Vehicle type information processing method, device, electronic device and storage medium

Abstract

The present disclosure provides a vehicle type information processing method, apparatus, electronic device, and storage medium, relating to the technical field of intelligent transportation. The specific implementation solution is as follows: identifying image information containing a target object to obtain a text recognition result contained in the target object; determining vehicle type information associated with a target lane based on the text recognition result, where the target lane is a lane within the area where the target object is located; and updating lane data information based on the vehicle type information associated with the target lane. The technical solution of the embodiments of the present disclosure can ensure the comprehensiveness and accuracy of lane data information and improve the accuracy of subsequent navigation using the lane data information.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent transportation technology. Specifically, it relates to a vehicle type information processing method, apparatus, electronic device, and storage medium. Background Art

[0002] Using a map for navigation has become a common means. However, in the process of map-based navigation, usually only the connection relationship between lanes is combined to obtain candidate navigation routes. In actual use, how to provide more comprehensive lane data information to make the navigation more accurate becomes a problem to be solved. Summary of the Invention

[0003] The present disclosure provides a vehicle type information processing method, apparatus, electronic device, and storage medium.

[0004] According to a first aspect of the present disclosure, there is provided a vehicle type information processing method, including:

[0005] Identifying image information including a target object to obtain a text recognition result included in the target object;

[0006] Based on the text recognition result, determining vehicle type information associated with a target lane; wherein the target lane is a lane within the area where the target object is located;

[0007] Updating lane data information based on the vehicle type information associated with the target lane.

[0008] According to a second aspect of the present disclosure, there is provided a vehicle type information processing apparatus, including:

[0009] An identification module for identifying image information including a target object to obtain a text recognition result included in the target object;

[0010] A vehicle type determination module for determining vehicle type information associated with a target lane based on the text recognition result; wherein the target lane is a lane within the area where the target object is located;

[0011] A data maintenance module for updating lane data information based on the vehicle type information associated with the target lane.

[0012] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0013] At least one processor; and

[0014] A memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the foregoing method.

[0016] According to a fourth aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the foregoing method.

[0017] According to a fifth aspect of the present disclosure, there is provided a computer program product including a computer program which, when executed by a processor, implements the foregoing method.

[0018] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description.

[0019] The solution provided in this embodiment determines the vehicle type information of the target lane based on the text recognition result of the image information, and then updates the lane data information based on the vehicle type information of the target lane. In this way, the comprehensiveness and accuracy of the lane data information can be ensured, and the accuracy of subsequent navigation using the lane data information can be improved. Description of the Drawings

[0020] The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. Among them:

[0021] Figure 1 is a schematic flowchart of a vehicle type information processing method according to an embodiment of the present disclosure;

[0022] Figure 2 is a schematic binding scene diagram of image information including a target object and a road according to an embodiment of the present disclosure;

[0023] Figure 3 is a schematic processing scene diagram of adding vehicle type information according to an embodiment of the present disclosure;

[0024] Figure 4 is an exemplary flowchart of a vehicle type information processing method according to an embodiment of the present disclosure;

[0025] Figure 5 is a schematic processing scene diagram of inputting vehicle type information according to an embodiment of the present disclosure;

[0026] Figure 6 is a schematic composition structure diagram of a vehicle type information processing device according to an embodiment of the present disclosure;

[0027] Figure 7 is another schematic composition structure diagram of a vehicle type information processing device according to an embodiment of the present disclosure;

[0028] Figure 8 It is another schematic structural diagram of a vehicle type information processing device according to an embodiment of the present disclosure;

[0029] Figure 9 It is a block diagram of an electronic device for implementing the embodiments of the present disclosure. Detailed implementation manners

[0030] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, descriptions of well-known functions and structures are omitted in the following description for clarity and conciseness.

[0031] An embodiment of the first aspect of the present disclosure provides a vehicle type information processing method, as Figure 1 shown, including:

[0032] S101: Identify the image information including the target object to obtain the text recognition result included in the target object;

[0033] S102: Based on the text recognition result, determine the vehicle type information associated with the target lane; wherein, the target lane is the lane within the area where the target object is located;

[0034] S103: Update the lane data information based on the vehicle type information associated with the target lane.

[0035] The above vehicle type information processing method can be applied to an electronic device, which can specifically be a server, or the electronic device can also be a terminal device; the terminal device can refer to any one of a laptop computer, a tablet computer, a desktop computer, etc.

[0036] It can be seen that by adopting the above solution, the vehicle type information of the target lane can be determined based on the text recognition result of the image information, and then the lane data information can be updated based on the vehicle type information of the target lane. In this way, the comprehensiveness and accuracy of the lane data information are ensured, and the accuracy of subsequent navigation using the lane data information is improved.

[0037] In one implementation manner, the foregoing identification of the image information including the target object to obtain the text recognition result included in the target object may include: inputting the image information including the target object into a first model to obtain the text recognition result included in the target object recognized by the first model.

[0038] The foregoing first model may be pre-trained and is used to identify the input image information containing the target object to obtain the text recognition result contained in the target object.

[0039] Among them, the target object may refer to a road sign, for example, it may be a sign hanging above or beside a highway. The method of collecting the image information containing the target object may be that the collector uses a camera device to collect it in the area where the target object is located; correspondingly, it can be sent to the electronic device implementing this embodiment by wire or wirelessly. It should be understood that in the foregoing electronic device, while saving the image information containing the target object, relevant information of the image information containing the target object may also be saved, and the relevant information may include at least one of the following: collection location, collection time, and relevant information of the lane associated with the target object.

[0040] The collection location may be represented by longitude and latitude information; the relevant information of the lane associated with the target object may include at least one of the following: the area where the lane associated with the target object is located, and the serial number of the lane associated with the target object. Among them, the area where the lane associated with the target object is located may be represented by the longitude and latitude information of the center point of the area, or may be represented by four sets of longitude and latitude information; if four sets of longitude and latitude are used to represent, the four sets of longitude and latitude information may represent the four corners of a rectangular area, and the rectangular area is the area where the lane associated with the target object is located. The serial number of the lane associated with the target object may be pre-configured; there may be multiple lanes in the map, and corresponding serial numbers may be configured for each lane in the map to distinguish different lanes. In one example, in the electronic device implementing this embodiment, in addition to saving the above-mentioned image information containing the target object and its relevant information, it may also be saved in the Figure 2 visual display manner shown, for example, the target object may be an image of a sign 201 with the content "small vehicle", and the sign 201 may be associated with a road 202, and in Figure 2 the target lane associated with the sign is represented by the binding point 2021 in the road 202; in addition, Figure 2 the collection location 203 of the image of the sign 201 may also be shown in it.

[0041] In one implementation manner, determining the vehicle type information associated with the target lane based on the text recognition result includes:

[0042] When the text recognition result contains passing direction information and category-related information, based on the passing direction information, determine N target lanes within the area where the target object is located; where N is a positive integer;

[0043] Determine M vehicle type information based on the category-related information and the mapping relationship; wherein, the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; M is a positive integer;

[0044] Based on the N target lanes and the M vehicle type information, obtain the M vehicle type information respectively associated with the N target lanes.

[0045] Here, the method for determining whether there is the traffic direction information and the category-related information in the text recognition result may include:

[0046] Input the text recognition result into a second model, and obtain one or more sub-information included in the text recognition result output by the second model and their respective corresponding attributes;

[0047] Judge whether the attributes corresponding to the one or more sub-information include a traffic direction attribute, and if so, use the sub-information corresponding to the traffic direction attribute as the traffic direction information; and judge whether the attributes corresponding to the one or more sub-information include a category attribute, and if so, use the sub-information corresponding to the category attribute as the category-related information.

[0048] The second model can be pre-trained and saved in the aforementioned electronic device. This second model is used to process the input text recognition result to obtain one or more sub-information included in the text recognition result, and the attribute corresponding to each of the one or more sub-information. Among them, among the one or more sub-information, the attribute corresponding to any one sub-information may include one of the following: traffic direction attribute, category attribute.

[0049] The determining of the M vehicle type information based on the category-related information and the mapping relationship may include: comparing the category-related information with the multiple candidate category-related information in the mapping relationship. If there is a matching candidate category-related information, use the one or more candidate vehicle type information corresponding to the matching candidate category-related information as the aforementioned M vehicle type information. Wherein, M is a positive integer, and the specific value of M is related to the number of vehicle type information matched by the category-related information, and it is not limited thereto.

[0050] The mapping relationship may at least include: multiple candidate category-related information and one or more candidate vehicle type information corresponding to each candidate category-related information. Among them, the multiple candidate category-related information may be preset and may include at least one of the following: small vehicle, car, large vehicle, truck, light truck, medium and heavy truck, passenger and cargo combination, etc., and no exhaustive list is made here.

[0051] Each piece of information related to the aforementioned candidate category may correspond to one piece of information about a candidate vehicle type, or multiple pieces of information about candidate vehicle types. For example, if a piece of information related to a candidate category is "passenger car", it may correspond to one piece of information about a candidate vehicle type: "compact car"; for example, if another piece of information related to a candidate category is "small vehicle", it may correspond to multiple pieces of information about candidate vehicle types, namely: "compact car", "mini truck", "light truck"; for example, if yet another piece of information related to a candidate category is "truck", it may correspond to multiple pieces of information about candidate vehicle types, namely: "mini truck", "light truck", "medium truck", "heavy truck"; for example, if still another piece of information related to a candidate category is "passenger and cargo combination", it may correspond to multiple pieces of information about candidate vehicle types, namely: "compact car", "truck"; for example, if still another piece of information related to a candidate category is "medium and heavy truck or medium and heavy taxi", it may correspond to multiple pieces of information about candidate vehicle types, namely: "medium truck", "heavy truck". It should be understood that the above is only an exemplary illustration and not an exhaustive list.

[0052] Obtaining the M pieces of information about vehicle types respectively associated with the N target lanes based on the N target lanes and the M pieces of information about vehicle types may include: associating each of the N target lanes with the M pieces of information about vehicle types to obtain the M pieces of information about vehicle types associated with each of the N target lanes.

[0053] Here, it should be noted that for the convenience of subsequent review visualization, associating each of the N target lanes with the M pieces of information about vehicle types to obtain the M pieces of information about vehicle types associated with each of the N target lanes may be to add the M pieces of information about vehicle types of the N target lanes to the M cells corresponding to each target lane respectively, so as to obtain the M pieces of information about vehicle types associated with each of the N target lanes. Among them, the M cells corresponding to each target lane may refer to a column of M cells corresponding to each target lane, and each cell is used to add a piece of information about a vehicle type. Figure 3 For example, Figure 3 the cells corresponding to 3 parallel lanes included in a region can be displayed simultaneously. Assuming N is equal to 1, the cell 301 corresponding to 1 target lane can be one of the cells corresponding to the 3 lanes; in the case where the 1 target lane corresponds to a single piece of information about a vehicle type, add this piece of information about the vehicle type to the cell 301, as Figure 3 shown in adding the single piece of information about the vehicle type "compact car" to the cell 301. In addition, although Figure 3 is not shown, 1 target lane can also be associated with multiple pieces of information about vehicle types. In this case, the multiple pieces of information about vehicle types corresponding to the 1 target lane can be added to the cell 301 and the multiple cells below it in sequence. That is to say, a column of cells corresponds to 1 target lane, and each cell in a column of cells corresponds to a piece of information about a vehicle type associated with the 1 target lane.

[0054] It can be seen that by adopting the above solution, the target lane selected this time and one or more vehicle type information associated with the target lane can be determined respectively according to the specific information included in the text recognition result. In this way, based on the text recognition result of the image information, the vehicle type information associated with the lane can be determined efficiently and accurately.

[0055] In one implementation manner, determining N target lanes within the area where the target object is located based on the traffic direction information may include: determining a starting target lane and an ending target lane from multiple candidate lanes within the area where the target object is located based on the traffic direction information; and determining the N target lanes based on the starting target lane and the ending target lane.

[0056] Specifically, determining a starting target lane and an ending target lane from multiple candidate lanes within the area where the target object is located based on the lane position direction information may include: obtaining the number of multiple candidate lanes included in the area where the target object is located; determining the starting target lane based on the number of the multiple candidate lanes and the traffic direction information, and determining the ending target lane from the multiple candidate lanes based on the traffic direction information.

[0057] The foregoing determining the starting target lane based on the number of the multiple candidate lanes and the traffic direction information may be: when the number of the multiple candidate lanes is odd, representing the number of the multiple candidate lanes as j (j is a natural number greater than 0), calculating a first value by ((j + 1) / 2)+1; determining the first value number of lanes starting from the opposite direction of the traffic direction information as the starting target lane based on the first value and the traffic direction information. Correspondingly, determining the ending target lane from the multiple candidate lanes based on the traffic direction information may be: determining the first lane in the direction included in the traffic direction information from the multiple candidate lanes as the ending target lane. For example, assuming the number of multiple candidate lanes is j (j is a natural number greater than 0), in the case where j is odd, the ((j + 1) / 2)+1-th lane from the left is the starting target lane, and the j-th lane is the ending target lane.

[0058] The determination of the starting target lane based on the number of the multiple candidate lanes and the traffic direction information may be: when the number of the multiple candidate lanes is an even number, representing the number of the multiple candidate lanes as j (j is a natural number greater than 0), using (j / 2) + 1 to calculate a second value; based on this second value and the traffic direction information, determining the second value-th lane from the opposite direction of the traffic direction information as the starting target lane. Correspondingly, the determination of the ending target lane from the multiple candidate lanes based on the traffic direction information may be: determining the first lane in the direction included in the traffic direction information from the multiple candidate lanes as the ending target lane. For example, assuming the number of the multiple candidate lanes is j (j is a natural number greater than 0), when j is an even number, the (j / 2 + 1)-th lane from the left is the starting target lane, and the j-th lane is the ending target lane.

[0059] The determination of the N target lanes based on the starting target lane and the ending target lane may be: determining whether there is an intermediate lane between the starting target lane and the ending target lane, if so, taking the starting target lane, the ending target lane, and the intermediate lane as the N target lanes; if not, taking the starting target lane and the ending target lane as the N target lanes.

[0060] It can be seen that by adopting the above solution, the target lanes can be directly determined based on the traffic direction information and the number of candidate lanes. In this way, it is ensured that the target lanes are selected more efficiently and accurately, and further, the efficiency and accuracy of setting vehicle type information are ensured.

[0061] In an implementation manner, the determination of the vehicle type information associated with the target lane based on the text recognition result includes: when the text recognition result only includes category-related information, determining the target lane based on the target object; determining the K vehicle type information associated with the target lane based on the category-related information and the mapping relationship; where the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; K is a positive integer.

[0062] The determination of the target lane based on the target object may refer to: using the lane associated with the target object as the target lane. As described in the foregoing embodiments, while saving the image information including the target object, relevant information of the image information including the target object may also be saved, and the relevant information may include the relevant information of the lane associated with the target object. Among them, the relevant information of the lane associated with the target object may be the serial number of the lane. When using the image information including the target object, the relevant information of the lane associated with the target object can be directly obtained, and then the lane directly associated with the target object can be determined. In this embodiment, since the text recognition result only includes category-related information and does not include traffic direction information, the lane associated with the target object can be directly used as the target lane. It should be understood that the number of target lanes here can be 1.

[0063] The description of the mapping relationship is the same as that in the foregoing embodiments and will not be repeated.

[0064] The foregoing determination of the K vehicle type information associated with the target lane based on the category-related information and the mapping relationship may include: determining the K vehicle type information based on the category-related information and the mapping relationship; associating the K vehicle type information with the target lane to obtain the K vehicle type information associated with the target lane. For example, assume that the category-related information can be a small car, and based on the mapping relationship, 1 vehicle type information, i.e., a car, can be obtained. Assume that the category-related information can be a micro-light truck, and based on the mapping relationship, 2 vehicle type information, i.e., a micro truck and a light truck, can be obtained. There is no need to list them all here. That is to say, by adopting the above solution, the single vehicle type information (i.e., only including one vehicle type information) or the combined vehicle type information (i.e., including the foregoing multiple vehicle type information) associated with a target lane can be input at one time. It should be understood that for the convenience of subsequent review visualization, the foregoing associating the K vehicle type information with the target lane to obtain the K vehicle type information associated with the target lane may be to add the K vehicle type information of the target lane to the corresponding K cells of the target lane respectively to obtain the K vehicle type information associated with the target lane.

[0065] It should be noted that there may also be a situation where the category-related information is directly vehicle type information. In this case, it may include: determining whether the candidate category-related information matching the category-related information is included in the mapping relationship. If not, taking the category-related information as the vehicle type information and associating the vehicle type information with the target lane to obtain one vehicle type information associated with the target lane. For example, at this time, the category-related information is any one of the following: car, bus, micro truck, light truck, medium truck, heavy truck. None of the above category-related information has a matching candidate category-related information in the foregoing mapping relationship. Therefore, any one of the foregoing category-related information can be directly used as a vehicle type information that can be directly associated with the lane.

[0066] It can be seen that by adopting the above solution, in the case where the text recognition result only includes category-related information, the corresponding vehicle type information can be determined based on the mapping relationship, and then bound to the target lane associated with the target object to obtain the vehicle type information associated with the target lane. In this way, it can ensure accurate and efficient determination of the vehicle type information of the target lane.

[0067] In one implementation, it may further include: when the time information is included in the text recognition result, determining the restricted passage time associated with the vehicle type information of the target lane based on the time information; updating the lane data information based on the restricted passage time associated with the vehicle type information of the target lane.

[0068] Here, the method for determining whether the time information is included in the text recognition result may include: inputting the text recognition result into a second model to obtain one or more sub-information included in the text recognition result output by the second model and their respective corresponding attributes; determining whether the time attribute is included in the attributes corresponding to the one or more sub-information respectively. If so, taking the sub-information corresponding to the time attribute as the time information.

[0069] Among them, the second model can be pre-trained and saved in the foregoing electronic device. The second model is used to process the input text recognition result to obtain one or more sub-information included in the text recognition result and the attribute corresponding to each sub-information among the one or more sub-information. The attribute corresponding to each sub-information may further include one of the following: time attribute.

[0070] Among them, the time information may include: a start time and an end time. Determining the restricted passage time associated with the vehicle type information of the target lane based on the time information may include: using the start time included in the time information as the restricted start time; and using the end time included in the time information as the restricted end time; based on the restricted start time and the restricted end time, as the restricted passage time associated with the vehicle type information of the target lane. In addition, the aforementioned time information may include: the date types applicable to the start time and the end time. For example, it may be applicable on weekdays, weekends, holidays, except holidays, etc., or it may also be applicable on Monday, Tuesday, etc. Correspondingly, the restricted passage time associated with the vehicle type information of the target lane may, in addition to including the restricted start time and the restricted end time, also include the applicable date type, which will not be elaborated here. For example, also to ensure the visualization of subsequent reviews, the cell corresponding to the target lane may further have a time-associated display interface, and the restricted passage time associated with the vehicle type information of the target lane may be displayed in the time-associated display interface. In another example, operations such as modifying, adding, and deleting the restricted passage time of a lane corresponding to a certain cell on the time-associated display interface may also be performed.

[0071] It can be seen that by adopting the above solution, on the basis of determining the vehicle type information associated with the target lane, the restricted passage time associated with the vehicle type information can be further determined. In this way, more accurate restricted information can be associated with the vehicle type information, ensuring the accuracy of subsequent navigation processing.

[0072] In one implementation manner, updating the lane data information based on the vehicle type information associated with the target lane may include: adding the vehicle type information associated with the target lane to the lane data information to obtain updated lane data information. Updating the lane data information based on the restricted passage time associated with the vehicle type information of the target lane may include: adding the restricted passage time associated with the vehicle type information of the target lane to the lane data information to obtain updated lane data information.

[0073] The lane data information can be stored in a database, and other information can also be stored in the database, which will not be exhausted in this embodiment; each piece of information stored in the database can be called by a map application for the map application to perform navigation.

[0074] Exemplarily, the information associated with the target lane saved in the lane data information may include the following: the relevant information of the target object, the vehicle type information associated with the target lane, the restricted passage time associated with the vehicle type information of the target lane, etc., which will not be elaborated here. It should be understood that since the target lane is a lane on the road, the above is only an exemplary description for one lane. In the lane data information, the information associated with each lane can be saved, but will not be elaborated one by one.

[0075] Among them, the relevant information of the target object may include the number of the target object. It should be noted that when saving the vehicle type information associated with the foregoing target lane, it can be represented by the identifier corresponding to the vehicle type information. For example, if the vehicle type information is a car, its corresponding identifier is 1; another example is that if the vehicle type information is a light truck, its corresponding identifier is 512, etc., which will not be elaborated here. The vehicle type information of the foregoing lane and the restricted passage time associated with the vehicle type information of the lane can be represented in the form of "lane number | vehicle type information | restricted passage time" when saved. For example, "1|1|[(h17)(h19)]" means that the lane number is 1, the vehicle type information is 1, that is, a car, and the restricted passage time of this vehicle type information is from 17:00 to 19:00.

[0076] Combined with Figure 4 An exemplary description of the solution provided in the foregoing embodiment may include:

[0077] S401: Identify the image information containing the target object to obtain the character recognition result contained in the target object;

[0078] S402: Based on the character recognition result, determine the vehicle type information associated with the target lane;

[0079] S403: Determine whether the character recognition result contains time information. If it contains, execute S404; otherwise, execute S405;

[0080] S404: Based on the time information, determine the restricted passage time associated with the vehicle type information of the target lane;

[0081] S405: Update the lane data information. Here, if S404 is not executed before executing S405, then the update of the lane data information may refer to updating the lane data information based on the vehicle type information associated with the target lane. If S404 is executed before executing S405, then the update of the lane data information may refer to updating the lane data information based on the vehicle type information associated with the target lane and the restricted passage time associated with the vehicle type information of the target lane.

[0082] It should be noted that multiple lanes can be included in the entire map, and multiple lanes can be connected to form a road. On the basis of determining the vehicle type information associated with the foregoing target lane, it is also possible to determine the vehicle type information associated with each lane in each road and its restricted passage time. In some possible implementation manners, it may further include: determining the road where the target lane is located; detecting whether there is image information including the next target object in the first direction of the road where the target lane is located; if so, setting the vehicle type information of all lanes between the target lane and the lane associated with the next target object (excluding the lane associated with the next target object) to be the same as the vehicle type information associated with the target lane; updating the lane data information based on the vehicle type information associated with all lanes between the target lane and the lane associated with the next target object (excluding the lane associated with the next target object). The foregoing first direction can be set according to the actual situation. In a preferred example, it can be the vehicle driving direction.

[0083] In some embodiments, on the basis of determining the restricted passage time associated with the vehicle type information associated with the foregoing target lane, it is also possible to determine the restricted passage time of the vehicle type information associated with each lane in each road. Specifically, it may include: if the vehicle type information of the target lane is associated with the restricted passage time, then setting the restricted passage time associated with the vehicle type information of all lanes between the target lane and the lane associated with the next target object (excluding the lane associated with the next target object) to be the same as the restricted passage time of the vehicle type information of the target lane; updating the lane data information based on the restricted passage time of the vehicle type information associated with all lanes between the target lane and the lane associated with the next target object (excluding the lane associated with the next target object).

[0084] Since on a road, there are not target objects (i.e., road signs) at all positions, therefore, the foregoing embodiments can determine the vehicle type information associated with the target lane within the area where the target object is located, and further, the vehicle type information can be set for other lanes before the next target object. Thus, it is possible to ensure that the vehicle type information is set for each lane in each road, ensuring the accuracy of subsequent navigation.

[0085] After completing the foregoing processing, the management personnel can also check whether the updated lane data information is correct. For example, it can be combined with the image information of the object associated with any lane to be checked. If it is found that there is an error in the vehicle type information associated with the lane to be checked, then editing processing such as adding, modifying, or deleting the vehicle type information associated with the lane to be checked saved in the lane data information can be performed.

[0086] In one example, the inspection lane to be checked within the area associated with the image information of the currently selected object is shown. If the number of cells corresponding to the inspection lane to be checked is 0, one or a combination of vehicle types can be clicked, and then a new column of cells will be automatically added to add the information of a single vehicle type or a combination of vehicle types associated with the inspection lane to be checked.

[0087] In one example, the inspection lane to be checked within the area associated with the image information of the currently selected object is shown. When there are cells corresponding to the inspection lane to be checked and the content they contain, if you want to modify the content (i.e., vehicle type information) contained in the cell, you can select the cell corresponding to the inspection lane to be checked and then choose one of the single vehicle type input methods or the combined vehicle type input methods; if you choose the single vehicle type input, each single vehicle type can be shown, and by selecting one of them, the selected single vehicle type can be used to replace the existing vehicle type information and saved in the cell; if you choose the combined vehicle type input, each combined vehicle type can be shown, and by selecting one of them, each vehicle type information contained in the selected combined vehicle type can be used to replace the existing vehicle type information and saved in multiple cells corresponding to the inspection lane to be checked in turn.

[0088] Combined with Figure 5 For example, assume that the management personnel choose the single vehicle type input method, then the content of part 501 can be shown, which can include multiple single vehicle types, namely cars, buses, mini trucks, light trucks, medium trucks, and heavy trucks. Assume that the management personnel choose the combined vehicle type input method, then the content of part 502 can be shown, which can include multiple combined vehicle types, namely trucks, passenger-cargo combinations, trucks on the right, light trucks, medium-heavy trucks, and large vehicles on the right; and at least part of the specific vehicle type content associated with the combined vehicle types can also be shown, such as "truck = mini + light + medium + heavy", "passenger-cargo combination = car + truck", "mini truck = mini + light", and "medium-heavy truck / large vehicle = medium + heavy".

[0089] In another example, if there is image information containing an object in a lane to be inspected, but the corresponding vehicle type information is not included in the cell corresponding to the lane to be inspected, the management personnel can search for the text description on the sign, that is, enter keywords in the input interface. Based on the keywords and the foregoing mapping relationship, one or more corresponding vehicle type information can be obtained, and the one or more vehicle type information can be directly used as the one or more vehicle type information associated with the lane to be inspected and added to the one or more cells corresponding to the lane to be inspected. For example, if the text description has a one-to-one relationship with the vehicle type of the corresponding lane, then enter one-to-one; if the text description has a one-to-many relationship with the vehicle type of the corresponding lane, then enter one-to-many. If the number of rows is insufficient, new entries are added. For example, when searching for "car lane", "car" is displayed. Click on the cell and then click on this piece of information, then "car" can be entered into the corresponding cell. Another example is when searching for "small vehicle lane", "car + micro truck + light truck" is displayed, then "car", "micro truck", and "light truck" can be entered into this cell and the two corresponding cells below it.

[0090] In one implementation, it may further include: in response to receiving a navigation request, determining the vehicle type information to be queried and the query range information based on the navigation request; based on the query range information, determining one or more lanes to be fed back from the lane data information, and determining one or more passable lanes that match the vehicle type information to be queried from the one or more lanes to be fed back; generating one or more candidate navigation routes based on the one or more passable lanes, and feeding back the one or more candidate navigation routes.

[0091] Based on the foregoing embodiments, lane data information can be obtained and stored in an electronic device.

[0092] The foregoing navigation request may be sent by a first device, and the first device may be a terminal device used by a user, such as a smart phone, a tablet computer, etc., and no exhaustive list is made here. More specifically, the navigation request may be generated by the map application of the first device; for example, the user uses the map application of the first device, enters the vehicle type of the vehicle he uses in the map application, and enters the destination. Based on the destination, the current location, and the vehicle type of the vehicle he uses, the foregoing navigation request can be generated; then the first device sends the navigation request to the foregoing electronic device.

[0093] Determining the vehicle type information to be queried and the query range information based on the navigation request may include: extracting the vehicle type of the vehicle used by the user from the navigation request, and using the vehicle type of the vehicle used by the user as the vehicle type information to be queried; and extracting the destination and the current location from the navigation request, and determining the query range information based on the destination and the current location. Among them, determining the query range information based on the destination and the current location may include: using all the roads that can be connected between the destination and the current location as the query range information.

[0094] Determining one or more lanes to be fed back from the lane data information based on the query range information may include: determining one or more lanes to be fed back included in all the roads that can be connected based on the query range information from the lane data information.

[0095] Determining one or more passable lanes that match the vehicle type information to be queried from the one or more lanes to be fed back may include: determining one or more passable lanes that match the vehicle type information to be queried based on the lane information respectively associated with the one or more lanes to be fed back.

[0096] Generating one or more candidate navigation routes based on the one or more passable lanes and feeding back the one or more candidate navigation routes may be: obtaining one or more candidate navigation routes based on the connection relationship between the one or more passable lanes, and feeding back the one or more candidate navigation routes to the first device. Correspondingly, after receiving the feedback information, the first device may select a target navigation route from the one or more navigation routes.

[0097] It can be seen that by adopting the above solution, when receiving a navigation request, the vehicle type to be queried and the passable lanes within the query range can be obtained and candidate navigation routes can be sent. In this way, more accurate navigation routes combined with vehicle type information can be provided, avoiding violations and thus improving the user experience.

[0098] The second aspect of the embodiments of the present disclosure also provides a vehicle type information processing device, as Figure 6 shown, including:

[0099] An identification module 601, configured to identify the image information including the target object to obtain the text recognition result included in the target object;

[0100] A vehicle type determination module 602, configured to determine the vehicle type information associated with the target lane based on the text recognition result; wherein, the target lane is the lane within the area where the target object is located;

[0101] A data maintenance module 603, configured to update lane data information based on the vehicle type information associated with the target lane.

[0102] The vehicle type determination module 602 is configured to, when the text recognition result includes traffic direction information and category-related information, based on the traffic direction information, determine N target lanes within the area where the target object is located; where N is a positive integer; based on the category-related information and the mapping relationship, determine M vehicle type information; where the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; M is a positive integer; based on the N target lanes and the M vehicle type information, obtain the M vehicle type information respectively associated with the N target lanes.

[0103] The vehicle type determination module 602 is configured to, based on the traffic direction information, determine a starting target lane and an ending target lane from multiple candidate lanes in the area where the target object is located; based on the starting target lane and the ending target lane, determine the N target lanes.

[0104] The vehicle type determination module 602 is configured to, when the text recognition result only includes category-related information, determine the target lane based on the target object; based on the category-related information and the mapping relationship, determine K vehicle type information associated with the target lane; where the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; K is a positive integer.

[0105] Based on Figure 6 , as Figure 7 shown, the apparatus further includes:

[0106] A time determination module 604, configured to, when the text recognition result includes time information, based on the time information, determine a restricted passing time associated with the vehicle type information of the target lane;

[0107] The data maintenance module 603 is configured to update lane data information based on the restricted passing time associated with the vehicle type information of the target lane.

[0108] Based on Figure 7 , as Figure 8 shown, the apparatus further includes:

[0109] The navigation module 605 is configured to, in response to receiving a navigation request, determine the vehicle type information to be queried and the query range information based on the navigation request; based on the query range information, determine one or more lanes to be fed back from the lane data information of the data maintenance module, and determine one or more passable lanes that match the vehicle type information to be queried from the one or more lanes to be fed back; generate one or more candidate navigation routes based on the one or more passable lanes, and feed back the one or more candidate navigation routes.

[0110] In the technical solution of the present disclosure, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0111] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0112] Figure 9 FIG. shows a schematic block diagram of an exemplary electronic device 900 that can be used to implement the embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0113] As Figure 9 shown, the electronic device 900 includes a computing unit 901, which can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 902 or the computer program loaded from the storage unit 908 into the random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the electronic device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. The input / output (I / O) interface 905 is also connected to the bus 904.

[0114] Multiple components in the electronic device 900 are connected to the I / O interface 905, including: an input unit 906, such as a keyboard, a mouse, etc.; an output unit 907, such as various types of displays, speakers, etc.; a storage unit 908, such as a disk, an optical disc, etc.; and a communication unit 909, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 909 allows the electronic device 900 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0115] The computing unit 901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 executes the vehicle type information processing method described above. For example, in some embodiments, the vehicle type information processing method described above can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 900 via the ROM 902 and / or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of the vehicle type information processing method described above can be executed. Alternatively, in other embodiments, the computing unit 901 can be configured to execute the vehicle type information processing method described above in any other suitable manner (e.g., by means of firmware).

[0116] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs, the one or more computer programs can be executed and / or interpreted on a programmable system including at least one programmable processor, the programmable processor can be a special or general-purpose programmable processor, can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0118] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0120] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0121] A computer system can include a client and a server. The client and the server are generally far from each other and typically interact through a communication network. The client - server relationship is generated by computer programs running on the respective computers and having a client - server relationship with each other. The server can be a cloud server, can also be a server of a distributed system, or a server incorporating a blockchain.

[0122] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this is not limited herein.

[0123] The above - described specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub - combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. A vehicle type information processing method, comprising: Identifying image information containing a target object to obtain a text recognition result contained in the target object; Determining vehicle type information associated with a target lane based on the text recognition result; wherein, the target lane is a lane within the area where the target object is located; Updating lane data information based on the vehicle type information associated with the target lane; Wherein, the determining method of the target lane includes one of the following: when the text recognition result contains traffic direction information and category-related information, based on the traffic direction information, from multiple candidate lanes within the area where the target object is located, determining a starting target lane and an ending target lane, and based on the starting target lane and the ending target lane, determining N target lanes, where N is a positive integer, and the traffic direction information is contained in the text recognition result; when the text recognition result only contains category-related information, determining the target lane based on the target object; Wherein, the determining the starting target lane from multiple candidate lanes within the area where the target object is located based on the traffic direction information includes one of the following: when the number of the multiple candidate lanes is odd, determining the first numerical lanes starting from the opposite direction of the traffic direction information as the starting target lane, where the opposite direction of the traffic direction information is left; when the number of the multiple candidate lanes is even, determining the second numerical lanes starting from the opposite direction of the traffic direction information as the starting target lane; Wherein, the determining the ending target lane from multiple candidate lanes within the area where the target object is located based on the traffic direction information includes: determining the first lane in the direction contained in the traffic direction information from the multiple candidate lanes as the ending target lane.

2. The method according to claim 1, wherein The determining vehicle type information associated with a target lane based on the text recognition result includes: When the text recognition result contains traffic direction information and category-related information, determining M vehicle type information based on the category-related information and a mapping relationship; wherein, the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; M is a positive integer; Obtaining the M vehicle type information respectively associated with the N target lanes based on the N target lanes and the M vehicle type information.

3. The method according to claim 1, wherein The determining vehicle type information associated with a target lane based on the text recognition result includes: When the text recognition result only contains category-related information, determining K vehicle type information associated with the target lane based on the category-related information and a mapping relationship; wherein, the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; K is a positive integer.

4. The method according to claim 1, further comprising: When the text recognition result contains time information, determining a restricted passage time associated with the vehicle type information of the target lane based on the time information; Update the lane data information based on the restricted passage time associated with the vehicle type information of the target lane.

5. The method according to any one of claims 1-4, further comprising: In response to receiving a navigation request, determine the vehicle type information to be queried and the query range information based on the navigation request; Based on the query range information, determine one or more lanes to be feedback from the lane data information, and determine one or more passable lanes matching the vehicle type information to be queried from the one or more lanes to be feedback; Generate one or more candidate navigation routes based on the one or more passable lanes, and feedback the one or more candidate navigation routes.

6. A vehicle type information processing device, comprising: An identification module, configured to identify image information including a target object to obtain a text recognition result included in the target object; A vehicle type determination module, configured to determine vehicle type information associated with a target lane based on the text recognition result; wherein the target lane is a lane within the area where the target object is located; A data maintenance module, configured to update lane data information based on the vehicle type information associated with the target lane; The vehicle type determination module is configured to perform one of the following: when the text recognition result includes passage direction information and category-related information, based on the passage direction information, determine a starting target lane and an ending target lane from multiple candidate lanes within the area where the target object is located, and determine N target lanes based on the starting target lane and the ending target lane, where N is a positive integer, and the passage direction information is included in the text recognition result; when the text recognition result only includes category-related information, determine the target lane based on the target object; The vehicle type determination module is configured to perform one of the following: when the number of the multiple candidate lanes is odd, determine the first numerical number of lanes starting from the reverse direction of the passage direction information as the starting target lane, where the reverse direction of the passage direction information is left; when the number of the multiple candidate lanes is even, determine the second numerical number of lanes starting from the reverse direction of the passage direction information as the starting target lane; The vehicle type determination module is configured to determine the first lane in the direction included in the passage direction information from the multiple candidate lanes as the ending target lane.

7. The device according to claim 6, wherein, The vehicle type determination module is configured to, when the text recognition result includes passage direction information and category-related information, determine M vehicle type information based on the category-related information and the mapping relationship; wherein the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; M is a positive integer; and obtain the M vehicle type information respectively associated with the N target lanes based on the N target lanes and the M vehicle type information.

8. The device according to claim 6, wherein, The vehicle type determination module is configured to determine K vehicle type information associated with the target lane based on the category-related information and the mapping relationship when the text recognition result only includes category-related information; wherein, the mapping relationship includes: multiple candidate category-related information and one or more candidate vehicle type information respectively corresponding thereto; K is a positive integer.

9. The apparatus according to claim 6, further comprising: A time determination module, configured to determine a restricted passage time associated with the vehicle type information of the target lane based on the time information when the text recognition result includes time information. The data maintenance module is configured to update the lane data information based on the restricted passage time associated with the vehicle type information of the target lane.

10. The apparatus according to any one of claims 6-9, further comprising: A navigation module, configured to, in response to receiving a navigation request, determine the vehicle type information to be queried and the query range information based on the navigation request. Based on the query range information, determine one or more lanes to be fed back from the lane data information of the data maintenance module, and determine one or more passable lanes that match the vehicle type information to be queried from the one or more lanes to be fed back; generate one or more candidate navigation routes based on the one or more passable lanes, and feed back the one or more candidate navigation routes.

11. An electronic device, comprising: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-5.

12. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.

13. A computer program product, comprising a computer program, wherein the computer program implements the method according to any one of claims 1-5 when executed by a processor.

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