CN112750328A - Driving path recommendation method, device, equipment and medium - Google Patents

Driving path recommendation method, device, equipment and medium Download PDF

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Publication number
CN112750328A
CN112750328A CN202011603866.3A CN202011603866A CN112750328A CN 112750328 A CN112750328 A CN 112750328A CN 202011603866 A CN202011603866 A CN 202011603866A CN 112750328 A CN112750328 A CN 112750328A
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information
driving path
vehicle owner
target vehicle
parking
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CN112750328B (en
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唐健
吴卫斌
黄应辉
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Shenzhen Shunyitong Information Technology Co Ltd
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Shenzhen Shunyitong Information Technology Co Ltd
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    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096805Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
    • G08G1/096811Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096833Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Navigation (AREA)

Abstract

The application discloses a method, a device, equipment and a medium for recommending a driving path, wherein the method comprises the following steps: the method comprises the steps that parking information of a target vehicle owner, sent by a big data platform, is obtained, wherein the parking information comprises parking lot information and time information of the target vehicle owner, wherein the parking lot information and the time information of the target vehicle owner enter and exit a parking lot frequently, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and records of the target vehicle owner entering and exiting an intelligent parking lot; determining driving path recommendation time based on the time information, and acquiring the position information of the target vehicle owner when the driving path recommendation time is reached; initiating a driving path planning request to a navigation platform based on the parking lot information and the position information; and receiving the driving path returned by the navigation platform, and pushing the driving path to the terminal equipment of the target vehicle owner. Therefore, the driving path recommendation can be automatically carried out based on the parking information of the vehicle owner, and the destination does not need to be manually input.

Description

Driving path recommendation method, device, equipment and medium
Technical Field
The application relates to the technical field of operation on a parking line, in particular to a driving path recommendation method, device, equipment and medium.
Background
Wisdom parking system is more and more perfect, and networking wisdom parking area based on license plate automatic identification is more and more popularized, and the business turn over record of all vehicles reports to parking cloud platform. And recommending a driving path for the vehicle owner based on the parking information of the vehicle owner can provide great convenience for the vehicle owner. In the driving path method in the prior art, after a destination is input in a navigation system, the navigation system plans a driving path according to the input destination and a current position, and in this way, the destination information can be acquired only by manually inputting the destination. Therefore, how to automatically recommend a driving path based on the parking information is a problem to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, an object of the present application is to provide a method, an apparatus, a device, and a medium for recommending a driving route, which can automatically recommend a driving route based on parking information of a vehicle owner without manually inputting a destination. The specific scheme is as follows:
in a first aspect, the application discloses a driving path recommendation method applied to a parking cloud platform, including:
the method comprises the steps that parking information of a target vehicle owner, sent by a big data platform, is obtained, wherein the parking information comprises parking lot information and time information of the target vehicle owner, wherein the parking lot information and the time information of the target vehicle owner enter and exit a parking lot frequently, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and records of the target vehicle owner entering and exiting an intelligent parking lot;
determining driving path recommendation time based on the time information, and acquiring the position information of the target vehicle owner when the driving path recommendation time is reached;
initiating a driving path planning request to a navigation platform based on the parking lot information and the position information;
and receiving the driving path returned by the navigation platform, and pushing the driving path to the terminal equipment of the target vehicle owner.
Optionally, after the pushing the driving path to the terminal device of the target vehicle owner, the method further includes:
acquiring first feedback information of the driving path clicked and checked by the target vehicle owner so as to optimize a driving path recommendation algorithm of the navigation platform according to the first feedback information;
and/or acquiring second feedback information of the satisfaction degree of the target vehicle owner on the driving path so as to optimize the driving path recommendation algorithm of the navigation platform according to the second feedback information.
Optionally, after the pushing the driving path to the terminal device of the target vehicle owner, the method further includes:
acquiring a parking space reservation request;
and reserving a parking space for the target vehicle owner according to the parking space condition of the target parking lot corresponding to the driving path.
Optionally, the acquiring the location information of the target vehicle owner includes:
acquiring the position information of the target vehicle owner acquired by a positioning device on the terminal equipment through a parking system user side;
or the parking system user side acquires the position information of the target vehicle owner acquired by a positioning device on the vehicle of the target vehicle owner;
or acquiring the position information of the target vehicle owner according to the parking information of the target vehicle owner sent by the big data platform.
Optionally, the receiving the driving path returned by the navigation platform and pushing the driving path to the terminal device of the target vehicle owner includes:
receiving a driving path returned by the navigation platform;
judging whether the number of the driving paths is more than 1;
and if the number of the driving paths is more than 1, pushing the driving paths which meet the driving path recommendation requirement preset by the target vehicle owner in the driving paths to the terminal equipment of the target vehicle owner.
Optionally, the receiving the driving path returned by the navigation platform and pushing the driving path to the terminal device of the target vehicle owner includes:
receiving a driving path returned by the navigation platform;
judging whether the number of the driving paths is more than 1;
if the number of the driving paths is more than 1, acquiring a driving path record of the target vehicle owner;
and determining a target driving path from the driving paths according to the driving path record, and pushing the target driving path to the terminal equipment of the target vehicle owner.
Optionally, before obtaining the parking information of the target vehicle owner sent by the big data platform, the method further includes:
and sending the owner information of the target owner and the record of the intelligent parking lot entering and exiting to the big data platform, so that the big data platform analyzes the owner information and the record of the intelligent parking lot entering and exiting to obtain the parking information, wherein the owner information comprises the owner identity information and the bound vehicle information, and the owner identity information represents that the target owner parks in a monthly card or temporarily.
In a second aspect, the application discloses driving route recommendation device is applied to parking cloud platform, includes:
the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module is used for acquiring parking information of a target vehicle owner sent by a big data platform, the parking information comprises parking lot information and time information of a frequently-entering parking lot of the target vehicle owner, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and records of entering and exiting an intelligent parking lot;
the time determining module is used for determining the recommended time of the driving path based on the time information;
the position acquisition module is used for acquiring the position information of the target vehicle owner when the driving path recommendation time is reached;
the request sending module is used for sending a driving path planning request to a navigation platform based on the parking lot information and the position information;
the path receiving module is used for receiving a driving path returned by the navigation platform;
and the path pushing module is used for pushing the driving path to the terminal equipment of the target vehicle owner.
In a third aspect, the present application discloses an electronic device, comprising:
a memory and a processor;
wherein the memory is used for storing a computer program;
the processor is configured to execute the computer program to implement the driving path recommendation method disclosed above.
In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned method for recommending a driving route.
It is thus clear that this application acquires the parking information of the target car owner that big data platform sent earlier, wherein, parking information includes the parking area information and the time information in the parking area are passed in and out frequently of target car owner, parking information is the analysis the car owner information of target car owner obtains with business turn over wisdom parking area record, then alright with in order based on time information determines driving route recommendation time, and is arriving during driving route recommendation time, acquire target car owner's positional information, again based on parking area information with positional information launches driving route planning request, then receives the driving route that navigation platform returned, and will driving route propelling movement arrives target car owner's terminal equipment. Therefore, in the application, the big data platform is firstly obtained to analyze the owner information of the target owner and the record of entering and exiting the intelligent parking lot, the obtained parking information is obtained, then the driving path recommendation time can be determined based on the time information in the parking information, when the driving path recommendation time is reached, the position information of the target owner can be obtained, then a driving path planning request is sent to the navigation platform based on the position information and the parking lot information in the parking information, then the received driving path returned by the navigation platform is pushed to the terminal equipment of the target owner, so that the driving path can be recommended for the owner based on the analysis of the owner information of the owner and the record of entering and exiting the intelligent parking lot, the automatic driving path recommendation based on the parking information of the owner is realized, the destination is not required to be manually input, the intelligent degree of the driving path recommendation 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, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a driving path recommendation method disclosed in the present application;
fig. 2 is a flowchart of a specific driving path recommendation method disclosed in the present application;
fig. 3 is a flowchart of a specific driving path recommendation method disclosed in the present application;
FIG. 4 is a flowchart of a specific driving path recommendation method disclosed in the present application;
fig. 5 is a schematic structural diagram of a driving path recommendation device disclosed in the present application;
fig. 6 is a schematic structural diagram of an electronic device disclosed in the present application.
Detailed Description
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 only a part of the embodiments of the present application, and not all of the 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.
In the driving path method in the prior art, after a destination is input in a navigation system, the navigation system plans a driving path according to the input destination and a current position, and in this way, the destination information can be acquired only by manually inputting the destination. In view of this, the application provides a driving path recommendation method, which can automatically recommend a driving path based on parking information of a vehicle owner without manually inputting a destination.
Referring to fig. 1, an embodiment of the application discloses a driving path recommendation method applied to a parking cloud platform, and the method includes:
step S11: the parking information of the target vehicle owner sent by the big data platform is obtained, wherein the parking information comprises the parking lot information and the time information of the target vehicle owner, wherein the parking lot information and the time information of the target vehicle owner enter and exit the parking lot frequently, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and the record of the intelligent parking lot entering and exiting the parking lot.
In the practical implementation process, the parking information of the target vehicle owner, which is sent by the big data platform, needs to be obtained first, the parking information includes the parking lot information and the time information of the target vehicle owner, which frequently enters and exits the parking lot, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and the record of the intelligent parking lot entering and exiting.
That is, the big data platform needs to analyze the owner information of the target owner and the intelligent parking lot entry and exit records to obtain the parking information of the target owner, that is, the parking lot information and the time information of the target owner, which frequently enters and exits the parking lot. The intelligent parking lot access record comprises parking lot information and access time of the intelligent parking lot performed by the target vehicle owner, and photos of the vehicle collected by the local parking system when the target vehicle enters the intelligent parking lot and possibly some vehicles enter the intelligent parking lot.
It is specific, right parking area information in the business turn over wisdom parking area record carries out the analysis, obtains the parking area information that business turn over wisdom parking area record corresponds, parking area information includes geographical position region, geographical position region can include city, district and specific parking area. And analyzing the time of entering and exiting the intelligent parking lot in the entering and exiting intelligent parking lot record to obtain the time information corresponding to the entering and exiting intelligent parking lot record.
Therefore, before obtaining the parking information of the target vehicle owner sent by the big data platform, the method further comprises the following steps: and sending the owner information of the target owner and the record of the intelligent parking lot entering and exiting to the big data platform, so that the big data platform analyzes the owner information and the record of the intelligent parking lot entering and exiting to obtain the parking information, wherein the owner information comprises the owner identity information and the bound vehicle information, and the owner identity information represents that the target owner parks in a monthly card or temporarily. When the vehicle owner identity information of the target vehicle owner is monthly card parking, the fact that the parking frequency of the target vehicle owner in a parking lot corresponding to the monthly card parking is generally greater than that of a temporary parking lot is shown, and therefore the determined parking information can better reflect the actual parking condition of the target vehicle owner by combining the vehicle owner identity information.
Step S12: and determining the recommended time of the driving path based on the time information, and acquiring the position information of the target vehicle owner when the recommended time of the driving path is reached.
After the parking information is obtained, the driving path recommendation time is determined according to the time information, and when the driving path recommendation time is reached, the position information of the target vehicle owner is obtained.
That is, it is necessary to determine the time to make the travel path recommendation first based on the time information in the parking information. For example, if the time of the subject vehicle owner's frequent entrance and exit parking lot is 8 am and 5 pm, 7 am and 5 pm may be determined as the travel path recommended time. Therefore, the recommended time can be determined according to the time information of the car owner entering and exiting the parking lot frequently, and the driving path is recommended more intelligently.
When the driving path recommendation is needed, a target position and an initial position are needed, wherein the target position is a corresponding parking lot in the parking information. For example, if the time of the target vehicle owner entering and exiting the parking lot frequently is 8 am and half, and the recommended travel route time is 7 am, the parking lot frequently entering and exiting corresponding to 8 am may be used as the destination location, and the current location of the vehicle owner may be used as the start location. It is necessary to acquire the location information of the owner of the target vehicle.
Specifically, the position information of the target vehicle owner, which is acquired by a positioning device on the terminal equipment, can be acquired through a parking system user side; or the parking system user side acquires the position information of the target vehicle owner acquired by a positioning device on the vehicle of the target vehicle owner; or acquiring the position information of the target vehicle owner according to the parking information of the target vehicle owner sent by the big data platform.
That is, the position information of the target vehicle owner may be directly obtained by a positioning device provided on the terminal device, and then the position information is obtained by the parking system user side, and the position information is reported to the parking cloud platform. The parking system user side may be APP (Application) or a page.
Or when the terminal device of the target vehicle owner is connected with the vehicle, the positioning device on the vehicle may acquire the position information of the target vehicle owner, transmit the position information to the terminal device, and report the position information to the parking cloud platform by the parking system user side on the terminal device.
That is, the real-time location information of the vehicle owner may be obtained through the positioning device, and in addition, the possible location of the vehicle owner may be obtained according to the parking information of the target vehicle owner sent by the big data platform, for example, the parking information indicates that the target vehicle owner generally leaves from a parking lot of a certain residential quarter at 8 am, stops at 9 am to a parking lot of a certain office building, and the recommended time of the driving route is 8 am, so that the parking lot of the residential quarter may be used as the location information of the target vehicle owner.
Step S13: and initiating a driving path planning request to a navigation platform based on the parking lot information and the position information.
After the position information is acquired, a driving route planning request can be initiated to a navigation platform based on the parking lot information and the position information.
That is, the position in the position information is used as an initial position, and the parking lot position in the parking lot information corresponding to the current travel route recommended time in the parking lot information is used as a destination position, so that the travel route planning request is sent to the navigation platform. Wherein the navigation platform includes road traffic information.
Step S14: and receiving the driving path returned by the navigation platform, and pushing the driving path to the terminal equipment of the target vehicle owner.
Correspondingly, the navigation platform carries out path planning according to the target position and the initial position in the driving path planning request and real-time road traffic information, and returns the planned driving path to the parking cloud platform, so that the parking cloud platform needs to receive the driving path returned by the navigation platform and push the driving path to the terminal equipment of the target vehicle owner. The driving path may include a plurality of driving paths.
When the driving paths comprise a plurality of paths, all the driving paths can be pushed to the terminal equipment of the target vehicle owner. One or more driving paths can be determined from the plurality of driving paths and used as final driving paths to be recommended to the terminal equipment corresponding to the target vehicle owner.
Specifically, a driving path returned by the navigation platform may be received first; judging whether the number of the driving paths is more than 1; and if the number of the driving paths is more than 1, pushing the driving paths which meet the driving path recommendation requirement preset by the target vehicle owner in the driving paths to the terminal equipment of the target vehicle owner. That is, the target vehicle owner may set a driving path recommendation requirement of interest, for example, recommending the vehicle with the shortest time consumption, or the vehicle with the shortest route, or the vehicle with the least traffic congestion currently. When the driving path returned by the navigation platform is larger than 1, the driving path meeting the driving path recommendation requirement preset by the target vehicle owner can be pushed to the terminal equipment of the target vehicle owner so as to meet the requirements of different vehicle owners.
Or if the number of the driving paths is more than 1, acquiring a driving path record of the target vehicle owner; and determining a target driving path from the driving paths according to the driving path record, and pushing the target driving path to the terminal equipment of the target vehicle owner. That is, the vehicle owner may not set a driving path recommendation requirement that is of interest to the vehicle owner, so that when the driving path returned by the navigation platform is greater than 1, the driving path record of the target vehicle owner may be obtained, then the target driving path is determined from the driving paths according to the driving path record, and the target driving path is pushed to the terminal device of the target vehicle owner, for example, the terminal device of the target vehicle owner is recommended to which the target vehicle owner has the largest number of times of walking. In addition, there may be other manners for determining the driving path finally pushed to the terminal device of the vehicle owner, which is not specifically limited herein.
In practical application, the big data platform is right the car owner information and the business turn over wisdom parking area record of the target car owner carry out analysis, obtain in addition to the parking area information and the time information of the parking area of the frequent business turn over parking area of the target car owner, can also obtain the purpose that the target car owner goes in and out the parking area frequently, for example, go home, work and shop etc.. The parking lot which the target vehicle owner often enters and exits can be more accurately determined.
It is thus clear that this application acquires the parking information of the target car owner that big data platform sent earlier, wherein, parking information includes the parking area information and the time information in the parking area are passed in and out frequently of target car owner, parking information is the analysis the car owner information of target car owner obtains with business turn over wisdom parking area record, then alright with in order based on time information determines driving route recommendation time, and is arriving during driving route recommendation time, acquire target car owner's positional information, again based on parking area information with positional information launches driving route planning request, then receives the driving route that navigation platform returned, and will driving route propelling movement arrives target car owner's terminal equipment. Therefore, in the application, the big data platform is firstly obtained to analyze the owner information of the target owner and the record of entering and exiting the intelligent parking lot, the obtained parking information is obtained, then the driving path recommendation time can be determined based on the time information in the parking information, when the driving path recommendation time is reached, the position information of the target owner can be obtained, then a driving path planning request is sent to the navigation platform based on the position information and the parking lot information in the parking information, then the received driving path returned by the navigation platform is pushed to the terminal equipment of the target owner, so that the driving path can be recommended for the owner based on the analysis of the owner information of the owner and the record of entering and exiting the intelligent parking lot, the automatic driving path recommendation based on the parking information of the owner is realized, the destination is not required to be manually input, the intelligent degree of the driving path recommendation is improved.
Referring to fig. 2, an embodiment of the present application discloses a specific driving path recommendation method, which is applied to a parking cloud platform, and the method includes:
step S21: the parking information of the target vehicle owner sent by the big data platform is obtained, wherein the parking information comprises the parking lot information and the time information of the target vehicle owner, wherein the parking lot information and the time information of the target vehicle owner enter and exit the parking lot frequently, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and the record of the intelligent parking lot entering and exiting the parking lot.
Step S22: and determining the recommended time of the driving path based on the time information, and acquiring the position information of the target vehicle owner when the recommended time of the driving path is reached.
Step S23: and initiating a driving path planning request to a navigation platform based on the parking lot information and the position information.
Step S24: and receiving the driving path returned by the navigation platform, and pushing the driving path to the terminal equipment of the target vehicle owner.
The specific implementation process of step S21 to step S24 may refer to the content disclosed in the foregoing embodiments, and will not be described herein again.
Step S25: and acquiring a parking space reservation request, and reserving a parking space for the target vehicle owner according to the parking space condition of the target parking lot corresponding to the driving path.
After the driving path is pushed to the terminal equipment of the target vehicle owner, a parking space reservation request triggered by the target vehicle owner can be obtained, and then a parking space is reserved for the target vehicle owner according to the parking space condition of the target parking lot corresponding to the driving path.
After the driving path is pushed to the terminal equipment of the target vehicle owner, first feedback information of the driving path clicked by the target vehicle owner to be checked can also be obtained, so that the driving path recommendation algorithm of the navigation platform can be optimized according to the first feedback information; and/or acquiring second feedback information of the satisfaction degree of the target vehicle owner on the driving path so as to optimize the driving path recommendation algorithm of the navigation platform according to the second feedback information.
That is, after the driving path is pushed to the terminal device corresponding to the target vehicle owner and the target vehicle owner clicks the driving path, the first feedback information of which driving path the target vehicle owner specifically clicks may be fed back to the parking cloud platform, so that the parking cloud platform needs to obtain the first feedback information reported by the terminal device. After the target vehicle owner clicks the driving path, the target vehicle owner can be prompted to evaluate the satisfaction degree, and corresponding second feedback information is reported to the parking cloud platform, so that the parking cloud platform needs to acquire the second feedback information.
The method for recommending the driving path can be realized by a system for recommending the driving path, and the system comprises a vehicle owner, a parking lot local system, a parking cloud platform, a big data platform and a navigation platform (containing road traffic information). Information such as a vehicle owner monthly card and a vehicle owner binding vehicle is recorded on the parking cloud platform, and the information of the vehicle owner of the parking cloud platform is synchronized to the big data platform. The parking lot local system and the parking cloud platform process relevant business of car owners entering and exiting the parking lot, and the parking cloud platform synchronizes the entering and exiting records to the big data platform. The big data platform analyzes the historical behavior of vehicles entering and exiting the parking lot, and obtains information such as parking lot, time, purpose (home/work/shopping) and the like frequently visited by the vehicle owner by combining information such as parking lot positions, parking lot types (community/office/shopping center and the like), vehicle owner identities (monthly card/temporary parking and the like). And the big data platform synchronizes the analysis result to the parking cloud platform, and the parking cloud platform stores the analysis result. Based on the position and time of the car owner frequently going to the parking lot, a certain time (namely the driving path recommended time) is advanced, and the current position of the car owner is obtained through modes such as a parking APP. The parking cloud platform requests a navigation platform with road traffic conditions to plan a driving route, and pushes the recommended driving route to a vehicle owner. The car owner looks over and recommends the route of going, according to the parking area parking stall condition, reserves the parking stall in advance.
Referring to fig. 3, a flow chart of the driving path recommendation is shown. That is, data acquisition is firstly carried out, and information such as vehicle owner entering and exiting smart parking lot records, vehicle owner monthly card and vehicle owner binding vehicle is acquired. And then data analysis is carried out, the historical behavior of the vehicles entering and exiting the parking lot is analyzed, and the information of the vehicle owners such as the frequent driving places, the time and the purposes is obtained by combining the information of the vehicle places, the types of the vehicle places, the identities of the vehicle owners and the like. And then, data application can be carried out, and based on the frequent departure yard and time of the vehicle owner and the current position of the vehicle owner, the driving route is recommended to the vehicle owner by combining the real-time road traffic condition.
Referring to fig. 4, a flow chart of the driving path recommendation is shown. The method comprises the steps that vehicle owner information (such as a monthly card) is reported to a parking cloud platform, and the parking cloud platform synchronizes the vehicle owner information to a big data platform. The parking lot local system reports the entry and exit records of the car owner to the parking cloud platform, then the parking cloud platform synchronizes the entry and exit records to the big data platform, the big data platform performs data analysis to obtain information of the car owner such as a frequently-going parking lot, time and purpose, the analysis result is synchronized to the parking cloud platform, the parking cloud platform stores the analysis result, the position of the car owner is obtained in advance for a period of time based on historical parking lot entering time, the historical parking lot entering position is obtained, then a planning driving route is requested to the navigation platform, the navigation platform returns the planned driving route to the parking cloud platform, then the parking cloud platform selects the recommended driving route, the driving route is recommended to the terminal equipment corresponding to the car owner, the car owner looks over the recommended driving route, and reserves the parking space.
Referring to fig. 5, an embodiment of the present application discloses a driving path recommendation device, which is applied to a parking cloud platform, and includes:
the system comprises an information acquisition module 11, a data storage module and a data processing module, wherein the information acquisition module is used for acquiring parking information of a target vehicle owner sent by a big data platform, the parking information comprises parking lot information and time information of a frequently-entering parking lot of the target vehicle owner, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and records of entering and exiting an intelligent parking lot;
the time determining module 12 is configured to determine a recommended travel path time based on the time information;
the position obtaining module 13 is configured to obtain position information of the target vehicle owner when the recommended travel path time is reached;
a request sending module 14, configured to initiate a driving path planning request to a navigation platform based on the parking lot information and the position information;
the path receiving module 15 is configured to receive a driving path returned by the navigation platform;
and the path pushing module 16 is configured to push the driving path to the terminal device of the target vehicle owner.
It is thus clear that this application acquires the parking information of the target car owner that big data platform sent earlier, wherein, parking information includes the parking area information and the time information in the parking area are passed in and out frequently of target car owner, parking information is the analysis the car owner information of target car owner obtains with business turn over wisdom parking area record, then alright with in order based on time information determines driving route recommendation time, and is arriving during driving route recommendation time, acquire target car owner's positional information, again based on parking area information with positional information launches driving route planning request, then receives the driving route that navigation platform returned, and will driving route propelling movement arrives target car owner's terminal equipment. Therefore, in the application, the big data platform is firstly obtained to analyze the owner information of the target owner and the record of entering and exiting the intelligent parking lot, the obtained parking information is obtained, then the driving path recommendation time can be determined based on the time information in the parking information, when the driving path recommendation time is reached, the position information of the target owner can be obtained, then a driving path planning request is sent to the navigation platform based on the position information and the parking lot information in the parking information, then the received driving path returned by the navigation platform is pushed to the terminal equipment of the target owner, so that the driving path can be recommended for the owner based on the analysis of the owner information of the owner and the record of entering and exiting the intelligent parking lot, the automatic driving path recommendation based on the parking information of the owner is realized, the destination is not required to be manually input, the intelligent degree of the driving path recommendation is improved.
In some specific embodiments, the driving path recommending apparatus further includes:
the information acquisition module is used for acquiring first feedback information of the driving path clicked and checked by the target vehicle owner so as to optimize a driving path recommendation algorithm of the navigation platform according to the first feedback information; and/or acquiring second feedback information of the satisfaction degree of the target vehicle owner on the driving path so as to optimize the driving path recommendation algorithm of the navigation platform according to the second feedback information.
In some specific embodiments, the driving path recommending apparatus further includes:
the parking space reservation module is used for acquiring a parking space reservation request; and reserving a parking space for the target vehicle owner according to the parking space condition of the target parking lot corresponding to the driving path.
In some specific embodiments, the position obtaining module 13 is configured to: acquiring the position information of the target vehicle owner acquired by a positioning device on the terminal equipment through a parking system user side; or the parking system user side acquires the position information of the target vehicle owner acquired by a positioning device on the vehicle of the target vehicle owner; or acquiring the position information of the target vehicle owner according to the parking information of the target vehicle owner sent by the big data platform.
In some specific embodiments, the path receiving module 15 is configured to: receiving a driving path returned by the navigation platform;
correspondingly, the path pushing module 16 is configured to: judging whether the number of the driving paths is more than 1; and if the number of the driving paths is more than 1, pushing the driving paths which meet the driving path recommendation requirement preset by the target vehicle owner in the driving paths to the terminal equipment of the target vehicle owner.
In some specific embodiments, the path receiving module 15 is configured to: receiving a driving path returned by the navigation platform;
correspondingly, the path pushing module 16 is configured to: judging whether the number of the driving paths is more than 1; if the number of the driving paths is more than 1, acquiring a driving path record of the target vehicle owner; and determining a target driving path from the driving paths according to the driving path record, and pushing the target driving path to the terminal equipment of the target vehicle owner.
In some specific embodiments, the driving path recommending apparatus further includes:
the information sending module is used for sending the owner information of the target owner and the intelligent parking lot access records to the big data platform, so that the big data platform analyzes the owner information and the intelligent parking lot access records to obtain the parking information, wherein the owner information comprises owner identity information and bound vehicle information, and the owner identity information represents that the target owner parks for a monthly card or temporarily.
Referring to fig. 6, a schematic structural diagram of an electronic device 20 provided in the embodiment of the present application is shown, where the electronic device 20 may specifically implement the steps of the driving route recommendation method disclosed in the foregoing embodiment.
In general, the electronic device 20 in the present embodiment includes: a processor 21 and a memory 22.
The processor 21 may include one or more processing cores, such as a four-core processor, an eight-core processor, and so on. The processor 21 may be implemented by at least one hardware of a DSP (digital signal processing), an FPGA (field-programmable gate array), and a PLA (programmable logic array). The processor 21 may also include a main processor and a coprocessor, where the main processor is a processor for processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 21 may be integrated with a GPU (graphics processing unit) which is responsible for rendering and drawing images to be displayed on the display screen. In some embodiments, the processor 21 may include an AI (artificial intelligence) processor for processing computing operations related to machine learning.
Memory 22 may include one or more computer-readable storage media, which may be non-transitory. Memory 22 may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In this embodiment, the memory 22 is at least used for storing the following computer program 221, wherein after being loaded and executed by the processor 21, the steps of the driving path recommendation method disclosed in any one of the foregoing embodiments can be implemented.
In some embodiments, the electronic device 20 may further include a display 23, an input/output interface 24, a communication interface 25, a sensor 26, a power supply 27, and a communication bus 28.
Those skilled in the art will appreciate that the configuration shown in FIG. 6 is not limiting of electronic device 20 and may include more or fewer components than those shown.
Further, an embodiment of the present application also discloses a computer-readable storage medium for storing a computer program, wherein the computer program is executed by a processor to implement the driving path recommendation method disclosed in any of the foregoing embodiments.
For the specific process of the driving path recommendation method, reference may be made to corresponding contents disclosed in the foregoing embodiments, which are not described herein again.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of other elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The method, the device, the equipment and the medium for recommending the driving route provided by the application are introduced in detail, specific examples are applied in the description to explain the principle and the implementation of the application, and the description of the embodiments is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (10)

1. The driving path recommendation method is applied to a parking cloud platform and comprises the following steps:
the method comprises the steps that parking information of a target vehicle owner, sent by a big data platform, is obtained, wherein the parking information comprises parking lot information and time information of the target vehicle owner, wherein the parking lot information and the time information of the target vehicle owner enter and exit a parking lot frequently, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and records of the target vehicle owner entering and exiting an intelligent parking lot;
determining driving path recommendation time based on the time information, and acquiring the position information of the target vehicle owner when the driving path recommendation time is reached;
initiating a driving path planning request to a navigation platform based on the parking lot information and the position information;
and receiving the driving path returned by the navigation platform, and pushing the driving path to the terminal equipment of the target vehicle owner.
2. The driving path recommendation method according to claim 1, wherein after the pushing the driving path to the terminal device of the target vehicle owner, the method further comprises:
acquiring first feedback information of the driving path clicked and checked by the target vehicle owner so as to optimize a driving path recommendation algorithm of the navigation platform according to the first feedback information;
and/or acquiring second feedback information of the satisfaction degree of the target vehicle owner on the driving path so as to optimize the driving path recommendation algorithm of the navigation platform according to the second feedback information.
3. The driving path recommendation method according to claim 1, wherein after the pushing the driving path to the terminal device of the target vehicle owner, the method further comprises:
acquiring a parking space reservation request;
and reserving a parking space for the target vehicle owner according to the parking space condition of the target parking lot corresponding to the driving path.
4. The method for recommending a driving route according to claim 1, wherein said obtaining the location information of the owner of the target vehicle comprises:
acquiring the position information of the target vehicle owner acquired by a positioning device on the terminal equipment through a parking system user side;
or the parking system user side acquires the position information of the target vehicle owner acquired by a positioning device on the vehicle of the target vehicle owner;
or acquiring the position information of the target vehicle owner according to the parking information of the target vehicle owner sent by the big data platform.
5. The driving path recommendation method according to claim 1, wherein the receiving the driving path returned by the navigation platform and pushing the driving path to the terminal device of the target vehicle owner comprises:
receiving a driving path returned by the navigation platform;
judging whether the number of the driving paths is more than 1;
and if the number of the driving paths is more than 1, pushing the driving paths which meet the driving path recommendation requirement preset by the target vehicle owner in the driving paths to the terminal equipment of the target vehicle owner.
6. The driving path recommendation method according to claim 1, wherein the receiving the driving path returned by the navigation platform and pushing the driving path to the terminal device of the target vehicle owner comprises:
receiving a driving path returned by the navigation platform;
judging whether the number of the driving paths is more than 1;
if the number of the driving paths is more than 1, acquiring a driving path record of the target vehicle owner;
and determining a target driving path from the driving paths according to the driving path record, and pushing the target driving path to the terminal equipment of the target vehicle owner.
7. The driving path recommendation method according to any one of claims 1 to 6, wherein before the obtaining of the parking information of the target vehicle owner sent by the big data platform, the method further comprises:
and sending the owner information of the target owner and the record of the intelligent parking lot entering and exiting to the big data platform, so that the big data platform analyzes the owner information and the record of the intelligent parking lot entering and exiting to obtain the parking information, wherein the owner information comprises the owner identity information and the bound vehicle information, and the owner identity information represents that the target owner parks in a monthly card or temporarily.
8. The utility model provides a driving route recommendation device which characterized in that is applied to parking cloud platform, includes:
the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module is used for acquiring parking information of a target vehicle owner sent by a big data platform, the parking information comprises parking lot information and time information of a frequently-entering parking lot of the target vehicle owner, and the parking information is obtained by analyzing the vehicle owner information of the target vehicle owner and records of entering and exiting an intelligent parking lot;
the time determining module is used for determining the recommended time of the driving path based on the time information;
the position acquisition module is used for acquiring the position information of the target vehicle owner when the driving path recommendation time is reached;
the request sending module is used for sending a driving path planning request to a navigation platform based on the parking lot information and the position information;
the path receiving module is used for receiving a driving path returned by the navigation platform;
and the path pushing module is used for pushing the driving path to the terminal equipment of the target vehicle owner.
9. An electronic device, comprising:
a memory and a processor;
wherein the memory is used for storing a computer program;
the processor is configured to execute the computer program to implement the driving path recommendation method according to any one of claims 1 to 7.
10. A computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the driving path recommendation method according to any one of claims 1 to 7.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115294791A (en) * 2022-07-29 2022-11-04 广州市粤迅特数码技术有限公司 Intelligent traffic guidance system for smart city

Citations (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001050760A (en) * 1999-08-10 2001-02-23 Sony Corp Navigation system
CN1573735A (en) * 2003-06-20 2005-02-02 松下电器产业株式会社 Place guidance system
JP2005315657A (en) * 2004-04-27 2005-11-10 Aisin Aw Co Ltd Navigation system and program
US20090171567A1 (en) * 2007-12-28 2009-07-02 Aisin Aw Co., Ltd. Navigation devices, methods and programs
CN103065380A (en) * 2012-12-07 2013-04-24 康佳集团股份有限公司 Method and system for interactive intelligent parking
CN103942229A (en) * 2013-01-22 2014-07-23 日电(中国)有限公司 Destination prediction device and method
CN104165634A (en) * 2014-07-28 2014-11-26 广州视源电子科技股份有限公司 Path planning method based on use habit of user
CN104318803A (en) * 2014-10-21 2015-01-28 小米科技有限责任公司 Parking information prediction method and apparatus
CN104833365A (en) * 2014-02-12 2015-08-12 华为技术有限公司 Prediction method and prediction device of user destination
US20150345970A1 (en) * 2013-01-21 2015-12-03 Mitsubishi Electric Corporation Destination prediction apparatus
CN105187484A (en) * 2014-05-30 2015-12-23 Lg电子株式会社 Mobile Terminal And Method For Controlling The Same
CN105277189A (en) * 2014-06-30 2016-01-27 高德软件有限公司 Route pushing method and device
CN105513395A (en) * 2015-11-30 2016-04-20 华南理工大学 Intelligent information pushing system and method based on vehicle destination prediction
CN106197450A (en) * 2016-07-06 2016-12-07 深圳市金立通信设备有限公司 A kind of navigation reminders method and terminal
CN106919993A (en) * 2015-12-25 2017-07-04 滴滴(中国)科技有限公司 A kind of high accuracy acquiescence destination Forecasting Methodology and device based on historical data
CN107331200A (en) * 2017-08-11 2017-11-07 武汉理工大学 A kind of CBD underground garages intelligent parking guiding system, method and device
CN107644542A (en) * 2017-09-11 2018-01-30 应石磊 A kind of air navigation aid and remote information process device based on parking space information
CN108091173A (en) * 2018-01-25 2018-05-29 贵州宜行智通科技有限公司 Parking stall guidance information method for pushing and device
CN108257407A (en) * 2016-12-28 2018-07-06 电信科学技术研究院 A kind of vehicle parking navigation and processing method, the device of navigation information
CN108286980A (en) * 2017-12-29 2018-07-17 广州通易科技有限公司 A method of prediction destination and recommendation drive route
CN108896061A (en) * 2018-05-11 2018-11-27 京东方科技集团股份有限公司 A kind of man-machine interaction method and onboard navigation system based on onboard navigation system
CN109612485A (en) * 2018-12-17 2019-04-12 许建国 A kind of intelligent route planning system of new-energy automobile
CN110832284A (en) * 2017-08-24 2020-02-21 北京嘀嘀无限科技发展有限公司 System and method for destination prediction
US20200166347A1 (en) * 2016-08-19 2020-05-28 Micware Co., Ltd. Navigation data processing system, apparatus and computer readable medium
US20200175871A1 (en) * 2018-11-29 2020-06-04 Toyota Jidosha Kabushiki Kaisha Information providing system, server, onboard device, and information providing method

Patent Citations (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001050760A (en) * 1999-08-10 2001-02-23 Sony Corp Navigation system
CN1573735A (en) * 2003-06-20 2005-02-02 松下电器产业株式会社 Place guidance system
JP2005315657A (en) * 2004-04-27 2005-11-10 Aisin Aw Co Ltd Navigation system and program
US20090171567A1 (en) * 2007-12-28 2009-07-02 Aisin Aw Co., Ltd. Navigation devices, methods and programs
CN103065380A (en) * 2012-12-07 2013-04-24 康佳集团股份有限公司 Method and system for interactive intelligent parking
US20150345970A1 (en) * 2013-01-21 2015-12-03 Mitsubishi Electric Corporation Destination prediction apparatus
CN103942229A (en) * 2013-01-22 2014-07-23 日电(中国)有限公司 Destination prediction device and method
CN104833365A (en) * 2014-02-12 2015-08-12 华为技术有限公司 Prediction method and prediction device of user destination
CN105187484A (en) * 2014-05-30 2015-12-23 Lg电子株式会社 Mobile Terminal And Method For Controlling The Same
CN105277189A (en) * 2014-06-30 2016-01-27 高德软件有限公司 Route pushing method and device
CN104165634A (en) * 2014-07-28 2014-11-26 广州视源电子科技股份有限公司 Path planning method based on use habit of user
CN104318803A (en) * 2014-10-21 2015-01-28 小米科技有限责任公司 Parking information prediction method and apparatus
CN105513395A (en) * 2015-11-30 2016-04-20 华南理工大学 Intelligent information pushing system and method based on vehicle destination prediction
CN106919993A (en) * 2015-12-25 2017-07-04 滴滴(中国)科技有限公司 A kind of high accuracy acquiescence destination Forecasting Methodology and device based on historical data
CN106197450A (en) * 2016-07-06 2016-12-07 深圳市金立通信设备有限公司 A kind of navigation reminders method and terminal
US20200166347A1 (en) * 2016-08-19 2020-05-28 Micware Co., Ltd. Navigation data processing system, apparatus and computer readable medium
CN108257407A (en) * 2016-12-28 2018-07-06 电信科学技术研究院 A kind of vehicle parking navigation and processing method, the device of navigation information
CN107331200A (en) * 2017-08-11 2017-11-07 武汉理工大学 A kind of CBD underground garages intelligent parking guiding system, method and device
CN110832284A (en) * 2017-08-24 2020-02-21 北京嘀嘀无限科技发展有限公司 System and method for destination prediction
CN107644542A (en) * 2017-09-11 2018-01-30 应石磊 A kind of air navigation aid and remote information process device based on parking space information
CN108286980A (en) * 2017-12-29 2018-07-17 广州通易科技有限公司 A method of prediction destination and recommendation drive route
CN108091173A (en) * 2018-01-25 2018-05-29 贵州宜行智通科技有限公司 Parking stall guidance information method for pushing and device
CN108896061A (en) * 2018-05-11 2018-11-27 京东方科技集团股份有限公司 A kind of man-machine interaction method and onboard navigation system based on onboard navigation system
US20200175871A1 (en) * 2018-11-29 2020-06-04 Toyota Jidosha Kabushiki Kaisha Information providing system, server, onboard device, and information providing method
CN109612485A (en) * 2018-12-17 2019-04-12 许建国 A kind of intelligent route planning system of new-energy automobile

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115294791A (en) * 2022-07-29 2022-11-04 广州市粤迅特数码技术有限公司 Intelligent traffic guidance system for smart city

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