Traffic route recommendation method, device, computer equipment and storage medium

Abstract

The present application relates to a method, device, computer equipment and storage medium for recommending traffic routes. The method can be applied to the field of maps and intelligent transportation, and the method includes: obtaining at least two traffic routes and route scores corresponding to the traffic routes; the traffic routes include a first traffic route based on public transportation and a second traffic route based on public transportation and non-public transportation; determining the comprehensive traffic coefficient of the second traffic route based on the traffic coefficients corresponding to public transportation and non-public transportation; sorting the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic route; and sorting the first traffic route according to the route score of the first traffic route; and recommending the sorted second traffic route and the first traffic route as recommended routes. The use of this method can make the high-quality traffic routes be sorted first.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device, computer equipment and storage medium for recommending a traffic route. Background Art

[0002] With the widespread popularization of information technology and the Internet, more and more users use electronic map applications to plan their travel routes. Users usually need to change transportation when traveling. However, in the existing public transportation route planning scheme, in order to highlight the bus travel scenario, when outputting the transportation route planned for the user, the first transportation route that only includes public transportation is usually directly ranked ahead of the second transportation route that includes bicycles, taxis and other transportation tools in addition to public transportation. As a result, the output sorted transportation routes cannot meet the timeliness requirements of the user's travel. Summary of the invention

[0003] Based on this, it is necessary to provide a method, device, computer equipment and storage medium for sorting traffic routes that can meet the timeliness requirements of users' travel in order to address the above technical problems.

[0004] In a first aspect, the present application provides a method for recommending a traffic route. The method comprises:

[0005] Acquire at least two transportation routes and route scores corresponding to the transportation routes; the transportation routes include a first transportation route based on public transportation and a second transportation route based on the public transportation and non-public transportation;

[0006] Determining a comprehensive traffic coefficient of the second traffic route based on the traffic coefficients corresponding to the public transportation means and the non-public transportation means;

[0007] sorting the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and sorting the first traffic routes according to the route score of the first traffic routes;

[0008] The sorted second traffic route and the first traffic route are recommended as recommended routes.

[0009] In a second aspect, the present application also provides a traffic route recommendation device. The device comprises:

[0010] A traffic route acquisition module, used to acquire at least two traffic routes and route scores corresponding to the traffic routes; the traffic routes include a first traffic route based on public transportation and a second traffic route based on the public transportation and non-public transportation;

[0011] A comprehensive traffic coefficient determination module, configured to determine the comprehensive traffic coefficient of the second traffic route based on the traffic coefficients corresponding to the public transportation vehicle and the non-public transportation vehicle;

[0012] a route sorting module, configured to sort the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and to sort the first traffic routes according to the route score of the first traffic routes;

[0013] The route recommendation module is used to recommend the sorted second traffic route and the first traffic route as recommended routes.

[0014] In one embodiment, the traffic route acquisition module is further used to:

[0015] Get route starting point information and route end point information;

[0016] Determine at least two traffic routes based on the route starting point information and the route end point information;

[0017] Based on the transportation tool corresponding to the transportation route, a route score corresponding to the transportation route is determined.

[0018] In one embodiment, the traffic route acquisition module is further used to:

[0019] Obtaining the road sections involved in the traffic route and the transportation tools corresponding to each of the road sections;

[0020] Determine the road section time corresponding to each road section based on the acquired transportation means;

[0021] Determining the route time of the traffic route according to the road section time;

[0022] A route score corresponding to the traffic route is determined according to the route time.

[0023] In one embodiment, the comprehensive traffic coefficient determination module is further used to:

[0024] Obtaining traffic coefficients of the public transportation vehicle and the non-public transportation vehicle under a target traffic model;

[0025] Based on the traffic coefficient, determining a model traffic coefficient of the second traffic route under the target traffic model;

[0026] A comprehensive traffic coefficient of the second traffic route is determined based on the model traffic coefficient.

[0027] In one embodiment, the comprehensive traffic coefficient determination module is further used to:

[0028] Obtaining the number of people entering and exiting each transportation station in the second transportation route, as well as popular sections of the transportation route that meet preset conditions;

[0029] Adjusting the traffic coefficient based on the number of people entering and exiting the station and the popular road section;

[0030] Based on the adjusted traffic coefficient, a model traffic coefficient of the second traffic route under the target traffic model is determined.

[0031] In one embodiment, the target traffic model includes at least one of a city model, a congestion model, and an origin-destination model; and the comprehensive traffic coefficient determination module is further used to:

[0032] Averaging the traffic coefficients of the various transportation tools under the city model to obtain a city model traffic coefficient;

[0033] Averaging the traffic coefficients of the various transportation tools under the congestion model to obtain a traffic coefficient of the congestion model;

[0034] Averaging the traffic coefficients of the various transportation tools under the start-end model to obtain the start-end model traffic coefficient;

[0035] Among them, the traffic coefficients corresponding to the traffic tools under different target traffic models are different.

[0036] In one embodiment, the comprehensive traffic coefficient determination module is further used to:

[0037] Summing at least one of the city model traffic coefficient, the congestion model traffic coefficient and the start-end point model traffic coefficient to obtain a summation result;

[0038] A comprehensive traffic coefficient of the second traffic route is determined based on the summation result.

[0039] In one embodiment, the comprehensive traffic coefficient determination module is further used to:

[0040] When the target traffic model is a congestion model, obtaining a departure time;

[0041] Based on the departure time, a traffic coefficient of at least one of the transportation tools under the congestion model is determined.

[0042] In one embodiment, the route sorting module is further used to:

[0043] adjusting the route score of the second traffic route according to the comprehensive traffic coefficient to obtain an adjusted route score;

[0044] The second traffic routes are sorted according to the adjusted route scores.

[0045] In one embodiment, the route sorting module is further used to:

[0046] determining the public transportation vehicles involved in the first transportation route;

[0047] Determining a route adjustment coefficient of the first traffic route based on the traffic coefficient of the public transportation vehicle;

[0048] adjusting the route score of the first traffic route according to the route adjustment coefficient;

[0049] The first traffic routes are sorted according to the adjusted route scores.

[0050] In one embodiment, the route recommendation module is further used to:

[0051] Determine the integration order between the sorted second traffic route and the first traffic route according to the order of the route score of the first traffic route and the adjusted route score of the second traffic route; the adjusted route score is the route score obtained by adjusting the route score of the second traffic route according to the comprehensive traffic coefficient;

[0052] Integrate the sorted second traffic route and the first traffic route according to the integration order to obtain an integrated traffic route;

[0053] Among the integrated traffic routes, a route whose ranking meets the ranking condition is selected as a recommended route; the recommended route is displayed, or the recommended route is pushed to a terminal for display.

[0054] In one embodiment, the route recommendation module is further used to:

[0055] Get the target object's transportation label;

[0056] Sorting the recommended routes according to a sorting method matching the transportation tool tags;

[0057] The sorted recommended routes are displayed, or the sorted recommended routes are pushed to a terminal for display.

[0058] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0059] Acquire at least two transportation routes and route scores corresponding to the transportation routes; the transportation routes include a first transportation route based on public transportation and a second transportation route based on the public transportation and non-public transportation;

[0060] Determining a comprehensive traffic coefficient of the second traffic route based on the traffic coefficients corresponding to the public transportation vehicle and the non-public transportation vehicle;

[0061] sorting the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and sorting the first traffic routes according to the route score of the first traffic routes;

[0062] The sorted second traffic route and the first traffic route are recommended as recommended routes.

[0063] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0064] Acquire at least two transportation routes and route scores corresponding to the transportation routes; the transportation routes include a first transportation route based on public transportation and a second transportation route based on the public transportation and non-public transportation;

[0065] Determining a comprehensive traffic coefficient of the second traffic route based on the traffic coefficients corresponding to the public transportation vehicle and the non-public transportation vehicle;

[0066] sorting the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and sorting the first traffic routes according to the route score of the first traffic routes;

[0067] The sorted second traffic route and the first traffic route are recommended as recommended routes.

[0068] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0069] Acquire at least two transportation routes and route scores corresponding to the transportation routes; the transportation routes include a first transportation route based on public transportation and a second transportation route based on the public transportation and non-public transportation;

[0070] Determining a comprehensive traffic coefficient of the second traffic route based on the traffic coefficients corresponding to the public transportation vehicle and the non-public transportation vehicle;

[0071] sorting the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and sorting the first traffic routes according to the route score of the first traffic routes;

[0072] The sorted second traffic route and the first traffic route are recommended as recommended routes.

[0073] The above-mentioned traffic route sorting method, device, computer equipment and storage medium obtain at least two traffic routes and route scores corresponding to the traffic routes; the traffic routes include a first traffic route based on public transportation and a second traffic route based on public transportation and non-public transportation; based on the traffic coefficients corresponding to public transportation and non-public transportation, the comprehensive traffic coefficient of the second traffic route is determined; according to the comprehensive traffic coefficient and the route score of the second traffic route, the second traffic route is sorted; and, according to the route score of the first traffic route, the first traffic route is sorted so that the high-quality traffic route is sorted first, so that the recommended sorted traffic route can better meet the timeliness requirements of the user's travel. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 A diagram of an application environment of a method for recommending a traffic route in one embodiment;

[0075] Figure 2 A schematic diagram of a flow chart of a method for recommending a traffic route in one embodiment;

[0076] Figure 3 A schematic diagram of a flow chart of traffic route recommendation in another embodiment;

[0077] Figure 4 A schematic flow chart of a method for recommending a traditional traffic route in another embodiment;

[0078] Figure 5 A schematic diagram of a recommendation result in an embodiment;

[0079] Figure 6 A schematic diagram of a route in an embodiment;

[0080] Figure 7 A schematic flow chart of a method for recommending a traffic route in another embodiment;

[0081] Figure 8 is a structural block diagram of a traffic route recommendation device in one embodiment;

[0082] Fig. 9 is an internal structure diagram of a computer device in one embodiment;

[0083] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0084] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0085] Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines so that machines have the functions of perception, reasoning and decision-making.

[0086] Artificial intelligence technology is a comprehensive discipline that covers a wide range of fields, including both hardware-level and software-level technologies. The basic technologies of artificial intelligence generally include sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics and other technologies. Artificial intelligence software technology mainly includes computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0087] Machine Learning (ML) is a multi-disciplinary subject that involves probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. It specializes in studying how computers simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to make computers intelligent. Its applications are spread across all areas of artificial intelligence. Machine learning and deep learning usually include artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and self-learning.

[0088] Intelligent Traffic System (ITS): also known as Intelligent Transportation System, is the effective and comprehensive application of advanced science and technology (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operations research, artificial intelligence, etc.) to transportation, service control and vehicle manufacturing, strengthening the connection between vehicles, roads and users, thus forming a comprehensive transportation system that ensures safety, improves efficiency, improves the environment and saves energy.

[0089] Intelligent Vehicle Infrastructure Cooperative Systems (IVICS): referred to as vehicle-infrastructure cooperative systems, it is a development direction of intelligent transportation systems (ITS). The vehicle-infrastructure cooperative system uses advanced wireless communication and new generation Internet technologies to implement dynamic real-time information interaction between vehicles and roads in all directions, and carries out active vehicle safety control and road cooperative management based on the collection and integration of dynamic traffic information in all time and space, fully realizing the effective coordination of people, vehicles and roads, ensuring traffic safety, and improving traffic efficiency, thus forming a safe, efficient and environmentally friendly road traffic system.

[0090] The traffic route recommendation method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other servers. The traffic route recommendation method can be executed by the terminal 102 or the server 104, or it can be realized through the interaction between the terminal 102 and the server 104. Taking the traffic route recommendation party executed on the terminal 102 as an example, the terminal 102 obtains at least two traffic routes and route scores corresponding to the traffic routes; the traffic routes include a first traffic route based on public transportation and a second traffic route based on public transportation and non-public transportation; based on the traffic coefficients corresponding to public transportation and non-public transportation, the comprehensive traffic coefficient of the second traffic route is determined; according to the comprehensive traffic coefficient and the route score of the second traffic route, the second traffic route is sorted; and, the first traffic route is sorted according to the route score of the first traffic route; the sorted second traffic route and the first traffic route are recommended as recommended routes.

[0091] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0092] The server 104 may be an independent physical server or a server cluster composed of multiple service nodes in the blockchain system. Each service node forms a peer-to-peer (P2P) network. The P2P protocol is an application layer protocol running on the Transmission Control Protocol (TCP).

[0093] In addition, server 104 can also be a server cluster composed of multiple physical servers, and can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), as well as big data and artificial intelligence platforms.

[0094] In one embodiment, Figure 2 As shown, a traffic route recommendation method is provided, which is applied to Figure 1 The computer device (terminal or server) in the example is used to illustrate, including the following steps:

[0095] S202: Obtain at least two traffic routes and route scores corresponding to the traffic routes.

[0096] Among them, the traffic route is the travel route, and the travel route refers to the route planned by the route planning algorithm under the public transportation travel mode. The public transportation travel mode refers to the travel mode based on public transportation. The transportation tools corresponding to the public transportation travel mode can be buses, subways, ferries, maglevs, taxis, bicycles and other tools for travel. Specifically, the above-mentioned transportation tools can be divided into two categories: public transportation tools and non-public transportation tools. Among them, buses, subways, ferries and maglevs belong to public transportation tools, and taxis and bicycles belong to non-public transportation tools. In addition, in some embodiments, walking can also be set as a non-public transportation tool category. The traffic route specifically includes a first traffic route based on public transportation tools and a second traffic route based on public transportation tools and non-public transportation tools. The first traffic route refers to a route that only uses transportation tools of the public transportation tool category, which can also be called a bus route, for example, a route that only uses at least one transportation tool of the bus, subway, ferry, and maglev; the second traffic route refers to a route that uses transportation tools of the public transportation tool category in combination with transportation tools of the non-public transportation tool category, which can also be called a multi-tool route, for example, a route that uses a combination of buses and bicycles.

[0097] The route score is used to represent the possibility of a traffic route being selected. The size of the route score is related to the size of the possibility of the traffic route being selected. Specifically, the larger the route score of a traffic route, the greater the possibility of the traffic route being selected. Specifically, the smaller the route score of a traffic route, the greater the possibility of the traffic route being selected.

[0098] In one embodiment, S202 specifically includes the following steps: obtaining route starting point information and route end point information; determining at least two traffic routes based on the route starting point information and route end point information; and determining route scores corresponding to the traffic routes based on the transportation tools corresponding to the traffic routes.

[0099] Specifically, the computer device responds to the route recommendation request, extracts the route starting point information and the route midpoint information from the route recommendation request, and uses the route planning algorithm to plan at least two transportation routes based on the route starting point information and the route end point information, and after obtaining the transportation routes, determines the cost information of each transportation route based on the transportation tools corresponding to each transportation route, and determines the route score corresponding to each transportation route based on the cost information.

[0100] Each traffic route includes at least one section, and each section has a corresponding means of transportation, that is, the corresponding means of transportation is used to pass through the section. For example, traffic route 1 includes section A and section B. The means of transportation corresponding to section A is a bus, and the means of transportation corresponding to section B is a bicycle, which means that the bus is used to pass through section A, and the bicycle is used to pass through section B. The cost information includes at least one of time cost and expense cost. The time cost refers to the time required to use the means of transportation corresponding to the traffic route to pass through each section of the traffic route, and the expense cost refers to the expense required to use the means of transportation corresponding to the traffic route to pass through each section of the traffic route.

[0101] S204: Determine a comprehensive traffic coefficient of the second traffic route based on traffic coefficients corresponding to public transportation vehicles and non-public transportation vehicles.

[0102] Among them, the traffic coefficient is a coefficient used to adjust the route score. The traffic coefficients corresponding to different means of transportation can be the same or different. The comprehensive traffic coefficient is a comprehensive value determined by comprehensively considering the traffic coefficients of multiple means of transportation.

[0103] Specifically, after obtaining each traffic route, the computer device obtains the transportation tools corresponding to each traffic route, and obtains the traffic coefficient corresponding to each transportation tool, and averages the traffic coefficients of each transportation tool corresponding to the traffic route to obtain the comprehensive traffic coefficient of each traffic route, wherein, when the traffic route is a first traffic route, the obtained comprehensive traffic coefficient is the comprehensive traffic coefficient of the first traffic route, and the comprehensive traffic coefficient of the first traffic route is also called the route adjustment coefficient; when the traffic route is a second traffic route, the obtained comprehensive traffic coefficient is the comprehensive traffic coefficient of the second traffic route.

[0104] As shown in Table 1 below, it is the traffic coefficient corresponding to each transportation tool in an embodiment, wherein the traffic coefficient corresponding to the bus is 0.5, the traffic coefficient corresponding to the subway is 1, the traffic coefficient corresponding to the ferry is 0, the traffic coefficient corresponding to the maglev is 0.5, the traffic coefficient corresponding to the taxi is 1, and the traffic coefficient corresponding to the bicycle is 0.5. Referring to Table 1 below, assuming that traffic route 1 is the first traffic route, and the corresponding transportation tools are the bus and the subway, and traffic route 2 is the second traffic route, and the corresponding transportation tools are the subway and the taxi, then for traffic route 1, the traffic coefficient of the corresponding transportation tool bus is 0.5, and the traffic coefficient of the subway is 1, then the comprehensive traffic coefficient of the traffic route 1 is (0.5+1) / 2=0.75; for traffic route 2, the traffic coefficient of the corresponding transportation tool subway is 1, and the traffic coefficient of the taxi is 1, then the comprehensive traffic coefficient of the traffic route 2 is (1+1) / 2=1.

[0105] Table 1 Comparison table of transportation tools and traffic coefficients

[0106] Transportation Public transportation subway FERRY SERVICE Maglev Taxi bicycle Traffic coefficient 0.5 1 0 0.5 1 0.5

[0107] S206, sorting the second transportation routes according to the comprehensive transportation coefficient and the route score of the second transportation routes; and sorting the first transportation routes according to the route score of the first transportation routes.

[0108] Specifically, for the second traffic routes, after obtaining the comprehensive traffic coefficients corresponding to the second traffic routes, the computer device may adjust the route scores of the second traffic routes based on the comprehensive traffic coefficients corresponding to the second traffic routes to obtain the adjusted route scores, and sort the second traffic routes separately according to the adjusted route scores; for the first traffic routes, the computer device may not adjust their route scores, and directly sort the first traffic routes based on their route scores.

[0109] In one embodiment, after obtaining the corresponding comprehensive traffic coefficient of each traffic route, the computer device may adjust the route score of each traffic route based on the comprehensive traffic coefficient of each traffic route to obtain the adjusted route score, and sort each traffic route according to the adjusted route score. The traffic route may be a first traffic route and a second traffic route, so that the first traffic route and the second traffic route are sorted together. The sorting may be in descending or ascending order according to the size of the adjusted route score.

[0110] In one embodiment, the route score may be adjusted using the following formula (1):

[0111]

[0112] Among them, R is the adjusted route score of the traffic route, r is the route score of the traffic route, Z is the comprehensive traffic coefficient of the traffic route, Z=C+Y+S, among which C is the urban model traffic coefficient of the traffic route, Y is the congestion model traffic coefficient of the traffic route, and S is the starting and ending model traffic coefficient of the traffic route.

[0113] S208: Recommend the sorted second traffic route and the first traffic route as recommended routes.

[0114] Specifically, after obtaining the sorted second traffic route and the first traffic route, the computer device can make a route recommendation based on the sorted second traffic route and the first traffic route. The sorted second traffic route and the first traffic route can be directly recommended as the recommended route, or a target traffic route can be selected from the sorted second traffic route and the first traffic route as the recommended route.

[0115] In one embodiment, S208 specifically includes the following steps: selecting a second traffic route whose ranking meets the ranking condition from the sorted second traffic routes, and selecting a first traffic route whose ranking meets the ranking condition from the sorted first traffic routes, integrating the selected second traffic route and the second traffic route to obtain an integrated traffic route, and using the integrated traffic route as a recommended route, displaying the recommended route, or pushing the recommended route to the terminal for display.

[0116] For example, the top three second transportation routes are selected from the sorted second transportation routes, and the top five first transportation routes are selected from the sorted first transportation routes, and then the selected three second transportation routes and the five first transportation routes are integrated to obtain an integrated transportation route including eight transportation routes, and the integrated transportation route including eight transportation routes is recommended as a recommended route.

[0117] In one embodiment, S208 specifically includes the following steps: determining the integration order between the sorted second traffic route and the first traffic route according to the order of magnitude between the route score of the first traffic route and the adjusted route score of the second traffic route; the adjusted route score is the route score obtained by adjusting the route score of the second traffic route according to the comprehensive traffic coefficient; integrating the sorted second traffic route and the first traffic route according to the integration order to obtain an integrated traffic route; selecting a route whose sorting rank meets the ranking condition as a recommended route from the integrated traffic route; displaying the recommended route, or pushing the recommended route to the terminal for display.

[0118] Specifically, after obtaining the comprehensive traffic coefficients corresponding to the second traffic routes, the computer device may adjust the route scores of the second traffic routes based on the comprehensive traffic coefficients corresponding to the second traffic routes to obtain the adjusted route scores, and sort the second traffic routes separately according to the adjusted route scores; for the first traffic routes, the computer device may not adjust the route scores thereof, and sort the first traffic routes directly based on the route scores of the first traffic routes. After obtaining the sorted second traffic routes and the sorted first traffic routes, the computer device sorts the sorted second traffic routes and the sorted first traffic routes according to the sorted route scores. According to the corresponding adjusted route scores and route scores, the integration order between the sorted second traffic route and the first traffic route is determined, for example, the integration is carried out in the order of the corresponding adjusted route scores and route scores from large to small or from small to large, and the sorted second traffic route and the first traffic route are integrated according to the integration order to obtain an integrated traffic route, and a traffic route whose sorting ranking meets the ranking threshold is selected from the integrated traffic route as a recommended route, and when the computer device is a terminal, the recommended route is directly displayed, and when the computer device is a server, the recommended route is pushed to the sending terminal of the route recommendation request for display. For example, the first 20% of the traffic routes are selected from the integrated traffic route as the recommended routes, or the second traffic route whose adjusted route score is greater than or equal to the score threshold is selected from the integrated traffic route, and the first traffic route whose route score is greater than or equal to the score threshold is selected as the recommended route.

[0119] For example, the second traffic route includes route A, route B and route C, wherein the route scores of route A, route B and route C are 30, 20 and 24 respectively, and the adjusted route scores are 25, 20 and 18 respectively, then the second traffic routes are sorted as "route C, route B and route A" based on the adjusted route scores, and the first traffic route includes route D and route E, wherein the route scores of route D and route E are 24 and 19 respectively, then the first traffic route is sorted as "route E, route D" based on the route scores, and the sorted second traffic route and the sorted first traffic route are integrated in the order of the corresponding adjusted route scores and route scores from small to large to obtain the integrated traffic route "route C, route E, route B, route D, route A", and the top 20% of the traffic routes in the integrated traffic routes are selected as recommended routes, then route C and route E are selected as recommended routes.

[0120] In one embodiment, the process of a computer device displaying a recommended route, or pushing a recommended route to a terminal for display, specifically includes the following steps: obtaining a vehicle tag of a target object; sorting the recommended routes in a sorting manner that matches the vehicle tag; displaying the sorted recommended routes, or pushing the sorted recommended routes to a terminal for display.

[0121] Among them, the target object is the object that triggers the route recommendation request, and the transportation tool label is used to characterize the travel habits of the transportation object. For example, if the target object likes a travel method that requires less walking, then the transportation tool label is less walking; if the target object likes a travel method that requires less time, then the transportation tool label is short time; if the target object likes a travel method that requires less cost, then the transportation tool label is low cost.

[0122] Specifically, after obtaining the recommended route, the computer device sorts the recommended routes in a sorting manner that matches the transportation tool label to obtain the sorted recommended routes. When the computer device is a terminal, the sorted recommended routes are directly displayed. When the computer device is a server, the sorted recommended routes are pushed to the sending terminal of the route recommendation request for display.

[0123] In the above embodiment, the computer device obtains at least two transportation routes and route scores corresponding to the transportation routes; the transportation routes include a first transportation route based on public transportation and a second transportation route based on public transportation and non-public transportation; based on the transportation coefficients corresponding to public transportation and non-public transportation, the comprehensive transportation coefficient of the second transportation route is determined; according to the comprehensive transportation coefficient and the route score of the second transportation route, the second transportation route is sorted; and, according to the route score of the first transportation route, the first transportation route is sorted so that the high-quality transportation routes are sorted first, so that the recommended sorted transportation routes can better meet the timeliness requirements of the user's travel.

[0124] In one embodiment, the cost information is time cost, and the process of a computer device determining a route score corresponding to a traffic route based on the means of transportation corresponding to the traffic route specifically includes: obtaining the road sections involved in the traffic route and the means of transportation corresponding to each road section; determining the section time corresponding to each road section based on the obtained means of transportation; determining the route time of the traffic route based on the section time; and determining the route score corresponding to the traffic route based on the route time.

[0125] Specifically, after obtaining the road sections involved in any traffic route and the vehicles corresponding to each section, the computer device determines the distance corresponding to each section and the average driving speed of the corresponding vehicles, and estimates the section time required to pass the section based on the distance of the section and the average driving speed of the corresponding vehicles. After estimating the section time of each section in the traffic route, the section time of each section is added together to determine the route time of the traffic route, and the route score corresponding to the traffic route is determined according to the route time.

[0126] For example, traffic route 1 includes section A and section B. The distance of section A is m meters, and the distance of section B is n meters. The means of transportation corresponding to section A is a bus, and the means of transportation corresponding to section B is a bicycle. The average speed of the bus is a meters / minute, and the average speed of the bicycle is b meters / minute. It is estimated that the time required to pass section A by bus is m / a minutes, and the time required to pass section B by bicycle is n / b minutes. The route time of this traffic route is m / a minutes + n / b minutes, and the route score corresponding to the traffic route is determined according to the route time m / a minutes + n / b minutes.

[0127] In one embodiment, after obtaining the route time of the traffic route, the computer device may directly determine the route time as the route score corresponding to the traffic route. For example, if the route time of the traffic route is 45 minutes, the route score of the traffic route is directly determined to be 45.

[0128] In the above embodiment, the computer device obtains the road sections involved in the traffic route and the transportation tools corresponding to each road section, determines the road section time corresponding to each road section based on the obtained transportation tools, and determines the route time of the traffic route according to the road section time, so that the route score corresponding to the traffic route can be determined according to the route time, and then the traffic routes can be sorted based on the route scores, so that high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0129] In one embodiment, the cost information is the fee cost, and the process of the computer device determining the route score corresponding to the traffic route based on the transportation tools corresponding to the traffic route specifically includes: obtaining the road sections involved in the traffic route and the transportation tools corresponding to each road section; determining the section fees corresponding to each road section based on the obtained transportation tools; determining the route fee of the traffic route according to the section fees; and determining the route score corresponding to the traffic route according to the route fees.

[0130] Specifically, after obtaining the road sections involved in any traffic route and the transportation tools corresponding to each road section, the computer equipment determines the corresponding billing method for each transportation tool, and estimates the section fee required to pass the road section using the corresponding transportation tool according to the corresponding billing method. After estimating the section fees of each road section in the traffic route, the sum of the section fees of each road section is added together to determine the route fee of the traffic route, and the route score corresponding to the traffic route is determined based on the route fee.

[0131] For example, traffic route 1 includes section A and section B. The distance of section A is m meters, and the distance of section B is n meters. The means of transportation corresponding to section A is bus, and the means of transportation corresponding to section B is bicycle. The bus fare is 2 yuan, the bicycle fare is c yuan per minute, and the average speed of the bicycle is b meters / minute. It is estimated that the section fee required to use the bus to pass section A is 2 yuan, and the section fee required to use the bicycle to pass section B is nc / b yuan. The route fee of the traffic route is 2 yuan + nc / b yuan, and the route score corresponding to the traffic route is determined based on the route fee of 2 yuan + nc / b yuan.

[0132] In one embodiment, after obtaining the route fee of the traffic route, the computer device may directly determine the route fee as the route score corresponding to the traffic route. For example, if the route fee of the traffic route is 10 yuan, the route score of the traffic route is directly determined to be 10.

[0133] In the above embodiment, the computer device obtains the road sections involved in the traffic route and the transportation tools corresponding to each road section; determines the road section fees corresponding to each road section based on the obtained transportation tools; determines the route fee of the traffic route according to the road section fees; thereby determining the route score corresponding to the traffic route according to the route fee, and then sorting the traffic routes based on the route scores, so that high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0134] In one embodiment, the cost information is time cost and expense cost. After calculating the route time and route cost of the transportation route, the computer device obtains the time weight corresponding to the route time and the expense weight corresponding to the route cost, and determines the route score corresponding to the transportation route based on the route time, route cost, time weight and expense weight of the transportation route.

[0135] Specifically, the computer device can determine the first route score based on the route time, determine the second route score based on the route cost, and weighted sum the first route score and the second route score based on the time weight and the cost weight, and determine the weighted sum result as the route score corresponding to the traffic route.

[0136] For example, the first route score of the traffic route is p, the second route score of the traffic route is q, the time weight corresponding to the route time is λ1, and the cost weight corresponding to the route cost is λ2, then the route score corresponding to the traffic route is λ1p+λ2q.

[0137] In the above embodiment, the computer device determines the route score corresponding to the traffic route according to the route cost and the route time, and then sorts the traffic routes based on the route score, so that the high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0138] In one embodiment, S204 specifically includes the following steps: obtaining traffic coefficients of public transportation and non-public transportation under the target traffic model; determining the model traffic coefficient of the second traffic route under the target traffic model based on the traffic coefficients; and determining the comprehensive traffic coefficient of the second traffic route based on the model traffic coefficients.

[0139] The target traffic model is used to construct the traffic coefficient corresponding to each mode of transportation, and the target traffic model includes at least one of a city model, a congestion model and an origin-destination model.

[0140] The city model is constructed based on at least one of the number of transportation vehicles in the city and the usage of each transportation vehicle in the city.

[0141] Referring to the correspondence between the number of vehicles and the traffic coefficient values ​​of the city shown in the table below, in a certain city, for any vehicle, if the number of the vehicle is 0, it is determined that under the city model corresponding to the city, the traffic coefficient of the vehicle is 0; if the number of the vehicle is greater than 0 and less than the number threshold corresponding to the vehicle, that is, it indicates that the number of the vehicle is average, then it is determined that under the city model corresponding to the city, the traffic coefficient of the vehicle is 0.5; if the number of the vehicle is greater than the number threshold corresponding to the vehicle, that is, it indicates that the number of the vehicle is large, then it is determined that under the city model corresponding to the city, the traffic coefficient of the vehicle is 1. As shown in Table 3 below, it is the traffic coefficient of each vehicle under the city model of three cities in one embodiment.

[0142] Table 2 Comparison table of the number of transportation tools and traffic coefficients under the urban model

[0143]

[0144] Table 3 Comparison of transportation tools and traffic coefficients under the urban model

[0145]

[0146]

[0147] In one embodiment, the city model is constructed based on the number of transportation vehicles in the city and the usage of each transportation vehicle in the city. Specifically, the initial city model is constructed based on the number of transportation vehicles in the city, and then the initial city model is adjusted in combination with the usage of each transportation vehicle in the city, thereby obtaining a constructed city model, wherein adjusting the initial city model refers to adjusting the initial traffic coefficient of each transportation vehicle. For example, the initial city model constructed based on the number of transportation vehicles in city C is shown in Table 3, and then the number of users corresponding to each transportation vehicle is obtained by analyzing the log data of user travel in city C, and then the traffic coefficient of each transportation vehicle is adjusted based on the number of users corresponding to each transportation vehicle, thereby obtaining an updated city model of city C, as shown in Table 4 below:

[0148] Table 4 Comparison of transportation tools and traffic coefficients under the urban model of city C

[0149] Traffic coefficient / city C Initial Value Update Value FERRY SERVICE 0 0 Maglev 0 0 subway 0.5 1 bicycle 1 1 Public transportation 1 0.5 Taxi 1 0.5

[0150] The congestion model is constructed based on the congestion of vehicles at different times. For example, a day or a year is divided into peak hours, normal hours and transitional hours, and the traffic coefficients corresponding to vehicles in different time periods can be different. The transitional period is the period between the peak hours and the normal hours. For example, 7 to 9 and 18 to 20 are peak hours, and 11 to 13 are normal hours, and 7 to 11 and 13 to 18 are transitional periods; for example, holidays in a year are divided into peak hours, the two days before and after holidays are divided into transitional periods, and the time outside the peak hours and transitional periods in a year is divided into normal hours.

[0151] It should be noted that for different means of transportation, the corresponding peak hours, normal hours and transition periods may be different. For example, the operating hours of buses, subways and taxis are different in a day, so the corresponding peak hours, normal hours and transition periods may be different.

[0152] Table 5 below shows a congestion model in an embodiment. The traffic coefficients corresponding to various transportation tools at different times of the day in the congestion model are shown in the following table.

[0153] Table 5 Comparison table of traffic coefficients and departure time of transportation tools under the congestion model

[0154] Traffic coefficient / time period Normal time peak hours Transition period FERRY SERVICE 1 0 Linear change between 1 and 0 Maglev 0 1 Linear change between 0 and 1 subway 0.5 1 Linear variation between 0.5 and 1 bicycle 1 0 Linear change between 1 and 0 Public transportation 1 0 Linear change between 1 and 0 Taxi 1 0 Linear change between 1 and 0

[0155] Among them, for any means of transportation, the value of its traffic coefficient in the transition period changes linearly between the corresponding traffic coefficient in the ordinary period and the traffic coefficient in the peak period. For example, under the congestion model, the peak period corresponding to taxi is from 7 to 9 o'clock, the transition period is from 6 to 7 o'clock and from 9 to 10 o'clock, and the ordinary period is before 6 o'clock and after 10 o'clock. At time t, the traffic coefficient corresponding to taxi is shown in the following formula (2):

[0156]

[0157] Table 6 below shows a congestion model in another embodiment. The starting point or end point corresponding to the congestion model is prone to congestion during holidays. For example, the starting point or end point is a large scenic spot. The traffic coefficients corresponding to various means of transportation in the congestion model at different times of the year are shown in the following table:

[0158] Table 6 Comparison table of traffic coefficients and departure time of transportation tools under the congestion model

[0159]

[0160] The start-end model is constructed based on the properties of the start or end point of the traffic route. For example, if the start or midpoint is a transportation hub such as an airport or a station, then taking a taxi or subway is better. If the start or end point is a pier, then the ferry is better. If the bicycle parking spot near the start or midpoint is far away or there are no bicycles available, then the bicycle method should be reduced or eliminated. As shown in Table 7 below, it is a start-end model in an embodiment. The start and end points involved in the start-end model are airports and high-speed rail stations. The traffic coefficients corresponding to each means of transportation at the corresponding start or end point in the start-end model are shown in the following table:

[0161] Table 7 Comparison table of traffic coefficients and starting and ending points of transportation tools under the starting and ending point model

[0162] Traffic coefficient / starting and ending point Airport High-speed rail Remark FERRY SERVICE 0 0 Very few people take the ferry to the airport or high-speed rail. Maglev 0.5 0 There is no maglev nearby subway 1 1 Many people use the subway to connect to the airport and high-speed rail. bicycle 0 0 There is a bicycle parking spot nearby Public transportation 0.5 0.2 Airport shuttle Taxi 1 1

[0163] In the above embodiment, the computer device obtains the traffic coefficient of the transportation tool under the target traffic model; based on the traffic coefficient, determines the model traffic coefficient of the second traffic route under the target traffic model; thereby, the comprehensive traffic coefficient of the second traffic route can be determined based on the model traffic coefficient, and then the traffic routes are sorted based on the comprehensive traffic coefficient and the route score, so that the high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0164] In one embodiment, the process of determining the model traffic coefficient of the second traffic route under the target traffic model based on the traffic coefficient by a computer device includes the following steps: obtaining the number of people entering and exiting each traffic station in the second traffic route, and the popular sections in the traffic route that meet preset conditions; adjusting the traffic coefficient based on the number of people entering and exiting and the popular sections; and determining the model traffic coefficient of the second traffic route under the target traffic model based on the adjusted traffic coefficient.

[0165] Among them, the traffic station is the intersection of two adjacent sections in the second traffic route. The preset condition can be a congestion condition. It can be understood that when there are too many people entering and exiting the traffic station, the traffic station is prone to congestion, and popular sections that meet the congestion conditions are prone to congestion, which will affect travel.

[0166] Specifically, after determining the traffic stations and popular road sections that are prone to congestion based on the number of people entering and exiting the station, obtain the transportation tools corresponding to the road sections to which the traffic stations and popular road sections belong, and reduce the traffic coefficients corresponding to the transportation tools to obtain the adjusted traffic coefficients. Based on the adjusted traffic coefficients, determine the model traffic coefficient of the second traffic route under the target traffic model.

[0167] In the above embodiment, the computer device obtains in real time the number of people entering and exiting each traffic station in the second traffic route, as well as the popular sections in the traffic route that meet preset conditions, and thereby adjusts the traffic coefficient based on the number of people entering and exiting and the popular sections. Based on the adjusted traffic coefficient, the model traffic coefficient of the second traffic route under the target traffic model is determined, so that the sorting of traffic routes based on the model traffic coefficient is more accurate, ensuring that high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0168] In one embodiment, the process of determining the model traffic coefficient of the second traffic route under the traffic model based on the traffic coefficient by the computer device includes the following steps: averaging the traffic coefficients of each transportation tool under the target traffic model, and determining the model traffic coefficient of the second traffic route under the target traffic model based on the averaging result.

[0169] Specifically, after the computer device determines the transportation tool corresponding to the traffic route, it obtains the target traffic model corresponding to the traffic route, and determines the traffic coefficient of each transportation tool corresponding to the traffic route under the target traffic model, averages the traffic coefficient of each transportation tool corresponding to the traffic route under the target traffic model, and determines the model traffic coefficient of the second traffic route under the target traffic model based on the averaging result.

[0170] In one embodiment, when the target traffic model is a city model, the traffic coefficients of each means of transportation under the city model are averaged to obtain the city model traffic coefficient; when the target traffic model is a congestion model, the traffic coefficients of each means of transportation under the congestion model are averaged to obtain the congestion model traffic coefficient; when the target traffic model is a start-end model, the traffic coefficients of each means of transportation under the start-end model are averaged to obtain the start-end model traffic coefficient; wherein the traffic coefficients corresponding to the means of transportation under different target traffic models are different.

[0171] Referring to Table 4 below, assuming that traffic route 1 of city C is the first traffic route, and the corresponding means of transportation are bus and subway, and traffic route 2 of city C is the second traffic route, and the corresponding means of transportation are subway and taxi, then for traffic route 1, the traffic coefficient of the bus under the city model is 0.5, and the traffic coefficient of the subway is 1, then the sum of the traffic coefficients of the traffic route 1 under the city model is 0.5+1=1.5, and the traffic coefficient of the city model corresponding to the traffic route 1 is 0.75; for traffic route 2, the traffic coefficient of the subway corresponding to the traffic route 2 is 1, and the traffic coefficient of the taxi is 0.5, then the sum of the traffic coefficients of the traffic route 2 under the city model is 1+0.5=1.5, and the traffic coefficient of the city model corresponding to the traffic route 2 is 0.75.

[0172] In one embodiment, when the transportation means corresponding to the traffic route is bus, subway, ferry, maglev, taxi, or bicycle, and when the target traffic model is a city model, the corresponding relationship between each transportation means of the traffic route and the traffic coefficient under the city model is represented as follows:

[0173] City model (ferry, maglev, subway, bicycle, bus, taxi) = (cb, cm, cs, cc, cg, cd)

[0174] Among them, "cb, cm, cs, cc, cg, cd" are the traffic coefficients corresponding to bus, subway, ferry, maglev, taxi, and bicycle in the city model. The city model traffic coefficient C of this traffic route in the city model is:

[0175]

[0176] When the target traffic model is a congestion model, the corresponding relationship between each traffic tool of the traffic route and the traffic coefficient under the congestion model is represented as follows:

[0177] Crowding model (ferry, maglev, subway, bicycle, bus, taxi) = (yb, ym, ys, yc, yg, yd)

[0178] Among them, "yb, ym, ys, yc, yg, yd" are the traffic coefficients corresponding to bus, subway, ferry, maglev, taxi, and bicycle under the congestion model. The traffic coefficient Y of the traffic route in the congestion model is:

[0179]

[0180] When the target traffic model is the start-end model, the corresponding relationship between each mode of transportation on the traffic route and the traffic coefficient under the start-end model is as follows:

[0181] Origin and destination model (ferry, maglev, subway, bicycle, bus, taxi) = (sb, sm, ss, sc, sg, sd)

[0182] Among them, "sb, sm, ss, sc, sg, sd" are the traffic coefficients corresponding to bus, subway, ferry, maglev, taxi, and bicycle in the start-end model. The traffic coefficient S of the start-end model of the traffic route is:

[0183]

[0184] In the above embodiment, the computer device averages the traffic coefficients of various transportation tools under the target traffic model, and determines the model traffic coefficient of the second traffic route under the target traffic model based on the average result, so that the sorting of traffic routes based on the model traffic coefficients is more accurate, ensuring that high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0185] In one embodiment, the process of determining the comprehensive traffic coefficient of the second traffic route based on the model traffic coefficient by a computer device specifically includes the following steps: summing at least one of the city model traffic coefficient, the congestion model traffic coefficient and the start-end point model traffic coefficient to obtain a summation result; and determining the comprehensive traffic coefficient of the second traffic route based on the summation result.

[0186] Specifically, when the target traffic model is any one of the city model, the congestion model and the start-end model, the model traffic coefficient of the traffic route under the city model, the congestion model or the start-end model is directly determined as the comprehensive traffic coefficient of the traffic route; when the target traffic model is any two of the city model, the congestion model and the start-end model, the sum of the model traffic coefficients of the traffic route under the any two target traffic models is directly determined as the comprehensive traffic coefficient of the traffic route; when the target traffic model is the city model, the congestion model and the start-end model, the sum of the model traffic coefficients of the traffic route under the city model, the congestion model and the start-end model is directly determined as the comprehensive traffic coefficient of the traffic route.

[0187] In the above embodiment, the computer device obtains a summation result by summing at least one of the city model traffic coefficient, the congestion model traffic coefficient and the start-end point model traffic coefficient, and determines the comprehensive traffic coefficient of the second traffic route based on the summation result, so that the sorting of traffic routes based on the comprehensive traffic coefficient is more accurate, ensuring that high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0188] In one embodiment, the process of a computer device obtaining a traffic coefficient of a vehicle under a target traffic model includes: when the target traffic model is a congestion model, obtaining a departure time; and determining a traffic coefficient of at least one vehicle under the congestion model based on the departure time.

[0189] The traffic coefficient corresponding to each mode of transportation in the congestion model is related to time, such as the congestion model represented by formula (2).

[0190] Specifically, the route recommendation request also carries the departure time. When the target traffic model is a congestion model, the computer device extracts the departure time and the corresponding relationship between the departure time and the traffic coefficient under the congestion model from the route recommendation request, and determines the traffic coefficient corresponding to each means of transportation at the departure time.

[0191] For example, the corresponding relationship between the departure time of taking a taxi and the traffic coefficient under the congestion model is shown in formula (2). Based on this corresponding relationship, the traffic coefficient f(t) of taking a taxi under the congestion model at the departure time t can be determined.

[0192] In the above embodiment, when the target traffic model is a congestion model, the computer device obtains the departure time, and based on the departure time, determines the traffic coefficient of at least one transportation tool under the congestion model, so that the obtained traffic coefficient is more accurate, so that the route score can be adjusted based on the traffic coefficient, so that the adjusted route score is more accurate, and then the sorting of traffic routes based on the adjusted route score is more accurate, ensuring that high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0193] In one embodiment, the process of sorting the first traffic route by a computer device according to the route score of the first traffic route includes the following steps: determining the public transportation tools involved in the first traffic route; determining the route adjustment coefficient of the first traffic route based on the traffic coefficient of the public transportation tools; adjusting the route score of the first traffic route according to the route adjustment coefficient; and sorting the first traffic route according to the adjusted route score.

[0194] The route adjustment coefficient of the first traffic route is the comprehensive traffic coefficient of the first traffic route.

[0195] Specifically, after obtaining the first traffic route, the computer device obtains the transportation tools corresponding to the Luxuan and each road section involved in the first traffic route, which are public transportation tools, and obtains the traffic coefficients corresponding to each transportation tool. The traffic coefficients of each transportation tool corresponding to the traffic route are summed to obtain the comprehensive traffic coefficients of each first traffic route. The comprehensive traffic coefficient of the first traffic route can also be called the route adjustment coefficient. The route score of the first traffic route is adjusted according to the route adjustment coefficient; the first traffic routes are sorted according to the adjusted route scores. Specifically, the route adjustment formula shown in formula (2) can be used to adjust the route score of the first traffic route, and the sorting can be descending or ascending according to the size of the adjusted route score.

[0196] In the above embodiment, the computer device can also adjust the route score of the first traffic route to obtain the route score of the adjustment week, and then sort the first traffic routes based on the adjusted route scores, so that high-quality traffic routes are sorted first, so that the recommended sorted traffic routes can better meet the timeliness requirements of the user's travel.

[0197] In one embodiment, Figure 3 As shown, a method for recommending a traffic route is also provided, and the method is applied to Figure 1 The computer device (terminal or server) in the example is used to illustrate, including the following steps:

[0198] S302: Obtain at least two traffic routes and route scores corresponding to the traffic routes.

[0199] S304: Determine the comprehensive traffic coefficient of each traffic route based on the traffic coefficient corresponding to the transportation tools of each traffic route.

[0200] S306, adjusting the route score of each traffic route according to the comprehensive traffic coefficient of each traffic route to obtain the adjusted route score.

[0201] S308: sorting the traffic routes according to the adjusted route scores.

[0202] S310, selecting a traffic route that meets the ranking from the sorted traffic routes as a recommended route, and recommending the recommended route.

[0203] Figure 4A flowchart of a route recommendation method for an existing public transportation travel mode in one embodiment is shown. The existing route recommendation method usually uses a public transportation route algorithm to calculate a public transportation route, and uses a multi-tool route algorithm to calculate a multi-tool route. After calculating the public transportation route and the multi-tool route, the route time is calculated according to the distance of each route, and the ranking score is calculated based on the route time. The sorted transportation routes are directly sorted based on the ranking score, and the transportation routes with the lowest ranking are deleted, so as to realize the exposure of a limited number of multi-tool routes and public transportation routes. However, this route recommendation method only mechanically limits the sorting position and the number of exposure of multiple transportation tools, and the limited number of multi-tool routes exposed may not be the best. For example, refer to Figure 5 The recommended result diagram from Building A to Square B is shown in Figure 6 The route diagram from Building A to Square B is shown in the figure. Figure 5 It can be seen that there are fewer multi-tool route options after getting off the ferry. Figure 6 It can be seen that after getting off the ferry, users can choose to take a weather or taxi to Square B (the dotted line in the figure), and Figure 5 The recommendation results show that no cycling or taxi options are recommended.

[0204] The present application provides an application scenario, and the application scenario applies the above-mentioned traffic route recommendation method. Specifically, the application of the traffic route recommendation in this application scenario is as follows: Figure 7 The flowchart of the route recommendation method shown is as follows: the route recommendation method obtains at least two transportation routes and route scores corresponding to the transportation routes; the transportation routes include bus routes based on public transportation and multi-tool routes based on public transportation and non-public transportation; based on the transportation coefficients of public transportation and non-public transportation under the city model, congestion model and start-end model, the comprehensive transportation coefficient of the multi-tool route is determined, and the multi-tool routes are sorted according to the comprehensive transportation coefficient and the route scores of the multi-tool routes; and the bus routes are sorted according to the route scores of the bus routes; the sorted multi-tool routes and bus routes are integrated and output, and finally multiple multi-tool routes and multiple bus routes are output, so that high-quality multi-tool routes can be revealed.

[0205] Among them, the traffic coefficient of each mode of transportation under the city model, congestion model and start-end model can be adjusted offline or online according to the historical traffic conditions or actual traffic conditions of the cities where the start and end points are located, the departure time, and the transportation stations involved in the start and end points. For example, in the offline stage, the city model and congestion model are established. The city model contains data on ferries, maglevs, and subways, and the congestion model contains data on peak hours, weekdays, and holidays; the start-end model is established online, including data on airports, high-speed railways, large transportation hubs, and bicycle parking spots; these data can be generated using artificial weights and the heat mined from user log big data. After using the route planning algorithm to calculate multiple multi-tool routes, the route scores of all routes are recalculated by adding city models, congestion models, and start-end models.

[0206] For example, if a user initiates a route recommendation request near a pier, or needs to go to the vicinity of a pier, the user may prefer to take a ferry. When there is no ferry plan, the user can be recommended to ride a bicycle or take a taxi, that is, the traffic coefficients of bicycles and taxis are increased. If the nearby bicycle point is far away or there are no bicycles available, the use of cycling should be reduced or eliminated, that is, the traffic coefficient of bicycles should be lowered.

[0207] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0208] Based on the same inventive concept, the embodiment of the present application also provides a traffic route recommendation device for implementing the traffic route recommendation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more traffic route recommendation device embodiments provided below can refer to the limitations of the traffic route recommendation method above, and will not be repeated here.

[0209] In one embodiment, Figure 8 As shown, a traffic route recommendation device is provided, comprising: a traffic route acquisition module 802, a comprehensive traffic coefficient determination module 804, a route sorting module 806 and a route recommendation module 808, wherein:

[0210] The traffic route acquisition module 802 is used to acquire at least two traffic routes and route scores corresponding to the traffic routes; the traffic routes include a first traffic route based on public transportation and a second traffic route based on public transportation and non-public transportation.

[0211] The comprehensive traffic coefficient determination module 804 is used to determine the comprehensive traffic coefficient of the second traffic route based on the traffic coefficients corresponding to public transportation vehicles and non-public transportation vehicles.

[0212] The route sorting module 806 is used to sort the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and to sort the first traffic routes according to the route score of the first traffic routes.

[0213] The route recommendation module 808 is used to recommend the sorted second traffic route and the first traffic route as recommended routes.

[0214] In the above embodiment, at least two transportation routes and route scores corresponding to the transportation routes are obtained; the transportation routes include a first transportation route based on public transportation and a second transportation route based on public transportation and non-public transportation; based on the transportation coefficients corresponding to public transportation and non-public transportation, the comprehensive transportation coefficient of the second transportation route is determined; according to the comprehensive transportation coefficient and the route score of the second transportation route, the second transportation route is sorted; and, according to the route score of the first transportation route, the first transportation route is sorted so that the high-quality transportation routes are sorted first, so that the recommended sorted transportation routes can better meet the timeliness requirements of the user's travel.

[0215] In one embodiment, the traffic route acquisition module 802 is further used to: acquire route starting point information and route end point information; determine at least two traffic routes based on the route starting point information and route end point information; and determine route scores corresponding to the traffic routes based on the transportation tools corresponding to the traffic routes.

[0216] In one embodiment, the traffic route acquisition module 802 is also used to: acquire the road sections involved in the traffic route and the means of transportation corresponding to each road section; determine the road section time corresponding to each road section based on the acquired means of transportation; determine the route time of the traffic route according to the road section time; and determine the route score corresponding to the traffic route according to the route time.

[0217] In one embodiment, the comprehensive traffic coefficient determination module 804 is further used to: obtain the traffic coefficients of public transportation and non-public transportation under the target traffic model; determine the model traffic coefficient of the second traffic route under the target traffic model based on the traffic coefficients; and determine the comprehensive traffic coefficient of the second traffic route based on the model traffic coefficients.

[0218] In one embodiment, the comprehensive traffic coefficient determination module 804 is also used to: obtain the number of people entering and exiting each traffic station in the second traffic route, and the popular sections in the traffic route that meet preset conditions; adjust the traffic coefficient based on the number of people entering and exiting and the popular sections; and determine the model traffic coefficient of the second traffic route under the target traffic model based on the adjusted traffic coefficient.

[0219] In one embodiment, the target traffic model includes at least one of a city model, a congestion model and a start-end model; the comprehensive traffic coefficient determination module 804 is further used to: average the traffic coefficients of each means of transportation under the city model to obtain the city model traffic coefficient; average the traffic coefficients of each means of transportation under the congestion model to obtain the congestion model traffic coefficient; average the traffic coefficients of each means of transportation under the start-end model to obtain the start-end model traffic coefficient; wherein the traffic coefficients corresponding to the means of transportation under different target traffic models are different.

[0220] In one embodiment, the comprehensive traffic coefficient determination module 804 is further used to: sum at least one of the city model traffic coefficient, the congestion model traffic coefficient and the start-end point model traffic coefficient to obtain a sum result; and determine the comprehensive traffic coefficient of the second traffic route based on the sum result.

[0221] In one embodiment, the comprehensive traffic coefficient determination module 804 is further used to: when the target traffic model is a congestion model, obtain the departure time; and determine the traffic coefficient of at least one transportation tool under the congestion model based on the departure time.

[0222] In one embodiment, the route sorting module 806 is further used to: adjust the route score of the second traffic route according to the comprehensive traffic coefficient to obtain an adjusted route score; and sort the second traffic route according to the adjusted route score.

[0223] In one embodiment, the route sorting module 806 is further used to: determine the public transportation tools involved in the first transportation route; determine the route adjustment coefficient of the first transportation route based on the traffic coefficient of the public transportation tools; adjust the route score of the first transportation route according to the route adjustment coefficient; and sort the first transportation route according to the adjusted route score.

[0224] In one embodiment, the route recommendation module 808 is further used to: determine the integration order between the sorted second traffic route and the first traffic route according to the order of magnitude between the route score of the first traffic route and the adjusted route score of the second traffic route; the adjusted route score is the route score obtained by adjusting the route score of the second traffic route according to the comprehensive traffic coefficient; integrate the sorted second traffic route and the first traffic route according to the integration order to obtain an integrated traffic route; select a route whose ranking meets the ranking condition from the integrated traffic routes as a recommended route; display the recommended route, or push the recommended route to the terminal for display.

[0225] In one embodiment, the route recommendation module 808 is further used to: obtain the vehicle tag of the target object; sort the recommended routes according to the sorting method matching the vehicle tag; display the sorted recommended routes, or push the sorted recommended routes to the terminal for display.

[0226] Each module in the above-mentioned traffic route sorting device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0227] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store traffic data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for sorting traffic routes is implemented.

[0228] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.10As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for sorting traffic routes is implemented. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse, etc.

[0229] Those skilled in the art will understand that Fig. 9 or Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0230] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0231] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0232] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0233] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0234] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0235] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0236] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for recommending a traffic route, characterized in that: The method comprises: Acquire at least two transportation routes and route scores corresponding to the transportation routes; the transportation routes include a first transportation route based on public transportation and a second transportation route based on the public transportation and non-public transportation; Obtaining each means of transportation corresponding to the second transportation route, obtaining a traffic coefficient corresponding to each means of transportation, averaging the traffic coefficients corresponding to each means of transportation, and obtaining a comprehensive traffic coefficient of the second transportation route; the traffic coefficient is a coefficient used to adjust the route score; the comprehensive traffic coefficient is a comprehensive value determined by comprehensively considering the traffic coefficients of multiple means of transportation; sorting the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and sorting the first traffic routes according to the route score of the first traffic routes; The sorted second traffic route and the first traffic route are recommended as recommended routes.

2. The method according to claim 1, characterized in that The obtaining of at least two traffic routes and route scores corresponding to the traffic routes includes: Get route starting point information and route end point information; Determine at least two traffic routes based on the route starting point information and the route end point information; Based on the transportation tool corresponding to the transportation route, a route score corresponding to the transportation route is determined.

3. The method according to claim 2, characterized in that The determining, based on the transportation tool corresponding to the transportation route, a route score corresponding to the transportation route comprises: Obtaining the road sections involved in the traffic route and the transportation tools corresponding to each of the road sections; Determine the road section time corresponding to each road section based on the acquired transportation means; Determining the route time of the traffic route according to the road section time; A route score corresponding to the traffic route is determined according to the route time.

4. The method according to claim 1, characterized in that: The obtaining of the traffic coefficient corresponding to each of the transportation means comprises: Obtaining traffic coefficients of the public transportation vehicle and the non-public transportation vehicle under a target traffic model; The averaging of the traffic coefficients corresponding to the various transportation means to obtain the comprehensive traffic coefficient of the second transportation route includes: averaging the traffic coefficients of the various transportation tools under the target traffic model to obtain a model traffic coefficient of the second traffic route under the target traffic model; A comprehensive traffic coefficient of the second traffic route is determined based on the model traffic coefficient.

5. The method according to claim 4, characterized in that The averaging of the traffic coefficients of the various transportation tools under the target traffic model to obtain the model traffic coefficient of the second traffic route under the target traffic model includes: Obtaining the number of people entering and exiting each transportation station in the second transportation route, as well as popular sections of the transportation route that meet preset conditions; Adjusting the traffic coefficient based on the number of people entering and exiting the station and the popular road section; The adjusted traffic coefficients of the various transportation tools under the target traffic model are averaged to obtain a model traffic coefficient of the second traffic route under the target traffic model.

6. The method according to claim 4, characterized in that The target traffic model includes at least one of a city model, a congestion model, and a start-end model; averaging the traffic coefficients of the various transportation tools under the target traffic model to obtain the model traffic coefficient of the second traffic route under the target traffic model includes: Averaging the traffic coefficients of the various transportation tools under the city model to obtain a city model traffic coefficient; Averaging the traffic coefficients of the various transportation tools under the congestion model to obtain a traffic coefficient of the congestion model; Averaging the traffic coefficients of the various transportation tools under the start-end model to obtain the start-end model traffic coefficient; Among them, the traffic coefficients corresponding to the traffic tools under different target traffic models are different.

7. The method according to claim 6, characterized in that The determining the comprehensive traffic coefficient of the second traffic route based on the model traffic coefficient includes: Summing at least one of the city model traffic coefficient, the congestion model traffic coefficient and the start-end point model traffic coefficient to obtain a summation result; A comprehensive traffic coefficient of the second traffic route is determined based on the summation result.

8. The method according to claim 6, characterized in that The obtaining of the traffic coefficient of the vehicle under the target traffic model includes: When the target traffic model is a congestion model, obtaining a departure time; Based on the departure time, a traffic coefficient of at least one of the transportation tools under the congestion model is determined.

9. The method according to any one of claims 1 to 8, characterized in that: The step of sorting the second traffic routes according to the comprehensive traffic coefficient and the route scores of the second traffic routes comprises: adjusting the route score of the second traffic route according to the comprehensive traffic coefficient to obtain an adjusted route score; The second traffic routes are sorted according to the adjusted route scores.

10. The method according to any one of claims 1 to 8, characterized in that The sorting of the first traffic routes according to the route scores of the first traffic routes includes: determining the public transportation vehicles involved in the first transportation route; Determining a route adjustment coefficient of the first traffic route based on the traffic coefficient of the public transportation vehicle; adjusting the route score of the first traffic route according to the route adjustment coefficient; The first traffic routes are sorted according to the adjusted route scores.

11. The method according to any one of claims 1 to 8, characterized in that The step of recommending the sorted second traffic route and the first traffic route as recommended routes includes: Determining the integration order between the sorted second traffic route and the first traffic route according to the order of the route score of the first traffic route and the adjusted route score of the second traffic route; the adjusted route score is the route score obtained by adjusting the route score of the second traffic route according to the comprehensive traffic coefficient; Integrate the sorted second traffic route and the first traffic route according to the integration order to obtain an integrated traffic route; Among the integrated traffic routes, a route whose ranking meets the ranking condition is selected as a recommended route; the recommended route is displayed, or the recommended route is pushed to a terminal for display.

12. The method according to claim 11, characterized in that The displaying of the recommended route, or pushing the recommended route to a terminal for display, includes: Get the target object's transportation label; Sorting the recommended routes according to a sorting method matching the transportation tool tags; The sorted recommended routes are displayed, or the sorted recommended routes are pushed to a terminal for display.

13. A traffic route recommendation device, characterized in that: The device comprises: A traffic route acquisition module, used to acquire at least two traffic routes and route scores corresponding to the traffic routes; the traffic routes include a first traffic route based on public transportation and a second traffic route based on the public transportation and non-public transportation; a comprehensive traffic coefficient determination module, used to obtain each means of transportation corresponding to the second traffic route, obtain the traffic coefficient corresponding to each of the means of transportation, and average the traffic coefficients corresponding to each of the means of transportation to obtain the comprehensive traffic coefficient of the second traffic route; the traffic coefficient is a coefficient used to adjust the route score; the comprehensive traffic coefficient is a comprehensive value determined by comprehensively considering the traffic coefficients of multiple means of transportation; a route sorting module, configured to sort the second traffic routes according to the comprehensive traffic coefficient and the route score of the second traffic routes; and to sort the first traffic routes according to the route score of the first traffic routes; The route recommendation module is used to recommend the sorted second traffic route and the first traffic route as recommended routes.

14. The device according to claim 13, characterized in that The traffic route acquisition module is also used for: Get route starting point information and route end point information; Determine at least two traffic routes based on the route starting point information and the route end point information; Based on the transportation tool corresponding to the transportation route, a route score corresponding to the transportation route is determined.

15. The device according to claim 14, characterized in that The traffic route acquisition module is also used for: Obtaining the road sections involved in the traffic route and the transportation tools corresponding to each of the road sections; Determine the road section time corresponding to each road section based on the acquired transportation means; Determining the route time of the traffic route according to the road section time; A route score corresponding to the traffic route is determined according to the route time.

16. The device according to claim 13, characterized in that The comprehensive traffic coefficient determination module is also used for: Obtaining traffic coefficients of the public transportation vehicle and the non-public transportation vehicle under a target traffic model; averaging the traffic coefficients of the various transportation tools under the target traffic model to obtain a model traffic coefficient of the second traffic route under the target traffic model; A comprehensive traffic coefficient of the second traffic route is determined based on the model traffic coefficient.

17. The device according to claim 16, characterized in that The comprehensive traffic coefficient determination module is also used for: Obtaining the number of people entering and exiting each transportation station in the second transportation route, as well as popular sections of the transportation route that meet preset conditions; Adjusting the traffic coefficient based on the number of people entering and exiting the station and the popular road section; The adjusted traffic coefficients of the various transportation tools under the target traffic model are averaged to obtain a model traffic coefficient of the second traffic route under the target traffic model.

18. The device according to claim 16, characterized in that The target traffic model includes at least one of a city model, a congestion model and an origin-destination model; the comprehensive traffic coefficient determination module is further used to: Averaging the traffic coefficients of the various transportation tools under the city model to obtain a city model traffic coefficient; Averaging the traffic coefficients of the various transportation tools under the congestion model to obtain a traffic coefficient of the congestion model; Averaging the traffic coefficients of the various transportation tools under the start-end model to obtain the start-end model traffic coefficient; Among them, the traffic coefficients corresponding to the traffic tools under different target traffic models are different.

19. The device according to claim 18, characterized in that The comprehensive traffic coefficient determination module is also used for: Summing at least one of the city model traffic coefficient, the congestion model traffic coefficient and the start-end point model traffic coefficient to obtain a summation result; A comprehensive traffic coefficient of the second traffic route is determined based on the summation result.

20. The device according to claim 18, characterized in that The comprehensive traffic coefficient determination module is also used for: When the target traffic model is a congestion model, obtaining a departure time; Based on the departure time, a traffic coefficient of at least one of the transportation tools under the congestion model is determined.

21. The device according to any one of claims 13 to 20, characterized in that The route sorting module is also used for: adjusting the route score of the second traffic route according to the comprehensive traffic coefficient to obtain an adjusted route score; The second traffic routes are sorted according to the adjusted route scores.

22. The device according to any one of claims 13 to 20, characterized in that The route sorting module is also used for: determining the public transportation vehicles involved in the first transportation route; Determining a route adjustment coefficient of the first traffic route based on the traffic coefficient of the public transportation vehicle; adjusting the route score of the first traffic route according to the route adjustment coefficient; The first traffic routes are sorted according to the adjusted route scores.

23. The device according to any one of claims 13 to 20, characterized in that The route recommendation module is also used for: Determining the integration order between the sorted second traffic route and the first traffic route according to the order of the route score of the first traffic route and the adjusted route score of the second traffic route; the adjusted route score is the route score obtained by adjusting the route score of the second traffic route according to the comprehensive traffic coefficient; Integrate the sorted second traffic route and the first traffic route according to the integration order to obtain an integrated traffic route; Among the integrated traffic routes, a route whose ranking meets the ranking condition is selected as a recommended route; The recommended route is displayed, or the recommended route is pushed to a terminal for display.

24. The device according to claim 23, characterized in that The route recommendation module is also used for: Get the target object's transportation label; Sorting the recommended routes according to a sorting method matching the transportation tool tags; The sorted recommended routes are displayed, or the sorted recommended routes are pushed to a terminal for display.

25. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 12 are implemented.

26. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.

27. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.

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