CN114281086A - Method, system, platform, medium and equipment for planning commercial vehicle path - Google Patents
Method, system, platform, medium and equipment for planning commercial vehicle path Download PDFInfo
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Abstract
The application discloses a method, a system, a platform, a medium and equipment for planning a path of a commercial vehicle, and belongs to the technical field of navigation of the commercial vehicle. The method comprises the following steps: segmenting the road map according to the map segmentation information to obtain a plurality of road units; classifying mass vehicle networking data of commercial vehicles corresponding to the road units according to preset categories, and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise oil consumption; according to a road network matching algorithm, matching each classification label with a corresponding road unit to obtain a road label corresponding to each road unit, wherein the road label comprises an oil consumption label; and extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating and determining the final planned path. This application is through a large amount of car networking data, and the stack of classifying is carried out, carries out the labellization to the car antithetical couplet data, takes into account the oil consumption factor when route planning, promotes route planning's economic nature.
Description
Technical Field
The application relates to the technical field of commercial vehicle navigation, in particular to a method, a system, a platform, a medium and equipment for planning a path of a commercial vehicle.
Background
Navigation of commercial vehicles on the market is based on traditional navigation path planning, 3 mainstream strategies of shortest time, shortest mileage and lowest high-speed charge can be realized, and path recommendation is given according to conditions of a road algorithm, truck height limit, truck width limit and the like; or carrying out weight iteration on the three modes to obtain a comprehensive optimal planning mode. The path planning mode comprises shortest time, shortest mileage, lowest high-speed charge and superposition of the modes. One of pain points of the commercial vehicle path planning is the path economy, the largest expense comes from fuel consumption and road toll in a transportation link, and currently, along with the change of the national highway toll standard, the estimation of the commercial vehicle high-speed toll needs to be combined with the number of vehicle axles, and the actual occurrence mileage is recorded through a high-speed electronic billing rod, so that the toll is charged. However, the cost of fuel consumption of the vehicle is difficult to estimate because the fuel consumption is difficult to estimate under one vehicle condition and one road condition. In addition, the conventional path planning method lacks statistical records about oil consumption cost, so that a driver cannot select an optimal driving path according to the oil consumption condition in the driving process, the oil consumption cost cannot be saved in the driving process, and the economical efficiency of the driving path is improved.
Disclosure of Invention
The method, the system, the platform, the medium and the equipment for planning the path of the commercial vehicle are provided by the application, aiming at the problems that in the prior art, in the path planning process of the commercial vehicle, the fuel consumption cost is difficult to calculate, the consideration of fuel consumption factors is lacked, the economical efficiency of the actual planned path is low, and the driving cost cannot be effectively reduced.
In one technical solution of the present application, a method for planning a path of a commercial vehicle is provided, including: segmenting the road map according to the map segmentation information to obtain a plurality of road units; classifying mass commercial vehicle networking data corresponding to the road units according to preset categories, and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise oil consumption; according to a road network matching algorithm, matching each classification label including oil consumption with a corresponding road unit to obtain a road label corresponding to each road unit, wherein the road label comprises an oil consumption label; and extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating and determining the final planned path.
Optionally, the mass commercial vehicle networking data corresponding to the plurality of road units are classified according to preset categories, and classification labels corresponding to the classification results are correspondingly generated, including: extracting the corresponding vehicle networking data of the commercial vehicle when the vehicle passes through a road unit from a vehicle networking database established by the commercial vehicle-mounted terminal, wherein the vehicle networking data comprises vehicle track, vehicle speed and oil consumption; the data of the internet of vehicles of different types are classified according to preset categories to obtain corresponding classification results, and then classification labels corresponding to the classification results are generated, the classification labels comprise oil consumption corresponding to the road units for commercial vehicles to drive through, when the data of the internet of vehicles are included in the same classification results, the data of the internet of vehicles of multiple dispersed lines are overlapped to obtain the overall data of the multiple lines of vehicles.
Optionally, matching each classification label with a corresponding road unit according to a road network matching algorithm to obtain a road label corresponding to each road unit, including: extracting a classification label of the commercial vehicle corresponding to the vehicle networking data when the commercial vehicle runs through the road unit, wherein the classification label comprises oil consumption; and assigning the classification labels to the road units to obtain road labels corresponding to the road units, wherein the road labels comprise fuel consumption labels.
Optionally, extracting data corresponding to the road labels in each road unit of the multiple planned paths according to the path planning requirement, calculating, and determining the final planned path further includes: extracting corresponding Internet of vehicles data according to the road labels corresponding to the road units; according to the preset scene type, calculating estimated driving data when commercial vehicles of corresponding vehicle types drive through each road unit, wherein the estimated driving data comprises oil consumption data corresponding to the road units; and establishing a driving data dictionary table corresponding to each one-way unit according to the estimated driving data.
Optionally, according to the path planning requirement, extracting data corresponding to the road labels in each road unit of the multiple planned paths, performing calculation, and determining a final planned path, including: determining corresponding road labels in a plurality of planned paths according to path planning requirements, and extracting estimated driving data corresponding to each road unit in the planned paths according to the road labels in a driving data dictionary table; respectively calculating the overall estimated driving data of each planned path according to the estimated driving data corresponding to each road unit; and judging the whole driving data according to a preset rule, and selecting a preset number of paths from the corresponding multiple planned paths as target paths.
Optionally, the process of extracting data corresponding to the road labels in each road unit of the multiple planned paths according to the path planning requirement, calculating, and determining the final planned path further includes: extracting fuel consumption labels corresponding to each road unit in the multiple planning paths according to the fuel consumption requirements; extracting corresponding oil consumption data of each road unit according to the oil consumption label, and calculating the oil consumption corresponding to each planned path; and sequencing the oil consumption, and determining the planned path with the least oil consumption as a target path according to a sequencing result.
In one embodiment of the present application, a path planning system for a commercial vehicle is provided, including: a module for segmenting the road map according to the map segmentation information to obtain a plurality of road units; the module is used for classifying mass commercial vehicle networking data corresponding to the road units according to preset categories and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise vehicle types, loads and oil consumption; the module is used for matching each classification label with a corresponding road unit according to a road network matching algorithm to obtain a road label corresponding to each road unit, wherein the road label comprises an oil consumption label; and the module is used for extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating and determining the final planned path.
In a technical solution of the present application, a platform for planning a path of a commercial vehicle is provided, which includes: the system comprises a plurality of vehicle-mounted terminals, a plurality of mobile terminals and a plurality of mobile terminals, wherein the vehicle-mounted terminals are used for collecting the driving data of the commercial vehicle, receiving the path planning requirement input by a user and uploading the path planning requirement; the server is used for classifying the mass commercial vehicle mass internet of vehicles data according to preset categories and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise vehicle types, loads and oil consumption; the road network matching system is used for matching each classification label with a corresponding road unit according to a road network matching algorithm to obtain a road label corresponding to each road unit, wherein the road label comprises an oil consumption label; and the data processing module is used for extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating, determining the final planned path, sending the final planned path to the vehicle-mounted terminal and displaying the final planned path to the user.
In one aspect of the present application, a computer-readable storage medium is provided, where the storage medium stores computer instructions, and the computer instructions are operated to execute the method for planning a path of a commercial vehicle in the first aspect.
In one aspect of the present application, a computer device is provided, which includes a processor and a memory, where the memory stores computer instructions, wherein: the processor operates the computer instructions to execute the method for planning the path of the commercial vehicle in the first scheme.
The beneficial effect of this application is: this application is through in the route planning in-process, through to a large amount of commercial car networking data, categorised stack carries out the labeling to the car antithetical couplet data, obtains the various road labels that each road unit corresponds. Meanwhile, oil consumption data in the internet of vehicles data are counted to generate corresponding oil consumption labels, and then when path planning is carried out, oil consumption is taken into account, and the economy of the path planning is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a schematic diagram illustrating an embodiment of a method for planning a path of a commercial vehicle according to the present application;
FIG. 2 is a schematic diagram illustrating an example of a method for planning a path of a commercial vehicle according to the present application;
FIG. 3 is a schematic diagram illustrating one embodiment of a commercial vehicle path planning system according to the present application;
fig. 4 shows a schematic diagram of an embodiment of the platform for planning the path of a commercial vehicle according to the present application.
With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the above-described drawings (if any) are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a product or apparatus that comprises a list of steps or elements is not necessarily limited to those elements explicitly listed, but may include other elements not expressly listed or inherent to such product or apparatus.
In the prior art, the navigation of commercial vehicles commonly used in the market at present is based on the traditional navigation path planning, 3 main flow strategies of shortest time, shortest mileage and lowest high-speed charge can be realized, and path recommendation is given according to a path calculation algorithm in combination with the conditions of truck height limit, width limit and the like; or carrying out weight iteration on the three modes to obtain a comprehensive optimal planning mode. The path planning mode comprises shortest time, shortest mileage, lowest high-speed charge and superposition of the modes. One of pain points of the commercial vehicle path planning is the path economy, the largest expense comes from fuel consumption and road toll in a transportation link, and currently, along with the change of the national highway toll standard, the estimation of the commercial vehicle high-speed toll needs to be combined with the number of vehicle axles, and the actual occurrence mileage is recorded through a high-speed electronic billing rod, so that the toll is charged. However, the cost of fuel consumption of the vehicle is difficult to estimate because the fuel consumption is difficult to estimate under one vehicle condition and one road condition. In addition, the conventional path planning method lacks statistical records about oil consumption cost, so that a driver cannot select an optimal driving path according to the oil consumption condition in the driving process, the oil consumption cost cannot be saved in the driving process, and the economical efficiency of the driving path is improved.
In order to solve the problems, the application provides a method, a system, a platform, a medium and equipment for planning the path of a commercial vehicle. The method comprises the following steps: segmenting the road map according to the map segmentation information to obtain a plurality of road units; classifying mass commercial vehicle networking data corresponding to the road units according to preset categories, and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise vehicle types, loads and oil consumption; according to a road network matching algorithm, matching each classification label with a corresponding road unit to obtain a road label corresponding to each road unit, wherein the road label comprises an oil consumption label; and extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating and determining the final planned path.
According to the commercial vehicle path planning method, massive commercial vehicle networking data are utilized for classification and superposition, and corresponding classification labels are generated and comprise vehicle type labels, load labels, oil consumption labels and the like. And matching each classification label with the road unit through a road network matching algorithm to obtain the road label corresponding to each road unit. And then extracting the data of the road labels corresponding to the road units from each planned path according to the actual path planning requirement, calculating and comparing, and selecting the optimal planned path as a target path. Through categorised stack to massive commercial car networking data to the labeling, consider the actual route planning with oil consumption data simultaneously for the route planning process is simple high-efficient, through various road labels, and the perfect requirement that accords with the user to road planning takes into account the oil consumption factor simultaneously, promotes commercial car route planning's economic nature.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of an embodiment of a method for planning a path of a commercial vehicle according to the present application.
In the embodiment shown in fig. 1, the method for planning the path of the commercial vehicle includes: the process S101 segments the road map according to the map segment information to obtain a plurality of road units.
In this embodiment, a road map is segmented according to map segmentation information to obtain a plurality of road units. The map segmentation information can be toll station sites or high-speed portal frames serving as route segmentation points, and then each road unit is obtained.
It should be noted that a road unit represents the minimum unit of a section of a road, there is no intersection between the road units, and there is no ambiguity in attribution for each road unit.
In the embodiment shown in fig. 1, the method for planning the path of the commercial vehicle includes: in the process S102, the mass commercial vehicle networking data corresponding to the road units are classified according to the preset categories, and the classification labels corresponding to the classification results are correspondingly generated, wherein the classification labels comprise oil consumption.
In the embodiment, in order to better perform more appropriate path planning on the vehicle with the planned path, the acquired mass commercial vehicle internet data is classified according to the preset category. The data of the Internet of vehicles comprise data such as driving tracks, mileage, driving time and oil consumption of the vehicles. The preset categories may include vehicle type, age, and load. And classifying the mass Internet of vehicles data according to a preset category, and correspondingly generating corresponding classification labels for the obtained classification result, wherein the classification labels comprise vehicle types, loads, oil consumption and the like. When data such as oil consumption and driving time in the data of the internet of vehicles are classified, the data such as the oil consumption and the like have direct relation with the vehicle type, the load and the like, so that the data such as the related oil consumption and the time are classified again on the basis of the classification result of the data such as the vehicle type, the load and the like.
Optionally, the mass commercial vehicle networking data corresponding to the plurality of road units are classified according to preset categories, and classification labels corresponding to the classification results are correspondingly generated, including: extracting the corresponding vehicle networking data of the commercial vehicle when the vehicle passes through a road unit from a vehicle networking database established by the commercial vehicle-mounted terminal, wherein the vehicle networking data comprises vehicle track, vehicle speed and oil consumption; the data of the car networking of different grade type are classified according to predetermineeing the classification, obtain corresponding classification result, and then generate the classification label that each classification result corresponds, and classification label includes the motorcycle type that the commercial car corresponds, and the load that the commercial car corresponds and the oil consumption that the commercial car went through the road unit and corresponds, wherein when including many car networking data in same classification result, superpose many car networking data of dispersion, obtain the whole data of many car networking data.
In this optional embodiment, a large amount of commercial vehicle networking data may be acquired through the vehicle-mounted terminal device, where the vehicle networking data includes data such as a driving track of a vehicle, a vehicle speed corresponding to a certain road on which the vehicle is driven, and oil consumption. And classifying the different types of Internet-of-vehicles data according to preset categories to obtain corresponding classification results, and correspondingly generating corresponding classification labels. When the classification is performed, a plurality of pieces of data may be included in one category. In order to fully improve the reference degree of data when subsequent path planning is carried out and avoid the problem that a path planning result has a large error due to less reference data, a plurality of scattered data in the same category are overlapped to obtain the whole data. For example, a plurality of pieces of oil consumption data on a section of road are overlapped to obtain a complete piece of oil consumption data, and when path planning is performed, existing data are fully considered, so that the accuracy of path planning is improved.
Specifically, when massive commercial vehicle networking data is classified, the data can be classified according to vehicle types, vehicle ages, loads, road types and the like. The vehicle type classification can classify the vehicles according to the platforms, strains, drives, horsepower, engine models and the like of the vehicles, and generates corresponding vehicle type labels for classified results; the vehicle age classification can be calculated based on the date of delivery of the vehicle or the date of first sale, and the vehicle age can be obtained by subtracting the current date from the date of delivery and can be converted into a unit year. When the car age is classified, the car age section can be set as a classification standard. For example, car ages 0-2 years, 2-5 years, etc. are taken as corresponding car age classification categories. The load classification can be based on vehicle historical track data and a load algorithm, and is used for classifying load data in the vehicle networking data and correspondingly generating corresponding load labels, wherein different load ranges can be set as follows: 0-20t, 20-30t, 30-40t, 40-50t, 50-60t and more than 60 t. The road classification may be performed based on existing road network data, and may be performed for each road unit according to the road condition. For example, the road category labels can be generated by classifying into a high-speed plain, a high-speed mountain area, a mixed-working-condition plain, a mixed-working-condition mountain area, a national-province road plain, a national-province road mountain area, and other working conditions.
In the embodiment shown in fig. 1, the method for planning the path of the commercial vehicle includes: in the process S103, each classification label is matched with a corresponding road unit according to a road network matching algorithm to obtain a road label corresponding to each road unit, where the road label includes an oil consumption label.
In this embodiment, after the classification label and the road unit of the vehicle networking data are obtained respectively, the road unit and the classification label are matched by using the existing road network matching algorithm, so that each road unit has the road label corresponding to the road segment. And then, performing subsequent path planning according to the road labels corresponding to the road units.
Optionally, when the commercial vehicle runs through the road unit, extracting a classification label of the commercial vehicle corresponding to the vehicle networking data, wherein the classification label comprises a vehicle type, a load and oil consumption; and assigning the classification labels to the road units to obtain road labels corresponding to the road units, wherein the road labels comprise fuel consumption labels which represent the fuel consumption of the corresponding commercial vehicles when the commercial vehicles run through the road units.
In this optional embodiment, in the acquisition of the internet of vehicles data, the vehicle-mounted terminal of each vehicle may record the driving track of the vehicle and information such as the corresponding mileage, the driving duration, and the oil consumption. The recorded driving track is matched with the road map, and then the road unit corresponding to the driving track can be obtained. And then according to the corresponding relation, matching the classification labels obtained by classifying the mass Internet of vehicles data with the road units to obtain the road labels corresponding to the road units. The vehicle networking data corresponding to the road labels corresponding to the road units are driving data of a plurality of vehicles driving through the road units.
Specifically, for example, after a truck travels a certain distance, the data of the internet of vehicles is classified, for example, there are classification labels corresponding to the vehicle type of the truck, the load is 20t, the driving time is 40 minutes, the mileage is 50 kilometers, and the oil consumption is 8 liters, and there are two sections of road units corresponding to the driving track in the data of the internet of vehicles, where, according to the record in the data of the internet of vehicles, the driving time corresponding to the first road unit is 15 minutes, the mileage is 20 kilometers, and the oil consumption is 3 liters. Matching the classification labels of the Internet of vehicles data with the first road unit and the second road unit to obtain road labels corresponding to the first road unit, wherein the road labels comprise a vehicle type label of a truck, a load label of a load of 20t, a time label of 15 minutes, a mileage label of 20 kilometers in mileage and a fuel consumption label of 3 liters in fuel consumption; the corresponding second road unit is also assigned a corresponding road label. And the road labels corresponding to the road units are used for subsequent accurate path planning.
In the embodiment shown in fig. 1, the method for planning the path of the commercial vehicle includes: and a process S104 of extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirement, calculating and determining the final planned path.
In this embodiment, when planning a route, a plurality of selectable planned routes can be calculated according to information such as a start point, an end point, and a departure time input by a user and an existing route navigation method. The reasonable path selection is carried out according to the path planning requirements of the user, such as shortest time, shortest mileage, lowest oil consumption, lowest traffic cost and the like. When the route planning is carried out, the oil consumption factors are counted, the oil consumption can be minimized, and a more economical route is selected. According to the path planning requirements of the user, for example, the oil consumption is the minimum, corresponding oil consumption labels are extracted from each road unit corresponding to each planned path, the oil consumption of each planned path is judged through the oil consumption labels, and the path with the minimum oil consumption is finally determined and serves as the final planned path.
Optionally, extracting data corresponding to the road labels in each road unit of the multiple planned paths according to the path planning requirement, calculating, and determining the final planned path further includes: extracting corresponding Internet of vehicles data according to the road labels corresponding to the road units; according to the preset scene type, calculating estimated driving data when commercial vehicles of corresponding vehicle types drive through each road unit, wherein the estimated driving data comprises oil consumption data corresponding to the road units; and establishing a driving data dictionary table corresponding to each one-way unit according to the estimated driving data.
In the optional embodiment, in the mass commercial vehicle networking data, one road label in one road unit corresponds to multiple pieces of data, so that when a path is planned, corresponding to one road unit, the vehicle networking data under one label dimension needs to calculate an average value, and the average value represents the average level of a corresponding vehicle passing through the road unit, so that in the path planning process, more accurate reference is provided, and the accuracy of the path planning is improved. Firstly, extracting corresponding data according to the road label corresponding to each road unit; and calculating estimated driving data corresponding to each road unit according to the preset scene type and corresponding vehicle networking data, wherein the estimated driving data is an average value of the type data. And finally, establishing a driving data dictionary table according to the corresponding relation between the estimated driving data and the preset scene type, so that subsequent data extraction is facilitated. The preset scene type is a combination of various road labels and corresponds to application scenes of various vehicle driving processes.
Specifically, the existing Weichai firewood certain type of commercial vehicle runs on a section of path from a starting point to an end point, and relates to two sections of road units, Link1 and Link 2. Through statistics and classification of networking data of the type of commercial vehicle, the vehicle speed interval of the type of commercial vehicle is below 40Km/h, the load interval comprises 20-30t, 30-40t, 40-50t and 50-60t, and the classification can be represented through corresponding road labels. And counting the running data such as the running time and the fuel consumption under various road labels, and calculating the average value to obtain a reference dictionary table of the commercial vehicle of the certain Weichai firewood model under the units Link1 and Link 2.
Table 1: weichai diesel and type commercial vehicle driving reference dictionary expression example
Optionally, according to the path planning requirement, extracting data corresponding to the road labels in each road unit of the multiple planned paths, performing calculation, and determining a final planned path, including: determining corresponding road labels in a plurality of planned paths according to path planning requirements, and extracting estimated driving data corresponding to each road unit in the planned paths according to the road labels in a driving data dictionary table; and respectively calculating the overall estimated driving data of each planned path according to the estimated driving data corresponding to each road unit.
In this alternative embodiment, when planning a route, a plurality of planned routes from the starting point to the end point are obtained after the user inputs the starting point and the end point through the conventional navigation means. Wherein each planned path comprises a plurality of road units. According to different requirements of a user on a planned path, such as the shortest distance, the lowest oil consumption and the like, corresponding road labels, namely mileage labels corresponding to road units and oil consumption labels corresponding to the road units, are determined. And then extracting corresponding estimated driving data when the planned vehicle passes through the road unit according to the road label in the established driving data dictionary table, further obtaining the overall estimated driving data of the whole planned path according to the estimated driving data of each road unit, and finally determining the target path by comparing different overall estimated driving data of different planned paths.
Specifically, for example, the user may require the least fuel consumption for the planned route. The user determines a corresponding fuel consumption label according to the path planning requirement with the least fuel consumption, and obtains fuel consumption data of each road unit involved in the planned path by inputting the labels of the vehicle type, the load and the like of the vehicle and the fuel consumption labels involved in the path planning into the navigation system and utilizing the reference dictionary table shown in the table 1. For example, at present, there are two planned paths, where the planned path 1 includes a Link1 and a Link2, and the planned path 2 includes Link3 and Link 4. Through a pre-constructed oil consumption dictionary table, the oil consumption of the road unit Link1 meeting the vehicle type conditions of the user is a1, the oil consumption of the road unit Link2 is a2, and the overall oil consumption of the planned path 1 is a1+ a 2; similarly, for the planned path 2, the oil consumption of the road unit Link3 in the dictionary table is a3, the oil consumption of the road unit Link4 is a4, the overall oil consumption of the planned path 2 is a3+ a4, and the planned path which best meets the user requirements in the two planned paths can be obtained by comparing a1+ a2 and a3+ a 4.
It should be noted that, similar to the oil consumption requirement, when the path planning requirement is the shortest time, the lowest high-speed charging, and the like, in the path planning, corresponding data is extracted from the dictionary table corresponding to the planned path for calculation, and the planned path is determined.
In an example of the present application, in a calculation scheme of the route planning, first, all road connectivity from a starting position to an ending position is calculated, and weighting conditions such as an average vehicle speed, a road type (whether to charge), a fuel charge (fuel amount and oil unit price), a high speed charge (a charging road mileage and charging unit price) are added to a calculation result. And finally, calculating the total time, the total mileage and the total cost of all the communication schemes, and planning according to the starting point, the terminal point, the vehicle type, the load and the departure time input by the user. In the common path planning requirement, when the related time is shortest, the time lengths of all the road units in the path are added based on the historical average time length of each road unit contained in the path planning process, and the estimated time lengths of different paths are compared. When the related distance is shortest, the lengths of all road units in the path are added based on the lengths of all road units contained in the path planning process, and the distances of different paths are compared. When the related cost is the lowest, calculating and estimating the high-speed fee according to the mileage of the toll road and the charging unit price based on the high-speed toll gate which is included in the path and is passed by each road unit in the path planning process; based on each road unit in the path, an average oil consumption value is taken out according to an oil consumption dictionary table, an estimated oil cost is calculated according to the fuel quantity and the oil product unit price, the high-speed cost and the oil cost are added to obtain an estimated total cost, and the cost of different paths is compared. Thus, the optimal routes of the three different angles are obtained, and the user can select the optimal routes according to needs. According to the method for planning the path of the commercial vehicle, the oil consumption factor is considered in the path planning process, and more economical selection of the path planning is achieved.
Optionally, according to the path planning requirement, extracting the road label corresponding to each road unit in the multiple planned paths, performing calculation, and determining the final planned path, further comprising: extracting fuel consumption labels corresponding to each road unit in the multiple planning paths according to the fuel consumption requirements; extracting corresponding oil consumption data of each road unit according to the oil consumption label, and calculating the oil consumption corresponding to each planned path; and sequencing the oil consumption, and determining the planned path with the least oil consumption as a target path according to a sequencing result.
In the optional embodiment, when path planning is performed according to the oil consumption requirement, that is, when the oil consumption of the final target path is the minimum, oil consumption labels corresponding to each road unit are extracted from a plurality of optional planning paths; and extracting corresponding oil consumption data of each road unit according to the actual vehicle running condition in a pre-established oil consumption dictionary table according to the oil consumption label, and calculating the oil consumption corresponding to each planned path. And sequencing the oil consumption, and determining the planned path with the least oil consumption as a target path according to a sequencing result. When the oil consumption data is counted, the converted oil fees can be sorted into a certain oil fee sequence or a certain route toll sequence according to the real-time oil price, and on the basis of considering the oil consumption, the conditions of high-speed charging and the like are considered at the same time, wherein the processes are similar and are not repeated.
Since the fuel consumption of the vehicle is related to conditions such as vehicle speed, distance, and time during the running of the vehicle, the target route determined by considering the requirements such as lowest fuel consumption and shortest time alone may not be the optimal route as a whole. When the oil consumption data is considered, because the oil consumption data is related to factors such as vehicle speed, duration and the like, when path planning is carried out according to oil consumption, corresponding weights can be set for various path planning requirements, and various requirements during path planning are considered integrally, so that an optimal planning path is obtained.
Fig. 2 shows an example of the method for planning the path of the commercial vehicle, and the specific process of the method is further described by using fig. 2.
As shown in fig. 2, by using a large amount of commercial vehicle networking data, historical tracks of commercial vehicle driving counted for many years are classified according to preset classification categories, wherein the preset categories include vehicle types, loads, vehicle ages and the like. And obtaining the corresponding classification label. The commercial vehicle driving tracks are classified, so that when the target vehicle is planned with road strength at the later stage, corresponding driving data are selected as the basis of path planning according to the type, the load and the like of the target vehicle, the path planning is more accurate, and the path planning requirements of users are met. And classifying the road map data, and segmenting the map data according to basic segmentation information of the road to obtain each road unit, wherein the basic segmentation information can be toll stations or portal frames and the like on the expressway. And classifying according to the road grade and the road condition to obtain the road grade and the road condition corresponding to each road unit, wherein the road grade comprises a high-speed plain, a high-speed mountain area, a national and provincial road plain and the like, and the road condition comprises smoothness, repair and the like.
And then matching the classification results through a road network matching algorithm. And matching the classification labels corresponding to the vehicle networking data with the corresponding road units through a road network matching algorithm, so as to obtain the road labels of the commercial vehicle driving data corresponding to each road unit. For example, for one road unit, through road network matching, the model label, the load label, the age label of each commercial vehicle passing through the road network unit, and the fuel consumption label, the duration label, etc. of the corresponding vehicle type when passing through the road unit can be known. And assigning corresponding road labels to each road unit in the road map through a road network matching algorithm. Since the time tag, the fuel consumption tag, and the like are related to the vehicle state such as the model, the age, and the load, the time tag in the road unit. The fuel consumption label and the like are all represented under the labels of the vehicle type, the load and the like. It should be noted that, since there are many corresponding commercial vehicle driving data in the same road unit, for example, there are many pieces of data of the time length passing through the road unit, the time length label, the fuel consumption label, and the like in the road unit represent the average data of the time length of the type and the average data of the fuel consumption. And after the road labels corresponding to the road units are obtained, path planning is carried out subsequently. As shown in fig. 2, the road unit Link1 corresponds to various road labels of the road unit, such as a vehicle type label, a load label, and a fuel consumption label. The remaining road units Link2, etc., are similar to Link 1.
And during path planning, according to the starting point, the end point, the vehicle type and the load input by the user through the current path planning model. And planning the path according to the information such as the departure time. And then, selecting the path according to the requirements of the user on the path, such as shortest time, lowest oil consumption and the like. When path calculation is carried out, if the requirement of a user is that the oil consumption is the lowest, path planning extracts oil consumption labels of all road units in all planning paths under vehicle types and load labels, acquires oil consumption data corresponding to the corresponding road units, and obtains paths with the lowest oil consumption in a plurality of planning paths as final target paths by calculating the oil consumption data of all road units in the planning paths. As shown in FIG. 2, a path of a first scheme is obtained through a path planning model, wherein the path comprises road units Link001-Link002-Link 003; the path of the second scheme comprises a road unit Link001-Link004-Link 005. When the target path is determined, if the oil consumption of the path required by a user is the lowest, corresponding oil consumption data are obtained according to the oil consumption labels of the Link001, Link002, Link003, Link004 and Link005 of the road units respectively, the oil consumption of the Link001, Link002 and Link003 of the first scheme is superposed to obtain the oil consumption of the path of the first scheme, the oil consumption data of the Link001, Link004 and Link005 of the second scheme are superposed to obtain the oil consumption of the path of the second scheme, and the path with the lowest oil consumption is determined as a final planning path by comparing the oil consumption of the Link001, Link004 and Link005 of the first scheme with the oil consumption of the second scheme. Wherein for ease of handling. The driving data dictionary table of each single-path unit under different preset driving scenes can be established, such as an oil consumption dictionary table, a duration dictionary table and the like under different vehicle types, different loads and different road types. After the user inputs the path planning requirement, corresponding data are extracted according to the corresponding dictionary table for calculation, so that the method is more convenient and faster, and the calculation amount is reduced.
It should be noted that the oil consumption of a section of road is related to the driving time, the vehicle speed, and the like. Therefore, the weight between different path planning requirements can be set, and further, the optimized path is selected from a plurality of planning paths to be used as a final target path.
According to the method for planning the commercial vehicle path, a large amount of vehicle networking data are classified and overlapped, and the vehicle networking data are labeled to obtain various road labels corresponding to each road unit. Meanwhile, oil consumption data in the internet of vehicles data are counted to generate corresponding labels, and then when path planning is carried out, the oil consumption is taken into account, and the economy of the path planning is improved.
Fig. 3 shows an embodiment of the present commercial vehicle path planning system.
As shown in fig. 3, the path planning system for a commercial vehicle according to the present application includes: a module 301 for segmenting the road map according to the map segmentation information to obtain a plurality of road units; a module 302 for classifying the mass commercial vehicle networking data corresponding to the plurality of road units according to preset categories and correspondingly generating classification labels corresponding to the classification results, wherein the classification labels comprise vehicle types, loads and oil consumption; a module 303, configured to match each classification label with a corresponding road unit according to a road network matching algorithm, to obtain a road label corresponding to each road unit, where the road label includes an oil consumption label; and a module 304 for extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating, and determining a final planned path.
Optionally, in the module 302, when the driving road unit is extracted from the vehicle networking database acquired by the vehicle-mounted terminal of the commercial vehicle, vehicle networking data corresponding to the commercial vehicle is extracted, where the vehicle networking data includes a vehicle track, a vehicle speed, and oil consumption; the data of the car networking of different grade type are classified according to predetermineeing the classification, obtain corresponding classification result, and then generate the classification label that each classification result corresponds, and classification label includes the motorcycle type that the commercial car corresponds, and the load that the commercial car corresponds and the oil consumption that the commercial car went through the road unit and corresponds, wherein when including many car networking data in same classification result, superpose many car networking data of dispersion, obtain the whole data of many car networking data.
Optionally, in the module 303, a classification label of the commercial vehicle corresponding to the vehicle networking data when the commercial vehicle runs through the road unit is extracted, where the classification label includes a vehicle type, a load, and an oil consumption; and assigning the classification labels to the road units to obtain road labels corresponding to the road units, wherein the road labels comprise fuel consumption labels which represent the fuel consumption of the corresponding commercial vehicles when the commercial vehicles run through the road units.
Optionally, the commercial vehicle path planning system of the present application further includes a driving data dictionary table creating module, which extracts corresponding vehicle networking data according to the road label corresponding to each road unit; according to the preset scene type, calculating estimated driving data corresponding to each road unit when a commercial vehicle of a corresponding vehicle type drives through, wherein the estimated driving data comprises oil consumption data corresponding to the road units; and establishing a driving data dictionary table corresponding to each one-way unit according to the estimated driving data.
Optionally, in the module 304, according to the path planning requirement, the driving data corresponding to each road unit is extracted from the driving data dictionary table; respectively calculating the overall driving data of each planned path in the plurality of planned paths according to the driving data corresponding to each road unit; and judging the whole driving data according to a preset rule, and selecting a preset number of paths from the corresponding multiple planned paths as target paths.
Optionally, in the module 304, according to the fuel consumption requirement, fuel consumption labels corresponding to each road unit in the multiple planned paths are extracted; extracting corresponding oil consumption data of each road unit according to the oil consumption label, and calculating the oil consumption corresponding to each planned path; and sequencing the oil consumption, and determining the planned path with the least oil consumption as a target path according to a sequencing result.
The utility vehicle path planning system of this application is through classifying the stack to a large amount of commercial car networking data at the path planning in-process, carries out the labellization to the car antithetical couplet data, obtains the various road labels that each road unit corresponds. Meanwhile, oil consumption data in the internet of vehicles data are counted to generate corresponding oil consumption labels, and then when path planning is carried out, oil consumption is taken into account, and the economy of the path planning is improved.
Fig. 4 shows an embodiment of the platform for planning the path of a commercial vehicle according to the present application.
In the embodiment shown in fig. 4, the platform for planning the path of the commercial vehicle according to the present application includes: the system comprises a plurality of vehicle-mounted terminals, a plurality of mobile terminals and a plurality of mobile terminals, wherein the vehicle-mounted terminals are used for collecting the driving data of the commercial vehicle, receiving the path planning requirement input by a user and uploading the path planning requirement; the server is used for classifying the mass commercial vehicle mass internet of vehicles data according to preset categories and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise vehicle types, loads and oil consumption; the road network matching system is used for matching each classification label with a corresponding road unit according to a road network matching algorithm to obtain a road label corresponding to each road unit, wherein the road label comprises an oil consumption label; and the road label extraction module is used for extracting the road labels corresponding to the road units in the multiple planned paths according to the path planning requirements, calculating, determining the final planned path, sending the final planned path to the vehicle-mounted terminal and displaying the final planned path to the user.
In the embodiment, the vehicle-mounted terminal is used as a data mobile phone device of the driving data of the commercial vehicle, and simultaneously interacts with a user during path planning. The user inputs data such as a starting point, a terminal point, starting time, a vehicle type, a load and the like into the vehicle-mounted terminal, the vehicle-mounted terminal sends the information to the rear-end server, the server carries out path planning according to the path planning requirement of the user, and sends a final path planning result to the corresponding vehicle-mounted terminal to be displayed to the user. Through classifying and superposing a large amount of commercial vehicle internet-of-vehicle data, the vehicle-associated data is labeled to obtain various road labels corresponding to each road unit. Meanwhile, oil consumption data in the internet of vehicles data are counted to generate corresponding oil consumption labels, and then when path planning is carried out, oil consumption is taken into account, and the economy of the path planning is improved.
In one embodiment of the present application, a computer-readable storage medium stores computer instructions, wherein the computer instructions are operable to perform the method for planning a path of a commercial vehicle described in any one of the embodiments. Wherein the storage medium may be directly in hardware, in a software module executed by a processor, or in a combination of the two.
A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium.
The Processor may be a Central Processing Unit (CPU), other general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), other Programmable logic devices, discrete Gate or transistor logic, discrete hardware components, or any combination thereof. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one embodiment of the present application, a computer device includes a processor and a memory, the memory storing computer instructions, wherein: the processor operates the computer instructions to perform the method for path planning for a commercial vehicle as described in any of the embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above embodiments are merely examples, which are not intended to limit the scope of the present disclosure, and all equivalent structural changes made by using the contents of the specification and the drawings, or any other related technical fields, are also included in the scope of the present disclosure.
Claims (10)
1. A method for planning a path of a commercial vehicle is characterized by comprising the following steps:
segmenting the road map according to the map segmentation information to obtain a plurality of road units;
classifying mass commercial vehicle networking data corresponding to the road units according to preset categories, and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise oil consumption;
according to a road network matching algorithm, matching each classification label including the oil consumption with the corresponding road unit to obtain a road label corresponding to each road unit, wherein the road label comprises an oil consumption label which represents the oil consumption of the corresponding commercial vehicle when the commercial vehicle runs through the road unit;
and extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating and determining the final planned path.
2. The method for planning the path of the commercial vehicle according to claim 1, wherein the step of classifying the massive commercial vehicle networking data corresponding to the plurality of road units according to preset categories and correspondingly generating classification labels corresponding to the classification results comprises the steps of:
extracting the corresponding vehicle networking data of the commercial vehicle when the commercial vehicle drives through the road unit from a vehicle networking database established by the commercial vehicle-mounted terminal, wherein the vehicle networking data comprises vehicle track, vehicle speed and oil consumption;
classifying the different types of the Internet of vehicles data according to the preset categories to obtain corresponding classification results, and further generating classification labels corresponding to the classification results, wherein the classification labels comprise corresponding oil consumption when the commercial vehicles drive through the road unit, and the fuel consumption is measured by the commercial vehicles
When the same classification result comprises a plurality of pieces of car networking data, the dispersed pieces of car networking data are overlapped to obtain the overall data of the pieces of car networking data.
3. The method for planning a path of a commercial vehicle according to claim 1, wherein the step of matching each classification label with the corresponding road unit according to a road network matching algorithm to obtain the road label corresponding to each road unit comprises:
extracting classification labels of the commercial vehicles corresponding to the vehicle networking data when the commercial vehicles drive through each road unit, wherein the classification labels comprise vehicle types, loads and oil consumption;
and assigning the classification labels to the corresponding road units to obtain the road labels corresponding to the road units, wherein the road labels comprise fuel consumption labels.
4. The method for planning a commercial vehicle path according to claim 1, wherein the step of extracting data corresponding to the road labels in each road unit of a plurality of planned paths according to the path planning requirement and calculating the data, and the step of determining the final planned path further comprises the steps of:
extracting corresponding Internet of vehicles data according to the road labels corresponding to the road units;
according to a preset scene type, calculating estimated driving data when a commercial vehicle of a corresponding vehicle type drives through each road unit, wherein the estimated driving data comprises oil consumption data corresponding to the road unit;
and establishing a driving data dictionary table corresponding to each one-way unit according to the estimated driving data.
5. The method for planning a commercial vehicle path according to claim 4, wherein the step of extracting data corresponding to the road labels in each road unit of a plurality of planned paths according to the path planning requirement and calculating the data to determine the final planned path comprises the steps of:
determining corresponding road labels in the plurality of planned paths according to path planning requirements, and extracting the estimated driving data corresponding to each road unit in the planned paths in the driving data dictionary table according to the road labels;
respectively calculating the overall estimated driving data of each planned path according to the estimated driving data corresponding to each road unit;
and judging the whole driving data according to a preset rule, and selecting a preset number of paths from the corresponding planning paths as target paths.
6. The method for planning a commercial vehicle path according to claim 1 or 5, wherein the process of extracting data corresponding to the road labels in each road unit of a plurality of planned paths according to the path planning requirement, calculating and determining the final planned path further comprises:
extracting the fuel consumption labels corresponding to the road units in the multiple planning paths according to the fuel consumption requirements;
extracting corresponding oil consumption data of each road unit according to the oil consumption label, and calculating the oil consumption corresponding to each planned path;
and sequencing the oil consumption, and determining the planned path with the least oil consumption as a target path according to a sequencing result.
7. A commercial vehicle path planning system, comprising:
a module for segmenting the road map according to the map segmentation information to obtain a plurality of road units;
the module is used for classifying massive commercial vehicle networking data corresponding to the road units according to preset categories and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise oil consumption;
a module, configured to match, according to a road network matching algorithm, each classification tag including the fuel consumption with the corresponding road unit to obtain a road tag corresponding to each road unit, where the road tag includes a fuel consumption tag indicating the fuel consumption of the corresponding commercial vehicle when the vehicle travels through the road unit;
and the module is used for extracting data corresponding to the road labels in each road unit of the plurality of planned paths according to the path planning requirements, calculating and determining the final planned path.
8. A commercial vehicle path planning platform, comprising:
the system comprises a plurality of vehicle-mounted terminals, a plurality of mobile terminals and a plurality of mobile terminals, wherein the vehicle-mounted terminals are used for collecting the driving data of the commercial vehicle, receiving the path planning requirement input by a user and uploading the path planning requirement;
the server is used for classifying the mass commercial vehicle mass internet-of-vehicles data according to preset categories and correspondingly generating classification labels corresponding to classification results, wherein the classification labels comprise vehicle types, loads and oil consumption;
the fuel consumption label matching system is used for matching each classification label including the fuel consumption with the corresponding road unit according to a road network matching algorithm to obtain a road label corresponding to each road unit, wherein the road label comprises a fuel consumption label which represents the fuel consumption of the corresponding commercial vehicle when the commercial vehicle runs through the road unit;
and the data corresponding to the road labels in each road unit of the multiple planned paths are extracted according to the path planning requirements, calculated, determined to be the final planned path, and sent to the vehicle-mounted terminal to be displayed to the user.
9. A computer-readable storage medium, characterized in that the storage medium stores computer instructions that are operative to perform the method of path planning for a commercial vehicle according to any one of claims 1-6.
10. A computer device comprising a processor and a memory, the memory storing computer instructions, wherein: the processor operates the computer instructions to perform the method of path planning for a commercial vehicle according to any of claims 1-6.
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