which represents the size of the work done by the motor driving force of the two-wheeled vehicle.

[0081] In the embodiments of the present application, it should be understood that, in the driving process of the two-wheeled vehicle driven by the user, the forces acting on the human-vehicle system of the two-wheeled vehicle include the air resistance F w , the tire-ground friction F m , the gravity F g of the human-vehicle system, the ground support force F s , and the wind force F f generated by nature. When the user is downhill, the gravity needs to be decomposed into the same dynamic force F′g and the support of the ground to the human-vehicle system; when the user climbs uphill, the gravity needs to be decomposed into resistance F' opposite to the direction of motion g and the support of the ground to the human-vehicle system. In addition, the wind force F generated by nature f When the direction of the wind force generated by nature is not the same as the direction of the vehicle body, the wind force generated by nature also needs to be decomposed, including when the angle between the wind force generated by nature and the direction of the vehicle body is in the range of [90°, 270°], the wind force generated by nature needs to be decomposed into resistance F' opposite to the direction of motion f and deflection force perpendicular to the direction of motion, when the angle between the wind force generated by nature and the direction of the vehicle body is in the range of [0°, 90°] or [270°, 360°], the wind force F generated by nature f needs to be decomposed into dynamic force F' in the same direction of motion f and deflection force perpendicular to the direction of motion.

[0082] In the embodiments of the present application, according to the above kinetic model, the corresponding data are collected, for example, the real-time wind speed and air density data are obtained from the meteorological data, and after the corresponding data are collected, the energy consumption of the two-wheeled vehicle in the regional grid is calculated according to the collected data and the preset data.

[0083] In one embodiment, the human riding model is:

[0084] The area of the front projection of the human-vehicle system on the windward surface = the proportionality coefficient * (the body surface area + the area increased by the thickness of the clothes); wherein the body surface area = the first coefficient * height + the second coefficient * weight + the third coefficient.

[0085] In the embodiments of the present application, the human riding model is used to calculate the area of the front projection of the human-vehicle system on the windward surface. The formula for calculating the body surface area of a male is: male body surface area = 0.0057 * height + 0.0121 * weight + 0.0882; wherein the unit of height is centimeters and the unit of weight is kilograms.

[0086] The formula for calculating the body surface area of a female is: female body surface area = 0.0073 * height + 0.0127 * weight - 0.2106; wherein the unit of height is centimeters and the unit of weight is kilograms.

[0087] If men and women are not distinguished, the general body surface area applicable to Chinese people is: general body surface area = 0.0061 * height + 0.0124 * weight - 0.0099; wherein the unit of height is centimeters and the unit of weight is kilograms.

[0088] In the embodiments of the present application, it should be noted that the area of the user sitting on the electric vehicle and the area of the user standing up are different, and therefore the proportion coefficient is added, which can be 85%, and of course can also be other values. In addition, the area of the increase in clothing thickness is negligible in summer, can increase the first area in autumn / spring, and can increase the second area in winter; wherein the second area is greater than the first area.

[0089] In one embodiment, after the step of determining the optimal path based on the energy consumption corresponding to different passable paths, further comprising:

[0090] Obtaining the remaining power of the two-wheeled vehicle;

[0091] Comparing the remaining power with the energy consumption corresponding to the optimal path;

[0092] If the remaining power is less than the energy consumption corresponding to the optimal path, a charging prompt signal is issued or a return prompt signal is issued or a destination change prompt signal is issued.

[0093] In the embodiments of the present application, by comparing the remaining power with the energy consumption corresponding to the optimal path, when the remaining power is less than the energy consumption corresponding to the optimal path, a charging prompt signal, a return prompt signal or a destination change prompt signal is issued, so that the user can be avoided from being in the embarrassing situation of driving to the halfway without power.

[0094] In one embodiment, after the step of planning the passable path of the two-wheeled vehicle according to the departure place and the destination, further comprising:

[0095] Obtaining geographical data of the passable path;

[0096] Calculating the total wind force on the passable path according to the geographical data of the passable path and the meteorological data of the passable path; wherein the meteorological data of the passable path is determined according to the meteorological data of the grid area passed by the passable path;

[0097] The optimal path is determined based on the energy consumption corresponding to different passable paths, comprising:

[0098] Determining the optimal path according to the total wind force corresponding to different passable paths and the energy consumption corresponding to different passable paths.

[0099] In the embodiment of the present application, the geographic data includes open locations such as intersections and squares without building shelter. The optimal path is determined by calculating the total wind of each passable path and according to the total wind of different passable paths and the energy consumption of different passable paths. Since the determination of the optimal path takes into account both wind and energy consumption, a more comfortable and energy-saving passable path can be provided for the user.

[0100] In one embodiment, after the step of determining the optimal path based on the energy consumption of different passable paths, the method further comprises:

[0101] determining whether the wind of any grid area of the optimal path is greater than a preset level or whether the rainfall of any grid area is greater than a preset threshold;

[0102] if the wind of any grid area of the optimal path is greater than a preset level or the rainfall of any grid area is greater than a preset threshold, a signal of driving danger is sent.

[0103] In the embodiment of the present application, for a two-wheeled vehicle, if the wind is too large, the two-wheeled vehicle may be blown over, and if the rainfall is too large, the driving safety is seriously affected. Therefore, when it is detected that the wind of any grid area of the optimal path is greater than a preset level or the rainfall of any grid area is greater than a preset threshold, a signal of driving danger is sent, which can reduce the harm of weather to the user of the two-wheeled vehicle.

[0104] Please refer to Figure 2 In one embodiment, after the step of planning the passable path of the two-wheeled vehicle according to the starting location and the destination, the method further comprises:

[0105] obtaining geographic data of the passable path;

[0106] obtaining the height of trees on the passable path according to the geographic data of the passable path;

[0107] evaluating the falling risk coefficient of the trees according to the height of the trees and the meteorological data of the grid area;

[0108] calculating the proportion of tree falling risk sections to total sections according to the falling risk coefficient of the trees;

[0109] The step of determining the optimal path based on the energy consumption of different passable paths comprises:

[0110] determining the optimal path according to the proportion of tree falling risk sections to total sections of different passable paths and the energy consumption of different passable paths.

[0111] It should be noted that the greater the wind and rainfall, the higher the tree, and the greater the falling risk coefficient, which is a direct proportional relationship. In addition, the falling risk coefficient of the tree can also be evaluated according to the age of the tree.

[0112] In addition, the specific manner of calculating the proportion of the tree falling risk section to the total section according to the tree falling risk coefficient is as follows:

[0113] If there are 100 trees on path A, and the tree falling risk coefficient is greater than 0.8, it is determined that the tree may fall. Assuming that the risk coefficients of tree A, tree B, and tree C are greater than 0.8, and the lengths after falling are 5 meters, 8 meters, and 10 meters, and the total length of path A is 1000 meters, then the proportion of the tree falling risk section to the total section (path A) is (5+8+10) / 1000.

[0114] The embodiments of the present application determine the optimal path by calculating the proportion of the tree falling risk section to the total section corresponding to each path, and then determining the optimal path according to the proportion of the tree falling risk section to the total section corresponding to different passable paths and the energy consumption corresponding to different passable paths. Since the determination of the optimal path combines the proportion of the tree falling risk section to the total section and the energy consumption, the user can be provided with a more secure and energy-saving passable path.

[0115] In one embodiment, the determination of the grid area passed by the passable path comprises:

[0116] Obtaining the latitude and longitude information of the passable path;

[0117] Determining the grid area passed by the passable path according to the latitude and longitude information of the passable path and the latitude and longitude information of the grid area in the database.

[0118] In the embodiments of the present application, the latitude and longitude information of the passable path can be obtained by GPS. By matching the latitude and longitude information of the passable path with the latitude and longitude information of the grid area in the database, the grid area passed by the passable path can be determined.

[0119] In one embodiment, the obtaining of the weather data of the grid area comprises:

[0120] Obtaining the weather data of the grid area from the intelligent grid weather forecasting system according to the latitude and longitude information of the grid area.

[0121] In the embodiments of the present application, the weather data of each grid area is collected into the intelligent grid weather forecasting system. The intelligent grid weather forecasting system provides an interface. By inputting the latitude and longitude information of the grid area into the interface, the interface returns the weather data of the grid area according to the latitude and longitude information of the grid area.

[0122] In one embodiment, the navigation method further comprises:

[0123] outputting the optimal path to a vehicle-mounted navigation interface or a mobile terminal interface of the two-wheeled vehicle for display.

[0124] In the embodiments of the present application, the optimal path is output to the vehicle-mounted navigation interface or the mobile terminal interface of the two-wheeled vehicle for display, so that the user can travel according to the optimal path.

[0125] In one embodiment, the navigation method further comprises:

[0126] obtaining geographical data of the passable paths;

[0127] calculating a total wind force on the passable paths according to the geographical data of the passable paths and meteorological data of the passable paths, wherein the meteorological data of the passable paths is determined according to meteorological data of the grid regions passed by the passable paths;

[0128] outputting the total wind forces of different passable paths to the vehicle-mounted navigation interface or the mobile terminal interface of the two-wheeled vehicle for comparative display.

[0129] In the embodiments of the present application, the intersection includes a crossroad, the total wind force on each passable path is calculated, and the total wind forces of different passable paths are output to the vehicle-mounted navigation interface or the mobile terminal interface of the two-wheeled vehicle for comparative display, so that the user can select a path with the least impact on driving.

[0130] In one embodiment, the navigation method further comprises:

[0131] obtaining geographical data of passable paths

[0132] obtaining the height of trees on the passable paths according to the geographical data of the passable paths;

[0133] evaluating a falling risk coefficient of the trees according to the height of the trees and meteorological data of the grid regions;

[0134] calculating a proportion of tree-falling danger sections to total sections according to the falling risk coefficient of the trees;

[0135] outputting the proportions of tree-falling danger sections to total sections corresponding to different passable paths to the vehicle-mounted navigation interface or the mobile terminal interface of the two-wheeled vehicle for comparative display.

[0136] The embodiment of the present application calculates the proportion of the tree falling danger section in the total section corresponding to each path, and then outputs the proportion of the tree falling danger section in the total section corresponding to different passable paths to the vehicle-mounted navigation interface or the mobile terminal interface of the two-wheeled vehicle for comparison and display. In this way, the user can select a relatively safe path for driving, and reduce the occurrence of accidents.

[0137] Embodiment two:

[0138] Please refer to Figure 3 The embodiment of the present application provides a two-wheeled vehicle navigation device based on wind resistance, comprising:

[0139] The acquisition module 1 is used for acquiring a departure place and a destination;

[0140] The passable path planning module 2 is used for planning a passable path of the two-wheeled vehicle according to the departure place and the destination;

[0141] The determination module 3 is used for determining a grid area passed by the passable path;

[0142] The meteorological data acquisition module 4 is used for acquiring meteorological data of the grid area;

[0143] The energy consumption calculation module 5 is used for predicting the energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area according to a two-wheeled vehicle human riding model; wherein the two-wheeled vehicle human riding model is constructed in combination with the meteorological data;

[0144] The optimal path determination module 6 is used for determining an optimal path based on the energy consumption corresponding to different passable paths.

[0145] In one embodiment, the two-wheeled vehicle human riding model is:

[0146]

[0147] F m =C r F s =C r Mgcosθ

[0148] ′

[0149] F g =F g sinθ

[0150]

[0151] F-F ′ f -F m -F w -F′ g = Ma

[0152]

[0153]

[0154] wherein, F f represents the wind force, represents the real-time wind speed at the altitude, and φ represents the wind force F f generated by nature, and the included angle with the forward direction of the vehicle body, F m represents the friction force between the tire of the two-wheeled vehicle and the ground, C r represents the rolling friction coefficient between the tire of the vehicle and the ground, F s represents the ground support force, M represents the total mass of the human-vehicle system, and g represents the gravitational acceleration, F g represents the gravity of the human-vehicle system, and θ represents the included angle between the road surface and the horizontal plane, F w represents the air resistance received by the human-vehicle system, ρ represents the air density at the altitude, V c represents the speed of the two-wheeled vehicle, A represents the frontal area of the human-vehicle system calculated by using the human riding model, C w represents the wind resistance coefficient of the two-wheeled vehicle, a represents the acceleration, V2 is the speed of the two-wheeled vehicle at t2, V1 is the speed of the two-wheeled vehicle at t1, F is the motor driving force of the two-wheeled vehicle, S is the driving distance estimated by the planned route, Л is the motor conversion efficiency, and W is the energy consumption, which represents the size of the work done by the motor driving force of the two-wheeled vehicle.

[0155] In one embodiment, the human riding model is as follows:

[0156] the frontal area of the human-vehicle system = proportional coefficient * (body surface area + area increased by clothing thickness); wherein the body surface area = first coefficient * height + second coefficient * weight + third coefficient.

[0157] In one embodiment, the navigation device further comprises:

[0158] a residual power acquisition module, configured to acquire the residual power of the two-wheeled vehicle;

[0159] a comparison module, configured to compare the residual power with the energy consumption corresponding to the optimal path;

[0160] a prompt module, configured to issue a charging prompt signal, a return prompt signal, or a destination change prompt signal if the residual power is less than the energy consumption corresponding to the optimal path.

[0161] In one embodiment, the navigation device further comprises:

[0162] a geographic data obtaining module configured to obtain geographic data of the passable path;

[0163] a wind force sum calculating module configured to calculate a wind force sum on the passable path according to the geographic data of the passable path and meteorological data of the passable path, wherein the meteorological data of the passable path is determined according to meteorological data of a grid region through which the passable path passes;

[0164] The step of determining the optimal path based on the energy consumptions corresponding to different passable paths comprises:

[0165] The step of determining the optimal path based on the wind force sums corresponding to different passable paths and the energy consumptions corresponding to different passable paths.

[0166] In one embodiment, the navigation device further comprises:

[0167] a judging module configured to judge whether the wind force of any grid region of the optimal path is greater than a preset level or whether the rainfall of any grid region is greater than a preset threshold;

[0168] The prompting module is further configured to issue a signal of driving danger if the wind force of any grid region of the optimal path is greater than the preset level or the rainfall of any grid region is greater than the preset threshold.

[0169] In one embodiment, the navigation device further comprises:

[0170] a geographic data obtaining module configured to obtain geographic data of the passable path;

[0171] a tree height obtaining module configured to obtain the height of a tree on the passable path according to the geographic data of the passable path;

[0172] an evaluating module configured to evaluate a falling danger coefficient of the tree according to the height of the tree and the meteorological data of the grid region;

[0173] a proportion calculating module configured to calculate the proportion of a tree falling danger section to total sections according to the falling danger coefficient of the tree;

[0174] The step of determining the optimal path based on the energy consumptions corresponding to different passable paths comprises:

[0175] The step of determining the optimal path based on the proportions of tree falling danger sections to total sections corresponding to different passable paths and the energy consumptions corresponding to different passable paths.

[0176] Embodiment three:

[0177] ReferenceFigure 4 The embodiment of the present application also provides a computer device, and an internal structure of the computer device can be as shown in the figure. Figure 4 The computer device comprises a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating device, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data of a wind resistance based two-wheeled vehicle navigation method. The network interface of the computer device is used to communicate with an external terminal through a network connection. Further, the computer device can be further provided with an input device and a display screen. The computer program is executed by the processor to implement the wind resistance based two-wheeled vehicle navigation method, and the method comprises the following steps: obtaining a departure place and a destination; planning a passable path of the two-wheeled vehicle according to the departure place and the destination; determining a grid area passed by the passable path; obtaining meteorological data of the grid area; and predicting energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area and according to a two-wheeled vehicle human riding model. The two-wheeled vehicle human riding model is constructed in combination with the meteorological data. An optimal path is determined based on the energy consumption corresponding to different passable paths. Figure 4 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied.

[0178] The embodiment of the present application finely considers the consumption of energy of the two-wheeled vehicle caused by meteorological conditions of each area on the passable path, and determines the optimal path according to the energy consumption of the two-wheeled vehicle on each passable path, so that the user can save the power of the two-wheeled vehicle by selecting the optimal path.

[0179] Embodiment four

[0180] The embodiment of the present application also provides a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program is executed by the processor to implement the wind resistance based two-wheeled vehicle navigation method, and the method comprises the following steps: obtaining a departure place and a destination; planning a passable path of the two-wheeled vehicle according to the departure place and the destination; determining a grid area passed by the passable path; obtaining meteorological data of the grid area; and predicting energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area and according to a two-wheeled vehicle human riding model. The two-wheeled vehicle human riding model is constructed in combination with the meteorological data. An optimal path is determined based on the energy consumption corresponding to different passable paths.

[0181] The embodiments of the present application consider in detail the meteorological conditions of each area on the passable path and the energy consumption of the two-wheeled vehicle, and determine the optimal path according to the energy consumption of the two-wheeled vehicle on each passable path, so that the user can save the power of the two-wheeled vehicle by selecting the optimal path.

[0182] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiments. Any reference to memory, storage, database or other medium provided by the present application and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM) and the like.

[0183] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that processes, devices, articles or methods including a series of elements not only include those elements, but also include other elements not explicitly listed, or include elements inherent to such processes, devices, articles or methods. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0184] The above description is only the preferred embodiments of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation using the content of the present application specification and drawings, or direct or indirect application in other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A two-wheeled vehicle navigation method based on wind resistance, characterized in that, The method includes: Obtain the departure point and destination; Plan the passable route for the two-wheeled vehicle based on the origin and destination; Determine the grid area traversed by the passable path; Obtain meteorological data for the grid area; Based on the meteorological data of the grid area, the energy consumption of the two-wheeled vehicle on the passable path is predicted according to the two-wheeled vehicle human riding model; wherein, the two-wheeled vehicle human riding model is constructed by combining meteorological data; The optimal path is determined based on the energy consumption corresponding to different feasible paths. Before the step of determining the optimal path based on the energy consumption corresponding to different traversable paths, the method further includes: Obtain the geographical data of the accessible route; Based on the geographical data of the accessible path, obtain the height of the trees on the accessible path; The risk factor of the trees falling is assessed based on the height of the trees and the meteorological data of the grid area. Based on the tree fall risk coefficient, calculate the proportion of road sections at risk of tree fall to the total road sections; The step of determining the optimal path based on the energy consumption corresponding to different traversable paths further includes: The optimal path is determined based on the proportion of road sections with a risk of tree falling on different passable paths and the energy consumption of different passable paths.

2. The two-wheeled vehicle navigation method based on wind resistance according to claim 1, characterized in that, The two-wheeled vehicle human riding model is as follows: = = = = Mg = = r A F - - - - = Ma a = W = ； in, Indicates wind force, Indicates the real-time wind speed at the altitude. This refers to the friction between the tires of a two-wheeled vehicle and the ground. Coefficient of rolling friction between wheel / tire and the ground M represents the ground support force, M represents the total mass of the human-vehicle system, and g represents the gravitational acceleration. Indicates the gravity of the human-vehicle system, Indicates the angle between the road surface and the horizontal plane. The air resistance experienced by the vehicle system is represented by ρ, and the air density at the altitude is represented by ρ. The speed of the two-wheeled vehicle is represented by A, which represents the projected area of ​​the windward vehicle-human system calculated using a human riding model. This represents the drag coefficient of a two-wheeled vehicle, and 'a' represents acceleration. yes The speed of the two-wheeled vehicle at any given moment yes The two-wheeled vehicle's speed at any given time, F is the driving force of the two-wheeled vehicle's motor, S is the estimated travel distance of the planned route, Л is the motor conversion efficiency, and W is the energy consumption, representing the magnitude of the driving force of the two-wheeled vehicle's motor.

3. The two-wheeled vehicle navigation method based on wind resistance according to claim 2, characterized in that, The human riding model is as follows: The projected area of ​​the windward-facing vehicle system = proportional coefficient * (body surface area + area increased by clothing thickness); where body surface area = first coefficient * height + second coefficient * weight + third coefficient.

4. The two-wheeled vehicle navigation method based on wind resistance according to claim 1, characterized in that, Following the step of determining the optimal path based on the energy consumption corresponding to different traversable paths, the method further includes: Obtain the remaining battery power of the two-wheeled vehicle; Compare the remaining power with the energy consumption corresponding to the optimal path; If the remaining battery power is less than the energy consumption corresponding to the optimal route, a charging prompt signal, a return-to-home prompt signal, or a destination change prompt signal will be issued.

5. The two-wheeled vehicle navigation method based on wind resistance according to claim 1, characterized in that, Following the step of planning a passable route for the two-wheeled vehicle based on the origin and destination, the method further includes: Obtain the geographical data of the accessible route; Based on the geographical data and meteorological data of the passable path, the total wind force along the passable path is calculated; wherein, the meteorological data of the passable path is determined based on the meteorological data of the grid areas through which the passable path passes. The process of determining the optimal path based on the energy consumption corresponding to different feasible paths includes: The optimal path is determined based on the total wind force and energy consumption of the different passable paths.

6. The two-wheeled vehicle navigation method based on wind resistance according to claim 1, characterized in that, Following the step of determining the optimal path based on the energy consumption corresponding to different traversable paths, the method further includes: Determine whether the wind force in any region of the optimal path is greater than a preset level or whether the rainfall in any region of the grid is greater than a preset threshold. If the wind force in any area of ​​the optimal path exceeds a preset level or the rainfall in any area exceeds a preset threshold, a driving hazard signal will be issued.

7. A two-wheeled vehicle navigation device based on wind resistance, used to implement the method described in any one of claims 1-6, characterized in that, The device includes: The acquisition module is used to obtain the origin and destination. A passable route planning module is used to plan a passable route for the two-wheeled vehicle based on the origin and the destination. A determination module is used to determine the grid area traversed by the passable path; The meteorological data acquisition module is used to acquire meteorological data for the grid area; The energy consumption calculation module is used to predict the energy consumption of the two-wheeled vehicle on the passable path based on the meteorological data of the grid area and the two-wheeled vehicle human riding model; wherein, the two-wheeled vehicle human riding model is constructed by combining the meteorological data; The optimal path determination module is used to determine the optimal path based on the energy consumption corresponding to different passable paths.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the two-wheeled vehicle navigation method based on wind resistance as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the two-wheeled vehicle navigation method based on wind resistance as described in any one of claims 1 to 6.

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