Path planning method, device and equipment

Abstract

The invention provides a path planning method, device and equipment. The method comprises the following steps: acquiring a path starting point and a path ending point of a target vehicle; acquiring a plurality of charging point locations in a preset area range; determining a plurality of driving paths according to each point location; the consumed time and the driving distance of each driving path are obtained, and the consumed electric quantity of each path is calculated; according to the user demand information, obtaining weights corresponding to the consumed time, the driving distance and the consumed electric quantity; and calculating a weighted sum to obtain a path weight corresponding to the driving path, and determining a target path according to each path weight. According to the method, the time weight, the distance weight and the power consumption weight are determined according to the user demand information, the path weight corresponding to the driving path is obtained by calculating the weighted sum of the three variables of the consumed time, the driving distance and the consumed electric quantity of the driving path, and therefore the target path is obtained, and compared with an existing path planning technology, the method is more intelligent and higher in efficiency. And diversified requirements of users can be met.

Description

Technical Field

[0001] The present invention relates to the field of path planning, and in particular to a path planning method, device and equipment. Background Art

[0002] In recent years, with the development of navigation and artificial intelligence technology, route planning has gradually become an increasingly important function in the user evaluation of navigation software. Whether the function is accurate enough and intelligent enough is an important indicator for users to evaluate whether it is easy to use. At present, the existing technology determines several routes by analyzing the location of the departure point and the destination, and then eliminates the congested sections to determine the final target route. When determining the target route, this method often considers the shortest time or the shortest distance. When faced with the diverse needs of users, it often cannot perfectly meet user needs, and there is a problem of low intelligence in path planning. Summary of the invention

[0003] The present invention application provides a path planning method, device and equipment to solve the technical problem of how to improve the intelligence of path planning.

[0004] In order to solve the above technical problems, the first aspect of the present invention application provides a path planning method, comprising:

[0005] Get the path start point and path end point of the target vehicle;

[0006] According to the path starting point and the path ending point, a plurality of charging points within a preset area are obtained; according to the path starting point, the path ending point and the plurality of charging points of the target vehicle, a plurality of driving paths are determined;

[0007] Obtaining the time consumed and the travel distance of each driving path, and calculating the power consumption of the target vehicle on each driving path according to the time consumed and the travel distance;

[0008] According to the user demand information, a time weight corresponding to the consumed time, a distance weight corresponding to the travel distance, and a power consumption weight corresponding to the consumed power are obtained;

[0009] A weighted sum is calculated based on the elapsed time, the travel distance, the power consumption, the time weight, the distance weight and the power consumption weight to obtain a path weight corresponding to the travel path, and a target path is determined based on the path weights of each travel path.

[0010] In the implementation of this aspect, the time weight, distance weight and power consumption weight are determined according to the user demand information, and the path weight corresponding to the driving path is obtained by calculating the weighted sum of the three variables of the driving path, namely, the time consumed, the driving distance and the power consumption, so as to obtain the target path. The target path can not only meet the user demand of the shortest time consumption (for example, the first weight value is one, and the second weight value and the third weight value are zero), but also meet the requirements of "the shortest time consumption and the smallest power consumption". Compared with the existing path planning technology, it is more intelligent and can meet the diverse needs of users. In addition, because the existing technology often determines the target path, What is considered is the shortest time or the shortest distance. In addition to considering the two factors of time and driving distance, the present application also takes into account the vehicle's power consumption. It is not only applicable to traditional fuel vehicles, but also to electric vehicles, hybrid vehicles, etc., with better applicability and a wider range of application scenarios; furthermore, the present application obtains the driving path based on the charging point, and then obtains the target path. This path planning method will pass through one or more charging piles along the target path. Therefore, the user does not need to choose the path by himself to solve the problem of charging along the way, which further improves the intelligence of the path planning and provides convenience for the user's travel.

[0011] In some implementations of the first aspect, the determining of multiple driving routes according to a route starting point, a route end point, and a plurality of charging points within a preset area of ​​the target vehicle is specifically as follows:

[0012] The starting point of the path is used as the starting point of the directed graph, the end point of the path is used as the end point of the directed graph, the starting point of the path, the end point of the path and the plurality of charging points are used as nodes to construct a target directed graph, and the plurality of driving paths are determined according to the directed vectors of the target directed graph.

[0013] In some implementations of the first aspect, determining the target path according to the path weights of the driving paths is specifically:

[0014] According to the path starting point, the path end point, the path weight of each driving path and the direction of the driving path on the target directed graph, a path set whose total path weight is less than a preset weight threshold is obtained; and the path set is determined as the target path.

[0015] In some implementations of the first aspect, obtaining a set of paths whose total path weight is less than a preset weight threshold according to the path starting point, the path end point, the path weight of each of the driving paths, and the direction on the target directed graph is specifically:

[0016] According to each of the charging points and each of the path weights, an initial distance matrix is ​​constructed, and the path weights in the distance matrix are updated by the Floyd algorithm to obtain a target distance matrix;

[0017] According to the weights of each path of the target distance matrix, a set of paths whose total path weight is less than a preset weight threshold is obtained.

[0018] In some implementations of the first aspect, after constructing the target directed graph, it also includes: eliminating driving paths in the target directed graph that consume power greater than a preset power threshold, and the preset power threshold is set according to the battery capacity or maximum charge of the target vehicle.

[0019] In some implementations of the first aspect, the power consumption of the target vehicle on each driving path is calculated according to the consumed time and the driving distance, specifically:

[0020] The average speed is calculated based on the time and distance spent on each driving path;

[0021] The power consumption is calculated according to the following formula:

[0022] e=s 1 ×v+s 2 ×t+s 3 ×k+s 4 ;

[0023] Wherein, e is the power consumption, s 1 、s 2 、s 3 and 4 is the coefficient, v is the average speed of the driving path, k is the height difference influence factor, and t is the temperature influence factor.

[0024] In some implementations of the first aspect, before acquiring a plurality of charging points within a preset area, the method further includes:

[0025] Obtaining the midpoint of the line between the path starting point and the path end point; and calculating the point selection radius according to the distance between the path starting point and the path end point;

[0026] The preset area range is determined by taking the midpoint of the connecting line as the center of the circle and combining it with the selected point radius.

[0027] In some implementations of the first aspect, the path planning method further includes:

[0028] Responding to a demand modification operation, the demand modification operation including: a first demand modification operation with a time demand priority, a second demand modification operation with a distance demand priority, a third demand modification operation with a power consumption demand priority, or a fourth demand modification operation with a preset configuration priority;

[0029] According to the first demand modification operation, the second demand modification operation, the third demand modification operation or the fourth demand modification operation, updating the time weight, the distance weight and the power consumption weight;

[0030] According to the updated time weight, distance weight and power consumption weight, the path weight corresponding to each updated driving path is calculated, and then the target path is updated.

[0031] The second aspect of the present invention application also provides a path planning device, including a basic data acquisition module, a driving path acquisition module, a path data acquisition module, a weight acquisition module and a path planning module; wherein,

[0032] The basic data acquisition module is used to obtain the path starting point and path end point of the target vehicle;

[0033] The driving path acquisition module is used to acquire a plurality of charging points within a preset area according to the path starting point and the path ending point; and determine a plurality of driving paths according to the path starting point, the path ending point and the plurality of charging points of the target vehicle;

[0034] The path data acquisition module is used to acquire the time consumed and the travel distance of each travel path, and calculate the power consumption of the target vehicle on each travel path according to the time consumed and the travel distance;

[0035] The weight acquisition module is used to acquire the time weight corresponding to the consumed time, the distance weight corresponding to the travel distance, and the power consumption weight corresponding to the consumed power according to the user demand information;

[0036] The path planning module is used to calculate the weighted sum according to the consumed time, the driving distance, the power consumption, the time weight, the distance weight and the power consumption weight to obtain the path weight corresponding to the driving path, and determine the target path according to the path weight of each driving path.

[0037] The third aspect of the present application also provides a path planning device, including: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus; the memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute the operation of the path planning method.

[0038] The fourth aspect of the present application also provides a computer-readable storage medium, which stores at least one executable instruction. When the executable instruction is executed on the path planning device / apparatus, the path planning device / apparatus performs the operation of the path planning method. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 : A flow chart of the first embodiment of the path planning method provided in the present application.

[0040] Figure 2 : A schematic diagram of the principles of the first embodiment of the path planning method provided in the present application.

[0041] Figure 3 : A flow chart of a second embodiment of the path planning method provided in the present application.

[0042] Figure 4 : A schematic diagram of the principles of an embodiment of the initial distance matrix of the path planning method provided in the present application.

[0043] Figure 5 : A schematic diagram of the principles of another embodiment of the target distance matrix of the path planning method provided in the present application.

[0044] Figure 6 : A flow chart of the third embodiment of the path planning method provided in the present application.

[0045] Figure 7 : A flow chart of the fourth embodiment of the path planning method provided in the present application.

[0046] Figure 8 : A schematic diagram of the principles of an embodiment of a method for determining a preset area range provided in the present application.

[0047] Fig. 9 : A flow chart of the fifth embodiment of the path planning method provided in the present application.

[0048] Fig.10 : A schematic structural diagram of the first embodiment of the path planning device provided in the present application.

[0049] Fig.11 : A schematic structural diagram of a second embodiment of the path planning device provided in the present application.

[0050] Fig.12 : A schematic structural diagram of the third embodiment of the path planning device provided in the present application.

[0051] Fig.13 : A schematic structural diagram of the first embodiment of the path planning device provided in the present application. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] According to relevant technical records, the current existing technology mainly analyzes the locations of the departure point and the destination, determines several routes by constructing a directed graph, and then eliminates the congested sections to determine the final target route. When determining the target route, this method often considers the shortest time or the shortest distance. When faced with the diverse needs of users, it often cannot perfectly meet user needs, and there is a problem of low intelligence in path planning.

[0054] In response to the above-mentioned diverse needs of users, for example, with the emergence of electric vehicles, electric vehicle users need to confirm their own routes during self-driving tours or long-distance driving to ensure that they can find a charging station for charging before the vehicle runs out of power. Therefore, in addition to meeting the needs of the shortest time or the shortest distance, factors such as power consumption also need to be considered, or personalized needs for a combination of any two or three of the time, distance and power consumption factors.

[0055] For one or more of the above technical issues, please refer to Figure 1 , Figure 1 The schematic diagram of the first embodiment of the path planning method provided by the present invention is a flow chart of the first embodiment of the path planning method provided by the present invention. The path planning method provided by the present invention is applicable to a computer device or a smart terminal such as a mobile phone, and the computer device may be a vehicle-mounted terminal.

[0056] Figure 1 The path planning method of the illustrated embodiment includes steps S101 to S105, and the specific contents of each step are as follows:

[0057] Step S101, obtaining the path start point and path end point of the target vehicle.

[0058] In this step, the target vehicle may be provided with the above-mentioned computer device or the above-mentioned vehicle-mounted terminal, and the computer device or the vehicle-mounted terminal is used to execute steps S101 to S105, or the path planning method described in any preferred embodiment of steps S101 to S105.

[0059] Before planning the target path, you need to determine the path start point and path end point. The path start point can be the current location of the target vehicle or the starting location set by the user. The path end point is mainly the destination location set by the user.

[0060] Furthermore, the target vehicle may be provided with a navigation function or navigation software. The starting point and the destination may be set by the user through the navigation function on the vehicle or a smart terminal such as a mobile phone.

[0061] Step S102, obtaining a plurality of charging points within a preset area according to the path starting point and the path ending point; and determining a plurality of driving paths according to the path starting point, the path ending point and the plurality of charging points of the target vehicle.

[0062] In this step, the charging point may be provided with a charging pile, and a number of charging points within a preset area may be obtained through manufacturer data or map service data. The preset area may be determined based on a path start point and a path end point, or based on preset configuration information.

[0063] Alternatively, if Figure 2 As shown, when determining multiple driving paths, the path starting point, path ending point and the several charging points of the target vehicle can be used as nodes. 1 , the end point of the path is C n , from the path starting point C 1 Start at the end of the path C n The charging points passed by all paths can be recorded as C 1 , C 2 ,…,C n .

[0064] Furthermore, by constructing directed vectors between nodes, several initial paths are determined, and then the initial paths are screened by preset rules to obtain the driving path. For example, the preset rule may be: taking the direction from the path starting point to the path end point as the positive direction, and eliminating the initial paths with the reverse direction to obtain the driving path.

[0065] Step S103, obtaining the time consumed and the travel distance of each driving path, and calculating the power consumption of the target vehicle on each driving path according to the time consumed and the travel distance.

[0066] In some embodiments, for any two nodes such as C i With C j The time and distance of the driving path can be directly obtained through the existing navigation software data. In other embodiments, the time and distance of the driving path can also be obtained by collecting vehicle data of the same type as the target vehicle, specifically the historical data of the same type of vehicle driving on the same driving path; by analyzing the historical data, such as taking the average distance or the average time, as the time and distance of the target vehicle on the driving path. The time can be the driving path C ito C j time spent during off-peak hours.

[0067] For example, in some embodiments, the average speed on the driving path can be calculated based on the time consumed and the driving distance. For example, the average speed v = l / h. Among them, l is the driving distance of the target vehicle on the driving path, and h is the time consumed by the target vehicle on the driving path. Based on the analysis of factors such as the time consumed, the driving distance and the average speed, for example, by using methods such as linear regression, the power consumption of the target vehicle on the driving path can be calculated.

[0068] Step S104, according to the user demand information, obtaining the time weight corresponding to the consumed time, the distance weight corresponding to the driving distance, and the power consumption weight corresponding to the consumed power.

[0069] In this step, the user demand may include single factor demands such as time demand priority, distance demand priority and power consumption demand priority, or may include demands of any combination of two or three such as time demand priority, distance demand priority and power consumption demand priority.

[0070] Optionally, the demand ratio between the two or three can be configured by a weighting method, and specifically the time weight corresponding to the time consumed, the distance weight corresponding to the driving distance, and the power consumption weight corresponding to the power consumption are obtained.

[0071] It can be understood that for the three factors of time consumption, driving distance and power consumption, the sum of the time weight, distance weight and power consumption weight is one. For any two of the factors, such as time consumption and driving distance, the sum of the time weight and distance weight is one, and the power consumption weight is zero. The same can be said for the remaining situations for any two of the factors, and the embodiments of the present application will not be repeated. For the demand of a single factor, for example, when the user demand is time demand priority, the time weight is one, and the distance weight and power consumption weight are zero. The same can be said for single-factor demands such as distance demand priority and power consumption demand priority, and the embodiments of the present application will not be repeated.

[0072] Step S105, calculating a weighted sum according to the consumed time, the driving distance, the consumed electricity, the time weight, the distance weight and the power consumption weight to obtain a path weight corresponding to the driving path, and determining a target path according to the path weight of each driving path.

[0073] After the time weight, distance weight and power consumption weight are determined in step S104, the path weight corresponding to the driving path can be obtained by calculating the weighted sum. For example, C can be calculated according to the following formula: i With C j The path weight w(i,j) of the driving path between:

[0074] w(i,j)=m 1 ×h(i,j)+m 2 ×l(i,j)+m 3 ×e(i,j);

[0075] Among them, l(i,j) is the target vehicle on the driving path C i To C j The driving distance of the target vehicle is h(i,j), and h(i,j) is the driving distance of the target vehicle on the driving path C. i To C j The time consumed by the target vehicle on the driving path C is i To C j Power consumption, m 1 is the time weight, m 2 is the distance weight, m 3 is the power consumption weight.

[0076] In some embodiments, the path weights of each driving path are calculated according to the above formula, and the driving paths with the smallest sum of path weights from the path starting point to the path end point can be screened out, and the selected driving paths are sequentially connected to obtain an optimal target path that meets the user's needs. In other embodiments, the path weights of each driving path are calculated according to the above formula, and the driving paths with the sum of path weights less than a preset weight threshold can be screened out from the path starting point to the path end point, and the selected driving paths are sequentially connected to obtain one or more target paths that meet the user's needs. When there are multiple target paths, the obtained multiple target paths can be recommended to the user for selection.

[0077] It should be noted that this embodiment determines the time weight, distance weight and power consumption weight according to the user demand information, and obtains the path weight corresponding to the driving path by calculating the weighted sum of the three variables of the driving path, namely, the time consumption, the driving distance and the power consumption, so as to obtain the target path. The target path can not only meet the user demand of the shortest time consumption (for example, the power consumption weight is one, and the time weight and the distance weight are zero), but also meet the demand of "the shortest time consumption and the minimum power consumption". Compared with the existing path planning technology, it is more intelligent and can meet the diverse needs of users. In addition, since the existing technology often takes into account when determining the target path, The shortest time or the shortest distance is considered in the present application. In addition to considering the time and driving distance, the present application also takes into account the vehicle's power consumption. It is not only applicable to traditional fuel vehicles, but also to electric vehicles, hybrid vehicles, etc., with better applicability and a wider range of application scenarios. Furthermore, the present application obtains the driving path according to the charging point, and then obtains the target path. This path planning method passes through one or more charging piles along the target path. Therefore, the user does not need to choose the path by himself to solve the problem of charging along the way, which further improves the intelligence of the path planning and provides convenience for the user's travel.

[0078] exist Figure 1 Based on the embodiment shown, Figure 3 The schematic diagram of the process of step S102 provided in the second embodiment of the path planning method of the present application is shown. It should be noted that Figure 1 The same steps will not be repeated here. Figure 3 As shown, step S102 includes step S301, which is described in detail as follows:

[0079] Step S301, taking the path starting point as the starting point of the directed graph, taking the path end point as the end point of the directed graph, taking the path starting point, the path end point and the plurality of charging points as nodes, constructing a target directed graph, and determining the plurality of driving paths according to the directed vectors of the target directed graph.

[0080] In this step, the above directed graph is Figure 2 As shown. The directed graph takes the path start point as the starting point and the path end point as the end point. The path start point, path end point and several charging points determined in the above steps are taken as nodes of the directed graph. By traversing each node, according to the connection relationship between each node (in the navigation system, considering short-distance driving, the shortest path between two points represents the driving path between the two charging points), several directed vectors are constructed. The direction of the directed vector is from the path start point to the path end point. Multiple driving paths can be determined by the directed vectors of the target directed graph.

[0081] In a preferred implementation of the second embodiment, the step S105 is specifically as follows: according to the path starting point, the path end point, the path weight of each of the driving paths, and the direction of the driving path on the target directed graph, a path set whose total path weight is less than a preset weight threshold is obtained; and the path set is determined as the target path.

[0082] In this preferred embodiment, through the path weight w(i, j) of each of the driving paths, according to the path starting point, the path end point, and the direction of the driving path, all driving paths in the same direction (the direction from the path starting point to the path end point) can be determined, and each path set is obtained based on the driving paths connected in sequence from beginning to end. This preferred embodiment obtains a path set whose total path weight is less than a preset weight threshold, and determines the path set as the target path. The preset weight threshold can be user-defined, or the target vehicle is pre-configured at the factory. It can be understood that there may be one or more path sets whose total path weight is less than the preset weight threshold, that is, the target paths correspond to one or more respectively. When there are multiple target paths, these target paths can be pushed to the user for the user to choose.

[0083] Furthermore, this embodiment also provides a method for solving a path set, which converts the path weight of the driving path into a mathematical model of a single-source shortest path without negative weights, and solves it through the Floyd algorithm. According to the path starting point, the path end point, the path weight of each driving path, and the direction on the target directed graph, a path set with a total path weight less than a preset weight threshold is obtained, specifically: according to each charging point and each path weight, an initial distance matrix is ​​constructed, and the path weights in the distance matrix are updated through the Floyd algorithm to obtain a target distance matrix; according to each path weight of the target distance matrix, a path set with a total path weight less than a preset weight threshold is obtained.

[0084] Figure 4 The following is a schematic diagram of the principle of Floyd's algorithm. In this algorithm, the driving path C i to C j The path weight is converted into a two-dimensional array, where C i =A, B, C or D, C j =A, B, C or D. For example, the path weight from node A to node B is 1, the path weight from node A to node C is 2, and there is no direct driving path from node A to node D, so it is positive infinity + ∞. The above distance matrix d [i][j] Specifically, it can be expressed as:

[0085]

[0086] Then the initial distance matrix is ​​updated by the interpolation method, such as Figure 5 As shown, specifically including:

[0087] (1) The distance from node B to the other nodes remains unchanged;

[0088] (2) The distance from node C to the other nodes remains unchanged;

[0089] (3) For nodes A and D, a new driving path ABD is added, and the length of the new driving path is the sum of AB and BD. At this time, positive infinity +∞ is updated as the path weight of the new path.

[0090] This can be expressed as: For node k, if d [i][k] +d [k][j] <d [i][j] , then update the distance between nodes i and j, that is, d [i][j] =min(d [i][j] ,d [i][k] +d [k][j] ). By updating the initial distance matrix and replacing “positive infinity + ∞” with the new path weight, the target distance matrix can be obtained. According to the path weights of the target distance matrix, a path set with a total path weight less than a preset weight threshold can be obtained, and a path set with the minimum total path weight can also be obtained, thereby obtaining the target path.

[0091] Preferably, in some application scenarios, in order to ensure that the target vehicle can reach a nearby charging station when it is fully charged before it is exhausted, the driving paths in the target directed graph that consume power greater than a preset power threshold can be eliminated, wherein the preset power threshold is set according to the battery capacity or maximum charge capacity of the target vehicle.

[0092] For example, for the target directed graph C i ->Cj, its preset power threshold can be set to 0.8*E max , the power consumption on the driving path is greater than 0.8*E max When the driving path is removed, the power consumption of the driving paths in the target directed graph is less than or equal to 0.8*E max This ensures that the target vehicle can reach a nearby charging station before its battery runs out.

[0093] It can be understood that when the directed graph method is adopted in this embodiment, the path weight from point A to point B is different from the path weight from point B to point A, because the driving direction between point A and point B is unidirectional, and can only be from the starting point of the path to the end point of the path. However, even so, it will not affect the solution of the Floyd algorithm.

[0094] exist Figure 1Based on the embodiment shown, Figure 6 The schematic diagram of the process of step S103 provided in the third embodiment of the path planning method of the present application is shown. It should be noted that Figure 1 The same steps will not be repeated here. Figure 6 As shown, step S103 includes step S601 to step S602, which are described in detail as follows:

[0095] Step S601, calculating the average speed according to the time consumed and the travel distance of each travel path.

[0096] Step S602: Calculate the power consumption according to the following formula:

[0097] e=s 1 ×v+s 2 ×t+s 3 ×k+s 4 ;

[0098] Wherein, e is the power consumption, s 1 、s 2 、s 3 and 4 is the coefficient, v is the average speed of the driving path, k is the height difference influence factor, and t is the temperature influence factor.

[0099] In this embodiment, the height difference influence factor and the temperature influence factor can be calculated by simulation of experimental data of the target vehicle, and the height difference influence factor can take into account the local terrain parameters of the driving path. The calculation method of this embodiment includes the average speed, height difference and temperature of the vehicle for calculation. Compared with the prior art that is based solely on the vehicle speed factor, it is more comprehensive and the calculated power consumption has higher accuracy.

[0100] exist Figure 1 Based on the embodiment shown, Figure 7 The fourth embodiment of the path planning method of the present application is shown in FIG. Figure 1 The same steps will not be repeated here. Figure 7 As shown, the fourth embodiment includes steps S701 to S702, and steps S701 to S702 can be performed before step S102, and are specifically described as follows:

[0101] Step S701, obtaining the midpoint of the line between the path starting point and the path end point; and calculating the point selection radius according to the distance between the path starting point and the path end point.

[0102] Step S702, taking the midpoint of the connecting line as the center of the circle and combining the selected point radius, determine the preset area range.

[0103] The preset area range is as follows: Figure 8 As shown, in the implementation of this embodiment, a suitable point selection radius is selected according to the distance between the path starting point and the path end point. For example, the point selection radius is selected to be 1.5 times or 2 times the distance between the path starting point and the path end point. When the path starting point and the path end point are 10 kilometers apart, and the battery of the driving vehicle is low, by selecting a charging point within the preset area determined in this embodiment, the planning result of the target path can enable the target vehicle to first go to a charging point 100 meters in the opposite direction of the path end point to replenish the battery, and then drive in the direction of the path end point, so as to ensure that the charging needs of the target vehicle can be met first.

[0104] Further, in Figure 1 Based on the embodiment shown, Fig. 9 The fifth embodiment of the path planning method of the present application is shown in FIG. Figure 1 The same steps will not be repeated here. Fig. 9 As shown, the fifth embodiment includes steps S901 to S903, and steps S901 to S903 can be performed after step S105, and are specifically described as follows:

[0105] Step S901, responding to a demand modification operation, wherein the demand modification operation includes: a first demand modification operation with time priority, a second demand modification operation with distance priority, a third demand modification operation with power consumption priority, or a fourth demand modification operation with preset configuration priority.

[0106] Step S902: updating the time weight, the distance weight and the power consumption weight according to the first demand modification operation, the second demand modification operation, the third demand modification operation or the fourth demand modification operation.

[0107] Step S903, calculating the updated path weights corresponding to each driving path according to the updated time weight, distance weight and power consumption weight, and then updating the target path.

[0108] In this embodiment, the demand modification operation may include time demand priority, distance demand priority, power consumption demand priority and a customized demand modification operation. The customized demand may be pre-configured.

[0109] For example, when the demand modification operation is the first demand modification operation with time priority, the time weight can be updated to one, and the distance weight and power consumption weight can be updated to zero. When the demand modification operation is the second demand modification operation with distance priority or the third demand modification operation with power consumption priority, the update method of each weight can be deduced in the same way, and this embodiment will not be repeated. When the custom demand is "time and minimum power consumption", the time weight can be set to 0.5, the power consumption weight can be set to 0.5, and the distance weight can be set to zero.

[0110] In this way, when the user has new needs, the time weight, distance weight and power consumption weight can be updated through the demand modification operation, and then the path weight can be updated, and the target path can be replanned to meet the user's needs.

[0111] like Fig.10 As shown, the present invention also provides a path planning device 1000, including a basic data acquisition module 1001, a driving path acquisition module 1002, a path data acquisition module 1003, a weight acquisition module 1004 and a path planning module 1005; wherein,

[0112] The basic data acquisition module 1001 is used to obtain the path starting point and path end point of the target vehicle;

[0113] The driving path acquisition module 1002 is used to acquire a plurality of charging points within a preset area according to the path starting point and the path ending point; and determine a plurality of driving paths according to the path starting point, the path ending point and the plurality of charging points of the target vehicle;

[0114] The path data acquisition module 1003 is used to acquire the time consumed and the travel distance of each travel path, and calculate the power consumption of the target vehicle on each travel path according to the time consumed and the travel distance;

[0115] The weight acquisition module 1004 is used to acquire the time weight corresponding to the consumed time, the distance weight corresponding to the travel distance, and the power consumption weight corresponding to the consumed power according to the user demand information;

[0116] The path planning module 1005 is used to calculate the weighted sum according to the consumed time, the driving distance, the power consumption, the time weight, the distance weight and the power consumption weight to obtain the path weight corresponding to the driving path, and determine the target path according to the path weight of each driving path.

[0117] In some preferred embodiments, the driving path acquisition module 1002 includes a path determination unit, and the path determination unit is used to:

[0118] The starting point of the path is used as the starting point of the directed graph, the end point of the path is used as the end point of the directed graph, the starting point of the path, the end point of the path and the plurality of charging points are used as nodes to construct a target directed graph, and the plurality of driving paths are determined according to the directed vectors of the target directed graph.

[0119] In some preferred embodiments, the path planning module 1005 includes a path planning unit, and the path planning unit is used to:

[0120] The path planning module 1005 obtains a path set whose total path weight is less than a preset weight threshold according to the path starting point, the path end point, the path weight of each driving path, and the direction of the driving path on the target directed graph; and determines the path set as the target path.

[0121] In some preferred embodiments, the path planning unit includes a set acquisition subunit, and the set acquisition subunit is used to:

[0122] According to each of the charging points and each of the path weights, an initial distance matrix is ​​constructed, and the path weights in the distance matrix are updated by the Floyd algorithm to obtain a target distance matrix;

[0123] According to the weights of each path of the target distance matrix, a set of paths whose total path weight is less than a preset weight threshold is obtained.

[0124] In some preferred embodiments, Fig.11 As shown, the path planning device 1000 also includes a elimination module 1006, which is used to eliminate the driving paths in the target directed graph that consume more power than a preset power threshold after the path determination unit constructs the target directed graph. The preset power threshold is set according to the battery capacity or maximum charge of the target vehicle.

[0125] In some preferred implementations, the path data acquisition module 1003 calculates the power consumption of the target vehicle on each driving path according to the consumed time and the driving distance, specifically:

[0126] The path data acquisition module 1003 calculates the average speed according to the time consumed and the travel distance of each travel path;

[0127] The power consumption is calculated according to the following formula:

[0128] e=s 1 ×v+s 2 ×t+s 3 ×k+s 4 ;

[0129] Wherein, e is the power consumption, s1 、s 2 、s 3 and 4 is the coefficient, v is the average speed of the driving path, k is the height difference influence factor, and t is the temperature influence factor.

[0130] In some preferred embodiments, Fig.12 As shown, the path planning device 1000 further includes an area determination module 1007, and the area determination module 1007 is used for, before the driving path acquisition module 1002 acquires a plurality of charging points within a preset area:

[0131] Obtaining the midpoint of the line between the path starting point and the path end point; and calculating the point selection radius according to the distance between the path starting point and the path end point;

[0132] The preset area range is determined by taking the midpoint of the connecting line as the center of the circle and combining it with the selected point radius.

[0133] In some preferred embodiments, Fig.13 As shown, the path planning device 1000 further includes an updating module 1008, and the updating module 1008 is used to:

[0134] Responding to a demand modification operation, the demand modification operation including: a first demand modification operation with a time demand priority, a second demand modification operation with a distance demand priority, a third demand modification operation with a power consumption demand priority, or a fourth demand modification operation with a preset configuration priority;

[0135] updating a time weight, a distance weight, and a power consumption weight according to the first demand modification operation, the second demand modification operation, the third demand modification operation, or the fourth demand modification operation;

[0136] According to the updated time weight, distance weight and power consumption weight, the path weight corresponding to each updated driving path is calculated, and then the target path is updated.

[0137] Please refer to Fig.13 , Fig.13 A schematic diagram of a structure of an embodiment of a path planning device provided by the present invention. The path planning device includes: a processor 1302, a memory 1306, a communication interface 1304 and a communication bus 1308, wherein the processor 1302, the memory 1306 and the communication interface 1304 communicate with each other via the communication bus 1308;

[0138] The memory 1306 is used to store at least one executable instruction, and the executable instruction enables the processor 1302 to perform the operation of the torque control method.

[0139] Fig.13 A schematic diagram of the structure of an embodiment of a path planning device of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the path planning device.

[0140] like Fig.13 As shown, the path planning device may include: a processor (processor) 1302 , a communications interface (Communications Interface) 1304 , a memory (memory) 1306 , and a communication bus 1308 .

[0141] The processor 1302, the communication interface 1304, and the memory 1306 communicate with each other via the communication bus 1308. The communication interface 1304 is used to communicate with other devices such as a client or other server network elements. The processor 1302 is used to execute the program 1130, and specifically, can execute the relevant steps in the above-mentioned path planning method embodiment.

[0142] Specifically, the program 1310 may include program code including computer executable instructions.

[0143] The processor 1302 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiment of the present invention. The one or more processors included in the path planning device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0144] The memory 1306 is used to store the program 1130. The memory 1306 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0145] The present application also provides a computer-readable storage medium, in which at least one executable instruction is stored. When the executable instruction is executed on a path planning device / apparatus, the path planning device / apparatus performs the operation of the path planning method described in any of the above-mentioned embodiments.

[0146] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system or other device. In addition, the embodiments of the present invention are not directed to any particular programming language.

[0147] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. Similarly, in order to simplify the present invention and help understand one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, the various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. Wherein, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself is a separate embodiment of the present invention.

[0148] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and further may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive.

[0149] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

[0150] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A path planning method, characterized in that: include: Get the path start point and path end point of the target vehicle; According to the path starting point and the path end point, a plurality of charging points within a preset area are obtained; Determine multiple driving routes according to the route starting point, the route ending point and the plurality of charging points of the target vehicle; Obtaining the time consumed and the travel distance of each driving path, and calculating the power consumption of the target vehicle on each driving path according to the time consumed and the travel distance; According to the user demand information, a time weight corresponding to the consumed time, a distance weight corresponding to the travel distance, and a power consumption weight corresponding to the consumed power are obtained; A weighted sum is calculated based on the elapsed time, the travel distance, the power consumption, the time weight, the distance weight and the power consumption weight to obtain a path weight corresponding to the travel path, and a target path is determined based on the path weights of each travel path.

2. A path planning method according to claim 1, characterized in that: The method of determining multiple driving routes according to the starting point and end point of the target vehicle's route and a plurality of charging points within a preset area is as follows: The starting point of the path is used as the starting point of the directed graph, the end point of the path is used as the end point of the directed graph, the starting point of the path, the end point of the path and the plurality of charging points are used as nodes to construct a target directed graph, and the plurality of driving paths are determined according to the directed vectors of the target directed graph.

3. A path planning method as claimed in claim 2, characterized in that: The target path is determined according to the path weight of each driving path, specifically: According to the path starting point, the path end point, the path weight of each driving path and the direction of the driving path on the target directed graph, a path set whose total path weight is less than a preset weight threshold is obtained; and the path set is determined as the target path.

4. A path planning method as claimed in claim 3, characterized in that: The method of obtaining a set of paths whose total path weight is less than a preset weight threshold according to the path starting point, the path end point, the path weight of each of the driving paths, and the direction on the target directed graph is as follows: According to each of the charging points and each of the path weights, an initial distance matrix is ​​constructed, and the path weights in the distance matrix are updated by the Floyd algorithm to obtain a target distance matrix; According to the weights of each path in the target distance matrix, a set of paths whose total path weight is less than a preset weight threshold is obtained.

5. A path planning method as claimed in claim 2, characterized in that: After constructing the target directed graph, the method further includes: eliminating driving paths in the target directed graph that consume power greater than a preset power threshold, where the preset power threshold is set according to the battery capacity or maximum charge capacity of the target vehicle.

6. A path planning method according to claim 1, characterized in that: The power consumption of the target vehicle on each driving path is calculated according to the consumed time and the driving distance, specifically: The average speed is calculated based on the time and distance spent on each driving path; The power consumption is calculated according to the following formula: e=s1×v+s2×t+s3×k+s4; Wherein, e is the power consumption, s1, s2, s3 and s4 are coefficients, v is the average speed of the driving path, k is the height difference influence factor, and t is the temperature influence factor.

7. A path planning method as claimed in claim 1, characterized in that: Before acquiring a plurality of charging points within a preset area, the method further includes: Obtaining the midpoint of the line between the path starting point and the path end point; and calculating the point selection radius according to the distance between the path starting point and the path end point; The preset area range is determined by taking the midpoint of the connecting line as the center of the circle and combining it with the selected point radius.

8. A path planning method as claimed in claim 1, characterized in that: The path planning method further includes: Responding to a demand modification operation, the demand modification operation including: a first demand modification operation with a time demand priority, a second demand modification operation with a distance demand priority, a third demand modification operation with a power consumption demand priority, or a fourth demand modification operation with a preset configuration priority; updating a time weight, a distance weight, and a power consumption weight according to the first demand modification operation, the second demand modification operation, the third demand modification operation, or the fourth demand modification operation; According to the updated time weight, distance weight and power consumption weight, the path weight corresponding to each updated driving path is calculated, and then the target path is updated.

9. A path planning device, characterized in that: It includes a basic data acquisition module, a driving path acquisition module, a path data acquisition module, a weight acquisition module and a path planning module; wherein, The basic data acquisition module is used to obtain the path starting point and path end point of the target vehicle; The driving path acquisition module is used to acquire a plurality of charging points within a preset area according to the path starting point and the path ending point; and determine a plurality of driving paths according to the path starting point, the path ending point and the plurality of charging points of the target vehicle; The path data acquisition module is used to acquire the time consumed and the travel distance of each travel path, and calculate the power consumption of the target vehicle on each travel path according to the time consumed and the travel distance; The weight acquisition module is used to acquire the time weight corresponding to the consumed time, the distance weight corresponding to the travel distance, and the power consumption weight corresponding to the consumed power according to the user demand information; The path planning module is used to calculate the weighted sum according to the consumed time, the driving distance, the power consumption, the time weight, the distance weight and the power consumption weight to obtain the path weight corresponding to the driving path, and determine the target path according to the path weight of each driving path.

10. A path planning device, characterized in that: include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform the operation of the path planning method as described in any one of claims 1 to 8.

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