A method and system for intelligent automobile navigation

Abstract

The present invention provides a method and system for intelligent automobile navigation, wherein the method comprises: obtaining description information input by a user; parsing the description information to determine a target position; determining whether the target position is a preset trigger position in the trigger position library based on a preset trigger position library; when the target position is a trigger position, outputting a preset first inquiry information; receiving first feedback information corresponding to the first inquiry information input by the user; when the first feedback information is confirmed, determining a first navigation target point and a second navigation target point based on the target position; generating a first navigation route based on the first navigation target point; outputting the first navigation route; when the user reaches the end point of the first navigation route, generating and outputting a second navigation route based on the second navigation target point. The intelligent automobile navigation method of the present invention enables the user to directly navigate with the parking space in the parking lot as the end point when going to a commercial center, truly achieving end point navigation, and facilitating the user's travel.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile navigation, and in particular to an automobile intelligent navigation method and system. Background Art

[0002] As people's living standards gradually improve, cars have gradually become the main means of transportation for families. The emergence of car navigation has provided convenience for people to drive. However, when users navigate to a commercial center, the end point of navigation is located on the road near the main entrances and exits of the commercial center. Users still need to drive into the parking lot to find a parking space, and true end point navigation cannot be achieved. Summary of the invention

[0003] One of the purposes of the present invention is to provide an intelligent automobile navigation method, which enables a user to directly navigate to a parking space in a parking lot as a destination when going to a commercial center, thus truly achieving destination navigation and facilitating the user's travel.

[0004] An embodiment of the present invention provides an intelligent automobile navigation method, comprising:

[0005] Get the description information entered by the user;

[0006] Parse the description information and determine the target location;

[0007] Based on the preset trigger position library, determining whether the target position is a preset trigger position in the trigger position library;

[0008] When the target position is the trigger position, output the preset first inquiry information;

[0009] Receiving first feedback information corresponding to the first inquiry information input by the user;

[0010] When the first feedback information is confirmed, determining a first navigation target point and a second navigation target point based on the target position;

[0011] Based on the first navigation target point, generating a first navigation route;

[0012] Outputting a first navigation route;

[0013] When the user reaches the end point of the first navigation route, a second navigation route is generated and output based on the second navigation target point.

[0014] Preferably, the automobile intelligent navigation method further includes:

[0015] When the first feedback information is negative, when the user reaches the end point of the first navigation route, a preset second inquiry information is output;

[0016] receiving second feedback information corresponding to the second inquiry information input by the user;

[0017] When the second feedback information is confirmed, a second navigation route is generated and output based on the second navigation target point.

[0018] Preferably, based on the second navigation target point, generating and outputting a second navigation route includes:

[0019] Access the management platform of the parking lot associated with the triggering end point;

[0020] Get the parking lot plan sent by the management platform;

[0021] Determine the locations of each entrance and exit connecting the parking lot and the second navigation target point;

[0022] Plan the shortest path from each entrance and exit to the second navigation target point;

[0023] Based on a preset path evaluation library, the shortest paths corresponding to each entrance and exit are scored to obtain a first scoring value corresponding to each entrance and exit;

[0024] Obtain the parking space usage information in the parking lot sent by the management platform;

[0025] Based on the parking space usage, determining at least one vacant parking space;

[0026] Obtain the driving conditions in the parking lot sent by the management platform;

[0027] Based on the traffic situation, determine the probability of each free parking space being used;

[0028] Determine the second scoring value corresponding to each vacant parking space based on the probability and a preset probability and second scoring value comparison table;

[0029] Based on the parking lot plan, determine the distance between each vacant parking space and each entrance and exit;

[0030] Based on the preset distance and relationship coefficient comparison table, determine the relationship coefficients corresponding to each vacant parking space and each entrance and exit;

[0031] Based on the relationship coefficient and the first score values ​​corresponding to each entrance and exit; determining the third score value corresponding to each vacant parking space;

[0032] Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table;

[0033] The vacant parking space with the highest priority is used as the navigation end point and a second navigation route is generated.

[0034] Preferably, based on the driving situation, determining the probability of each vacant parking space being used includes:

[0035] Based on the driving situation, determine the driving position of each vehicle in the parking lot;

[0036] Based on the driving position, determine the shortest path from each vehicle to each vacant parking space;

[0037] Inputting the path information of the shortest path from each vehicle to each free parking space into a preset neural network model to determine the probability of each vehicle occupying each free parking space;

[0038] Construct a feature vector based on the probability of each vehicle occupying the vacant parking space;

[0039] Get the preset prediction library;

[0040] The feature vector is matched with each prediction vector in the prediction library; and the probability value associated with the prediction vector matching the feature vector is obtained as the probability of the vacant parking space being used.

[0041] Preferably, based on the second navigation target point, generating and outputting a second navigation route includes:

[0042] Access the management platform of the parking lot associated with the triggering end point;

[0043] Get the parking lot plan sent by the management platform;

[0044] Obtain the parking space usage information in the parking lot sent by the management platform;

[0045] Based on the parking space usage, determine the vacant parking spaces and the occupied parking spaces;

[0046] On the parking lot plan, the used parking spaces are marked using the preset first marking method;

[0047] Obtain the driving conditions in the parking lot sent by the management platform;

[0048] Based on the traffic situation, determine the probability of each free parking space being used;

[0049] Based on the probability of each vacant parking space being used, querying a preset parameter determination table to determine the parameters of the second marking method corresponding to each vacant parking space;

[0050] Based on the parameters of the second marking method corresponding to each vacant parking space, the second marking method is used to mark each vacant parking space on the parking lot plan;

[0051] Obtaining an association table constructed based on descriptive information of destinations associated with each entrance and exit of the parking lot;

[0052] Place the association table into the parking lot plan and set it next to each corresponding entrance and exit;

[0053] Determine the association table corresponding to the second navigation target point and the description information of the destination in the association table, and use the preset first display mode to display the description information corresponding to the second navigation target point;

[0054] Plan the shortest path from each entrance and exit to the second navigation target point;

[0055] Based on a preset path evaluation library, the shortest paths corresponding to each entrance and exit are scored to obtain a first scoring value corresponding to each entrance and exit;

[0056] Determine the second scoring value corresponding to each vacant parking space based on the probability and a preset probability and second scoring value comparison table;

[0057] Based on the parking lot plan, determine the distance between each vacant parking space and each entrance and exit;

[0058] Based on the preset distance and relationship coefficient comparison table, determine the relationship coefficients corresponding to each vacant parking space and each entrance and exit;

[0059] Based on the relationship coefficient and the first score values ​​corresponding to each entrance and exit; determining the third score value corresponding to each vacant parking space;

[0060] Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table;

[0061] Mark the priority of each free parking space on the parking lot plan;

[0062] Output the parking lot plan after annotation and display processing;

[0063] Receive a user's selection of the location of each vacant parking space in the output parking lot plan;

[0064] The vacant parking space clicked by the user is used as the end point to generate a second navigation route.

[0065] Preferably, after outputting the parking lot plan after being marked and displayed, the method further includes:

[0066] Receive user's clicks on each descriptive information in each associated table;

[0067] When the selected description information is not the description information corresponding to the second navigation target point, the location point corresponding to the description information is used as a new second navigation target point, and the priority on the parking lot plan is updated again.

[0068] The present invention also provides an automobile intelligent navigation system, comprising:

[0069] An acquisition module is used to obtain the description information input by the user;

[0070] A target location determination module is used to parse the description information and determine the target location;

[0071] A judgment module, used for determining whether the target position is a preset trigger position in the trigger position library based on the preset trigger position library;

[0072] A first inquiry output module, used for outputting a preset first inquiry information when the target position is a trigger position;

[0073] A first feedback receiving module, configured to receive first feedback information corresponding to first inquiry information input by a user;

[0074] A target point determination module, used for determining a first navigation target point and a second navigation target point based on a target position when the first feedback information is confirmed;

[0075] A first route generating module, used for generating a first navigation route based on a first navigation target point;

[0076] A first route output module, used for outputting a first navigation route;

[0077] The second route generating module is used to generate and output a second navigation route based on a second navigation target point when the user reaches the end point of the first navigation route.

[0078] Preferably, the automobile intelligent navigation system further includes:

[0079] A second inquiry output module, configured to output a preset second inquiry information when the first feedback information is negative and the user reaches the end point of the first navigation route;

[0080] A second feedback information receiving module, used to receive second feedback information corresponding to the second inquiry information input by the user;

[0081] The second route generating module is further used to generate and output a second navigation route based on the second navigation target point when the second feedback information is confirmed.

[0082] Preferably, the second route generation module generates and outputs a second navigation route based on the second navigation target point, and performs the following operations:

[0083] Access the management platform of the parking lot associated with the triggering end point;

[0084] Get the parking lot plan sent by the management platform;

[0085] Determine the locations of each entrance and exit connecting the parking lot and the second navigation target point;

[0086] Plan the shortest path from each entrance and exit to the second navigation target point;

[0087] Based on a preset path evaluation library, the shortest paths corresponding to each entrance and exit are scored to obtain a first scoring value corresponding to each entrance and exit;

[0088] Obtain the parking space usage information in the parking lot sent by the management platform;

[0089] Based on the parking space usage, determining at least one vacant parking space;

[0090] Obtain the driving conditions in the parking lot sent by the management platform;

[0091] Based on the traffic situation, determine the probability of each free parking space being used;

[0092] Determine the second scoring value corresponding to each vacant parking space based on the probability and a preset probability and second scoring value comparison table;

[0093] Based on the parking lot plan, determine the distance between each vacant parking space and each entrance and exit;

[0094] Based on the preset distance and relationship coefficient comparison table, determine the relationship coefficients corresponding to each vacant parking space and each entrance and exit;

[0095] Based on the relationship coefficient and the first score values ​​corresponding to each entrance and exit; determining the third score value corresponding to each vacant parking space;

[0096] Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table;

[0097] The vacant parking space with the highest priority is used as the navigation end point and a second navigation route is generated.

[0098] Preferably, based on the driving situation, determining the probability of each vacant parking space being used includes:

[0099] Based on the driving situation, determine the driving position of each vehicle in the parking lot;

[0100] Based on the driving position, determine the shortest path from each vehicle to each vacant parking space;

[0101] Inputting the path information of the shortest path from each vehicle to each free parking space into a preset neural network model to determine the probability of each vehicle occupying each free parking space;

[0102] Construct a feature vector based on the probability of each vehicle occupying the vacant parking space;

[0103] Get the preset prediction library;

[0104] The feature vector is matched with each prediction vector in the prediction library; and the probability value associated with the prediction vector matching the feature vector is obtained as the probability of the vacant parking space being used.

[0105] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0106] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0107] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0108] Figure 1 A schematic diagram of an automobile intelligent navigation method according to an embodiment of the present invention;

[0109] Figure 2 The figure is a schematic diagram of an automobile intelligent navigation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0110] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0111] The embodiment of the present invention provides a method for intelligent automobile navigation. Figure 1 As shown, including:

[0112] Step S1: Obtaining description information input by the user; description information of the destination input by the user in the navigation interface of the car; for example: XX mall XX merchant;

[0113] Step S2: Parse the description information to determine the target location; for example, parse based on address association to determine that the XX store in XX mall is located at No. XX, XXX Road, 3F4A; where 3F represents the floor and 4A represents the store number;

[0114] Step S3: Based on the preset trigger position library, determine whether the target position is a preset trigger position in the trigger position library; determine whether the target position is a trigger position through the trigger position library, that is, when the target position is an address of the format of XXX Road, No. XX, 3F4A and is included in the trigger position library, it can be determined as a trigger;

[0115] Step S4: When the target location is the trigger location, output the preset first inquiry information; for example, the first inquiry information is "Do you need to execute the destination navigation?"

[0116] Step S5: receiving first feedback information corresponding to the first inquiry information input by the user;

[0117] Step S6: when the first feedback information is confirmed, the first navigation target point and the second navigation target point are determined based on the target position; for example, when the first feedback information is "yes", "okay", etc., the first feedback information is confirmed at this time; then the first navigation target point and the second navigation target point are determined based on the target position; when the target position is No. XX, XXX Road, 3F4A; then the first navigation target point is the position point corresponding to No. XX, XXX Road (for example, the position point on the road surface corresponding to each entrance and exit of the commercial center); the second navigation target point is the position point corresponding to 3F4A (the position of the merchant in the commercial center);

[0118] Step S7: Based on the first navigation target point, a first navigation route is generated; the first navigation route starts from the current location of the car and ends at the first navigation target point; when the commercial center has multiple entrances and exits, a query method can be output to obtain confirmation data of the user selecting one of them as the first navigation target point;

[0119] Step S8: outputting the first navigation route;

[0120] Step S9: When the user reaches the end point of the first navigation route, a second navigation route is generated and output based on the second navigation target point. When the first navigation route is finished, the second navigation route is generated, so that the parking navigation is connected with the road navigation, and the user is guided to the end point of the commercial center, so that the user can enjoy a more convenient navigation service.

[0121] In the case where the user selects "no" during the first inquiry, in order to enable the user to experience the destination navigation function again, in one embodiment, the automobile intelligent navigation method further includes:

[0122] When the first feedback information is negative, when the user reaches the end point of the first navigation route, the preset second inquiry information is output; for example, the second inquiry information is "Do you want to perform parking navigation?"

[0123] receiving second feedback information corresponding to the second inquiry information input by the user;

[0124] When the second feedback information is confirmed, a second navigation route is generated and output based on the second navigation target point.

[0125] In one embodiment, based on the second navigation target point, generating and outputting a second navigation route includes:

[0126] Accessing the management platform of the parking lot corresponding to the triggering end point; the implementation method may be: the server providing the car navigation function accesses the server corresponding to the parking lot management platform; the parking lot management platform (access method) and the commercial center (address) are pre-associated and stored in the server providing the car navigation function;

[0127] Get the parking lot plan sent by the management platform;

[0128] Determine the positions of each entrance and exit connecting the parking lot to the second navigation target point; if one can move to the position of the second navigation target point through the entrance and exit, it can be considered that the entrance and exit are connected to the second navigation target point;

[0129] Plan the shortest path from each entrance to the second navigation target point; plan the path through the internal structure diagram of the shopping mall, that is, the shortest path to the second navigation target point through the entrance;

[0130] Based on the preset path evaluation library, the shortest paths corresponding to each entrance and exit are scored, and the first score value corresponding to each entrance and exit is obtained; the path evaluation library is established in advance based on a large amount of data analysis, and mainly scores the shortest paths corresponding to each entrance and exit. The specific scoring items are the total distance, whether to take the elevator, etc.; the shorter the total distance, the higher the score, and the path with the same distance taking the elevator has a higher score;

[0131] Obtain the parking space usage information in the parking lot sent by the management platform;

[0132] Based on the parking space usage, determining at least one vacant parking space;

[0133] Obtain the driving conditions in the parking lot sent by the management platform;

[0134] Based on the traffic situation, determine the probability of each free parking space being used;

[0135] Determine the second scoring value corresponding to each vacant parking space based on the probability and a preset probability and second scoring value comparison table;

[0136] Based on the parking lot plan, determine the distance between each vacant parking space and each entrance and exit;

[0137] Based on the preset distance and relationship coefficient comparison table, determine the relationship coefficients corresponding to each vacant parking space and each entrance and exit;

[0138] Based on the relationship coefficient and the first score value corresponding to each entrance and exit; determine the third score value corresponding to each vacant parking space; first, calculate the product of the relationship coefficient and the first score value, determine the value determined by the vacant parking space for each entrance and exit, take the entrance and exit with the largest value as the optimal entrance and exit corresponding to the vacant parking space, and take the largest value as the third score value;

[0139] Determine the priority of each vacant parking space based on the second score value, the third score value and a preset score value and priority comparison table; the score value and priority comparison table is established in advance, wherein the second score value, the third score value and the priority are correspondingly associated;

[0140] The vacant parking space with the highest priority is used as the navigation destination and the second navigation route is generated. The vacant parking spaces are screened by priority, and the screening mainly considers the optimal solution to reach the second navigation destination and the probability of being used, so as to ensure that after the second navigation route is completed, that is, after the user parks, the optimal path can be used to move to the second navigation target point.

[0141] In one embodiment, based on the driving situation, determining the probability of each vacant parking space being used includes:

[0142] Based on the driving situation, determine the driving position of each vehicle in the parking lot;

[0143] Based on the driving position, determine the shortest path from each vehicle to each vacant parking space;

[0144] Input the path information of the shortest path from each vehicle to each free parking space into a preset neural network model to determine the probability of each vehicle occupying each free parking space; analyze the path information of the shortest path from each vehicle to each free parking space based on the neural network model to determine the probability of the vehicle using each free parking space; for example: sort the total mileage of the shortest paths of each vehicle to each free parking space, and the vehicle uses the parking space with the shortest shortest path, the shortest path is 3 meters, and the paths of the remaining parking spaces are more than 15 meters. At this time, the probability of the vehicle using the parking space with the shortest shortest path is 100%; the probability of using other parking spaces is 0; when the shortest path is 10 meters, the next level is also 10 meters, and the paths of the remaining parking spaces are more than 15 meters, the relative shortest path is 50%, the next level is also 50%, and the rest are 0;

[0145] Based on the probability of each vehicle occupying an empty parking space, a feature vector is constructed; for example, for the same empty parking space, the probability of the first vehicle using the empty parking space is 50%, the probability of the second vehicle using the empty parking space is 30%, the probability of the third vehicle using the empty parking space is 30%, and the probability of the remaining vehicles using the empty parking space is 20%; then the constructed feature vector is (0.50.30.30.2); that is, the probability values ​​of the first four digits are extracted as the data values ​​of the four dimensions corresponding to the feature vector;

[0146] Get the preset prediction library;

[0147] Match the feature vector with each prediction vector in the prediction library; obtain the probability value associated with the prediction vector that matches the feature vector as the probability that the vacant parking space is used. Vector matching can be achieved by calculating the similarity of the vectors. The specific calculation formula is as follows: D is the similarity between the feature vector and the prediction vector; t i is the i-th data value of the feature vector; y i is the i-th data value of the prediction vector; n is the vector dimension; when the similarity is the largest in the prediction library, the two are determined to match; for example: the feature vector is (0.5 0.3 0.3 0.2), the probability value of the association after matching is 100%; that is, the probability of the vacant parking space being used is 100%

[0148] The neural network model and prediction library are integrated to predict the probability of each free parking space being used, ensuring that when the user arrives at the parking space corresponding to the second navigation route, the parking space is free, thereby improving the intelligence of navigation.

[0149] In one embodiment, based on the second navigation target point, generating and outputting a second navigation route includes:

[0150] Access the management platform of the parking lot associated with the triggering end point;

[0151] Get the parking lot plan sent by the management platform;

[0152] Obtain the parking space usage information in the parking lot sent by the management platform;

[0153] Based on the parking space usage, determine the vacant parking spaces and the occupied parking spaces;

[0154] On the parking lot plan, the used parking spaces are marked using a preset first marking method; the first marking method includes: filling the area corresponding to the parking space with red;

[0155] Obtain the driving conditions in the parking lot sent by the management platform;

[0156] Based on the traffic situation, determine the probability of each free parking space being used;

[0157] Based on the probability of each free parking space being used, a preset parameter determination table is queried to determine the parameters of the second marking method corresponding to each free parking space; the probability in the parameter determination table is associated with the parameter; the parameters of the second marking method are determined by probability, and the second marking method can also be a method of filling the area corresponding to the parking space with a color, and the color is determined by the parameter, for example, the probability is 80%, the corresponding parameter is 01, and the determined color is yellow, that is, yellow is used for filling; the probability is 0%, the corresponding parameter is 10, and the determined color is green, that is, green is used for filling; parameters 02 to 09 are one of the gradient colors from yellow to green;

[0158] Based on the parameters of the second marking method corresponding to each vacant parking space, the second marking method is used to mark each vacant parking space on the parking lot plan;

[0159] Obtain an association table constructed based on the descriptive information of the destination associated with each entrance and exit of the parking lot (e.g., the name of the business); that is, each business can be moved to through the entrance and exit; the association table is sorted according to the shortest distance to move to each business;

[0160] The association table is placed in the parking lot plan and set beside each corresponding entrance and exit; in addition, the association table can be indicated to each corresponding entrance and exit by an indicator mark;

[0161] Determine the association table corresponding to the second navigation target point and the description information of the destination in the association table, and use the preset first display mode (green highlight, font enlargement, etc.) to display the description information corresponding to the second navigation target point;

[0162] Plan the shortest path from each entrance and exit to the second navigation target point;

[0163] Based on a preset path evaluation library, the shortest paths corresponding to each entrance and exit are scored to obtain a first scoring value corresponding to each entrance and exit;

[0164] Determine the second scoring value corresponding to each vacant parking space based on the probability and a preset probability and second scoring value comparison table;

[0165] Based on the parking lot plan, determine the distance between each vacant parking space and each entrance and exit;

[0166] Based on the preset distance and relationship coefficient comparison table, determine the relationship coefficients corresponding to each vacant parking space and each entrance and exit;

[0167] Based on the relationship coefficient and the first score values ​​corresponding to each entrance and exit; determining the third score value corresponding to each vacant parking space;

[0168] Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table;

[0169] Mark the priority of each free parking space on the parking lot plan;

[0170] Output the parking lot plan after annotation and display processing;

[0171] Receive a user's selection of the location of each vacant parking space in the output parking lot plan;

[0172] The vacant parking space clicked by the user is used as the end point to generate a second navigation route.

[0173] The working principle and beneficial effects of the above technical solution are:

[0174] By marking and displaying the processed parking lot plan, a reference is provided for the user to select the end point of the second navigation route, thereby achieving navigation that meets the user's needs.

[0175] In one embodiment, after the parking lot plan after being marked and displayed is output, the method further includes:

[0176] Receive user's clicks on each descriptive information in each associated table;

[0177] When the selected description information is not the description information corresponding to the second navigation target point, the location point corresponding to the description information is used as a new second navigation target point, and the priority on the parking lot plan is updated again.

[0178] The working principle and beneficial effects of the above technical solution are:

[0179] By marking and displaying the processed parking lot plan, users are provided with opportunities to change the second navigation target point to cope with the situation where the user changes the destination by going to the commercial center. Specifically: In the early stage, when the user is preparing to go to merchant A for dinner, but changes his mind and wants to go to merchant B during the journey, he can click on the description information corresponding to merchant B in the association table of the parking lot plan. In this way, the system automatically updates the marking priority, making it easier for the user to decide on the parking space at the end point of the second navigation route.

[0180] The present invention also provides an automobile intelligent navigation system, such as Figure 2 As shown, including:

[0181] Acquisition module 1, used to obtain description information input by the user;

[0182] The target location determination module 2 is used to parse the description information and determine the target location;

[0183] A judgment module 3 is used to determine whether the target position is a preset trigger position in the trigger position library based on the preset trigger position library;

[0184] A first inquiry output module 4, used for outputting a preset first inquiry information when the target position is a trigger position;

[0185] A first feedback receiving module 5, configured to receive first feedback information corresponding to the first inquiry information input by the user;

[0186] A target point determination module 6, configured to determine a first navigation target point and a second navigation target point based on the target position when the first feedback information is confirmed;

[0187] A first route generating module 7, used for generating a first navigation route based on a first navigation target point;

[0188] A first route output module 8, used for outputting a first navigation route;

[0189] The second route generating module 9 is used to generate and output a second navigation route based on a second navigation target point when the user reaches the end point of the first navigation route.

[0190] In one embodiment, the automobile intelligent navigation system further includes:

[0191] A second inquiry output module, used for outputting a preset second inquiry information when the feedback information is negative and the user reaches the end point of the first navigation route;

[0192] A second feedback information receiving module, used to receive second feedback information corresponding to the second inquiry information input by the user;

[0193] The second route generating module is further used to generate and output a second navigation route based on the second navigation target point when the second feedback information is confirmed.

[0194] In one embodiment, the second route generating module 9 generates and outputs a second navigation route based on the second navigation target point, and performs the following operations:

[0195] Access the management platform of the parking lot associated with the triggering end point;

[0196] Get the parking lot plan sent by the management platform;

[0197] Determine the locations of each entrance and exit connecting the parking lot and the second navigation target point;

[0198] Plan the shortest path from each entrance and exit to the second navigation target point;

[0199] Based on a preset path evaluation library, the shortest paths corresponding to each entrance and exit are scored to obtain a first scoring value corresponding to each entrance and exit;

[0200] Obtain the parking space usage information in the parking lot sent by the management platform;

[0201] Based on the parking space usage, determining at least one vacant parking space;

[0202] Obtain the driving conditions in the parking lot sent by the management platform;

[0203] Based on the traffic situation, determine the probability of each free parking space being used;

[0204] Determine the second scoring value corresponding to each vacant parking space based on the probability and a preset probability and second scoring value comparison table;

[0205] Based on the parking lot plan, determine the distance between each vacant parking space and each entrance and exit;

[0206] Based on the preset distance and relationship coefficient comparison table, determine the relationship coefficients corresponding to each vacant parking space and each entrance and exit;

[0207] Based on the relationship coefficient and the first score values ​​corresponding to each entrance and exit; determining the third score value corresponding to each vacant parking space;

[0208] Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table;

[0209] The vacant parking space with the highest priority is used as the navigation end point and a second navigation route is generated.

[0210] In one embodiment, based on the driving situation, determining the probability of each vacant parking space being used includes:

[0211] Based on the driving situation, determine the driving position of each vehicle in the parking lot;

[0212] Based on the driving position, determine the shortest path from each vehicle to each vacant parking space;

[0213] Inputting the path information of the shortest path from each vehicle to each free parking space into a preset neural network model to determine the probability of each vehicle occupying each free parking space;

[0214] Construct a feature vector based on the probability of each vehicle occupying the vacant parking space;

[0215] Get the preset prediction library;

[0216] The feature vector is matched with each prediction vector in the prediction library; and the probability value associated with the prediction vector matching the feature vector is obtained as the probability of the vacant parking space being used.

[0217] In one embodiment, the second route generating module 9 generates and outputs a second navigation route based on the second navigation target point, and performs the following operations:

[0218] Access the management platform of the parking lot associated with the triggering end point;

[0219] Get the parking lot plan sent by the management platform;

[0220] Obtain the parking space usage information in the parking lot sent by the management platform;

[0221] Based on the parking space usage, determine the vacant parking spaces and the occupied parking spaces;

[0222] On the parking lot plan, the used parking spaces are marked using the preset first marking method;

[0223] Obtain the driving conditions in the parking lot sent by the management platform;

[0224] Based on the traffic situation, determine the probability of each free parking space being used;

[0225] Based on the probability of each vacant parking space being used, querying a preset parameter determination table to determine the parameters of the second marking method corresponding to each vacant parking space;

[0226] Based on the parameters of the second marking method corresponding to each vacant parking space, the second marking method is used to mark each vacant parking space on the parking lot plan;

[0227] Obtaining an association table constructed based on descriptive information of destinations associated with each entrance and exit of the parking lot;

[0228] Place the association table into the parking lot plan and set it next to each corresponding entrance and exit;

[0229] Determine the association table corresponding to the second navigation target point and the description information of the destination in the association table, and use the preset first display mode to display the description information corresponding to the second navigation target point;

[0230] Plan the shortest path from each entrance and exit to the second navigation target point;

[0231] Based on a preset path evaluation library, the shortest paths corresponding to each entrance and exit are scored to obtain a first scoring value corresponding to each entrance and exit;

[0232] Determine the second scoring value corresponding to each vacant parking space based on the probability and a preset probability and second scoring value comparison table;

[0233] Based on the parking lot plan, determine the distance between each vacant parking space and each entrance and exit;

[0234] Based on the preset distance and relationship coefficient comparison table, determine the relationship coefficients corresponding to each vacant parking space and each entrance and exit;

[0235] Based on the relationship coefficient and the first score values ​​corresponding to each entrance and exit; determining the third score value corresponding to each vacant parking space;

[0236] Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table;

[0237] Mark the priority of each free parking space on the parking lot plan;

[0238] Output the parking lot plan after annotation and display processing;

[0239] Receive a user's selection of the location of each vacant parking space in the output parking lot plan;

[0240] The vacant parking space clicked by the user is used as the end point to generate a second navigation route.

[0241] In one embodiment, after the parking lot plan after being marked and displayed is output, the method further includes:

[0242] Receive user's clicks on each descriptive information in each associated table;

[0243] When the selected description information is not the description information corresponding to the second navigation target point, the location point corresponding to the description information is used as a new second navigation target point, and the priority on the parking lot plan is updated again.

[0244] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for intelligent automobile navigation, characterized in that: include: Get the description information entered by the user; Parsing the description information to determine the target location; Based on a preset trigger position library, determining whether the target position is a preset trigger position in the trigger position library; When the target position is the trigger position, outputting a preset first inquiry information; Receiving first feedback information corresponding to the first inquiry information input by a user; When the first feedback information is confirmed, determining a first navigation target point and a second navigation target point based on the target position; Based on the first navigation target point, generating a first navigation route; outputting the first navigation route; When the user reaches the end point of the first navigation route, a second navigation route is generated and output based on the second navigation target point. The generating and outputting a second navigation route based on the second navigation target point includes: Accessing a management platform of a parking lot corresponding to the triggering end point; Obtaining the parking lot plan sent by the management platform; Determine the locations of each entrance and exit connecting the parking lot and the second navigation target point; Planning the shortest path from each of the entrances and exits to the second navigation target point; Based on a preset path evaluation library, the shortest paths corresponding to the respective entrances and exits are scored to obtain first scoring values ​​corresponding to the respective entrances and exits; Obtaining the parking space usage status in the parking lot sent by the management platform; Based on the parking space usage, determining at least one vacant parking space; Obtaining the driving conditions in the parking lot sent by the management platform; Based on the driving situation, determining the probability of each of the vacant parking spaces being used; Determine the second scoring value corresponding to each of the vacant parking spaces based on the probability and a preset probability and second scoring value comparison table; Based on the parking lot plan, determining the distance between each vacant parking space and each of the entrances and exits; Based on a preset distance and relationship coefficient comparison table, determining the relationship coefficients corresponding to each vacant parking space and each of the entrances and exits; Based on the relationship coefficient and the first score value corresponding to each of the entrances and exits; determining a third score value corresponding to each of the vacant parking spaces; Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table; The vacant parking space with the highest priority is used as the navigation destination and the second navigation route is generated. The determining, based on the driving situation, the probability of each of the vacant parking spaces being used includes: Based on the driving situation, determining the driving position of each vehicle in the parking lot; Based on the driving position, determining the shortest path from each vehicle to each of the vacant parking spaces; Inputting the path information of the shortest path from each vehicle to each of the vacant parking spaces into a preset neural network model to determine the probability of each vehicle occupying each of the vacant parking spaces; Constructing a feature vector based on the probability of occupancy of each vehicle in the vacant parking space; Get the preset prediction library; The feature vector is matched with each prediction vector in the prediction library; and a probability value corresponding to the prediction vector matching the feature vector is obtained as the probability that the vacant parking space is used.

2. The intelligent automobile navigation method according to claim 1, characterized in that: Also includes: When the first feedback information is negative, when the user reaches the end point of the first navigation route, outputting a preset second inquiry information; receiving second feedback information input by a user corresponding to the second inquiry information; When the second feedback information is confirmed, a second navigation route is generated and output based on the second navigation target point.

3. The intelligent automobile navigation method according to claim 1, characterized in that: The generating and outputting a second navigation route based on the second navigation target point includes: Accessing a management platform of a parking lot corresponding to the triggering end point; Obtaining the parking lot plan sent by the management platform; Obtaining the parking space usage status in the parking lot sent by the management platform; Based on the parking space usage, determine the vacant parking spaces and the used parking spaces; On the parking lot plan, the used parking spaces are marked using a preset first marking method; Obtaining the driving conditions in the parking lot sent by the management platform; Based on the driving situation, determining the probability of each of the vacant parking spaces being used; Based on the probability of each of the vacant parking spaces being used, querying a preset parameter determination table to determine the parameters of the second marking method corresponding to each of the vacant parking spaces; Based on the parameters of the second marking method corresponding to each vacant parking space, the second marking method is used to mark each of the vacant parking spaces on the parking lot plan; Obtaining an association table constructed based on descriptive information of destinations associated with each entrance and exit of the parking lot; The association table is placed in the parking lot plan and arranged beside each corresponding entrance and exit; Determine an association table corresponding to the second navigation target point and description information of the destination in the association table, and display the description information corresponding to the second navigation target point in a preset first display mode; Planning the shortest path from each of the entrances and exits to the second navigation target point; Based on a preset path evaluation library, the shortest paths corresponding to the respective entrances and exits are scored to obtain first scoring values ​​corresponding to the respective entrances and exits; Determine the second scoring value corresponding to each of the vacant parking spaces based on the probability and a preset probability and second scoring value comparison table; Based on the parking lot plan, determining the distance between each vacant parking space and each of the entrances and exits; Based on a preset distance and relationship coefficient comparison table, determining the relationship coefficients corresponding to each vacant parking space and each of the entrances and exits; Based on the relationship coefficient and the first score value corresponding to each of the entrances and exits; determining a third score value corresponding to each of the vacant parking spaces; Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table; Marking the priority of each vacant parking space into the parking lot plan; Outputting the parking lot plan after being marked and displayed; receiving a user's selection of a position of each vacant parking space in the output parking lot plan; The second navigation route is generated by taking the vacant parking space selected by the user as the end point.

4. The intelligent automobile navigation method according to claim 3, characterized in that: After the parking lot plan after being marked and displayed is output, the method further includes: Receive user's clicks on each descriptive information in each associated table; When the selected description information is not the description information corresponding to the second navigation target point, the location point corresponding to the description information is used as a new second navigation target point, and the priority on the parking lot plan is updated again.

5. An intelligent automobile navigation system, characterized in that: include: An acquisition module is used to obtain the description information input by the user; A target location determination module, used to parse the description information and determine the target location; A judgment module, used for determining whether the target position is a preset trigger position in the trigger position library based on the preset trigger position library; A first inquiry output module, configured to output a preset first inquiry message when the target position is the trigger position; A first feedback receiving module, configured to receive first feedback information input by a user corresponding to the first inquiry information; a target point determination module, configured to determine a first navigation target point and a second navigation target point based on the target position when the first feedback information is determined; A first route generating module, used for generating a first navigation route based on the first navigation target point; A first route output module, used for outputting the first navigation route; A second route generating module is configured to generate and output a second navigation route based on the second navigation target point when the user reaches the end point of the first navigation route. The second route generation module generates and outputs a second navigation route based on the second navigation target point, and performs the following operations: Accessing a management platform of a parking lot corresponding to the triggering end point; Obtaining the parking lot plan sent by the management platform; Determine the locations of each entrance and exit connecting the parking lot and the second navigation target point; Planning the shortest path from each of the entrances and exits to the second navigation target point; Based on a preset path evaluation library, the shortest paths corresponding to the respective entrances and exits are scored to obtain first scoring values ​​corresponding to the respective entrances and exits; Obtaining the parking space usage status in the parking lot sent by the management platform; Based on the parking space usage, determining at least one vacant parking space; Obtaining the driving conditions in the parking lot sent by the management platform; Based on the driving situation, determining the probability of each of the vacant parking spaces being used; Determine the second scoring value corresponding to each of the vacant parking spaces based on the probability and a preset probability and second scoring value comparison table; Based on the parking lot plan, determining the distance between each vacant parking space and each of the entrances and exits; Based on a preset distance and relationship coefficient comparison table, determining the relationship coefficients corresponding to each vacant parking space and each of the entrances and exits; Based on the relationship coefficient and the first scoring value corresponding to each of the entrances and exits; Determine a third scoring value corresponding to each vacant parking space; Determine the priority of each vacant parking space based on the second scoring value, the third scoring value and a preset scoring value and priority comparison table; The vacant parking space with the highest priority is used as the navigation destination and the second navigation route is generated. The determining, based on the driving situation, the probability of each of the vacant parking spaces being used includes: Based on the driving situation, determining the driving position of each vehicle in the parking lot; Based on the driving position, determining the shortest path from each vehicle to each of the vacant parking spaces; Inputting the path information of the shortest path from each vehicle to each of the vacant parking spaces into a preset neural network model to determine the probability of each vehicle occupying each of the vacant parking spaces; Constructing a feature vector based on the probability of occupancy of each vehicle in the vacant parking space; Get the preset prediction library; The feature vector is matched with each prediction vector in the prediction library; and a probability value corresponding to the prediction vector matching the feature vector is obtained as the probability that the vacant parking space is used.

6. The automobile intelligent navigation system as claimed in claim 5, characterized in that: Also includes: A second inquiry output module, configured to output a preset second inquiry information when the first feedback information is negative and the user reaches the end point of the first navigation route; A second feedback information receiving module, used to receive second feedback information input by a user corresponding to the second inquiry information; The second route generating module is further used to generate and output a second navigation route based on the second navigation target point when the second feedback information is confirmed.

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