Resource scheduling method and device for intelligent connected vehicle

Abstract

The present invention provides a resource scheduling method and device for intelligent networked vehicles, and relates to the field of vehicle scheduling technology. In this application, a user's vehicle request information set, user behavior information, and travel fare information are obtained; a first cost evaluation value is calculated according to each vehicle request information and the geographical location information of each resource domain, and the resource domains are arranged in ascending order according to the first cost evaluation value to obtain a first candidate center sequence; starting from the first resource domain in the first candidate center sequence, a second cost evaluation value is calculated based on each of the vehicle request information, user behavior information, and travel fare information; the first candidate center sequence is arranged in ascending order based on the second cost evaluation value to obtain a second candidate center sequence; resource scheduling matching is performed based on the second candidate center sequence and the vehicle request information set to obtain a vehicle resource scheduling plan, which comprehensively considers the costs of users and operators, and meets the personalized travel concerns of users and the efficiency of dispatching vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle scheduling, and in particular to a resource scheduling method and device for an intelligent networked vehicle. Background Art

[0002] With the continuous breakthroughs in new technologies in fields such as artificial intelligence and mobile communications, vehicle networks are booming. As the information carrier platform of the new generation of intelligent transportation systems, the Internet of Vehicles provides driving safety and road condition monitoring information for new applications such as autonomous driving. With the continuous development and popularization of autonomous driving technology, driverless online ride-hailing services are gradually becoming a reality. This new type of online ride-hailing service not only improves travel efficiency, but also reduces operating costs, providing passengers with a more convenient and economical travel option.

[0003] However, with the explosive growth of massive users, how to carry out personalized and high travel economic efficiency vehicle resource scheduling based on user needs is an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to provide a resource scheduling method and device for an intelligent connected vehicle to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present application provides a resource scheduling method for an intelligent connected vehicle, comprising:

[0006] The user's car request information set, user behavior information and travel fare information are obtained, wherein the car request information set contains at least one car request information, and the car request information contains at least information about the departure place, the destination, the number of travelers and the travel mode; a first cost evaluation value is calculated according to each car request information and the geographical location information of each resource domain, and the resource domains are arranged in ascending order according to the first cost evaluation value to obtain a first candidate center sequence, where the resource domain is an allocable vehicle resource constructed based on a preset geographical range; starting from the first resource domain in the first candidate center sequence, a second cost evaluation value is calculated based on each of the car request information, user behavior information and travel fare information; based on the second cost evaluation value, the first candidate center sequence is arranged in ascending order to obtain a second candidate center sequence; resource scheduling matching is performed based on the second candidate center sequence and the car request information set to obtain a car resource scheduling plan.

[0007] In a second aspect, the present application also provides a resource scheduling device for an intelligent connected vehicle, comprising an acquisition module, a first calculation module, a second calculation module, a sorting module and a scheduling module, wherein:

[0008] Acquisition module: used to obtain the user's car request information set, user behavior information and travel fare information. The car request information set contains at least one car request information, and the car request information contains at least information about the departure place, destination, number of travelers and travel mode;

[0009] A first calculation module: used to calculate a first cost evaluation value according to each vehicle request information and the geographical location information of each resource domain, and to arrange the resource domains in ascending order according to the first cost evaluation value to obtain a first candidate center sequence, where the resource domains are deployable vehicle resources constructed based on a preset geographical range;

[0010] A second calculation module: used to calculate a second cost evaluation value based on each of the vehicle request information, user behavior information and travel fare information, starting from the first resource domain in the first candidate center sequence;

[0011] Sorting module: used for arranging the first candidate center sequence in ascending order based on the second cost evaluation value to obtain a second candidate center sequence;

[0012] Scheduling module: used to perform resource scheduling matching based on the second candidate center sequence and the vehicle request information set to obtain a vehicle resource scheduling plan.

[0013] The beneficial effects of the present invention are:

[0014] In this application, from the perspective of the dispatching operator, the distance between the departure point of the car and the resource domain, travel risk, and congestion are comprehensively considered. The first cost evaluation value is calculated for each user, and then the resource domain is arranged in ascending order based on the first cost evaluation value, so that the resource domain that is close to the user's departure point, has a low travel risk, and has smooth traffic is arranged in the front. When the car sub-resource is subsequently dispatched, the first resource domain in the first candidate center sequence is used to dispatch the matching car resources, which not only reduces the risk and cost of dispatching the car, but also improves the efficiency of dispatching the car. On the basis of reducing the risk and cost of dispatching the car and improving the efficiency of dispatching the car, the second cost evaluation value is calculated from the user's perspective by comprehensively considering the cost required for the user's car use, the user's car use habits, and other factors to evaluate the travel value cost of the user's car use. Based on the user's travel cost, the first candidate center sequence is arranged in descending order by considering the different concerns of the user in a personalized way. Based on the personalized needs of the user, the resource domain with lower travel cost is placed in the front to obtain the second candidate center sequence to reduce the user's travel cost. Finally, according to the resource domain corresponding to each vehicle request information, the corresponding vehicle matching information is found from the corresponding second candidate center sequence to obtain a vehicle resource scheduling plan. This vehicle resource scheduling plan not only takes into account the operator's cost (including explicit cost and implicit cost), but also takes into account the user's travel cost, and also meets the user's personalized travel concerns and vehicle dispatch efficiency, thereby improving user satisfaction.

[0015] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flowchart of a resource scheduling method for an intelligent connected vehicle in an embodiment of the present invention;

[0018] Figure 2 A block diagram of a resource scheduling device for an intelligent connected vehicle in an embodiment of the present invention;

[0019] Figure 3 It is a block diagram of a resource scheduling device for an intelligent connected vehicle in an embodiment of the present invention.

[0020] Markings in the figure: 710-acquisition module; 720-first calculation module; 721-first subunit; 722-second subunit; 723-judgment unit; 724-classification unit; 725-third subunit; 726-fourth subunit; 727-fifth subunit; 730-second calculation module; 731-analysis unit; 732-sixth subunit; 733-seventh subunit; 734-eighth subunit; 740-sorting module; 750-scheduling module; 751-collection unit; 752-arrangement unit; 753-matching unit; 800-resource scheduling device of intelligent connected vehicle; 801-processor; 802-memory; 803-multimedia component; 804-I / O interface; 805-communication component. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0022] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0023] Embodiment 1:

[0024] See also Figure 1 , Figure 1 The flowchart of the resource scheduling method of the intelligent networked vehicle in this embodiment is shown. This embodiment provides a resource scheduling method of the intelligent networked vehicle, and the method includes step S1, step S2, step S3, step S4 and step S5.

[0025] Step S1, obtaining a user's car request information set, user behavior information and travel fare information, wherein the car request information set includes at least one car request information, and the car request information includes at least information on the departure place, destination, number of travelers and travel mode.

[0026] Furthermore, the resource domain construction method includes step S11, step S12, step S13 and step S14, wherein:

[0027] Step S11: Acquire a set of vehicle allocation areas, wherein each vehicle allocation area in the set of vehicle allocation areas corresponds to an administrative area of ​​the same level.

[0028] It can be understood that in this step, the vehicle allocation area is divided according to the level of administrative divisions. For example, different dispatching areas are divided at the city level. For example, Xi'an is one vehicle allocation area, Chengdu is another vehicle allocation area, and so on. All vehicle allocation areas constitute a vehicle allocation area set.

[0029] Step S12: Obtain the first geographic information of each unmanned vehicle to be dispatched.

[0030] Step S13, traverse the vehicle allocation area set to determine whether the first geographic information belongs to any of the vehicle allocation areas, and if so, assign the unmanned vehicle to be dispatched to the corresponding vehicle allocation area to obtain a resource domain.

[0031] It can be understood that in this step, the vehicle allocation area set is traversed and matched according to the first geographic information of each unmanned vehicle to be dispatched, and the unmanned vehicle to be dispatched is classified to obtain a resource domain. For example, the first geographic information of the unmanned vehicle X to be dispatched is the Beilin District of Xi'an City. Based on the first geographic information, the belonging relationship is judged from the first vehicle allocation area in the vehicle allocation area set. If the first geographic information belongs to the corresponding vehicle allocation area of ​​Xi'an City, it is included in the vehicle allocation area to obtain a resource domain. If it does not belong, the belonging relationship is judged from the second vehicle allocation area in the vehicle allocation area set until the corresponding vehicle allocation area is found.

[0032] Step S14: acquiring the travel mode based on each resource domain, and classifying the travel mode to obtain a plurality of subdomains, wherein the travel mode at least includes hitchhiking, carpooling and exclusive use.

[0033] It can be understood that in this step, travel modes are obtained for the same resource domain, and the same travel mode is classified into the same category to obtain multiple subdomains.

[0034] Step S2, calculate a first cost evaluation value based on each of the vehicle request information and the geographic location information of each resource domain, and arrange the resource domains in ascending order according to the first cost evaluation value to obtain a first candidate center sequence, wherein the resource domains are deployable vehicle resources constructed based on a preset geographical range.

[0035] It can be understood that in this step, from the perspective of the dispatching operator, factors such as the distance between the departure point of the vehicle and the resource domain, travel risk, and congestion are comprehensively considered, and the first cost evaluation value is calculated for each user. Then, based on the first cost evaluation value, the resource domains are arranged in ascending order, so that the resource domains that are close to the user's departure point, have low travel risks, and have smooth traffic are arranged in the front. Subsequently, when the vehicle sub-resource scheduling is performed, the matching vehicle resources are dispatched from the first resource domain in the first candidate center sequence, which not only reduces the risk and cost of vehicle dispatch, but also improves the efficiency of vehicle dispatch.

[0036] Furthermore, the calculation method of the first cost evaluation value includes step S21, step S22 and step S23, wherein:

[0037] Step S21, based on the departure place and the destination corresponding to each of the vehicle use request information, determine the travel risk information and the first duration information corresponding to the vehicle use path; the travel risk information is the sum of the historical probability of public safety incidents occurring on the vehicle use path and the probability of traffic congestion.

[0038] It can be understood that in this step, based on the first total number of public safety incidents that occurred in the vehicle use path between the departure point and the destination in the vehicle use request information, the second total number of public safety incidents that occurred in the resource domain is queried at the same time, and the ratio of the first total number to the second total number is calculated as the travel risk information. The time required for the vehicle to travel between the departure point and the destination is the first time information. The traffic congestion probability is the ratio of the total number of people in the corresponding area of ​​the resource domain to the population mobility rate.

[0039] Step S22: based on the distance between the departure place and each of the resource domain center points.

[0040] Step S23: Obtain the first cost assessment value based on the travel risk information, the duration information and the distance calculation.

[0041] It can be understood that in this step, the first cost evaluation value is calculated according to formula (1):

[0042] A=ω1X+ω2Y+ω3Z (1)

[0043] Among them, A is the first cost assessment value; ω1, ω2 and ω3 are the corresponding weight values ​​of travel risk information, duration information and spacing, all between 0 and 1; X, Y and are travel risk information, duration information and spacing, respectively.

[0044] Step S3, starting from the first resource domain in the first candidate center sequence, a second cost evaluation value is calculated based on each of the vehicle request information, user behavior information and travel fare information.

[0045] It can be understood that in this step, on the basis of reducing the risk and cost of dispatching vehicles and improving the efficiency of dispatching vehicles, the second cost assessment value is calculated from the user's perspective by comprehensively considering factors such as the cost required for the user to use the vehicle and the user's vehicle usage habits, so as to evaluate the travel value cost of the user's vehicle use.

[0046] Furthermore, the calculation method of the second cost evaluation value includes step S31, step S32, step S33 and step S34, wherein:

[0047] Step S31: Analyze and determine a travel concern weight value set based on the user behavior information, wherein the travel concern weight value set at least includes the user's concern weight values ​​for travel time and cost.

[0048] It is understandable that in this step, statistics are collected based on all the user's car usage history information. For example, for the same destination involving multiple different routes (some of which may pass through highways), it can be determined whether the user prefers shorter travel time or higher cost.

[0049] Step S32: Obtain geographic information of the unmanned vehicle to be dispatched, and calculate second duration information based on the departure location information and the geographic information of the unmanned vehicle to be dispatched.

[0050] Step S33: obtaining travel fare information based on the vehicle usage path, the number of travelers and the travel mode.

[0051] It is understandable that in this step, the travel fare information is calculated based on the pricing rules of different taxi platforms, taking into account the route, number of travelers and travel mode. The pricing rules of the taxi platform can be Didi Hitch pricing rules, or AutoNavi carpool pricing rules, etc.

[0052] Step S34: Calculate based on the travel concern weight value set, the travel fare information and the second duration information to obtain a second cost evaluation value.

[0053] It can be understood that in this step, the second cost evaluation value is calculated according to formula (2):

[0054] B=αm+βn (2)

[0055] Among them, B is the second cost evaluation value; α and β are the user's concern values ​​for the travel fare information and the second duration information when traveling; m and n are the travel fare information and the second duration information respectively.

[0056] Step S4: Arrange the first candidate center sequence in ascending order based on the second cost evaluation value to obtain a second candidate center sequence.

[0057] It can be understood that in this step, based on the user's travel cost, the first candidate center sequence is arranged in descending order by personalized consideration of the user's different concerns, and based on the user's personalized needs, the resource domains with lower travel costs are placed at the front to obtain the second candidate center sequence to reduce the user's travel cost.

[0058] Step S5: performing resource scheduling matching based on the second candidate center sequence and the vehicle request information set to obtain a vehicle resource scheduling solution.

[0059] It can be understood that, in this step, according to the resource domain corresponding to each vehicle request information, the corresponding vehicle matching information is found from the corresponding second candidate center sequence to obtain the vehicle resource scheduling plan.

[0060] Furthermore, the above-mentioned method for confirming the vehicle resource scheduling plan includes steps S51, S52 and S53, wherein:

[0061] Step S51, obtaining the user's reputation value for riding a vehicle, wherein the reputation value is data determined based on the breach rate of the user's historical orders.

[0062] Step S52: Arrange the vehicle request information set based on the departure place, the credit value and the initiation time of each user's corresponding vehicle request information to obtain a user request list.

[0063] It can be understood that in this step, the initiation time of the car request information is arranged based on the time axis to obtain a first subsequence set, wherein each first subsequence corresponds to the car request information at the same time; then the user group is divided based on the user's departure place and the preset range from the resource domain center in each first subsequence to obtain a second subsequence set, wherein each second subsequence set is the car request information corresponding to the same spacing range in the same first subsequence; then the corresponding credit value is arranged in descending order based on each second subsequence set to obtain a third subsequence set, and the user request list is obtained based on all sequence sets on the time axis. In this application, considering the distance from the user's departure place to the dispatch center, the user's credit value and the time when the user initiates the request as an evaluation of the profit value of the car dispatch, the user request with a higher profit value of the car dispatch is placed in front of the response priority to achieve rapid turnover payment and improve user satisfaction.

[0064] Step S53: Based on the second candidate center sequence and the user request list, a dispatch request is made for each application vehicle, and the dispatch request is sent to the corresponding unmanned vehicle to be dispatched.

[0065] It can be understood that in this step, based on the order of the first subsequence, vehicle scheduling is first performed from each third subsequence in the first subsequence, and a one-to-one match is performed between the resource domain corresponding to the departure place of each second subsequence and the resource domain in the corresponding second selected center sequence, so as to obtain the vehicle scheduling plan requested by each user and form a scheduling request for the vehicle, and then send the scheduling request for the vehicle to the corresponding vehicle and execute the corresponding scheduling.

[0066] Embodiment 2:

[0067] See also Figure 2 , Figure 2 7 is a block diagram of a resource scheduling device for an intelligent networked vehicle according to an exemplary embodiment, including an acquisition module 710, a first calculation module 720, a second calculation module 730, a sorting module 740 and a scheduling module 750, wherein:

[0068] Acquisition module 710: used to acquire a user's car request information set, user behavior information and travel fare information, wherein the car request information set includes at least one car request information, and the car request information includes at least information on the departure place, the destination, the number of travelers and the travel mode;

[0069] A first calculation module 720 is used to calculate a first cost evaluation value according to each of the vehicle request information and the geographical location information of each resource domain, and to arrange the resource domains in ascending order according to the first cost evaluation value to obtain a first candidate center sequence, wherein the resource domains are deployable vehicle resources constructed based on a preset geographical range;

[0070] Preferably, the first calculation module 720 includes a first subunit 721, a second subunit 722, a judgment unit 723 and a classification unit 724, wherein:

[0071] The first subunit 721 is used to obtain a set of vehicle allocation areas, each of which corresponds to an administrative area of ​​the same level;

[0072] The second subunit 722 is used to obtain the first geographic information of each unmanned vehicle to be dispatched;

[0073] The judgment unit 723 is used to traverse the vehicle allocation area set, determine whether the first geographic information belongs to any of the vehicle allocation areas, and if so, classify the unmanned vehicle to be dispatched into the corresponding vehicle allocation area to obtain a resource domain; and

[0074] The classification unit 724 is used to obtain the travel mode based on each resource domain, and classify the travel mode to obtain multiple subdomains, wherein the travel mode at least includes hitchhiking, carpooling and exclusive use.

[0075] Furthermore, the first calculation module 720 includes a third subunit 725, a fourth subunit 726 and a fifth subunit 727, wherein:

[0076] The third subunit 725 is used to determine the travel risk information and the first duration information corresponding to the vehicle use path based on the departure place and the destination corresponding to each vehicle use request information; the travel risk information is the sum of the historical probability of public safety incidents occurring on the vehicle use path and the probability of traffic congestion;

[0077] Fourth subunit 726: used for calculating the distance based on the departure place and each of the resource domain center points;

[0078] The fifth subunit 727 is used to calculate the first cost evaluation value based on the travel risk information, the duration information and the distance.

[0079] The second calculation module 730 is used to calculate the second cost evaluation value based on each of the vehicle request information, user behavior information and travel fare information, starting from the first resource domain in the first candidate center sequence;

[0080] Preferably, the second calculation module 730 includes an analysis unit 731, a sixth subunit 732, a seventh subunit 733 and an eighth subunit 734, wherein:

[0081] Analysis unit 731: used to analyze and determine a travel concern weight value set based on the user behavior information, wherein the travel concern weight value set at least includes the user's concern weight values ​​for travel time and cost;

[0082] The sixth subunit 732 is used to obtain the geographic information of the unmanned vehicle to be dispatched, and calculate the second duration information based on the departure place information and the geographic information of the unmanned vehicle to be dispatched;

[0083] The seventh subunit 733 is used to obtain travel fare information based on the vehicle usage path, the number of travelers and the travel mode;

[0084] The eighth subunit 734 is used to calculate and obtain a second cost evaluation value based on the travel concern weight value set, the travel fare information and the second duration information.

[0085] A sorting module 740 is used to sort the first candidate center sequence in ascending order based on the second cost evaluation value to obtain a second candidate center sequence; and

[0086] Scheduling module 750: used to perform resource scheduling matching based on the second candidate center sequence and the vehicle request information set to obtain a vehicle resource scheduling solution.

[0087] Preferably, the scheduling module 750 includes a collection unit 751, an arrangement unit 752 and a matching unit 753, wherein:

[0088] Collection unit 751: used to obtain the user's reputation value for taking a ride, where the reputation value is data determined based on the breach rate of the user's historical orders;

[0089] Arrangement unit 752: used to arrange the departure place, the reputation value and the initiation time of the car request information corresponding to each user in the car request information set to obtain a user request list;

[0090] Matching unit 753: used to make a one-to-one dispatch request for the application vehicle based on the second candidate center sequence and the user request list, and send the dispatch request to the corresponding unmanned vehicle to be dispatched.

[0091] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0092] Embodiment 3:

[0093] Corresponding to the above method embodiment, this embodiment also provides a resource scheduling device 800 for an intelligent connected vehicle. The resource scheduling device 800 for an intelligent connected vehicle described below and the resource scheduling method for an intelligent connected vehicle described above can be referred to each other.

[0094] Figure 3 FIG. 8 is a block diagram of a resource scheduling device 800 for an intelligent connected vehicle according to an exemplary embodiment. Figure 3 As shown, the resource scheduling device 800 of the intelligent networked vehicle may include: a processor 801 and a memory 802. The resource scheduling device 800 of the intelligent networked vehicle may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0095] The processor 801 is used to control the overall operation of the resource scheduling device 800 of the intelligent networked vehicle to complete all or part of the steps in the resource scheduling method of the intelligent networked vehicle. The memory 802 is used to store various types of data to support the operation of the resource scheduling device 800 of the intelligent networked vehicle, and these data may include, for example, instructions for any application or method operating on the resource scheduling device 800 of the intelligent networked vehicle, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, which is used to receive external audio signals. The received audio signal may be further stored in the memory 802 or sent via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the resource scheduling device 800 of the intelligent networked vehicle and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 can include: Wi-Fi module, Bluetooth module, NFC module.

[0096] In an exemplary embodiment, the resource scheduling device 800 of the intelligent connected vehicle can be implemented by one or more application specific integrated circuits (Application Specific Integrated Circuit, referred to as ASIC), digital signal processors (Digital Signal Processor, referred to as DSP), digital signal processing devices (Digital Signal Processing Device, referred to as DSPD), programmable logic devices (Programmable Logic Device, referred to as PLD), field programmable gate arrays (Field Programmable Gate Array, referred to as FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned resource scheduling method of the intelligent connected vehicle.

[0097] In another exemplary embodiment, a computer storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the resource scheduling method for the intelligent connected vehicle are implemented. For example, the computer storage medium may be the memory 802 including the program instructions, and the program instructions may be executed by the processor 801 of the resource scheduling device 800 for the intelligent connected vehicle to complete the resource scheduling method for the intelligent connected vehicle.

[0098] Embodiment 4:

[0099] Corresponding to the above method embodiment, a storage medium is also provided in this embodiment. The storage medium described below and the resource scheduling method for an intelligent connected vehicle described above can refer to each other.

[0100] A storage medium stores a computer program, which, when executed by a processor, implements the steps of the resource scheduling method for an intelligent connected vehicle in the above-mentioned method embodiment.

[0101] The storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other storage medium that can store program codes.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0103] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A resource scheduling method for an intelligent connected vehicle, characterized in that: include: Obtaining a user's car request information set, user behavior information, and travel fare information, wherein the car request information set includes at least one car request information, and the car request information includes at least information on a departure place, a destination, the number of travelers, and a travel mode; Calculating a first cost evaluation value according to each of the vehicle request information and the geographical location information of each resource domain, and arranging the resource domains in ascending order according to the first cost evaluation value to obtain a first candidate center sequence, wherein the resource domains are deployable vehicle resources constructed based on a preset geographical range; Starting from the first resource domain in the first candidate center sequence, a second cost evaluation value is calculated based on each of the vehicle request information, user behavior information and travel fare information; Arrange the first sequence of candidate centers in ascending order based on the second cost evaluation value to obtain a second sequence of candidate centers; A vehicle resource scheduling solution is obtained by performing resource scheduling matching based on the second candidate center sequence and the vehicle request information set.

2. The resource scheduling method for an intelligent connected vehicle according to claim 1, characterized in that: The method for constructing the resource domain includes: Obtain a set of vehicle allocation areas, each of which corresponds to an administrative area of ​​the same level; Obtaining first geographic information of each unmanned vehicle to be dispatched; Traversing the vehicle allocation area set, determining whether the first geographic information belongs to any of the vehicle allocation areas, and if so, assigning the unmanned vehicle to be dispatched to the corresponding vehicle allocation area to obtain a resource domain; The travel mode is obtained based on each resource domain, and multiple subdomains are obtained based on the travel mode classification, and the travel mode at least includes hitchhiking, carpooling and exclusive use.

3. The resource scheduling method for an intelligent connected vehicle according to claim 1, characterized in that: Calculating the first cost evaluation value according to the departure location information in each of the vehicle use request information and the geographical location information of each resource domain includes: Based on the departure place and the destination corresponding to each of the vehicle use request information, determining the travel risk information and the first duration information corresponding to the vehicle use path; the travel risk information is the sum of the historical probability of a public safety incident occurring on the vehicle use path and the probability of traffic congestion; Based on the distance between the departure place and each of the resource domain center points; The first cost evaluation value is obtained based on the travel risk information, the duration information and the distance calculation.

4. The resource scheduling method for an intelligent connected vehicle according to claim 3, characterized in that: Calculating the second cost evaluation value based on each of the vehicle request information, user behavior information, and travel fare information includes: Analyze and determine a travel concern weight value set based on the user behavior information, wherein the travel concern weight value set at least includes the user's concern weight values ​​for travel time and cost; Acquire geographic information of the unmanned vehicle to be dispatched, and calculate second duration information based on the departure location information and the geographic information of the unmanned vehicle to be dispatched; Based on the vehicle usage path, the number of travelers and the travel mode, obtaining travel fare information; A second cost evaluation value is obtained based on the travel concern weight value set, the travel fare information and the second duration information.

5. The resource scheduling method for an intelligent connected vehicle according to claim 1, characterized in that: The vehicle resource scheduling solution obtained by performing resource scheduling matching based on the second candidate center sequence and the vehicle request information set includes: Obtaining the user's reputation value for taking a ride, wherein the reputation value is determined based on the breach rate of the user's historical orders; Arrange the vehicle request information set based on the departure place, the credit value and the vehicle request information initiation time corresponding to each user, to obtain a user request list; Based on the second candidate center sequence and the user request list, a one-to-one dispatch request is made for the application vehicle, and the dispatch request is sent to the corresponding unmanned vehicle to be dispatched.

6. A resource scheduling device for an intelligent connected vehicle, characterized in that: include: Acquisition module: used to acquire a user's car request information set, user behavior information and travel fare information, wherein the car request information set includes at least one car request information, and the car request information includes at least information on the departure place, destination, number of travelers and travel mode; A first calculation module: used to calculate a first cost evaluation value according to each of the vehicle request information and the geographical location information of each resource domain, and to arrange the resource domains in ascending order according to the first cost evaluation value to obtain a first candidate center sequence, wherein the resource domains are deployable vehicle resources constructed based on a preset geographical range; A second calculation module: used to calculate a second cost evaluation value based on each of the vehicle request information, user behavior information and travel fare information, starting from the first resource domain in the first candidate center sequence; A sorting module: used for sorting the first candidate center sequence in ascending order based on the second cost evaluation value to obtain a second candidate center sequence; and Scheduling module: used to perform resource scheduling matching based on the second candidate center sequence and the vehicle request information set to obtain a vehicle resource scheduling solution.

7. The resource scheduling device for an intelligent connected vehicle according to claim 6, characterized in that: The first calculation module includes: The first subunit is used to obtain a set of vehicle allocation areas, each of which corresponds to an administrative area of ​​the same level; The second subunit is used to obtain the first geographic information of each unmanned vehicle to be dispatched; A judgment unit: used for traversing the set of vehicle allocation areas, judging whether the first geographic information belongs to any of the vehicle allocation areas, and if so, assigning the unmanned vehicle to be dispatched to the corresponding vehicle allocation area to obtain a resource domain; and Classification unit: used for acquiring the travel mode based on each resource domain, and classifying the travel mode to obtain multiple subdomains based on the travel mode, and the travel mode at least includes hitchhiking, carpooling and exclusive use.

8. The resource scheduling device for an intelligent connected vehicle according to claim 6, characterized in that: The first calculation module includes: The third subunit is used to determine the travel risk information and the first duration information corresponding to the vehicle use path based on the departure place and the destination corresponding to each vehicle use request information; the travel risk information is the sum of the historical probability of public safety incidents occurring on the vehicle use path and the probability of traffic congestion; The fourth subunit is used for calculating the distance based on the departure place and each resource domain center point; The fifth subunit is used to obtain the first cost evaluation value based on the travel risk information, the duration information and the distance calculation.

9. The resource scheduling device for an intelligent connected vehicle according to claim 8, characterized in that: The second calculation module includes: An analysis unit: configured to determine a travel concern weight value set by analyzing the user behavior information, wherein the travel concern weight value set at least includes the user's concern weight values ​​for travel time and cost; The sixth subunit is used to obtain the geographic information of the unmanned vehicle to be dispatched, and calculate the second duration information based on the departure place information and the geographic information of the unmanned vehicle to be dispatched; The seventh subunit is used to obtain travel fare information based on the vehicle usage path, the number of travelers and the travel mode; The eighth subunit is used to calculate and obtain a second cost evaluation value based on the travel concern weight value set, the travel fare information and the second duration information.

10. The resource scheduling device for an intelligent connected vehicle according to claim 6, characterized in that: The scheduling module includes: Collection unit: used to obtain the user's reputation value for taking a ride, where the reputation value is data determined based on the breach rate of the user's historical orders; Arranging unit: used for arranging the vehicle request information set based on the departure place, the credit value and the initiation time of the vehicle request information corresponding to each user to obtain a user request list; Matching unit: used for making one-to-one dispatch requests for application vehicles based on the second candidate center sequence and the user request list, and sending the dispatch requests to the corresponding unmanned vehicles to be dispatched.

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