CN115437377A - Automatic driving speed planning method, electronic device, vehicle, and storage medium - Google Patents
Automatic driving speed planning method, electronic device, vehicle, and storage medium Download PDFInfo
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- 238000004590 computer program Methods 0.000 claims description 6
- 230000032683 aging Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000004134 energy conservation Methods 0.000 abstract description 6
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/028—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using a RF signal
Abstract
The invention provides an automatic driving speed planning method, electronic equipment, a vehicle and a storage medium, wherein the automatic driving speed planning method comprises the steps of obtaining historical operation data and actual road characteristics in each operation route; creating nodes according to the actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise historical operation data; counting historical information of each road section according to the directed graph, wherein the historical information of each road section is used for training an oil consumption model; the real-time information of the vehicle is input into the trained oil consumption model, the target speed of the vehicle at each road section is output according to the oil consumption model, the historical information of each road section is counted from the mass data through the directed graph, and the historical information of the road section is input into the oil consumption model, so that the vehicle speed is planned according to the oil consumption, the vehicle operation cost is reduced, the energy conservation and emission reduction are realized, and the method is suitable for heavy vehicles.
Description
Technical Field
The present invention relates to the field of automatic driving technologies, and in particular, to an automatic driving speed planning method, an electronic device, a vehicle, and a storage medium.
Background
With the continuous development of science and technology, automatic control or manual driving assistance is realized through a vehicle control device, and the improvement of the automation and the intellectualization of vehicles has become a popular trend. In automatic driving control, the vehicle running speed influences the vehicle safety, so that the vehicle speed is particularly important to plan, more researches on speed planning methods in the existing automatic driving pay attention to car speed planning control, oil consumption factors are ignored in the planning process, and the oil consumption is an important aspect of energy conservation and emission reduction, so that the existing automatic driving speed planning method is high in cost, can cause environmental pollution and cannot meet the requirements of energy conservation and emission reduction. Also, fuel consumption is one of the major concerns for heavy vehicles, and therefore, the existing automatic driving speed planning method is not suitable for heavy vehicles.
Disclosure of Invention
The invention provides an automatic driving speed planning method, electronic equipment, a vehicle and a storage medium, which are used for solving the defects that the automatic driving speed planning method in the prior art is high in cost, cannot meet the requirements of energy conservation and emission reduction and is not suitable for heavy vehicles.
The invention provides an automatic driving speed planning method, which comprises the following steps:
acquiring historical operation data and actual road characteristics in each operation route;
creating nodes according to the actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise the historical operation data;
counting historical information of each road section according to the directed graph, wherein the historical information of each road section is used for training an oil consumption model;
and inputting the real-time information of the vehicle into the trained oil consumption model so as to output the target speed of the vehicle at each road section according to the oil consumption model.
The automatic driving speed planning method provided by the invention further comprises the following steps:
when the length of the edge of the directed graph is larger than a preset length threshold value, adding nodes on the edge according to splitting parameters corresponding to the edge, wherein the splitting parameters comprise at least one of speed distribution, travelable lane number distribution and gradient distribution on a road section corresponding to the edge.
According to the automatic driving speed planning method provided by the invention, the oil consumption model comprises an objective function F and a constraint condition, and the objective function F corresponds to the formula as follows:
wherein F is a function of the fuel consumption value, gamma is a fuel consumption coefficient, and y e ，a e ，b e ，c e Respectively a first, a second, a third and a fourth calculation coefficient, v e Is the target speed on the road section e, w is the vehicle weight, x is the load;
the constraints include a speed constraint:
α e ≤v e ≤β e
wherein v is e Is the target speed, alpha, on the road section e e ≤v e ≤β e As a constraint condition of road speed limit, α e For minimum speed requirement of section e, beta e Is the maximum speed requirement for section e.
Further, the constraint conditions further include an aging constraint condition:
wherein s is e Is the length of the section e, t e And predicting the effective running time of the vehicle according to the historical operation data and the vehicle real-time information.
According to an automatic driving speed planning method provided by the invention, the historical operation data comprises:
at least one of road segment length distribution, grade distribution, speed limit, number of turns, predicted transit time, parking/congestion time distribution, and speed distribution.
According to the automatic driving speed planning method provided by the invention, the real-time information of the vehicle comprises actual parking/jam time, and the predicted effective running time of the vehicle is the difference value between the predicted passing time and the actual parking/jam time.
According to the automatic driving speed planning method provided by the invention, the actual road characteristics comprise:
vehicle location, type of location, and type of detail data.
The present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for planning the automatic driving speed as described in any of the above when executing the program.
The present invention also provides a vehicle comprising: an electronic device as described above.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements an automated driving speed planning method as described in any of the above.
According to the automatic driving speed planning method, the electronic equipment, the vehicle and the storage medium, historical operation data and actual road characteristics in each operation route are obtained; creating nodes according to the actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise historical operation data; counting historical information of each road section according to the directed graph, wherein the historical information of each road section is used for training an oil consumption model; the real-time information of the vehicle is input into the trained oil consumption model, the target speed of the vehicle at each road section is output according to the oil consumption model, the historical information of each road section is counted from the mass data through the directed graph, and the historical information of the road section is input into the oil consumption model, so that the vehicle speed is planned according to the oil consumption, the vehicle operation cost is reduced, the energy conservation and emission reduction are realized, and the method is suitable for heavy vehicles.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of an automated driving speed planning method provided by the present invention;
FIG. 2 is a schematic diagram of a directed graph in the automated driving speed planning method provided by the present invention;
fig. 3 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. 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 invention.
Fig. 1 is a flowchart of an automatic driving speed planning method according to an embodiment of the present invention, and as shown in fig. 1, the automatic driving speed planning method according to the embodiment of the present invention includes:
in the embodiment of the present invention, the historical operation data includes, but is not limited to, road section length distribution, slope distribution, speed limit, number of turns, predicted transit time, parking/congestion time distribution, speed distribution, and the like;
the actual road characteristics include but are not limited to vehicle position, type of the position, detailed data of the type and the like;
the vehicle position can acquire detailed position information according to a GPS; the types of the locations include, for example, ordinary roads, ramps, toll stations, service areas, and the like;
taking the type of the location as the service area as an example, the detailed data of the type includes the distribution of the residence time of the service area.
102, creating nodes according to actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise historical operation data;
in the embodiment of the invention, the stop position information of the ramp, the toll station and the service area in the historical vehicle operation data is converted into the nodes of the digraph, the edges of the digraph are drawn according to the sequence of the nodes, the node attribute comprises position, type and metadata, and the metadata comprises the detailed data of the corresponding node type; the edge attributes include length, speed limit, grade profile, parking/congestion time profile, speed profile, etc.
In some embodiments of the invention, further comprising:
when the length of the edge of the directed graph is larger than a preset length threshold value, adding nodes on the edge according to splitting parameters corresponding to the edge, wherein the splitting parameters include but are not limited to speed distribution, drivable lane number distribution, gradient distribution and the like on a road section corresponding to the edge.
For example, when the distance between the toll station and the service area is long, the length of the edge can be reduced by adding the ramp node, so that the speed planning is more specific, and the purpose of optimizing the speed of each road section is achieved. It will be appreciated that the lower the edge length threshold, the shorter the segment, and the more accurate the speed planned for the entire route. It should be noted that, those skilled in the art can set the length threshold of the edge according to actual needs, and the application is not limited thereto.
As shown in fig. 2, the directed graph obtained from the historical operation data and the actual road characteristics is G (k, e), where k denotes a node of the directed graph and e denotes an edge of the directed graph. The node k corresponds to a geographical location on an actual route, and the edge e corresponds to a section of the operation route. As can be seen from fig. 2, since the distance between the solid line nodes 2, 3 is long, the dotted line node 7 is added between the solid line nodes 2, 3 to make the length of each edge smaller than the preset length threshold.
in the embodiment of the invention, each parameter value in the oil consumption model can be fitted by using a supervised learning method so as to solve the oil consumption model.
And 104, inputting the real-time information of the vehicle into the trained oil consumption model so as to output the target speed of the vehicle on each road section according to the oil consumption model.
In some embodiments of the invention, the vehicle is, for example, a truck. Since the fuel consumption is an important factor of truck operation, the real-time information of the vehicle is input into the trained fuel consumption model so as to output the target speed of the truck on each road section according to the fuel consumption model, and the method has important significance for the truck operation.
The automatic driving speed planning method provided by the embodiment of the invention obtains historical operation data and actual road characteristics in each operation route; creating nodes according to the actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise historical operation data; counting historical information of each road section according to the directed graph, wherein the historical information of each road section is used for training an oil consumption model; the real-time information of the vehicle is input into the trained oil consumption model, the target speed of the vehicle at each road section is output according to the oil consumption model, the historical information of each road section is counted from the mass data through the directed graph, and the historical information of the road section is input into the oil consumption model, so that the vehicle speed is planned according to the oil consumption, the vehicle operation cost is reduced, the energy conservation and emission reduction are realized, and the method is suitable for heavy vehicles.
Based on any one of the above embodiments, in the embodiment of the present invention, the oil consumption model includes an objective function F and a constraint condition, and the objective function F corresponds to a formula:
wherein F is a fuel consumption function, gamma is a fuel consumption coefficient, and y e ，a e ，b e ，c e Respectively a first, a second, a third and a fourth calculation coefficient, v e Is the target speed on road section e, w is the vehicle weight, and x is the load.
The constraint conditions of the fuel consumption model comprise a speed constraint condition:
α e ≤v e ≤β e
wherein v is e Is the target speed, alpha, on the road section e e ≤v e ≤β e As a constraint condition of road speed limit, α e For minimum speed requirement of section e, beta e Is the maximum speed requirement for road segment e;
the speed limiting requirement can be met through the speed constraint condition, and safe driving is guaranteed.
The constraint conditions of the fuel consumption model further comprise an aging constraint condition:
wherein s is e Is the length of the section e, t e And the predicted effective running time of the vehicle is calculated according to the historical operation data and the real-time information of the vehicle.
In the embodiment of the invention, the real-time information of the vehicle comprises actual parking/jam time, and the predicted effective running time of the vehicle is the difference value between the predicted passing time and the actual parking/jam time.
In the embodiment of the invention, the oil consumption model with the constraint condition is solved, the optimal speed of each road section in each operation line which meets the time efficiency constraint and has the lowest oil consumption can be obtained, and the vehicle global speed planning result is obtained according to the optimal speed of each road section.
In some embodiments of the invention, by means of a vehicle-cloud cooperative link, the cloud receives real-time information feedback of vehicles in operation, calculates and outputs a speed distribution strategy of each vehicle on each road section, and continuously updates an optimized speed distribution strategy according to accumulation of historical operation data to further realize optimal speed distribution.
The automatic driving speed planning method provided by the embodiment of the invention can solve the speed planning problem of the heavy vehicle in automatic driving, can save oil while meeting the time effect, and further realizes environmental protection and cost saving.
The following describes the automatic driving speed planning apparatus provided by the present invention, and the automatic driving speed planning apparatus described below and the automatic driving speed planning method described above may be referred to in correspondence with each other.
Fig. 3 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 3: a processor (processor) 310, a communication Interface (Communications Interface) 320, a memory (memory) 330 and a communication bus 340, wherein the processor 310, the communication Interface 320 and the memory 330 communicate with each other via the communication bus 340. The processor 310 may invoke logic instructions in the memory 330 to perform an automated driving speed planning method comprising: acquiring historical operation data and actual road characteristics in each operation route; creating nodes according to the actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise historical operation data; counting historical information of each road section according to the directed graph, wherein the historical information of each road section is used for training an oil consumption model; and inputting the real-time information of the vehicle into the trained oil consumption model so as to output the target speed of the vehicle on each road section according to the oil consumption model.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a vehicle comprising: the electronic device according to the above embodiment.
In some embodiments of the invention, the vehicle is a heavy vehicle, such as a truck.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for automated driving speed planning provided by the above methods, the method comprising: acquiring historical operation data and actual road characteristics in each operation route; creating nodes according to the actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise historical operation data; counting historical information of each road section according to the directed graph, wherein the historical information of each road section is used for training an oil consumption model; and inputting the real-time information of the vehicle into the trained oil consumption model so as to output the target speed of the vehicle on each road section according to the oil consumption model.
The above-described embodiments of the apparatus are merely illustrative, and the 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 modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on the understanding, the above technical solutions substantially or otherwise contributing to the prior art may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the various embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. An automated driving speed planning method, comprising:
acquiring historical operation data and actual road characteristics in each operation route;
creating nodes according to the actual road characteristics, and constructing a directed graph by taking road sections among the nodes as edges, wherein the attributes of the edges comprise the historical operation data;
counting historical information of each road section according to the directed graph, wherein the historical information of each road section is used for training an oil consumption model;
and inputting the real-time information of the vehicle into the trained oil consumption model so as to output the target speed of the vehicle on each road section according to the oil consumption model.
2. The automated driving speed planning method of claim 1, further comprising:
when the length of the edge of the directed graph is larger than a preset length threshold value, adding nodes on the edge according to splitting parameters corresponding to the edge, wherein the splitting parameters comprise at least one of speed distribution, travelable lane number distribution and gradient distribution on a road section corresponding to the edge.
3. The automatic driving speed planning method of claim 1, wherein the fuel consumption model comprises an objective function F and a constraint condition, and the objective function F corresponds to the formula:
wherein F is a function of fuel consumption and gamma isCoefficient of fuel consumption, y e ，a e ，b e ，c e Respectively a first, a second, a third and a fourth calculation coefficient, v e Is the target speed on the road section e, w is the vehicle weight, x is the load;
the constraints include a speed constraint:
α e ≤v e ≤β e
wherein v is e Is the target speed, alpha, on the road section e e ≤v e ≤β e As a constraint condition of road speed limit, α e For minimum speed requirement of section e, beta e Is the maximum speed requirement for section e.
4. The automated driving speed planning method of claim 3 in which the constraints further comprise aging constraints:
wherein s is e Is the length of the section e, t e And predicting effective predicted running time of the vehicle according to the historical operation data and the vehicle real-time information.
5. The automated driving speed planning method of claim 4, wherein the historical operational data comprises:
at least one of road segment length distribution, grade distribution, speed limit, number of turns, predicted transit time, parking/congestion time distribution, and speed distribution.
6. The automated driving speed planning method of claim 5, wherein the vehicle real-time information includes an actual stop/jam time, and the vehicle predicted effective travel time is a difference between the predicted transit time and the actual stop/jam time.
7. The automated driving speed planning method of claim 1, wherein the actual road characteristics comprise:
vehicle location, type of location, and type of detail data.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements an automated driving speed planning method according to any of claims 1 to 7.
9. A vehicle characterized by comprising the electronic device of claim 8.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the automated driving speed planning method according to any one of claims 1 to 7.
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| CN116653962A (en) * | 2023-07-12 | 2023-08-29 | 南京项尚车联网技术有限公司 | Intelligent driving vehicle efficient energy-saving system and energy-saving method |
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| CN116653962A (en) * | 2023-07-12 | 2023-08-29 | 南京项尚车联网技术有限公司 | Intelligent driving vehicle efficient energy-saving system and energy-saving method |
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