Travel route recommendation method and device, electronic equipment and readable storage medium

Abstract

The embodiment of the invention provides a travel route recommendation method and device, electronic equipment and a readable storage medium, and is applied to a server, and the method comprises the following steps: obtaining a starting position and a destination position of a vehicle; acquiring a plurality of travel routes according to the initial position and the destination position; obtaining vehicle state information and / or user information of the vehicle; according to the vehicle state information and / or the user information, determining a first road section in each travel route in the plurality of travel routes, wherein the first road section is a dangerous road section in road sections corresponding to each travel route; determining the risk degree of each travel route according to the first road section in each travel route; and recommending a final travel route to the user according to the risk degree. Therefore, the road danger is pre-judged and prompted in advance, a guarantee can be provided for the user to smoothly arrive at the destination, casualties are reduced, and the travel efficiency of the user can be improved.

Description

Technical Field

[0001] The present application relates to the field of navigation, and specifically to a travel route recommendation method and device, an electronic device, and a readable storage medium. Background Art

[0002] When planning travel routes for users, current navigation systems recommend routes to users based on the distance between the starting point and the destination or the estimated time it takes for the user to travel from the starting point to the destination. As for road hazards, users are not reminded until they are near the danger, or they are not reminded at all, requiring the user to actively discover the danger. Since such a recommendation method does not take into account the objective conditions of the vehicle driven by the user and the restrictions of certain roads, users do not receive road hazard warnings before traveling, and only discover the danger when the vehicle reaches a specific section of the road. This not only wastes a lot of users' time and energy, but may even put users in danger. Summary of the invention

[0003] The present application provides a travel route recommendation method and device, an electronic device, and a readable storage medium, in order to improve the travel efficiency of users and ensure the travel safety of users.

[0004] In a first aspect, an embodiment of the present application provides a travel route recommendation method, which is applied to a server, and the method comprises the following steps:

[0005] Get the starting position and destination position of the vehicle;

[0006] Acquire multiple travel routes according to the starting location and the destination location;

[0007] Acquiring vehicle status information and / or user information of the vehicle;

[0008] Determining a first road section in each of the multiple travel routes according to the vehicle state information and / or the user information, wherein the first road section is a dangerous road section in the road sections corresponding to each of the travel routes;

[0009] Determining the danger level of each travel route according to the first section of each travel route;

[0010] A final travel route is recommended to the user according to the risk level.

[0011] In a second aspect, an embodiment of the present application provides a travel route recommendation device, which is applied to a server, and the device includes:

[0012] A first acquisition unit, used to acquire a starting position and a destination position of the vehicle;

[0013] a second acquisition unit, the second acquisition unit being in communication with the first acquisition unit and configured to acquire a plurality of travel routes according to the starting position and the destination position;

[0014] A third acquisition unit, used to acquire vehicle status information and / or user information of the vehicle;

[0015] a first determining unit, the first determining unit being in communication connection with the second obtaining unit and the third obtaining unit respectively, and being configured to determine a first road section in each of the plurality of travel routes according to the vehicle state information and / or the user information, wherein the first road section is a dangerous road section in the road sections corresponding to each of the travel routes;

[0016] a second determining unit, the second determining unit being in communication connection with the first determining unit and configured to determine the danger level of each travel route according to the first road section in each travel route;

[0017] A recommendation unit, the recommendation unit is in communication with the second determination unit, and is used to recommend a final travel route to the user according to the risk level.

[0018] In a third aspect, the present application provides an electronic device, characterized in that it includes a processor, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps of any method described in the first aspect or the second aspect above.

[0019] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in any method of the first aspect or the second aspect of the embodiment of the present application.

[0020] It can be seen that in the embodiment of the present application, the server first obtains the starting position and the destination position of the vehicle, then obtains multiple travel routes based on the starting position and the destination position, and then obtains the vehicle status information and / or user information of the vehicle. Then, the first section of each of the multiple travel routes is determined based on the vehicle status information and / or user information, and then the danger level of each travel route is determined based on the first section of each travel route, and finally the final travel route is recommended to the user based on the danger level. Predicting and prompting road hazards in advance can not only provide guarantees for users to reach their destinations smoothly and reduce casualties, but also improve user travel efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1a is a schematic diagram of a travel route recommendation system provided in an embodiment of the present application;

[0023] Figure 1b It is a structural schematic diagram of an electronic device provided in an embodiment of the present application;

[0024] Figure 2a It is a flowchart of a travel route recommendation method provided in an embodiment of the present application;

[0025] Figure 2b This is a schematic diagram of a travel route recommendation interface provided in an embodiment of the present application;

[0026] Figure 3 is a structural schematic diagram of a travel route recommendation device provided in an embodiment of the present application;

[0027] Figure 4 It is a structural schematic diagram of another travel route recommendation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0030] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] In order to better understand the technical solutions of the embodiments of the present application, the electronic devices and travel route recommendation systems that may be involved in the embodiments of the present application are first introduced below.

[0032] See also Figure 1a , Figure 1a : is a schematic diagram of a travel route recommendation system provided in an embodiment of the present application, the travel route recommendation system 100 includes a server 101 and an electronic device 102, and the server is communicatively connected to the electronic device 102. The electronic device 102 is used to send the starting position, the destination position, the vehicle information and the user information to the server 101, and the server 101 is used to determine a plurality of travel routes after obtaining the information from the electronic device 102, and then perform a risk analysis on the plurality of travel routes, and then recommend the final travel route to the user according to the risk. Among them, when recommending a route to the user, the recommendation results of each travel route can be sent to the electronic device through the server, and can also be sent to other electronic devices specified by the user. The electronic device 101 can include a mobile electronic device, such as a mobile phone, a computer, etc., and the electronic device 101 can also include a vehicle-mounted device located in the vehicle.

[0033] Specifically, Figure 1a The specific structure of the electronic device can be found in Figure 1b , Figure 1b 1 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. As shown in the figure, the electronic device 110 can implement the steps in the message push method, and the electronic device 110 includes a processor 120, a memory 130, a communication interface 140, and one or more programs 131, wherein the one or more programs 131 are stored in the above-mentioned memory 130 and are configured to be executed by the above-mentioned processor 120, and the one or more programs 131 include instructions for executing any step in the following method embodiment.

[0034] The communication interface 140 is used to support the communication between the electronic device 110 and other devices. The memory 130 included in the electronic device 110 is used to store program codes and data of the electronic device.

[0035] Among them, the processor 120 can be a central processing unit (CPU), a general processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, units and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements a computing function, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The communication unit can be a communication interface 140, a transceiver, a transceiver circuit, etc., and the storage unit can be a memory 130.

[0036] The memory 130 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Among them, the nonvolatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0037] In a specific implementation, the processor 120 is used to execute any step performed by the electronic device in the following method embodiment, and when performing data transmission such as sending, the communication interface 140 can be selectively called to complete the corresponding operation.

[0038] At present, when applications recommend travel routes to users, they are basically based on the estimated travel time or travel distance from the starting point to the destination. They are unable to inform users of the dangers in the travel process before the user travels. As a result, users may suddenly find that the route is not suitable for the current vehicle halfway through the trip, and can only turn around or re-plan the travel route. For example, when a user drives on the road and finds a bridge ahead, the bridge only allows vehicles under 2 tons to pass, and the user's current vehicle weight is 3 tons, the user will have no way to go. This will not only waste a lot of users' time and energy, but may even put users in danger.

[0039] Combined with the above description, the following will introduce the execution steps of the travel route recommendation method from the perspective of a method example. Figure 2a , Figure 2a : is a flow chart of a travel route recommendation method provided in an embodiment of the present application. As shown in the figure, the travel route recommendation method includes the following steps:

[0040] S201, obtaining the starting position and destination position of the vehicle.

[0041] S202: Acquire multiple travel routes according to the starting location and the destination location.

[0042] The starting position of the vehicle may be input by the user on the electronic device and then sent to the server, or may be determined by the server based on the positioning information of the electronic device obtained.

[0043] S203: Acquire vehicle status information and / or user information of the vehicle.

[0044] The vehicle status information includes the objective status of the vehicle, such as the vehicle level, body type, length, width, height and wheelbase, etc. The user information may be the user's age, physical condition, driving experience, etc.

[0045] S204: Determine a first road section in each of the multiple travel routes according to the vehicle state information and / or the user information, where the first road section is a dangerous road section in the road sections corresponding to each of the travel routes.

[0046] The distance of the first section can be arbitrary. For example, the first section can be only the length of a narrow bridge, or it can be the entire highway in the travel route. The first section is dangerous to the current user or the current vehicle, but may not be dangerous to other vehicles. For example, if the user's driving experience is less than one year, and there is a highway in the travel route, then the highway is the first section for the current user. Therefore, there may be multiple first sections in each travel route. And these multiple first sections can be in an inclusive relationship, for example, one first section is a highway, and another first section is a section of the highway.

[0047] In a possible example, determining the first section of each of the multiple travel routes based on the vehicle status information and / or user information includes the following steps: obtaining map information corresponding to each of the travel routes; determining keywords based on the vehicle status information and / or user information; and determining the first section of each of the travel routes from the map information corresponding to each of the travel routes based on the keywords.

[0048] The map information may be stored in a database of a server. The server may obtain road information regularly or in real time to update the map information, or may obtain road information uploaded by other users, and then update the map information according to the road information. For example, a user uploads road information that a landslide occurred on a certain road 10 minutes ago. At this time, the data will be updated on the map information, so this road section will become the first road section at this time. After the road section is reopened to traffic, the map information will be updated again, and the road section may not be the first road section at this time. The keywords may correspond to the dangers on the road. For example, the keywords determined according to the vehicle status information may be vehicle weight of 3 tons and height of 1.8 meters. The keywords determined according to the user information may be driving experience of 5 years, etc.

[0049] It can be seen that in this example, determining the first section of each travel route based on map information and keywords can not only simplify the calculation steps and improve the efficiency of determining the first section, but also accurately and comprehensively determine the first section, thereby improving the user experience.

[0050] In a possible example, determining the first road section in each travel route from the map information corresponding to each travel route based on the keyword includes the following steps: obtaining the traffic requirements of each of the multiple road sections corresponding to the map information based on the map information; determining whether the keyword matches the traffic requirements of each road section; if not, determining the section of the multiple road sections whose traffic requirements do not match the keyword as the first road section.

[0051] Each travel route is divided into different sections on the map, such as a highway, a sharp turn, a dirt road, or a narrow bridge. Each section has specific traffic requirements or restrictions, such as the traffic requirement for dirt roads is that the vehicle weight is less than 2 tons. Based on the previous keywords of vehicle weight of 3 tons, height of 1.8 meters, driving experience of 5 years, etc., it can be determined that the current vehicle weight does not match the vehicle weight limit of the dirt road, and the dirt road can be determined as the first section. In other words, as long as one of the information in the keywords does not match the traffic requirements, the section is the first section.

[0052] It can be seen that in this example, determining the first section of each travel route based on map information and keywords can not only simplify the calculation steps and improve the efficiency of determining the first section, but also accurately and comprehensively determine the first section, thereby improving the user experience.

[0053] S205: Determine the danger level of each travel route according to the first road section in each travel route.

[0054] Among them, the danger level of each first road section can be determined first, and then the danger level of each travel route can be determined. That is, if there is only one first road section in the current route, where the first road section is a road section with restrictions on drivers or vehicles, then the danger level of the first road section is the danger level of the current travel route. If there are multiple first road sections in the current travel route, the danger level of the current travel route can be determined by the danger levels of these multiple first road sections. Determining the danger level of each travel route based on the danger levels of multiple first road sections includes: determining the danger level corresponding to the first road section with the highest danger level in each travel route as the danger level of the travel route. Alternatively, determining the danger level of each travel route based on the danger levels of multiple first road sections includes: when each travel route includes multiple first road sections, determining the danger level corresponding to the first road section with the highest danger level in each travel route; determining the danger coefficients corresponding to other first road sections in each travel route, wherein the other first road sections are the first road sections in each travel route other than the first road section with the highest danger level; determining the danger level of each travel route based on the danger level corresponding to the first road section with the highest danger level, the danger levels of the other first road sections, and the danger coefficients. For example, the current travel route includes three first sections, the danger level corresponding to the first section A is 1, the danger level corresponding to the first section B is 4, the danger level corresponding to the third section C is 2, the danger coefficient corresponding to danger level 1 is 0.1, the danger coefficient corresponding to danger level 2 is 0.2, and so on. The danger level of the travel route can be the danger level of the first section B with the highest danger level plus the product of the danger level of the first section A and the danger coefficient, plus the product of the danger level of the first section C and the danger coefficient. The danger level of the route is 4.5.

[0055] In a possible example, determining the danger level of each travel route based on the first road section in each travel route includes the following steps: acquiring characteristic information of the first road section; acquiring second vehicle restriction information based on the characteristic information; acquiring a danger coefficient of the first road section based on the second vehicle restriction information and the vehicle status information; and determining the danger level of each travel route based on the danger coefficient of the first road section.

[0056] Among them, the characteristic information of the first road section includes the road type of the first road section, and the characteristic information can also be understood as the label of the road. For example, the characteristic information of the current first road section is sharp turns or dirt roads. Each characteristic information corresponds to specific restriction information, that is, under the current characteristic information, there are specific restrictions on vehicles or users, and each first road section can also include multiple labels. For example, the current first road section corresponds to two characteristic information including highways and crosswinds, then the second vehicle restriction information is the driving experience corresponding to the highway exceeding 1 year and the restriction on the center of gravity of the vehicle corresponding to the crosswind. For a first road section, the risk coefficient corresponding to each characteristic information in the first road section can be determined, and then the risk coefficient of all the characteristic information of the road section can be combined to determine the risk coefficient of the first road section.

[0057] It can be seen that in this example, the danger coefficient of each first road section is determined based on the characteristic information and the second vehicle restriction information, and then the danger level of each travel route is determined. This can not only simplify the calculation steps and improve the efficiency of determining the first road section, but also accurately and comprehensively determine the first road section, thereby improving the user experience.

[0058] In a possible example, the characteristic information includes vehicle load information, and the method of obtaining the danger coefficient of the first road section based on the second vehicle restriction information and the vehicle status information includes the following steps: obtaining the first vehicle load information in the vehicle status information; obtaining the load range of the vehicle load information included in the characteristic information; obtaining the vehicle usage type of the vehicle; predicting whether the first vehicle load information will change when the vehicle is located at the first road section based on the vehicle usage type; if not, obtaining the danger coefficient of the first road section based on the first vehicle load information and the load range; if yes, predicting the second vehicle load information when the vehicle arrives at the first road section, and obtaining the danger coefficient of the first road section based on the second vehicle load information.

[0059] Among them, the load range here refers to that determined according to the characteristic information of the road, that is, the current first road section has restrictions on vehicle load, and a load range can be obtained according to the characteristic information, that is, how much load the current road can bear. The vehicle usage type includes the purpose of the vehicle, and whether the vehicle load of the vehicle will change midway can be determined to the user based on the purpose. For example, if the vehicle is a passenger car or a truck, the vehicle may pick up and drop off passengers or load and drop off goods midway. When it is determined that the vehicle usage type is a certain type, the second load information of the vehicle can be determined again, that is, the specific load situation of the vehicle when it arrives at the first road section can be determined. The second vehicle load information of the vehicle when the vehicle arrives at the first road section is predicted to include: obtaining the load information uploaded by the user, determining that the load information is the second vehicle load information; and / or obtaining the historical load record of the vehicle, and determining the second load information according to the historical load record. That is to say, vehicles that usually pick up and drop off passengers or load and unload goods during the journey, which causes a large change in the vehicle load, are mostly vehicles that travel on the route for a long time, such as buses on a certain line or trucks that transport goods between two places for a long time. The load when they arrive at the first section again can be predicted based on their historical records.

[0060] In a specific implementation, the vehicle model can be directly determined based on the vehicle information, and then the upper load limit of the current vehicle can be determined based on the vehicle model, and the risk factor of the first road section can be determined based on the upper load limit. Alternatively, the vehicle load information can be obtained through weight sensors or tire pressure monitoring.

[0061] It can be seen that in this example, it is first determined whether the current vehicle load information will change when reaching the first road section, and then the corresponding vehicle load information is determined according to different situations, and finally the risk factor of the first road section is determined according to the vehicle load information. In this way, the risk factor of the first road section can be accurately and comprehensively determined, improving the user experience.

[0062] In a possible example, determining the danger level of each travel route based on the danger coefficient of the first road section includes the following steps: obtaining a first driving record of a user; obtaining first driving information of the user based on the first driving record; and determining the danger level of each travel route based on the danger coefficient of the first road section and the first driving information.

[0063] The first driving record includes information such as the user's travel record, and the first driving information can be used to characterize the user's driving style, or the passing situation on certain sections of the road. For example, if the user's driving style is determined to be wild or stable based on the driving record, the corresponding risk level of users with different driving styles will be different for the same first section. For example, if the characteristic information corresponding to the current first section is a section with many accidents, the risk level of users with wild driving styles will be higher than that of users with stable driving styles. The driving style can be determined based on the first driving record by obtaining the user's average speed, maximum speed, number of times the speed is greater than a preset value, average number of accelerations in a trip, etc. It can also be determined based on the driving record that the user has traveled on the first section or a section with similar characteristic information to the first section and successfully passed through it many times, and the risk level in the travel route is relatively small relative to the current user. Different first driving information has different judgments on the risk level of the first section, and the risk level of the first driving information to the first section can be determined based on the characteristic information corresponding to the first section, and then the risk level of each travel route is determined in combination with the risk coefficient. For example, for the first road section with a danger level of 2, it is determined based on the user's first driving information that the user has successfully traveled on the first road section many times, and then the danger level of the first road section may be less than 2 at this time.

[0064] It can be seen that in this example, the danger level of the travel route is determined based on the user's driving style and the danger factor of the first road section previously determined, which can ensure the comprehensiveness of the calculation of the travel route, be closer to user use, and improve the user experience.

[0065] In a possible example, the method of determining the danger level of each travel route according to the danger coefficient of the first road section and the first driving information includes the following steps: obtaining a second driving record and a second driving information of another user; determining a first user coefficient X according to the feature information and the second driving information; i ; Obtain the first user coefficient X according to the characteristic information and the second driving record i The corresponding first safety factor Y i According to the first user coefficient X i and the first safety factor Y i Establishing a danger level prediction model; determining the danger level of each travel route according to the danger level prediction model, the first driving information and the danger coefficient of the first road section.

[0066] Among them, the first user coefficient can be a value calculated based on the content in the first driving information. For example, when the current scene is determined to be a sharp turn based on the characteristic information, the user's driving information is a driving experience of 3 years, and the average driving speed is greater than A, then the first user coefficient can be calculated to be m, etc. Different characteristic information corresponds to different indicators in the driving information. The first safety factor can be used to characterize the user's ability to overcome the danger in the scene corresponding to the characteristic information based on the current user coefficient. For example, if the scene corresponding to the current characteristic information is a narrow bridge, and the user coefficient is m, the first safety factor Y can be calculated based on the probability of other users with coefficients m passing through the narrow bridge in the past. i . The user coefficient can be determined comprehensively based on the content included in the second driving information such as the user's driving experience and driving style. Finally, the danger level of the final travel route is determined by the danger level of the first section determined based on the vehicle status information and the first safety factor corresponding to the first section. For example, the influence rate of the first safety factor corresponding to the current feature information on the danger level can be determined first, and then the danger level of the travel route can be determined based on the influence rate and the danger level. Danger level = danger level - first safety factor × influence rate.

[0067] It can be seen that in this example, a danger level prediction model is created based on the driving records and driving information of other users, and then the danger level of each travel route is determined based on the danger level prediction model, the first driving information and the danger coefficient of the first road section. This can enhance the accuracy and objectivity of the calculated danger level and improve the user experience.

[0068] In a possible example, determining the danger level of each travel route based on the danger level prediction model, the first driving information and the danger coefficient of the first road section includes the following steps: obtaining a second user coefficient X of the user based on the characteristic information and the first driving information; determining a second safety coefficient Y based on the danger level prediction model and the second user coefficient X; and determining the danger level of each travel route based on the second safety coefficient Y and the danger coefficient of the first road section.

[0069] The second user coefficient is a user coefficient determined by the current user on a certain road section for a specific characteristic information, and then the second user coefficient is input into a pre-trained danger level prediction model to obtain a second safety factor corresponding to the current characteristic information.

[0070] It can be seen that in this example, determining the danger level of each travel route based on the danger level prediction model, the first driving information and the danger coefficient of the first road section can enhance the accuracy and objectivity of the calculated danger level and improve the user experience.

[0071] In a possible example, determining the predicted safety factor Y according to the danger level prediction model and the second user factor X includes:

[0072] The predicted safety factor Y is determined by the following formula:

[0073] Y = aX + b;

[0074]

[0075] Among them, the For each first user coefficient X i The average value, For each of the first safety factors Y i The average value of .

[0076] It can be seen that in this example, by jointly determining the safety factor under the current user coefficient based on multiple first user coefficients and their corresponding first safety factors, the accuracy and precision of the risk level of the travel route finally determined can be improved.

[0077] In a possible example, the first user coefficient X is determined according to the feature information and the second driving information. i , comprising the following steps: obtaining a plurality of information dimensions included in the second driving information; determining a dimension coefficient of each information dimension in the plurality of information dimensions according to the characteristic information; determining a first user coefficient X according to the dimension coefficient and the plurality of information dimensions i .

[0078] Among them, the dimensionality coefficient is the importance of a certain information in the second driving information in a specific scenario corresponding to a certain feature information. For example, in the scenario of a sharp turn, the information of the dimension of average vehicle speed may be more important than the information of the dimension of driving experience. Then the dimensionality coefficient of average vehicle speed is higher than the dimensionality coefficient of driving experience.

[0079] It can be seen that in this example, determining the first user coefficient according to different dimensional coefficients can improve the accuracy and precision of the risk level of the travel route finally determined.

[0080] S206: recommending a final travel route to the user according to the risk level.

[0081] The final travel routes can be arranged in order according to the degree of danger, or can be arranged in order according to other information such as the degree of danger and the arrival time. When recommending the final travel route to the user, the specific dangerous sections and the reasons why the sections are dangerous can be displayed on the interface. Figure 2b As shown, Figure 2bThis is a schematic diagram of a travel route recommendation interface provided in an embodiment of the present application. In the figure, the degree of danger is also marked in the recommendation column on the left, and specific information can be obtained based on the degree of danger. In the map, the circled areas are dangerous places in the travel route. Clicking on a specific road will display the cause of the danger and other content on the interface at the same time.

[0082] In a possible example, after recommending the final travel route to the user based on the degree of danger, the method further includes the following steps: obtaining the current travel route of the vehicle and the current position of the vehicle in the current travel route; obtaining road information of a second section within a preset distance range in front of the current position, the second section being a portion of the section corresponding to the current travel route; determining first vehicle restriction information based on the road information; determining whether the vehicle status information matches the first vehicle restriction information; if not, determining that the second section is the first section in the current travel route.

[0083] Among them, the first vehicle restriction information refers to the vehicle state of the vehicle that is not suitable for passing according to the road information. For example, if the road information here shows that there is a narrow bridge ahead, then according to the narrow bridge, the first vehicle restriction information can be determined as not suitable for vehicles with a width greater than a certain value to pass. Then the vehicle state information of the vehicle is compared with the determined first vehicle restriction to determine whether the vehicle can pass this section. When the vehicle is traveling on the road, the situation of the road within a certain distance in front of the vehicle can be obtained based on the real-time positioning of the vehicle or the vehicle-mounted camera and other equipment. The second section includes the section in the current route, or according to the current location of the user, the second section is the section that the user will inevitably pass. When the user does not enter the destination, through the user's historical driving route record, the route that has not been used will have a larger prediction range than the route that has been frequently used.

[0084] It can be seen that in this example, real-time danger monitoring of the road ahead of the vehicle has been carried out, and the user has been promptly reminded when an emergency occurs, ensuring the user's travel safety.

[0085] In a possible example, after recommending a final travel route to the user based on the risk level, the method further includes the following steps: sending a warning message to the user when the distance between the current position and a first section of the current travel route is less than a first preset distance.

[0086] Among them, the warning information is used to remind the user that he is about to reach the first section of road where there is danger or restriction. The user can be informed in advance of the countermeasures based on the characteristic information corresponding to the first section of road. For example, if there is a sharp turn ahead, the user will be informed in advance to slow down.

[0087] It can be seen that in this example, sending warning information to users in advance can enable users to predict dangers, make preparations for responses, and reduce the probability of user injury.

[0088] In a possible example, the current speed of the vehicle is controlled to be less than the maximum travel speed until the distance between the current position of the vehicle and the first section in the current travel route is greater than a second preset distance.

[0089] Among them, when the cloud-based vehicle speed exceeds the maximum safe speed, even if the user steps on the accelerator to accelerate, it will not exceed the cloud-based speed limit. In other words, the user's vehicle speed is controlled in advance to prevent the user from failing to respond to the danger ahead in time or making mistakes due to anxiety.

[0090] It can be seen that in this example, controlling the user's vehicle speed can prevent the user from being unable to respond to dangers ahead in a timely manner or making erroneous operations in a hurry, thereby reducing the probability of user injury.

[0091] It can be seen that in the embodiment of the present application, the server first obtains the starting position and the destination position of the vehicle, then obtains multiple travel routes based on the starting position and the destination position, and then obtains the vehicle status information and / or user information of the vehicle. Then, the first section of each of the multiple travel routes is determined based on the vehicle status information and / or user information, and then the danger level of each travel route is determined based on the first section of each travel route, and finally the final travel route is recommended to the user based on the danger level. Predicting and prompting road hazards in advance can not only provide guarantees for users to reach their destinations smoothly and reduce casualties, but also improve user travel efficiency.

[0092] With the above Figure 2a For details on the implementation examples, please refer to Figure 3 , Figure 3300 is a structural diagram of a travel route recommendation device provided by an embodiment of the present application, the travel route recommendation device is applied to a server, and the device 300 includes: a first acquisition unit 301, used to acquire a starting position and a destination position of a vehicle; a second acquisition unit 302, the second acquisition unit is communicated with the first acquisition unit, and is used to acquire multiple travel routes according to the starting position and the destination position; a third acquisition unit 303, used to acquire vehicle status information and / or user information of the vehicle; a first determination unit 304, the first determination unit is communicated with the second acquisition unit and the third acquisition unit respectively, and is used to determine a first section in each of the multiple travel routes according to the vehicle status information and / or user information, the first section being a dangerous section in the sections corresponding to each travel route; a second determination unit 305, the second determination unit is communicated with the first determination unit, and is used to determine the degree of danger of each travel route according to the first section in each travel route; a recommendation unit 306, the recommendation unit is communicated with the second determination unit, and is used to recommend a final travel route to the user according to the degree of danger.

[0093] In a possible example, after recommending the final travel route to the user based on the degree of danger, the device 300 is specifically used to: obtain the current travel route of the vehicle and the current position of the vehicle in the current travel route; obtain road information of a second section within a preset distance range in front of the current position, the second section being a portion of the section corresponding to the current travel route; determine first vehicle restriction information based on the road information; determine whether the vehicle status information matches the first vehicle restriction information; if not, determine that the second section is the first section in the current travel route.

[0094] In a possible example, after recommending the final travel route to the user based on the risk level, the device 300 is specifically used to send a warning message to the user when the distance between the current position and the first section of the current travel route is less than a first preset distance.

[0095] In a possible instance, the warning information includes a maximum driving speed. After sending the warning information to the user, the device 300 is specifically used to: control the current speed of the vehicle to be less than the maximum driving speed until the distance between the current position of the vehicle and the first section in the current travel route is greater than a second preset distance.

[0096] In a possible example, in terms of determining the first section of each of the multiple travel routes based on the vehicle status information and / or user information, the first determination unit 304 is specifically used to: obtain map information corresponding to each travel route; determine keywords based on the vehicle status information and / or user information; and determine the first section of each travel route from the map information corresponding to each travel route based on the keywords.

[0097] In a possible example, in terms of determining the first road section in each travel route from the map information corresponding to each travel route according to the keyword, the first determination unit 304 is specifically used to: obtain the traffic requirements of each of the multiple road sections corresponding to the map information according to the map information; determine whether the keyword matches the traffic requirements of each road section; if not, determine that the road section in the multiple road sections whose traffic requirements do not match the keyword is the first road section.

[0098] In a possible example, in terms of determining the danger level of each travel route based on the first road section in each travel route, the second determination unit 305 is specifically used to: obtain characteristic information of the first road section; obtain second vehicle restriction information based on the characteristic information; obtain the danger coefficient of the first road section based on the second vehicle restriction information and the vehicle status information; and determine the danger level of each travel route based on the danger coefficient of the first road section.

[0099] In a possible example, the characteristic information includes vehicle load information, and in terms of obtaining the danger coefficient of the first road section based on the second vehicle restriction information and the vehicle status information, the second determination unit 305 is specifically used to: obtain the first vehicle load information in the vehicle status information; obtain the load range of the vehicle load information included in the characteristic information; obtain the vehicle usage type of the vehicle; predict whether the first vehicle load information will change when the vehicle is located at the first road section based on the vehicle usage type; if not, obtain the danger coefficient of the first road section based on the first vehicle load information and the load range; if so, predict the second vehicle load information when the vehicle arrives at the first road section, and obtain the danger coefficient of the first road section based on the second vehicle load information.

[0100] In a possible example, in terms of determining the danger level of each travel route based on the danger coefficient of the first road section, the second determination unit 305 is specifically used to: obtain a first driving record of a user; obtain first driving information of the user based on the first driving record; and determine the danger level of each travel route based on the danger coefficient of the first road section and the first driving information.

[0101] In a possible example, in determining the danger level of each travel route according to the danger coefficient of the first road section and the first driving information, the second determining unit 305 is specifically used to: obtain the second driving record and the second driving information of other users; determine the first user coefficient X according to the feature information and the second driving information i ; Obtain the first user coefficient X according to the characteristic information and the second driving record i The corresponding first safety factor Y i According to the first user coefficient X i and the first safety factor Y i Establishing a danger level prediction model; determining the danger level of each travel route according to the danger level prediction model, the first driving information and the danger coefficient of the first road section.

[0102] In a possible example, in terms of determining the danger level of each travel route based on the danger level prediction model, the first driving information and the danger coefficient of the first road section, the second determination unit 305 is specifically used to: obtain a second user coefficient X of the user based on the characteristic information and the first driving information; determine a second safety coefficient Y based on the danger level prediction model and the second user coefficient X; and determine the danger level of each travel route based on the second safety coefficient Y and the danger coefficient of the first road section.

[0103] In a possible example, in determining the predicted safety factor Y according to the risk level prediction model and the second user coefficient X, the second determination unit 305 is specifically configured to: determine the predicted safety factor Y by the following formula:

[0104] Y = aX + b;

[0105]

[0106] Among them, the For each first user coefficient X i The average value, For each of the first safety factors Y i The average value of .

[0107] In a possible example, in determining the first user coefficient X according to the feature information and the second driving information iIn terms of the aspect, the second determining unit 305 is specifically used to: obtain multiple information dimensions included in the second driving information; determine the dimension coefficient of each information dimension in the multiple information dimensions according to the characteristic information; determine the first user coefficient X according to the dimension coefficient and the multiple information dimensions i .

[0108] It can be understood that since the method embodiment and the device embodiment are different presentation forms of the same technical concept, the content of the method embodiment part in this application should be synchronously adapted to the device embodiment part and will not be repeated here.

[0109] In the case of integrated units, such as Figure 4 As shown, Figure 4 is a schematic diagram of the structure of another travel route recommendation device provided in an embodiment of the present application. Figure 4 In the example, the travel route recommendation device 400 includes: a processing module 402 and a communication module 401. The processing module 402 is used to control and manage the actions of the travel route recommendation device, for example, the steps performed by the first acquisition unit 301, the second acquisition unit 202, the third acquisition unit 303, the first determination unit 304, the second determination unit 305 and the recommendation unit 306, and / or other processes for performing the technology described herein. The communication module 401 is used to support the interaction between the travel route recommendation device and other devices. Figure 4 As shown, the travel route recommendation device may further include a storage module 403, and the storage module 403 is used to store program codes and data of the travel route recommendation device.

[0110] Among them, the processing module 402 can be a processor or a controller, for example, a central processing unit (CPU), a general processor, a digital signal processor (DSP), an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements a computing function, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The communication module 401 can be a transceiver, an RF circuit or a communication interface, and the like. The storage module 403 can be a memory.

[0111] All relevant contents of each scenario involved in the above method embodiment can be referred to the functional description of the corresponding functional module, and will not be repeated here. The above travel route recommendation device 300 and the travel route recommendation device 400 can both execute the above Figure 2a The recommended travel route is shown.

[0112] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0113] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0114] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0115] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0116] In the several embodiments provided in the present application, it should be understood that the disclosed methods, devices and systems can be implemented in other ways. For example, the device embodiments described above are merely schematic; for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0117] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0118] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may be physically included separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0119] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store program codes.

[0120] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present invention, and can make various changes and modifications, including the combination of the above-mentioned different functions and implementation steps, including software and hardware implementation methods, all of which are within the scope of protection of the present invention.

Claims

1. A travel route recommendation method, characterized in that: Applied to the server, the method comprises the following steps: Obtaining characteristic information of the first section of the travel route; determining a risk factor of the first road section according to the characteristic information of the first road section and the vehicle state information of the vehicle; Acquiring second driving information of other users to establish a risk level prediction model based on the second driving information and the characteristic information; Acquire first driving information of a user to obtain a second user coefficient X of the user based on the first driving information and the characteristic information; Determining the danger level of each travel route based on the danger coefficient of the first road section, the danger level prediction model, and the second user coefficient X of the user; A final travel route is recommended to the user according to the risk level.

2. The method according to claim 1, after obtaining the second driving information of other users, further comprising: Determine a first user coefficient Xi corresponding to the other user according to the characteristic information and the second driving information; Acquire a first safety factor Yi corresponding to the first user factor Xi according to the characteristic information and the second driving record; A danger level prediction model is established based on the first user coefficient Xi and the first safety coefficient Yi.

3. The method according to claim 1, wherein obtaining the first driving information of the user further comprises: Get the user's first driving record; The first driving information of the user is acquired according to the first driving record.

4. The method according to claim 1, wherein determining the risk level of each travel route further comprises: Acquire a second user coefficient X of the current user according to the feature information and the first driving information; Determine a second safety factor Y according to the danger level prediction model and the second user factor X; The danger level of each travel route is determined according to the second safety factor Y and the danger factor of the first road section.

5. The method according to claim 1, after recommending the final travel route to the user according to the risk level, the method further comprises the following steps: Acquire a current travel route of the vehicle and a current position of the vehicle in the current travel route; Acquire road information of a second road section within a preset distance range ahead of the current position, where the second road section is a partial road section of the road section corresponding to the current travel route; determining first vehicle restriction information according to the road information; determining whether the vehicle status information matches the first vehicle restriction information; If there is no match, the second road section is determined to be the first road section in the current travel route.

6. The method according to claim 1, after recommending the final travel route to the user according to the risk level, the method further comprises the following steps: When the distance between the current position and the first section in the current travel route is less than a first preset distance, a warning message is sent to the user.

7. The method according to claim 1, wherein the characteristic information includes vehicle load information, and the determining the risk factor of the first road section according to the characteristic information of the first road section and the vehicle state information of the vehicle further comprises: Acquire first vehicle load information in the vehicle status information; Obtaining a load range of the vehicle load information included in the characteristic information; obtaining a vehicle usage type of the vehicle; Predicting, based on the vehicle usage type, whether the load information of the first vehicle will change when the vehicle is located on the first road section; If not, obtaining the risk factor of the first road section according to the first vehicle load information and the load range; If so, predict the second vehicle load information when the vehicle arrives at the first road section, and obtain the danger factor of the first road section based on the second vehicle load information.

8. The method according to claim 2, wherein determining the first user coefficient Xi according to the characteristic information and the second driving information comprises the following steps: Acquire multiple information dimensions included in the second driving information; Determine a dimension coefficient of each information dimension in the multiple information dimensions according to the characteristic information; A first user coefficient Xi is determined according to the dimension coefficient and the multiple information dimensions.

9. An electronic device, characterized in that: It includes a processor, a memory and a communication interface, the processor and the communication interface are respectively connected to the memory for communication, the memory stores one or more programs, and the one or more programs are executed by the processor, and the one or more programs include instructions for executing the method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program is operable to cause a computer to execute the method according to any one of claims 1 to 8.

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