CN111091216A - Method and server for network contract intelligent transportation means - Google Patents
Method and server for network contract intelligent transportation means Download PDFInfo
- Publication number
- CN111091216A CN111091216A CN201911283432.7A CN201911283432A CN111091216A CN 111091216 A CN111091216 A CN 111091216A CN 201911283432 A CN201911283432 A CN 201911283432A CN 111091216 A CN111091216 A CN 111091216A
- Authority
- CN
- China
- Prior art keywords
- information
- lessee
- intelligent vehicle
- client
- lessor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 60
- 230000008569 process Effects 0.000 claims abstract description 19
- 230000006855 networking Effects 0.000 claims abstract description 13
- 206010039203 Road traffic accident Diseases 0.000 claims description 32
- 239000011159 matrix material Substances 0.000 claims description 31
- 238000013507 mapping Methods 0.000 claims description 28
- 230000009467 reduction Effects 0.000 claims description 24
- 238000007781 pre-processing Methods 0.000 claims description 10
- 238000012216 screening Methods 0.000 claims description 8
- 238000012544 monitoring process Methods 0.000 claims description 7
- 238000010606 normalization Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 6
- 238000012790 confirmation Methods 0.000 claims description 4
- 238000011835 investigation Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 8
- 230000008439 repair process Effects 0.000 description 4
- 230000036541 health Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000012550 audit Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/02—Reservations, e.g. for tickets, services or events
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0605—Supply or demand aggregation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
- G06Q30/0637—Approvals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0645—Rental transactions; Leasing transactions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
-
- G06Q50/40—
Abstract
The invention discloses a method and a server for networking intelligent vehicles, wherein the method comprises the following steps: acquiring lessor information and the leasing information of the intelligent transportation means from a lessor client; acquiring tenant information and lease requirement information from a tenant client; acquiring a credit level of a lessee from a credit card platform; judging whether the lessee can rent the intelligent vehicle according to the credit level; when the credit level of the lessee is determined to be greater than the set credit level, sending the matched leasing information of the intelligent vehicle to the lessee client side according to the leasing requirement information for the lessee to select; and acquiring order placing information of the lessee from the lessee client and confirming information of the lessee from the lessee client to generate order information. By adopting the method, various complicated processes of offline leasing can be avoided, the leasing is more convenient, and meanwhile, the credit level of the lessee can be checked, so that the leasing is safer and more reliable.
Description
Technical Field
The invention relates to the technical field of vehicle leasing, in particular to a method and a server for network contracting an intelligent vehicle.
Background
Along with the continuous development of scientific technology, vehicles are more and more intelligent, and people also are more and more convenient to appear, wherein, the net appointment car is a mode of people for selecting a trip. In the prior art, renting of vehicles by people is complicated, the process is various, and the credit level of a lessee is not checked, so that a plurality of problems can be caused.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, the first purpose of the invention is to provide a method for networking an intelligent vehicle, which can avoid various complicated processes of offline leasing, is more convenient to lease, and can audit the credit level of a lessee to ensure that the leasing is safer and more reliable.
A second object of the present invention is to provide a server.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides a method for networking an intelligent vehicle, which is applied to a server, and includes:
acquiring lessor information and the leasing information of the intelligent transportation means from a lessor client;
acquiring tenant information and lease requirement information from a tenant client;
acquiring a credit level of a lessee from a credit card platform;
judging whether the lessee can rent the intelligent vehicle according to the credit level;
when the credit level of the lessee is determined to be greater than the set credit level, sending the matched leasing information of the intelligent vehicle to the lessee client side according to the leasing requirement information for the lessee to select;
and acquiring order placing information of the lessee from the lessee client and confirming information of the lessee from the lessee client to generate order information.
According to the method for networking the intelligent vehicle, which is provided by the embodiment of the first aspect of the invention, the lessor information and the leasing information of the intelligent vehicle are obtained from the lessee client, and acquires the tenant information and the rental requirement information from the tenant client, acquires the credit level of the tenant from the credit card platform, judges whether the tenant can rent the intelligent vehicle according to the credit level of the tenant, the lessee may not lease the intelligent vehicle if the credit level of the lessee is less than the set credit level, and when it is determined that the credit level of the lessee is greater than the set credit level, recommending matched renting information to the lessees according to the renting requirement information of the lessees to enable the lessees to select, when the lessees select the intelligent transportation means to be rented, and directly placing orders, and generating order information after the lessor confirms the order placing information of the lessee. The whole leasing process is more convenient and easy to operate, and meanwhile, the credit level of the lessee can be audited, so that the leasing is safer and more reliable.
According to some embodiments of the invention, before the order is placed, the face information of the lessee is obtained from the lessee client side and is identified, and when the lessee is determined to be the lessee, the lessee can place the order.
According to some embodiments of the invention, the network contract intelligent vehicle acquires and identifies face information of a lessee from a lessee client before ordering, and the lessee can order when the lessee is determined to be the lessee; the method comprises the following steps of carrying out image normalization preprocessing on the face image of the lessee, screening effective characteristic pixels of the preprocessed image to obtain an effective characteristic pixel set, carrying out linear discriminant analysis on the effective characteristic pixel set to obtain a dimension reduction mapping image matrix, matching the dimension reduction mapping image matrix with the face image database of the lessee of the server, and executing a ordering operation command according to a matching result, wherein the specific steps comprise:
step A1, randomly collecting the lessee face image samples according to the method of the network contract intelligent vehicle;
step A2, according to a pre-established image preprocessing model, carrying out image normalization preprocessing on the renter face image samples randomly acquired in the step A1, and meanwhile, screening effective feature pixels on the randomly acquired renter face image samples according to a formula (1) to obtain an effective feature pixel set;
therein, exp is an exponential function of a natural constant e, and δ is (k)i-hi)-(ki-1-hi-1) D is the total dimension value of the randomly acquired lessee face image samples, i, j are the randomly acquired lessee face image samples with the size of i x j, kiFor the randomly collected effective column vector value, h, of the lessee face image sample in the direction of the horizontal axisjA valid column vector value in a vertical axis direction for the randomly acquired lessee-face image sample,
is the mean vector value in the direction of the horizontal axis of the image sample,
the mean vector value in the direction of the longitudinal axis of the image sample,
is a value within the range of the mean vector valid interval, P (k)i,hj) Effective characteristic pixel set formed after effective characteristic pixels are screened;
a3, performing linear discriminant analysis on the effective characteristic pixel set obtained in the step A2 according to a formula (2) to obtain a dimension reduction mapping image matrix;
wherein t is the number of columns of the dimensionality reduction mapping image matrix, ztMapping image matrix horizontal column vector values, g, for said dimension reductiontMapping longitudinal column vector values of the image matrix for the dimensionality reduction,
is k is theiThe projected values of the map of (2),
is the hj(z) is calculated from the projection data of (c)t-ki)(gt-hj)tFor linear discriminant analysis processing, L (z)t,gt) The image matrix is subjected to the linear discriminant analysis processing and dimension reduction mapping;
step A4, matching the dimension reduction mapping image matrix obtained in the step A3 with the server tenant face image database, and judging whether the matching is successful or not through a formula (3);
wherein N is the number of samples in the server tenant face image database, m and N are the space coordinates of the samples in the server tenant face image database, and xm、ynRespectively, the horizontal and vertical space distance values, P (x) of the image matrix of the dimensionality reduction mappingm,yn) Is equal to L (z)t,gt) Space distance of image matrix is reduced and mapped when P (x)m,yn) And when the calculated value is 1, the method means that the lessee face image samples are randomly acquired to be matched with the lessee face image database samples of the server, and ordering operation can be executed in the network-bound intelligent vehicle.
According to some embodiments of the invention, after the order information is generated, partial authority of the intelligent vehicle given by the lessor is acquired from a lessor client, and the intelligent vehicle is remotely controlled to execute the order information.
According to some embodiments of the invention, during execution of the order information by the intelligent vehicle, whether a traffic accident occurs in the intelligent vehicle is automatically monitored.
According to some embodiments of the invention, when a traffic accident is monitored, acquiring insurance application information of a lessor from a lessor client and video information of a traffic accident scene from a video acquisition device of the intelligent vehicle, and sending the insurance application information and the video information to an insurance claim settlement platform;
receiving insurance claim settlement information given by an insurance claim settlement platform according to the insurable information and the video information, and sending the insurance claim settlement information to a lessor;
and acquiring feedback information of the lessor on the insurance claim settlement information from the lessor client to perform insurance claim settlement on the intelligent vehicle.
According to some embodiments of the present invention, after the intelligent vehicle performs the process of the order information, fee information for renting the intelligent vehicle is calculated and transmitted to the lessee.
In order to achieve the above object, a second embodiment of the present invention provides a server suitable for a networked intelligent vehicle, including:
the system comprises a first receiving module, a second receiving module and a third receiving module, wherein the first receiving module is used for acquiring lessor information and leasing information of the intelligent transportation tool from a lessor client;
the second receiving module is used for acquiring the tenant information and the lease requirement information from the tenant client;
the third receiving module is used for acquiring the credit level of the lessee from the credit investigation platform;
the judging module is used for judging whether the lessee can rent the intelligent vehicle according to the credit level;
the recommendation module is used for sending the rental information of the intelligent vehicle matched with the rental demand information to a client of the lessee according to the rental demand information for the lessee to select when the credit level of the lessee is determined to be greater than the set credit level;
and the fourth receiving module is used for acquiring order placing information of the lessee from the lessee client and acquiring confirmation information of the lessee from the lessee client to generate order information.
According to the server provided by the embodiment of the second aspect of the invention, the lessor information and the leasing information of the intelligent vehicle are obtained from the lessee client, and acquires the tenant information and the rental requirement information from the tenant client, acquires the credit level of the tenant from the credit card platform, judges whether the tenant can rent the intelligent vehicle according to the credit level of the tenant, the lessee may not lease the intelligent vehicle if the credit level of the lessee is less than the set credit level, and when it is determined that the credit level of the lessee is greater than the set credit level, recommending matched renting information to the lessees according to the renting requirement information of the lessees to enable the lessees to select, when the lessees select the intelligent transportation means to be rented, and directly placing orders, and generating order information after the lessor confirms the order placing information of the lessee. The whole leasing process is more convenient and easy to operate, and meanwhile, the credit level of the lessee can be audited, so that the leasing is safer and more reliable.
According to some embodiments of the invention, the second receiving module is further configured to, before the order is placed, obtain and identify face information of the tenant from the tenant client, and when the tenant is determined to be the tenant himself, the tenant can place the order.
According to some embodiments of the invention, the server further comprises a control module, which is used for acquiring partial authority of the intelligent vehicle given by the lessor from the lessor client after the order information is generated, and remotely controlling the intelligent vehicle to execute the order information.
According to some embodiments of the invention, the server further comprises:
the monitoring module is used for automatically monitoring whether a traffic accident happens to the intelligent vehicle in the process of executing the order information by the intelligent vehicle;
the system comprises a first transceiving module, a second transceiving module and an insurance claim settlement platform, wherein the first transceiving module is used for acquiring insurance information of a lessor from a lessor client and video information of a traffic accident scene from a video acquisition device of an intelligent vehicle when a traffic accident is monitored, and transmitting the insurance information and the video information to the insurance claim settlement platform;
the second transceiver module is used for receiving insurance claim settlement information given by an insurance claim settlement platform according to the insurable information and the video information and sending the insurance claim settlement information to the lessor;
the first receiving module is further used for obtaining feedback information of the lessor on the insurance claim settlement information from the lessor client side and conducting insurance claim settlement on the intelligent vehicle.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow diagram of a method of contracting an intelligent vehicle according to one embodiment of the present invention;
FIG. 2 is a flow diagram of an insurance claim according to one embodiment of the invention;
FIG. 3 is a block diagram of a server according to a first embodiment of the present invention;
fig. 4 is a block diagram of a server according to a second embodiment of the present invention.
Reference numerals:
the system comprises a server 100, a first receiving module 1, a second receiving module 2, a third receiving module 3, a judging module 4, a recommending module 5, a fourth receiving module 6, a control module 7, a monitoring module 8, a first transceiver module 9 and a second transceiver module 10.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The method and the server for providing a network-bound intelligent vehicle according to the embodiment of the present invention are described below with reference to fig. 1 to 4.
Before introducing the method and the server for providing the network contract intelligent vehicle, the application scenarios related to the embodiments of the invention are introduced. In an application scenario, the intelligent vehicle can realize unmanned driving, and the intelligent vehicle comprises an intelligent vehicle, an intelligent ship and an intelligent aircraft. The present invention is explained taking the intelligent vehicle as an intelligent vehicle.
FIG. 1 is a flow diagram of a method of contracting an intelligent vehicle according to one embodiment of the present invention; as shown in fig. 1, an embodiment of the first aspect of the present invention provides a method for networking an intelligent vehicle, which is applied to a server, and includes the following steps S1-S6,
s1, acquiring lessor information and leasing information of the intelligent transportation tool from a lessor client, wherein the lessor information comprises names, mobile phone numbers, identity card numbers and the like, and the leasing information comprises leasing time, leasing rent, type of the intelligent transportation tool, license plate, color, model and the like;
the method comprises the steps that a lessor client downloads APP of an intelligent network transportation tool for a lessor by utilizing a first terminal and registers a lessor account number, the first terminal can be a mobile phone, a tablet personal computer or a vehicle-mounted terminal, the lessor inputs lessor information and leasing information of the intelligent transportation tool into the APP of the intelligent network transportation tool, the lessor information comprises a name, a mobile phone number, an identity card number and the like, and the leasing information comprises leasing time, leasing rent, type of the intelligent transportation tool, license plate, color, model number and the like; for example, the smart vehicle type may be a smart vehicle implementing unmanned driving, which may be charged on an hourly basis, on a daily basis, or on a distance traveled. The renting information is published on an APP platform of the network contract intelligent vehicle, so that online renting information publication is realized for the lessees to select.
S2, acquiring tenant information and lease requirement information from a tenant client; the information of the lessees comprises names, mobile phone numbers, identity card numbers and the like; the rental requirement information comprises rental time, rental rent, the type, color, model and the like of the intelligent vehicle;
the method comprises the steps that a tenant client downloads APP of an intelligent transportation means of the network for the tenant by using a second terminal and registers a tenant account, the second terminal can be a mobile phone or a tablet personal computer, the tenant inputs tenant information and lease demand information in the APP of the intelligent transportation means of the network, and the tenant information comprises names, mobile phone numbers, identity numbers and the like; the rental requirement information comprises rental time, rental rent, the type, color, model and the like of the intelligent vehicle; for example, a lessee may rent a smart vehicle at a wedding time with a rental of 500 dollars per day. The renting demand information of the lessees is published on the APP platform of the networked intelligent transportation tool, so that the lessees can select the APP platform, and the APP platform of the networked intelligent transportation tool can recommend the appropriate intelligent transportation tool to the lessees according to the renting demand information.
S3, acquiring the credit level of the lessee from the credit accreditation platform;
specifically, the credit level condition of the lessee can be obtained from the bank.
S4, judging whether the lessee can rent the intelligent vehicle according to the credit level;
the credit grades are divided into AAA grade, AA grade, A grade, BBB grade, BB grade, B grade, CCC grade, CC grade and C grade; the AAA level represents the highest credit level, the C level represents the lowest credit level, when the credit level of the lessee is lower than the B level (the B level is the set credit level), the default phenomenon can be more easily caused in the leasing transaction, in order to ensure the safe and reliable execution of the leasing order and avoid causing unnecessary loss to the lessee, and when the credit level of the lessee is lower than the B level, the lessee can not rent the intelligent transportation tool.
S5, when the credit level of the lessee is determined to be larger than the set credit level, sending the matched leasing information of the intelligent vehicle to the lessee client side according to the leasing requirement information for the lessee to select;
and when the credit level of the lessee is greater than the set credit level B level, allowing the lessee to carry out lease transaction, and recommending the lease information of the intelligent transportation means which is more matched with the lease requirement to the lessee according to the big data by the APP of the network-bound intelligent transportation means in order to enable the lessee to find the intelligent transportation means which is more matched with the lease requirement of the lessee, so that the lessee can select the lease information, and the user experience is improved.
And S6, acquiring order placing information of the lessee from the lessee client and acquiring confirmation information of the lessee from the lessee client to generate order information.
The intelligent transportation means needing renting are selected by the lessees, orders are placed in the APP in a clicking mode, after the lessees confirm the information, order information can be generated, and the whole renting process is simple, fast, safe and reliable.
According to the method for networking the intelligent vehicle, which is provided by the embodiment of the first aspect of the invention, the lessor information and the leasing information of the intelligent vehicle are obtained from the lessee client, and acquires the tenant information and the rental requirement information from the tenant client, acquires the credit level of the tenant from the credit card platform, judges whether the tenant can rent the intelligent vehicle according to the credit level of the tenant, the lessee may not lease the intelligent vehicle if the credit level of the lessee is less than the set credit level, and when it is determined that the credit level of the lessee is greater than the set credit level, recommending matched renting information to the lessees according to the renting requirement information of the lessees to enable the lessees to select, when the lessees select the intelligent transportation means to be rented, and directly placing orders, and generating order information after the lessor confirms the order placing information of the lessee. The whole leasing process is more convenient and easy to operate, and meanwhile, the credit level of the lessee can be audited, so that the leasing is safer and more reliable.
In one embodiment, before the order is placed, the face information of the lessee is acquired from the lessee client side and is identified, and when the lessee is determined to be the lessee, the lessee can place the order.
The face recognition is carried out on the lessee, the operation of safely verifying whether the lessee is the lessee can be carried out, the safety of the whole leasing process is improved, and the auditing cost is reduced.
In one embodiment, the network contract intelligent vehicle acquires face information of a lessee from a lessee client side and identifies the face information before ordering, and the lessee can order the face information when the face information is determined to be the lessee; the method comprises the following steps of carrying out image normalization preprocessing on the face image of the lessee, screening effective characteristic pixels of the preprocessed image to obtain an effective characteristic pixel set, carrying out linear discriminant analysis on the effective characteristic pixel set to obtain a dimension reduction mapping image matrix, matching the dimension reduction mapping image matrix with the face image database of the lessee of the server, and executing a ordering operation command according to a matching result, wherein the specific steps comprise:
step A1, randomly collecting the lessee face image samples according to the method of the network contract intelligent vehicle;
step A2, according to a pre-established image preprocessing model, carrying out image normalization preprocessing on the renter face image samples randomly acquired in the step A1, and meanwhile, screening effective feature pixels on the randomly acquired renter face image samples according to a formula (1) to obtain an effective feature pixel set;
where exp is an exponential function of the natural constant e and δ is (k)i-hi)-(ki-1-hi-1) D is the total dimension value of the randomly acquired lessee face image samples, i, j are the randomly acquired lessee face image samples with the size of i x j, kiFor the randomly collected effective column vector value, h, of the lessee face image sample in the direction of the horizontal axisjA valid column vector value in a vertical axis direction for the randomly acquired lessee-face image sample,
is the mean vector value in the direction of the horizontal axis of the image sample,
the mean vector value in the direction of the longitudinal axis of the image sample,
is a value within the range of the mean vector valid interval, P (k)i,hj) For screening of significant feature pixel post-structuringForming a set of valid feature pixels;
a3, performing linear discriminant analysis on the effective characteristic pixel set obtained in the step A2 according to a formula (2) to obtain a dimension reduction mapping image matrix;
wherein t is the number of columns of the dimensionality reduction mapping image matrix, ztMapping image matrix horizontal column vector values, g, for said dimension reductiontMapping longitudinal column vector values of the image matrix for the dimensionality reduction,
is k is theiThe projected values of the map of (2),
is the hj(z) is calculated from the projection data of (c)t-ki)(gt-hj)tFor linear discriminant analysis processing, L (z)t,gt) The image matrix is subjected to the linear discriminant analysis processing and dimension reduction mapping;
step A4, matching the dimension reduction mapping image matrix obtained in the step A3 with the server tenant face image database, and judging whether the matching is successful or not through a formula (3);
wherein N is the number of samples in the server tenant face image database, m and N are the space coordinates of the samples in the server tenant face image database, and xm、ynRespectively, the horizontal and vertical space distance values, P (x) of the image matrix of the dimensionality reduction mappingm,yn) Is equal to L (z)t,gt) Space distance of image matrix is reduced and mapped when P (x)m,yn) When the calculated value is 1, the method means that the lessee face image sample and the server lessee face image database sample are randomly collectedThe matching can be carried out by the network contract intelligent vehicle.
The beneficial effects of the above technical scheme are: the technical scheme provides technical support for judging whether a lessee provides a valid order in the network-constrained intelligent vehicle system, image normalization preprocessing is carried out on a face image of the lessee, a dimension-reduction mapping image matrix is obtained through screening of valid feature pixels and linear discriminant analysis, and the result is matched with a server lessee face image database to judge whether the order is valid.
In one embodiment, after the order information is generated, partial authority of the intelligent vehicle given by a lessor is acquired from a lessor client, and the intelligent vehicle is remotely controlled to execute the order information.
And the lessor gives partial authority of the intelligent vehicle including unlocking authority, automatic navigation authority, unmanned authority and the like of the intelligent vehicle to the APP background for remotely controlling the intelligent vehicle to execute order information. In an example, the server remotely realizes the unlocking of the intelligent vehicle through the unlocking authority, the intelligent vehicle is controlled to reach the appointed departure place of the lessee through the automatic navigation authority and the unmanned authority, the lessee sits on the intelligent vehicle, the intelligent vehicle can realize unmanned driving, the lessee is sent to the appointed destination place, and the lease transaction is completed.
The intelligence of intelligent transportation means is embodied, the transportation trip of people becomes more convenient and reliable, and the lease transaction becomes more controllable and safer.
In one embodiment, during execution of the order information by the intelligent vehicle, whether a traffic accident occurs in the intelligent vehicle is automatically monitored.
APP backstage can real time monitoring order information's execution conditions, can ensure the rights and interests of lessees and lessees, when confirming that the traffic accident takes place, in time carry out insurance claim settlement, can make intelligent vehicle obtain the indemnity or repair to the repair shop, reduce the damage to minimum, when the traffic accident is lighter, can change intelligent vehicle for the lessee, or send the lessee to appointed destination place, can not cause the trouble to the lessee, when the traffic accident is serious, can in time send the hospital to the lessee, guarantee its life health safety.
FIG. 2 is a flow diagram of an insurance claim according to one embodiment of the invention; as shown in FIG. 2, in one embodiment, the above steps S7-S9 are included;
s7, when a traffic accident is monitored, acquiring insurance information of a lessor from a lessor client, acquiring video information of a traffic accident scene from a video acquisition device of the intelligent vehicle, and sending the insurance information and the video information to an insurance claim settlement platform;
the method comprises the steps that the networking intelligent vehicle APP and an insurance claim settlement platform carry out the intercommunication of the taxi insurance information, when a traffic accident happens, the insurance information of the taxi and the video information of the traffic accident scene are sent to the insurance claim settlement platform, the insurance information comprises insurance application date, insurance application amount, contact modes, license plates and the like, the video information of the traffic accident scene can pass through a video acquisition device loaded on the intelligent vehicle, and the video acquisition device can be exemplified by a vehicle traveling recorder on an intelligent vehicle.
S8, receiving insurance claim settlement information given by the insurance claim settlement platform according to the insurable information and the video information, and sending the insurance claim settlement information to a lessor;
and S9, acquiring feedback information of the lessor on the insurance claim settlement information from the lessor client, and performing insurance claim settlement on the intelligent vehicle.
The method can quickly process the claim settlement events of traffic accidents, save the time cost of lessors, save the manpower and material cost of an insurance claim settlement platform and simplify the claim settlement procedure.
In one embodiment, after the intelligent vehicle executes the process of the order information, fee information for renting the intelligent vehicle is calculated and transmitted to the lessee.
After the order information is completed, the APP issues the calculated expense information to the lessee, the lessee is reminded to pay, the whole lease order is completed, the transaction is more convenient, safe and reliable, and the lease efficiency is improved.
FIG. 3 is a block diagram of a server according to a first embodiment of the present invention; as shown in fig. 3, a second embodiment of the present invention provides a server 100, suitable for a smart transportation vehicle, including:
the system comprises a first receiving module 1, a first service module and a second receiving module, wherein the first receiving module is used for acquiring lessor information and leasing information of the intelligent transportation tool from a lessor client; the taxi information comprises a name, a mobile phone number, an identity card number and the like, and the taxi information comprises taxi time, a taxi rent, the type of the intelligent transportation tool, a license plate, color, model and the like;
the method comprises the steps that a lessor client downloads APP of an intelligent network transportation tool for a lessor by utilizing a first terminal and registers a lessor account number, the first terminal can be a mobile phone, a tablet personal computer or a vehicle-mounted terminal, the lessor inputs lessor information and leasing information of the intelligent transportation tool into the APP of the intelligent network transportation tool, the lessor information comprises a name, a mobile phone number, an identity card number and the like, and the leasing information comprises leasing time, leasing rent, type of the intelligent transportation tool, license plate, color, model number and the like; for example, the smart vehicle type may be a smart vehicle implementing unmanned driving, which may be charged on an hourly basis, on a daily basis, or on a distance traveled. The renting information is published on an APP platform of the network contract intelligent vehicle, so that online renting information publication is realized for the lessees to select.
The second receiving module 2 is used for acquiring tenant information and lease requirement information from a tenant client; the information of the lessees comprises names, mobile phone numbers, identity card numbers and the like; the rental requirement information comprises rental time, rental rent, the type, color, model and the like of the intelligent vehicle;
the method comprises the steps that a tenant client downloads APP of an intelligent transportation means of the network for the tenant by using a second terminal and registers a tenant account, the second terminal can be a mobile phone or a tablet personal computer, the tenant inputs tenant information and lease demand information in the APP of the intelligent transportation means of the network, and the tenant information comprises names, mobile phone numbers, identity numbers and the like; the rental requirement information comprises rental time, rental rent, the type, color, model and the like of the intelligent vehicle; for example, a lessee may rent a smart vehicle at a wedding time with a rental of 500 dollars per day. The renting demand information of the lessees is published on the APP platform of the networked intelligent transportation tool, so that the lessees can select the APP platform, and the APP platform of the networked intelligent transportation tool can recommend the appropriate intelligent transportation tool to the lessees according to the renting demand information.
The third receiving module 3 is used for acquiring the credit level of the lessee from the credit investigation platform;
specifically, the credit level condition of the lessee can be obtained from the bank.
The judging module 4 is used for judging whether the lessee can rent the intelligent vehicle according to the credit level;
the credit grades are divided into AAA grade, AA grade, A grade, BBB grade, BB grade, B grade, CCC grade, CC grade and C grade; the AAA level represents the highest credit level, the C level represents the lowest credit level, when the credit level of the lessee is lower than the B level (the B level is the set credit level), the default phenomenon can be more easily caused in the leasing transaction, in order to ensure the safe and reliable execution of the leasing order and avoid causing unnecessary loss to the lessee, and when the credit level of the lessee is lower than the B level, the lessee can not rent the intelligent transportation tool.
The recommending module 5 is used for sending the renting information of the intelligent transportation tool matched with the renting demand information to a client of the lessee for the lessee to select when the credit level of the lessee is determined to be greater than the set credit level;
when the credit level of the lessee is greater than the set credit level, the lessee is allowed to conduct lease transaction, in order to enable the lessee to find the intelligent vehicle which is more matched with the lease demand of the lessee, the APP of the network contract intelligent vehicle recommends the lease information of the intelligent vehicle which is more matched with the lease demand of the lessee to the lessee according to the big data, the lessee is allowed to select, and the user experience is improved.
And the fourth receiving module 6 is used for acquiring order placing information of the lessee from the lessee client and acquiring confirmation information of the lessee from the lessee client to generate order information.
The intelligent transportation means needing renting are selected by the lessees, orders are placed in the APP in a clicking mode, after the lessees confirm the information, order information can be generated, and the whole renting process is simple, fast, safe and reliable.
According to the server 100 proposed by the embodiment of the second aspect of the present invention, the lessor information and the rental information of the intelligent vehicle are acquired from the lessee client, and acquires the tenant information and the rental requirement information from the tenant client, acquires the credit level of the tenant from the credit card platform, judges whether the tenant can rent the intelligent vehicle according to the credit level of the tenant, the lessee may not lease the intelligent vehicle if the credit level of the lessee is less than the set credit level, and when it is determined that the credit level of the lessee is greater than the set credit level, recommending matched renting information to the lessees according to the renting requirement information of the lessees to enable the lessees to select, when the lessees select the intelligent transportation means to be rented, and directly placing orders, and generating order information after the lessor confirms the order placing information of the lessee. The whole leasing process is more convenient and easy to operate, and meanwhile, the credit level of the lessee can be audited, so that the leasing is safer and more reliable.
FIG. 4 is a block diagram of a server according to a second embodiment of the present invention; as shown in fig. 4, in an embodiment, the second receiving module 2 is further configured to, before the tenant makes an order, obtain and identify face information of the tenant from a tenant client, and when the tenant is determined to be the tenant himself, the tenant may make an order.
The face recognition is carried out on the lessee, the operation of safely verifying whether the lessee is the lessee can be carried out, the safety of the whole leasing process is improved, and the auditing cost is reduced.
In an embodiment, the server 100 further includes a control module 7, configured to obtain, from the lessor client, a part of rights of the intelligent vehicle given by the lessor after the order information is generated, and remotely control the intelligent vehicle to execute the order information.
The lessor gives part of authority of the intelligent vehicle, including unlocking authority, automatic navigation authority, unmanned authority and the like of the intelligent vehicle, to the server 100 to remotely control the intelligent vehicle to execute order information. In an example, the server remotely realizes the unlocking of the intelligent vehicle through the unlocking authority, the intelligent vehicle is controlled to reach the appointed departure place of the lessee through the automatic navigation authority and the unmanned authority, the lessee sits on the intelligent vehicle, the intelligent vehicle can realize unmanned driving, the lessee is sent to the appointed destination place, and the lease transaction is completed.
The intelligence of intelligent transportation means is embodied, the transportation trip of people becomes more convenient and reliable, and the lease transaction becomes more controllable and safer.
In an embodiment, the server 100 further includes a monitoring module 8, configured to automatically monitor whether a traffic accident occurs in the intelligent vehicle during execution of the order information by the intelligent vehicle;
the server 100 can monitor the execution condition of order information in real time, can guarantee the rights and interests of a lessor and a lessee, timely carry out insurance claim when determining that a traffic accident occurs, can enable an intelligent vehicle to obtain compensation or repair the intelligent vehicle in a repair shop, reduces the damage to the minimum, can replace the intelligent vehicle for the lessee or send the lessee to a specified destination place when the traffic accident is light, cannot cause troubles to the lessee, and can timely send the lessee to a hospital when the traffic accident is serious, so that the life health and safety of the lessee are ensured.
The first transceiving module 9 is used for acquiring insurance information of a lessor from a lessor client and video information of a traffic accident scene from a video acquisition device of the intelligent vehicle when a traffic accident is monitored, and sending the insurance information and the video information to an insurance claim settlement platform;
the method comprises the steps that the networking intelligent vehicle APP and an insurance claim settlement platform carry out the intercommunication of the taxi insurance information, when a traffic accident happens, the insurance information of the taxi and the video information of the traffic accident scene are sent to the insurance claim settlement platform, the insurance information comprises insurance application date, insurance application amount, contact modes, license plates and the like, the video information of the traffic accident scene can pass through a video acquisition device loaded on the intelligent vehicle, and the video acquisition device can be exemplified by a vehicle traveling recorder on an intelligent vehicle.
The second transceiver module 10 is configured to receive insurance claim settlement information given by an insurance claim settlement platform according to the insurable information and the video information, and send the insurance claim settlement information to a lessor;
the first receiving module 1 is further configured to obtain feedback information of the insurance claim settlement information from the lessor client to perform insurance claim settlement on the intelligent vehicle.
The method can quickly process the claim settlement events of traffic accidents, save the time cost of lessors, save the manpower and material cost of an insurance claim settlement platform and simplify the claim settlement procedure.
In one embodiment, the server 100 further includes a fee calculating module for calculating and transmitting fee information for renting the intelligent vehicle to the lessee after the intelligent vehicle performs the process of the order information.
After the order information is completed, the server 100 issues the calculated fee information to the lessee to remind the lessee to pay, so that the whole lease order is completed, the transaction is more convenient, safe and reliable, and the lease efficiency is improved.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description. And are not intended to indicate or imply that the referenced device or element must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (11)
1. A method for networking an intelligent vehicle, applied to a server, is characterized by comprising the following steps:
acquiring lessor information and the leasing information of the intelligent transportation means from a lessor client;
acquiring tenant information and lease requirement information from a tenant client;
acquiring a credit level of a lessee from a credit card platform;
judging whether the lessee can rent the intelligent vehicle according to the credit level;
when the credit level of the lessee is determined to be greater than the set credit level, sending the matched leasing information of the intelligent vehicle to the lessee client side according to the leasing requirement information for the lessee to select;
and acquiring order placing information of the lessee from the lessee client and confirming information of the lessee from the lessee client to generate order information.
2. The method for networking an intelligent vehicle according to claim 1, wherein the lessee obtains and recognizes the face information of the lessee from the lessee client before placing an order, and the lessee can place the order when the lessee is determined to be the lessee himself.
3. The method of claim 2, wherein:
the network contract intelligent vehicle acquires the face information of the lessee from the lessee client side and identifies the face information before ordering, and the lessee can order the face information when the lessee is determined to be the lessee; the method comprises the following steps of carrying out image normalization preprocessing on the face image of the lessee, screening effective characteristic pixels of the preprocessed image to obtain an effective characteristic pixel set, carrying out linear discriminant analysis on the effective characteristic pixel set to obtain a dimension reduction mapping image matrix, matching the dimension reduction mapping image matrix with the face image database of the lessee of the server, and executing a ordering operation command according to a matching result, wherein the specific steps comprise:
step A1, randomly collecting the lessee face image samples according to the method of the network contract intelligent vehicle;
step A2, according to a pre-established image preprocessing model, carrying out image normalization preprocessing on the renter face image samples randomly acquired in the step A1, and meanwhile, screening effective feature pixels on the randomly acquired renter face image samples according to a formula (1) to obtain an effective feature pixel set;
where exp is an exponential function of the natural constant e and δ is (k)i-hi)-(ki-1-hi-1) D is the total dimension value of the randomly acquired lessee face image samples, i, j are the randomly acquired lessee face image samples with the size of i x j, kiFor the randomly collected effective column vector value, h, of the lessee face image sample in the direction of the horizontal axisjA valid column vector value in a vertical axis direction for the randomly acquired lessee-face image sample,
is the mean vector value in the direction of the horizontal axis of the image sample,
the mean vector value in the direction of the longitudinal axis of the image sample,
is a value within the range of the mean vector valid interval, P (k)i,hj) Effective characteristic pixel set formed after effective characteristic pixels are screened;
a3, performing linear discriminant analysis on the effective characteristic pixel set obtained in the step A2 according to a formula (2) to obtain a dimension reduction mapping image matrix;
wherein t is the number of columns of the dimensionality reduction mapping image matrix, ztMapping image matrix horizontal column vector values, g, for said dimension reductiontMapping longitudinal column vector values of the image matrix for the dimensionality reduction,
is k is theiThe projected values of the map of (2),
is the hj(z) is calculated from the projection data of (c)t-ki)(gt-hj)tFor linear discriminant analysis processing, L (z)t,gt) The image matrix is subjected to the linear discriminant analysis processing and dimension reduction mapping;
step A4, matching the dimension reduction mapping image matrix obtained in the step A3 with the server tenant face image database, and judging whether the matching is successful or not through a formula (3);
wherein N is the number of samples in the server tenant face image database, m and N are the space coordinates of the samples in the server tenant face image database, and xm、ynRespectively, the horizontal and vertical space distance values, P (x) of the image matrix of the dimensionality reduction mappingm,yn) Is equal to L (z)t,gt) Space distance of image matrix is reduced and mapped when P (x)m,yn) And when the calculated value is 1, the method means that the lessee face image samples are randomly acquired to be matched with the lessee face image database samples of the server, and ordering operation can be executed in the network-bound intelligent vehicle.
4. The method of networking intelligent vehicles according to claim 2, wherein after the order information is generated, partial authority of the intelligent vehicle given by a lessor is acquired from a lessor client, and the intelligent vehicle is remotely controlled to execute the order information.
5. The method of networking an intelligent vehicle according to claim 4, wherein the intelligent vehicle is automatically monitored for the occurrence of a traffic accident during execution of the order information by the intelligent vehicle.
6. The method of claim 5,
when a traffic accident is monitored, acquiring insurance application information of a lessor from a lessor client, acquiring video information of a traffic accident scene from a video acquisition device of the intelligent vehicle, and sending the insurance application information and the video information to an insurance claim settlement platform;
receiving insurance claim settlement information given by an insurance claim settlement platform according to the insurable information and the video information, and sending the insurance claim settlement information to a lessor;
and acquiring feedback information of the lessor on the insurance claim settlement information from the lessor client to perform insurance claim settlement on the intelligent vehicle.
7. The method of networking an intelligent vehicle according to claim 4, wherein after the intelligent vehicle performs the process of ordering information, fee information for renting the intelligent vehicle is calculated and transmitted to a lessee.
8. A server adapted for use in a networked intelligent vehicle, comprising:
the system comprises a first receiving module, a second receiving module and a third receiving module, wherein the first receiving module is used for acquiring lessor information and leasing information of the intelligent transportation tool from a lessor client;
the second receiving module is used for acquiring the tenant information and the lease requirement information from the tenant client;
the third receiving module is used for acquiring the credit level of the lessee from the credit investigation platform;
the judging module is used for judging whether the lessee can rent the intelligent vehicle according to the credit level;
the recommendation module is used for sending the rental information of the intelligent vehicle matched with the rental demand information to a client of the lessee according to the rental demand information for the lessee to select when the credit level of the lessee is determined to be greater than the set credit level;
and the fourth receiving module is used for acquiring order placing information of the lessee from the lessee client and acquiring confirmation information of the lessee from the lessee client to generate order information.
9. The server of claim 8, wherein the second receiving module is further configured to, before the order is placed, obtain and identify face information of a tenant from a tenant client, and when the tenant is determined to be the tenant himself, the tenant can place the order.
10. The server according to claim 9, wherein the server further comprises a control module for acquiring partial authority of the intelligent vehicle given by the lessor from a lessor client after the order information is generated, and remotely controlling the intelligent vehicle to execute the order information.
11. The server of claim 10, wherein the server further comprises:
the monitoring module is used for automatically monitoring whether a traffic accident happens to the intelligent vehicle in the process of executing the order information by the intelligent vehicle;
the system comprises a first transceiving module, a second transceiving module and an insurance claim settlement platform, wherein the first transceiving module is used for acquiring insurance information of a lessor from a lessor client and video information of a traffic accident scene from a video acquisition device of an intelligent vehicle when a traffic accident is monitored, and transmitting the insurance information and the video information to the insurance claim settlement platform;
the second transceiver module is used for receiving insurance claim settlement information given by an insurance claim settlement platform according to the insurable information and the video information and sending the insurance claim settlement information to the lessor;
the first receiving module is further used for obtaining feedback information of the lessor on the insurance claim settlement information from the lessor client side and conducting insurance claim settlement on the intelligent vehicle.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911283432.7A CN111091216A (en) | 2019-12-13 | 2019-12-13 | Method and server for network contract intelligent transportation means |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911283432.7A CN111091216A (en) | 2019-12-13 | 2019-12-13 | Method and server for network contract intelligent transportation means |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111091216A true CN111091216A (en) | 2020-05-01 |
Family
ID=70395559
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911283432.7A Pending CN111091216A (en) | 2019-12-13 | 2019-12-13 | Method and server for network contract intelligent transportation means |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111091216A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113222688A (en) * | 2021-04-23 | 2021-08-06 | 亿海蓝（北京）数据技术股份公司 | Ship leasing method and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108701324A (en) * | 2018-05-31 | 2018-10-23 | 深圳市元征科技股份有限公司 | A kind of management method and server of shared vehicle |
| CN108846762A (en) * | 2018-06-01 | 2018-11-20 | 上海博泰悦臻电子设备制造有限公司 | Traffic accident is quickly settled a claim method, system and a kind of server |
| CN109360054A (en) * | 2018-09-30 | 2019-02-19 | 中链科技有限公司 | Automobile leasing method, apparatus and electronic equipment based on block chain |
-
2019
- 2019-12-13 CN CN201911283432.7A patent/CN111091216A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108701324A (en) * | 2018-05-31 | 2018-10-23 | 深圳市元征科技股份有限公司 | A kind of management method and server of shared vehicle |
| CN108846762A (en) * | 2018-06-01 | 2018-11-20 | 上海博泰悦臻电子设备制造有限公司 | Traffic accident is quickly settled a claim method, system and a kind of server |
| CN109360054A (en) * | 2018-09-30 | 2019-02-19 | 中链科技有限公司 | Automobile leasing method, apparatus and electronic equipment based on block chain |
Non-Patent Citations (1)
| Title |
|---|
| 王胜: "基于流形学习的人脸识别算法研究" * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113222688A (en) * | 2021-04-23 | 2021-08-06 | 亿海蓝（北京）数据技术股份公司 | Ship leasing method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10800354B2 (en) | Digital vehicle tag and method of integration in vehicle allocation system | |
| US11715143B2 (en) | Network-based system for showing cars for sale by non-dealer vehicle owners | |
| US11972487B1 (en) | Systems and methods for allocating vehicle costs between vehicle users for anticipated trips | |
| JP3834463B2 (en) | In-vehicle failure alarm reporting system | |
| CN110263946B (en) | Maintenance service platform and method based on automobile data collection and bidding and robbing orders | |
| US10181104B2 (en) | Allocation system and method of deploying resources | |
| US20020186144A1 (en) | System and method for automating a vehicle rental process | |
| US20190266897A1 (en) | Drone usage in connected user and connected fleet communication and interface systems | |
| CN104620277A (en) | Method and mobile terminal for providing transport service information, method and server for managing transport service, and method and vehicle for providing transport service | |
| US20180336738A1 (en) | On-Board Vehicle Parking Transaction System | |
| US20240095686A1 (en) | Autonomous car repair | |
| US20190019114A1 (en) | Remote vehicle access and multi-application program for car-sharing | |
| CN111091216A (en) | Method and server for network contract intelligent transportation means | |
| KR101694230B1 (en) | Method and service server for managing transport vehicle | |
| WO2016040808A1 (en) | Digital vehicle tag and method of integration in vehicle allocation system | |
| JP6637105B2 (en) | Vehicle lending management system | |
| TWM573041U (en) | Decentralized vehicle risk assessment system | |
| CA2445580A1 (en) | System and method for automating a vehicle rental process | |
| WO2023100335A1 (en) | Authentication system and authentication method | |
| JP7283925B2 (en) | Transportation information processing device and transportation information processing method | |
| CN117575585A (en) | Method, device, terminal equipment and storage medium for vehicle refueling | |
| KR20220145183A (en) | System and method for registering information for vehicle sharing among residents of an apartment house | |
| JP2021140457A (en) | Vehicle rental service management apparatus, vehicle rental service management method, and program | |
| UA146424U (en) | METHOD OF AUTOMATIC DETERMINATION OF THE INSURANCE PAYMENT OF THE VEHICLE ON THE BASIS OF DATA ON THE OPERATION OF THE VEHICLE | |
| TW202016858A (en) | Decentralized vehicle risk assessment system and method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200501 |
|
| RJ01 | Rejection of invention patent application after publication |