CN107389085B - Method and device for determining road traffic attributes, computer and storage medium - Google Patents
Method and device for determining road traffic attributes, computer and storage medium Download PDFInfo
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- CN107389085B CN107389085B CN201710513560.0A CN201710513560A CN107389085B CN 107389085 B CN107389085 B CN 107389085B CN 201710513560 A CN201710513560 A CN 201710513560A CN 107389085 B CN107389085 B CN 107389085B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3697—Output of additional, non-guidance related information, e.g. low fuel level
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3626—Details of the output of route guidance instructions
- G01C21/3641—Personalized guidance, e.g. limited guidance on previously travelled routes
Abstract
The embodiment of the invention discloses a method, a device, a computer and a storage medium for determining road traffic attributes. The method comprises the following steps: identifying an actual free width of a road of a current road section; and/or acquiring the set vehicle type passing data passing state of the current road section; and determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing data passing state of the set vehicle type. The embodiment of the invention solves the problem that the navigation technology in the prior art can not recommend the navigation route according to the driving experience of the user, and determines the road passing attribute capable of reflecting the road driving difficulty, so that the navigation route screened according to the road passing attribute meets the requirements of the user, and the user experience is improved.
Description
Technical Field
The embodiment of the invention relates to a navigation technology, in particular to a method, a device, a computer and a storage medium for determining road traffic attributes.
Background
With the continuous development of navigation technology, more and more users drive vehicles according to navigation routes, and the navigation routes recommended to the users by devices such as vehicle-mounted navigation devices are more and more intelligent. For example, it is possible to recommend a navigation route having different characteristics to the user according to road attributes such as the road width of a link, the number of lanes, and the speed of restriction.
However, the navigation route determined according to the road attribute cannot reflect the passing difficulty of the road segment, and for a novice driver, the navigation route determined according to the road attribute often has the problems of high road passing difficulty and poor driving experience.
Disclosure of Invention
The embodiment of the invention provides a method, a device, a computer and a storage medium for determining road passing attributes, which are used for determining the passing attributes capable of reflecting road passing difficulty.
In a first aspect, an embodiment of the present invention provides a method for determining a road traffic attribute, where the method includes:
identifying an actual free width of a road of a current road section; and/or
Acquiring a set vehicle type passing state of the current road section;
determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing state of the set vehicle type
In a second aspect, an embodiment of the present invention further provides an apparatus for determining a road traffic attribute, where the apparatus includes:
the idle width identification module is used for identifying the actual idle width of the road of the current road section; and/or
The passing state determining module is used for acquiring the passing state of the set vehicle type of the current road section;
and the passing attribute determining module is used for determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing state of the set vehicle type.
In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the method for determining a road traffic attribute according to any embodiment of the present invention when executing the program.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the program, when executed by a processor, implements the method for determining a road traffic attribute provided in any embodiment of the present invention.
According to the embodiment of the invention, the actual idle width of the road of the current road section is obtained, the actual road width through which vehicles can pass is determined, the number of medium and large vehicles on the road of the current road section is determined by obtaining the passing state of the set vehicle type passing data, and the driving difficulty of the road of the current road section is determined according to the actual idle width of the road of the current road section and/or the passing state of the set vehicle type passing data, so that different users can select corresponding navigation routes according to the driving difficulty.
Drawings
Fig. 1 is a flowchart of a method for determining road traffic attributes according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for determining road traffic attributes according to a second embodiment of the present invention;
FIG. 3 is a schematic diagram of a street view image provided by the second embodiment of the invention;
fig. 4 is a flowchart of a method for determining road traffic attributes according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of a device for determining road traffic attributes according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of a computer device according to a fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a method for determining road traffic attributes according to an embodiment of the present invention, where the embodiment is applicable to a case of determining traffic attributes that can reflect difficulty in passing a road segment, and the method can be executed by a device for determining road traffic attributes according to an embodiment of the present invention, where the device can be implemented in a software and/or hardware manner, referring to fig. 1, and the method specifically includes:
and S110, identifying the actual idle width of the road of the current road section.
In this embodiment, each road is formed by combining a plurality of road segments, where the road segments may be a plurality of road segments divided by a preset length, or a plurality of road segments divided by traffic lights. The actual free width of the road refers to the actual width that can be traveled by the vehicle. The theoretical width of the road is the width between two edges of the road, including the actual idle width of the vehicle running and the width of the parking occupied lane. For drivers with poor driving experience, especially for novice drivers, the larger the actual idle width is, the smaller the driving difficulty is; correspondingly, the smaller the actual idle width, the greater the difficulty of driving.
In the embodiment, the actual idle width of the road of the current road section is obtained instead of the theoretical width of the road of the current road section, so that the increase of the driving difficulty of the road of the current road section due to the fact that the theoretical width of the road is large and the actual idle width is small is avoided.
And S120, acquiring a set vehicle type passing state of the road of the current road section, wherein the set vehicle type is a large vehicle.
The passing state of the vehicles on the current road section refers to a dense state of vehicle passing, and is determined according to the width of the current road section and the number of the vehicles passing through the current road section. For example, the traffic state of the vehicle may be divided into different levels, such as dense, general, sparse, etc., wherein the higher the traffic dense level, the greater the number of vehicles passing.
The large vehicle may be, for example, a heavy transport vehicle and/or a bus. Heavy transport vehicle and/or bus automobile body are bulky, and there are the lane width that occupies greatly in the driving process, shelter from multiple problems such as follow-up vehicle driver sight, and the user is in the driving vehicle in-process, especially to novice driver, and the large-scale car quantity of current highway section road is more, and the degree of difficulty of traveling is bigger, and is higher to driver's experience requirement.
It should be noted that step S110 and step S120 have no sequential relationship, and step S110 and step S120 may be executed separately or synchronously.
And S130, determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing state of the set vehicle type.
In the current navigation technology, a plurality of navigation routes are automatically generated by setting a starting point and a destination, wherein the navigation routes can be determined according to road basic attributes such as theoretical road width, traffic control speed, road theoretical width, road congestion and the like of roads in different road sections. The navigation route determined according to the road basic attribute cannot reflect the driving difficulty of the navigation route, and the obtained navigation route recommendations of different users are the same on the basis of the same starting point and destination, so that the navigation route meeting the user requirements cannot be screened according to the driving experience of the driver user. For users with a poor driving experience, especially novice users, the requirements may include, for example, good road traffic status, low driving difficulty, and the like, and specifically, the actual idle width of each road segment in the navigation route is large, the number of large vehicles is small, and the like.
In the embodiment, a new road passing attribute is defined by acquiring the actual idle width and/or the set vehicle type passing data passing state and according to the actual idle width and/or the set vehicle type passing data passing state, and the new road passing attribute is used for representing the driving difficulty of the road section.
Optionally, step S130 includes:
and carrying out weighted calculation on the actual idle width and/or the set vehicle type passing state to determine the driving difficulty coefficient of the road of the current road section.
In this embodiment, weights are set for the actual idle width and the set vehicle type passing state, weighted calculation is performed on the actual idle width and/or the set vehicle type passing state, and the driving difficulty coefficient of the road on the current road section is determined according to the calculation result. Illustratively, the smaller the actual idle width, the larger the driving difficulty factor; the larger the number of passing vehicles, the higher the density level of the passing state, and the larger the difficulty factor of driving.
In the embodiment, the driving difficulty coefficient of the road of the current road section is calculated according to the actual idle width and/or the set vehicle type passing state, so that the driving difficulty coefficient of each navigation route is determined while the navigation route is generated, a user can select a navigation route suitable for the driving capability of the user according to the driving difficulty coefficient, and the driving experience of the user is improved.
According to the technical scheme, the actual free width of the current road section is obtained, the actual road width through which vehicles can pass is determined, the passing state of middle and large-sized vehicles on the current road section is determined by obtaining the passing state of the set vehicle type passing data, the driving difficulty of the current road section is determined according to the actual free width of the current road section and/or the passing state of the set vehicle type passing data, so that different users can select proper navigation routes according to the driving difficulty, the problem that the navigation routes cannot be recommended according to the driving experience of the users in the prior art is solved, the road passing attribute capable of reflecting the driving difficulty of the roads is determined, the navigation routes screened according to the road passing attribute can meet the requirements of the users, and the user experience is improved.
On the basis of the above embodiment, after step S130, the method includes:
and identifying the user type of the navigation request, and screening and sequencing the navigation route generated by the route planning according to the user type and the driving difficulty coefficient of the road of the current road section.
The user type may be determined according to a driving experience of the user. Optionally, the user types are divided according to the driving time of the user, and exemplarily include a primary user, a middle-level user and a high-level user, wherein the primary user refers to a user with a driving experience of less than two years, namely a novice driver; a medium user refers to a user with two to five years of driving experience; advanced users refer to users having more than five years of driving experience. Optionally, the user types are divided according to driving distance, and for example, the larger the distance the user drives the vehicle, the higher the user grade.
In this embodiment, a plurality of navigation routes are generated according to a departure point and a destination input by a user, a driving difficulty coefficient of each navigation route is calculated, and the navigation routes corresponding to the driving difficulty coefficients are sorted and screened according to the user type. For example, if the user type is a primary user, the navigation route with a small driving difficulty coefficient is recommended as the optimal route. Optionally, the navigation route generated by the route planning is filtered and sorted according to the user type and the user requirement. Illustratively, the user requirement can be that the consumed time is shortest, the road is smooth, and the like, and illustratively, if the user requirement of the medium-level user is that the consumed time is shortest, the navigation route which consumes the shortest consumed time is selected from the navigation routes corresponding to the medium driving difficulty coefficient and recommended as the optimal route.
In the embodiment, the driving difficulty coefficient of each navigation route is calculated according to the actual idle width and/or the set vehicle type passing state, the navigation route suitable for the driving difficulty of the current user is screened according to the user type, and the driving experience of the user is improved.
Example two
Fig. 2 is a method for determining road traffic attributes according to a second embodiment of the present invention, and on the basis of the second embodiment, a method for identifying an actual free width of a road in a current road segment is further provided. Correspondingly, the method comprises the following steps:
and S210, obtaining a street view image of the road of the current road section.
The street view image is a 360-degree panoramic image for displaying the road of the current road segment, for example, see fig. 3, and fig. 3 is a schematic diagram of the street view image provided by the second embodiment of the present invention. The theoretical width of the road of the current road section and the driving condition of the vehicle can be identified in the street view image of fig. 3. Optionally, the street view image of the current road segment is collected and updated according to a preset period. Wherein the preset period may be three months. Preferably, the obtained street view images of the current road section include street view images of different time periods in the same day, and the road state of the current road section is evaluated according to the street view images of different time periods, so that the evaluation accuracy of the current road section is improved.
S220, carrying out image recognition on the street view image, and determining the number of occupied lanes occupied by long-term parking in the road of the current road section.
In this embodiment, the theoretical width of the road on the current road segment includes an actual idle width and an occupied lane width. Among them, long-term parking is a major factor causing occupation of the lane.
Optionally, step S220 includes:
identifying at least one vehicle of the same lane in the street view image;
judging whether the lane is an occupied lane or not according to the number of the turned-on lamps of at least one vehicle;
and counting the number of occupied lanes according to the lane occupation judgment result of each lane.
In the present embodiment, there is a case where the lamps are turned on during the running of the vehicle, and for example, the daytime running lamps of the vehicle are in a turned-on state during the running of the vehicle, or corresponding indicator lamps are turned on when the vehicle turns or brakes, or the like. Whether the vehicle is in a running state or not can be identified through the lighting condition of the lamp of the vehicle. For example, if at least one lamp of the vehicle is in the lighting state, the vehicle is determined to be in the running state, and if the number of the lighting lamps of the vehicle is zero, the vehicle is determined to be in the parking state. And if at least one vehicle in the current lane is in a driving state, determining that the current lane does not belong to an occupied lane, and correspondingly, if the vehicles in the current lane are all in a parking state, determining that the current lane belongs to the occupied lane.
Referring to fig. 3, the theoretical lane number of the current road number in fig. 3 is 4, where both the middle two lanes include at least one vehicle in a driving state, and the number of lights on the vehicle is greater than zero, so as to further determine that the middle two lanes do not belong to an occupied lane. Similarly, in fig. 3, the number of the turned-on lamps of all the vehicles in the leftmost lane and the rightmost lane is zero, and both the left lane and the rightmost lane belong to a parking state, and it is further determined that the leftmost lane and the rightmost lane are occupied lanes.
Preferably, whether the lane is an occupied lane is judged according to the lighting number of the lamps of at least one vehicle and a preset vehicle threshold value. For example, if the number of the vehicles in the parking state is greater than the preset vehicle threshold value, the lane is determined to be the occupied lane, the problem of recognition errors caused by lighting lamps of the vehicles in the parking state due to external reasons is solved, and the lane occupation recognition accuracy is improved.
In this embodiment, the number of occupied lanes is counted according to the recognition result of the occupied lanes of each lane in the current road section, and for example, the number of occupied lanes in the current road section in fig. 3 is 2.
And S230, determining an actual idle lane according to the theoretical lane number and the occupied lane number of the road on the current road section, and taking the actual idle lane as an actual idle width.
For example, referring to fig. 3, the theoretical number of lanes of the road on the current road section in fig. 3 is 4, and the number of occupied lanes is 2, it may be determined that the number of actual free lanes is 2. The actual free width can be determined according to the actual free lane number and the single lane width.
And S240, determining the passing attribute of the road of the current road section according to the actual idle width.
According to the technical scheme, the number of occupied lanes in the current road section is determined by obtaining and identifying the street view image of the current road section, the actual idle width is determined according to the theoretical number of lanes and the number of occupied lanes, the accurate driving width of the current road section is provided, the problem that in the prior art, when navigation is carried out according to the theoretical width of a road, the actual idle width is smaller than the theoretical width of the road, the driving difficulty is increased is solved, and the accuracy of a navigation route is improved.
EXAMPLE III
Fig. 4 is a flowchart of a method for determining road traffic attributes according to a third embodiment of the present invention, and on the basis of the third embodiment, a method for obtaining a set vehicle type traffic state of a current road section is further provided. Correspondingly, the method comprises the following steps:
s310, acquiring the number of the bus lines passing through the road on the current road section and/or the passing probability of the heavy transport vehicle.
The buses run on the same bus line at preset intervals, and the passing number of the buses in the current road section can be determined according to the number of the bus lines and the preset intervals of the buses. Optionally, the number of bus routes passing through the road on the current road section is obtained based on the bus route database.
The heavy transport vehicle refers to a transport type vehicle with large volume and heavy tonnage, and includes a container transport vehicle, a semi-trailer or a large crane, for example.
Optionally, obtaining the traffic probability of the heavy transport vehicle in the road of the current road section includes:
acquiring navigation information of the heavy transport vehicle in historical navigation data, or acquiring traffic information of the heavy transport vehicle of a transport route, and extracting the navigation information of the heavy transport vehicle;
and determining the passing probability of the heavy transport vehicle in the road of the current road section according to the navigation information.
In this embodiment, the historical navigation data includes navigation route information and vehicle information that requests navigation, where the vehicle information includes a vehicle type. And extracting the navigation information of the heavy transport vehicle with the vehicle type, matching the current road section road in the navigation information, and counting the passing number of the heavy transport vehicle on the current road section road.
The transportation route refers to a directional movement route of a transportation vehicle, and may be, for example, a logistics transportation route, a coal or oil transportation route, or the like. Optionally, the passing information of the heavy transport vehicle is obtained through the charging information of a toll station in the transport route, wherein the charging information includes information such as the vehicle type and the license plate number of the toll vehicle. The passing number of the heavy transport vehicles in the transport route is counted according to the charging information of the heavy transport vehicles, the navigation information of the corresponding vehicles is extracted according to the information such as license plate numbers, the current road section is matched according to the navigation information, and the passing number of the heavy vehicles on the current road section is counted.
In the embodiment, the passing probability of the heavy transport vehicles is determined according to the passing number of the heavy transport vehicles and the total passing amount of the heavy transport vehicles in the road of the current road section.
And S320, determining the passing state of the large-sized vehicle according to the number of the bus lines and/or the passing probability of the heavy-duty transport vehicle.
In this embodiment, the greater the number of the bus lines and/or the greater the traffic probability of the heavy-duty transport vehicle, the higher the passing density level of the large-sized vehicles on the road at the current road section is determined to be.
Optionally, step S320 includes:
and determining the passing state of the large-sized vehicle according to the number of the bus lines and/or the passing probability of the heavy-duty transport vehicle, the number of actual passing lanes of the road on the current road section and a preset threshold value.
In this embodiment, if the number of the bus lines is greater than the preset number threshold, and/or the heavy-duty transport vehicle passing probability is greater than the preset probability threshold, and the actual number of the passing lanes of the current road section is less than the preset lane threshold, it is determined that the passing state security level of the current road section is high. For example, the preset number threshold of the number of bus lines may be 5, the preset probability threshold of the passage probability of the heavy-duty transport vehicle may be 30%, and the preset lane threshold of the number of actual passage lanes may be 3.
Optionally, a weight is set for the number of bus lines and/or the traffic probability of the heavy-duty transport vehicle and the number of actual traffic lanes on the road of the current road section, and the traffic state of the large-sized vehicle is determined through weighting calculation.
And S330, determining the passing attribute of the road of the current road section according to the passing state of the large vehicle type.
In this embodiment, the higher the dense level of the traffic state of the large vehicle type on the current road section is, the larger the driving difficulty coefficient is, and correspondingly, the lower the traffic dense level is, the smaller the driving difficulty coefficient is.
According to the technical scheme, the passing state of the large-sized vehicles is determined by obtaining the number of the buses passing through the road on the current road section and/or the passing probability of the heavy-duty transport vehicles, and the passing attribute of the road on the current road section is determined according to the passing state of the large-sized vehicles, so that the driving difficulty caused by the passing of the large-sized vehicles is provided, the problem that the driving difficulty is increased due to the intensive passing of the large-sized vehicles on the road on the current road section is solved by the generated navigation route, the passing attribute reflecting the driving difficulty of the road is increased, and the accuracy of the navigation route is improved.
Example four
Fig. 5 is a schematic structural diagram of a device for determining road traffic attributes, provided by a fourth embodiment of the present invention, where the device specifically includes:
an idle width identification module 410, configured to identify an actual idle width of a road on a current road segment; and/or
A passing state determining module 420, configured to obtain a passing state of a set vehicle type of a road on a current road section;
and a passing attribute determining module 430, configured to determine a passing attribute of the road in the current road segment according to the actual idle width and/or the set vehicle type passing state.
Optionally, the idle width identifying module includes:
the street view image acquisition unit is used for acquiring a street view image of a street of a current road section;
the number of occupied lanes determining unit is used for carrying out image recognition on the street view image and determining the number of occupied lanes occupied by long-term parking in the road of the current road section;
and the idle width determining unit is used for determining an actual idle lane according to the theoretical lane number and the occupied lane number of the road on the current road section, and taking the actual idle lane as the actual idle width.
Optionally, the occupied lane number determining unit is specifically configured to:
identifying at least one vehicle of the same lane in the street view image;
judging whether the lane is an occupied lane or not according to the number of the turned-on lamps of at least one vehicle;
and counting the number of occupied lanes according to the lane occupation judgment result of each lane.
Optionally, the vehicle type is set to be a large vehicle, and the passing state determining module comprises:
the traffic data acquisition unit is used for acquiring the number of bus lines passing through the road on the current road section and/or the traffic probability of the heavy transport vehicle;
and the passing state determining unit is used for determining the passing state of the large-sized vehicle according to the bus line number and/or the passing probability of the heavy-duty transport vehicle.
Optionally, the traffic data acquiring unit is specifically configured to:
acquiring navigation information of the heavy transport vehicle in historical navigation data, or acquiring traffic information of the heavy transport vehicle of a transport line by the transport line, and extracting the navigation information of the heavy transport vehicle;
and determining the passing probability of the heavy transport vehicle in the road of the current road section according to the navigation information.
Optionally, the traffic state determining unit is specifically configured to:
and determining the passing state of the large-sized vehicle according to the number of the bus lines and/or the passing probability of the heavy-duty transport vehicle, the number of actual passing lanes of the road on the current road section and a preset threshold value.
Optionally, the passing attribute determining module is specifically configured to:
and carrying out weighted calculation on the actual idle width and/or the set vehicle type passing state to determine the driving difficulty coefficient of the road of the current road section.
Optionally, the apparatus further comprises:
and the route screening module is used for identifying the user type of the navigation request after determining the passing attribute of the current road section according to the actual idle width and/or the set vehicle type passing state, and screening and sequencing the navigation route generated by the route planning according to the user type and the driving difficulty coefficient of the current road section.
The device for determining the road traffic attribute provided by the embodiment of the invention can execute the method for determining the road traffic attribute provided by any embodiment of the invention, and has the corresponding functional module and beneficial effects of the method for determining the road traffic attribute.
EXAMPLE five
Fig. 6 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention. FIG. 6 illustrates a block diagram of an exemplary computer device 500 suitable for use in implementing embodiments of the present invention. The computer device 500 shown in fig. 6 is only an example and should not bring any limitations to the function and scope of use of the embodiments of the present invention.
As shown in fig. 6, computer device 500 is in the form of a general purpose computing device. The components of computer device 500 may include, but are not limited to: one or more processors or processing units 501, a system memory 502, and a bus 503 that couples the various system components (including the system memory 502 and the processing unit 501).
The system memory 502 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)504 and/or cache memory 505. The computer device 500 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 506 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard drive"). Although not shown in FIG. 6, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 503 by one or more data media interfaces. Memory 502 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 508 having a set (at least one) of program modules 507 may be stored, for instance, in memory 502, such program modules 507 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 507 generally perform the functions and/or methodologies of embodiments of the invention as described herein.
The computer device 500 may also communicate with one or more external devices 509 (e.g., keyboard, pointing device, display 512, etc.), with one or more devices that enable a user to interact with the computer device 500, and/or with any devices (e.g., network card, modem, etc.) that enable the computer device 500 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 510. Moreover, computer device 500 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network such as the Internet) via network adapter 511. As shown, the network adapter 511 communicates with the other modules of the computer device 500 over a bus 503. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with computer device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 501 executes various functional applications and data processing by running a program stored in the system memory 502, for example, to implement the determination method of road traffic attributes provided by the embodiment of the present invention.
The method comprises the following steps:
identifying an actual free width of a road of a current road section; and/or
Acquiring a set vehicle type passing data passing state of the current road section;
and determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing data passing state of the set vehicle type.
EXAMPLE six
Sixth embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for determining a road traffic attribute as provided in all the embodiments of the present invention of the present application. The method comprises the following steps:
identifying an actual free width of a road of a current road section; and/or
Acquiring a set vehicle type passing data passing state of the current road section;
and determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing data passing state of the set vehicle type.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for determining road traffic attributes, comprising:
identifying an actual free width of a road of a current road section; and/or
Acquiring a set vehicle type passing state of the current road section;
determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing state of the set vehicle type;
the actual idle width is determined by the number of actual idle lanes and the width of a single lane, and whether the lane in the current road section is an occupied lane or not is determined by the lighting number of lamps of at least one vehicle in the lane;
the set vehicle type is a heavy transport vehicle;
the step of acquiring the set vehicle type passing state of the current road section comprises the following steps:
extracting navigation information of the heavy transport vehicle with the vehicle type, matching the current road section road in the navigation information, and counting the passing number of the heavy transport vehicle on the current road section road;
determining the passing probability of the heavy transport vehicles according to the passing quantity of the heavy transport vehicles in the road of the current road section and the total passing quantity of the vehicles;
and determining the passing state of the heavy transport vehicle according to the passing probability of the heavy transport vehicle.
2. The method of claim 1, wherein identifying the actual free width of the road of the current road segment comprises:
acquiring a street view image of the street of the current road section;
carrying out image recognition on the street view image, and determining the number of occupied lanes occupied by long-term parking in the road of the current road section;
and determining an actual idle lane according to the theoretical lane number and the occupied lane number of the current road section, and taking the actual idle lane as the actual idle width.
3. The method of claim 2, wherein performing image recognition on the street view image to determine the number of occupied lanes occupied by the long-term parking in the current road segment comprises:
identifying at least one vehicle of the same lane in the street view image;
judging whether the lane is an occupied lane or not according to the number of the turned-on lamps of the at least one vehicle;
and counting the number of occupied lanes according to the lane occupation judgment result of each lane.
4. The method according to claim 1, wherein determining the traffic attribute of the road on the current road section according to the actual free width and/or the traffic state of the set vehicle type comprises:
and performing weighted calculation on the actual idle width and/or the set vehicle type passing state to determine the driving difficulty coefficient of the road of the current road section.
5. The method according to claim 4, characterized in that after determining the passing attribute of the current road section according to the actual idle width and/or the set vehicle type passing state, the method comprises the following steps:
and identifying the user type of the navigation request, and screening and sequencing the navigation route generated by the route planning according to the user type and the driving difficulty coefficient of the road of the current road section.
6. An apparatus for determining a road traffic attribute, comprising:
the idle width identification module is used for identifying the actual idle width of the road of the current road section; and/or
The passing state determining module is used for acquiring the passing state of the set vehicle type of the current road section;
the passing attribute determining module is used for determining the passing attribute of the road of the current road section according to the actual idle width and/or the passing state of the set vehicle type;
the actual idle width is determined by determining the actual idle width according to the actual idle lane number and the single lane width, and whether the lane in the current road section is the occupied lane is determined by the lighting number of the lamps of at least one vehicle in the lane;
the set vehicle type is a heavy transport vehicle;
the passage state determination module is specifically configured to:
extracting navigation information of the heavy transport vehicle with the vehicle type, matching the current road section road in the navigation information, and counting the passing number of the heavy transport vehicle on the current road section road;
determining the passing probability of the heavy transport vehicles according to the passing quantity of the heavy transport vehicles in the road of the current road section and the total passing quantity of the vehicles;
and determining the passing state of the heavy transport vehicle according to the passing probability of the heavy transport vehicle.
7. The apparatus of claim 6, wherein the idle width identification module comprises:
the street view image acquisition unit is used for acquiring a street view image of the street of the current road section;
the occupied lane number determining unit is used for carrying out image recognition on the street view image and determining the number of occupied lanes occupied by long-term parking in the road of the current road section;
and the idle width determining unit is used for determining an actual idle lane according to the theoretical lane number and the occupied lane number of the current road section and taking the actual idle lane as the actual idle width.
8. The apparatus according to claim 7, wherein the occupied lane number determining unit is specifically configured to:
identifying at least one vehicle of the same lane in the street view image;
judging whether the lane is an occupied lane or not according to the number of the turned-on lamps of the at least one vehicle;
and counting the number of occupied lanes according to the lane occupation judgment result of each lane.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-5 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
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| CN110271554B (en) * | 2018-03-13 | 2023-02-17 | 奥迪股份公司 | Driving assistance system and method for vehicle |
| CN108656962A (en) * | 2018-05-10 | 2018-10-16 | 中国石油大学(华东) | A kind of intelligent network connection electric sightseeing vehicle and control method |
| CN111325999A (en) * | 2018-12-14 | 2020-06-23 | 奥迪股份公司 | Vehicle driving assistance method, device, computer device, and storage medium |
| CN110455303A (en) * | 2019-08-05 | 2019-11-15 | 深圳市大拿科技有限公司 | AR air navigation aid, device and the AR navigation terminal suitable for vehicle |
| CN111798658A (en) * | 2019-11-08 | 2020-10-20 | 方勤 | Traffic lane passing efficiency detection platform |
| CN111121814A (en) * | 2020-01-08 | 2020-05-08 | 百度在线网络技术（北京）有限公司 | Navigation method, navigation device, electronic equipment and computer readable storage medium |
| CN113218406B (en) * | 2020-01-21 | 2022-11-25 | 百度在线网络技术（北京）有限公司 | Navigation method, device, equipment and medium of electronic map |
| CN111626495A (en) * | 2020-05-22 | 2020-09-04 | 重庆广播电视大学重庆工商职业学院 | Job scheduling system based on cloud platform |
| CN112907945A (en) * | 2021-01-18 | 2021-06-04 | 阿里巴巴集团控股有限公司 | Road state determination and navigation route planning method and equipment |
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