CN113065921A - Travel order distribution and initiation method, device, terminal and storage medium - Google Patents
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Abstract
The invention provides a travel order distribution and initiation method, a travel order distribution and initiation device, a terminal and a storage medium, wherein the travel order distribution and initiation method comprises the following steps: receiving a travel order; determining the starting position of the travel order and searching for vehicles within a preset straight-line distance; generating a planned path for each of the vehicles from its current location to the origin location; and calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path, and selecting the vehicle with the shortest time consumption to match the travel order. The method and the system can promote the order pushing from the empty vehicle to the non-empty vehicle, improve the base number of matched drivers, and select the optimal driver of the most suitable vehicle for the trip order. According to the method, a shortest route selection method is abandoned, a shortest expected time consumption selection method is used instead, a speed sampling method adopted for calculating the expected time consumption is used for limiting the speed of the road, calculation is carried out by combining weather, intersection number, passenger carrying conditions and the like, more accurate time consumption calculation is achieved, and the matching efficiency and the matching quality of travel orders are greatly improved.
Description
Technical Field
The invention relates to the technical field of order management, in particular to a travel order distribution and initiation method, a travel order distribution and initiation device, a travel order distribution and initiation terminal and a storage medium.
Background
The network taxi booking, namely the short name of the network taxi booking operation service, refers to the operation activities of booking taxi service for non-tour by establishing a service platform based on the internet technology, accessing vehicles and drivers meeting the conditions and integrating supply and demand information.
In the field of online booking, when a driver is assigned to a user, a method is needed to calculate the order taking time of the driver so as to find the fastest-arriving driver for the user. When the current online booking vehicle assigns drivers to users, only empty drivers within a certain distance are generally considered, but sometimes the empty drivers are not necessarily the best choice. Therefore, how to adopt a technical scheme to judge and compare, select the least drivers for taking a pickup and push passenger orders to the drivers is a technical problem which needs to be solved urgently in the field.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the technical problem to be solved by the present invention is how to adopt a technical solution to perform judgment and comparison, select the least drivers for taking a drive and push passenger orders to the drivers.
In order to achieve the purpose, the invention provides a travel order distribution method which is applied to a server; the method comprises the following steps: receiving a travel order; determining the starting position of the travel order and searching for vehicles within a preset straight-line distance; generating a planned path for each of the vehicles from its current location to the origin location; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order; and calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path, and selecting the vehicle with the shortest time consumption to match the travel order.
In a preferred embodiment of the present invention, the process of calculating the estimated time spent by each vehicle to reach the departure location according to the planned route comprises: acquiring the average speed limit of the planned path, and correcting the average speed limit according to a vehicle speed correction coefficient to obtain the actual driving speed of each vehicle; and calculating to obtain average consumed time according to the total distance length of the planned path and the actual running speed, and correcting the average consumed time according to a time correction coefficient to obtain the predicted consumed time of each vehicle.
In another preferred embodiment of the present invention, the vehicle speed correction factor is associated with a weather factor and/or a travel period factor; the time correction factor is related to a traffic light quantity factor and/or a passenger carrying factor.
In another preferred embodiment of the present invention, the vehicle speed correction coefficient positively correlates the downward correction degree of the actual driving speed with the degree of adverse weather to vehicle travel and/or the road congestion degree during travel.
In another preferred embodiment of the present invention, the time correction coefficient positively correlates the predicted time-consuming upward correction degree with the number of left-turn intersections, the number of right-turn intersections controlled by traffic lights, and the number of single-lane intersections; the time correction factor corrects the predicted elapsed time upward in the case of a passenger in the vehicle.
In another preferred embodiment of the present invention, the actual driving route from the non-empty vehicle to the departure location after the non-empty vehicle completes the in-progress order includes: the actual driving path from the current position of the non-empty vehicle to the place of departure after the non-empty vehicle reaches the target position of the order in progress; and/or the non-empty vehicle goes to the destination position of the order in progress from the current position of the non-empty vehicle to the departure place of the order in progress and then to the actual driving path of the departure place position.
In another preferred embodiment of the present invention, if all the vehicles within the preset straight-line distance are searched for non-empty vehicles, the preset straight-line distance is expanded until an empty vehicle is searched for.
In another preferred embodiment of the present invention, if a plurality of vehicles are matched, the following is processed: if the matched vehicles are all empty vehicles, selecting the optimal vehicle according to the driver image; if the empty vehicles and the non-empty vehicles are matched, judging whether the current travel order quantity is sufficient; if the travel orders are not sufficient, matching the travel orders to empty vehicles; and if the distance between the destination position of the order and the departure position of the travel order during the non-empty vehicle running is less than a preset threshold value, matching the travel order to the non-empty vehicle.
In order to achieve the above object, the present invention further provides a travel order initiating method, which is applied to a user terminal; the method comprises the following steps: responding to a travel request sent by a user, and generating a corresponding travel order; sending the travel order to a server for the server to determine the starting position of the travel order and search for vehicles within a preset linear distance; generating a planned path for each of the vehicles from its current location to the origin location; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order; calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path, and selecting the vehicle with the shortest time consumption to match the travel order; and receiving the matched vehicle information sent by the server.
In order to achieve the above object, the present invention further provides a travel order distribution device, including: the order module is used for receiving a travel order; the searching module is used for determining the starting position of the travel order and searching for vehicles within a preset linear distance; the path module is used for generating a planned path from the current position of each vehicle to the departure place position; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order; and the matching module is used for calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path and selecting the vehicle with the shortest time consumption to match the travel order.
In order to achieve the above object, the present invention further provides a service terminal, including: a processor and a memory; the memory is used for storing a computer program; the processor is used for executing the computer program stored in the memory so as to enable the terminal to execute the travel order allocation method.
In order to achieve the above object, the present invention further provides a user terminal; the method comprises the following steps: a processor and a memory; the memory is used for storing a computer program; the processor is configured to execute the computer program stored in the memory, so as to enable the terminal to execute the travel order initiating method.
To achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a first computer program and/or a second computer program, the first computer program, when executed by a processor, implementing the travel order allocation method; the second computer program, when executed by a processor, implements the travel order initiating method.
The travel order distribution and initiation method, the travel order distribution and initiation device, the travel order distribution and initiation terminal and the travel order storage medium have the following technical effects: the method and the system can promote the order pushing from the empty vehicle to the non-empty vehicle, improve the base number of matched drivers, and select the optimal driver of the most suitable vehicle for the trip order. According to the method, a shortest route selection method is abandoned, a shortest expected time consumption selection method is used instead, a speed sampling method adopted for calculating the expected time consumption is used for limiting the speed of the road, calculation is carried out by combining weather, intersection number, passenger carrying conditions and the like, more accurate time consumption calculation is achieved, and the matching efficiency and the matching quality of travel orders are greatly improved.
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Drawings
Fig. 1 is a flow chart illustrating a travel order allocation method according to an embodiment of the present invention.
FIG. 2A is a schematic illustration of a travel path of a non-empty vehicle in accordance with an embodiment of the present invention.
FIG. 2B is a schematic illustration of a travel path of a non-empty vehicle in accordance with an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a travel order initiating method according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a travel order distribution device according to an embodiment of the present invention.
Fig. 5 is a schematic structural diagram of a service terminal according to an embodiment of the present invention.
Fig. 6 is a schematic structural diagram of a ue according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and/or "including" specify the presence of stated features, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, operations, elements, components, items, species, and/or groups thereof. It should be further understood that the terms "or" and/or "as used herein are to be interpreted as being inclusive or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions or operations are inherently mutually exclusive in some way.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the drawings only show the components related to the present invention rather than the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated. Some exemplary embodiments of the invention have been described for illustrative purposes, and it is to be understood that the invention may be practiced otherwise than as specifically described.
As shown in fig. 1, a flow chart of a travel order allocation method according to an embodiment of the present invention is shown, and mainly includes steps S11 to S14. It should be noted that the travel order allocation method of this embodiment is applied to a server, where the server may be arranged on one or more entity servers according to various factors such as functions, loads, and the like, or may be formed by a distributed or centralized server cluster, and this embodiment is not limited.
Step S11: and receiving a travel order. The travel order should at least include the following basic information: departure location, destination location information, passenger portrait information (such as passenger name, gender, contact information, reputation), travel people information, and the like.
For example, when a user registers through a mobile phone APP, the user inputs basic information (such as name, gender, contact information and the like), and the basic information is uploaded to a server; the method comprises the steps that when a user uses a mobile phone APP to generate an order, a departure place position and a destination position need to be input; in addition, the user can generate corresponding result data each time the user completes an order, and the reputation of the user can be generated through the result data, for example, if all orders are successfully completed, the user can be judged to have high reputation, and for example, if the user cancels orders for many times without accident, the reputation of the user can be influenced, and the like. It should be understood that the manner in which the server obtains the above information is not limited thereto, and the above example is only for illustration and is not intended to limit the scope of the present invention.
Step S12: and determining the starting position of the travel order and searching for vehicles within a preset straight-line distance. Specifically, after receiving a travel order, the server extracts departure location information of the user from the travel order, performs positioning in map software (such as a high-grade map, a Baidu map, a Google map, and the like) according to the departure location, and then locates all vehicles within a preset linear distance from the positioning location. All searched vehicles may be empty vehicles or non-empty vehicles; whether the vehicle is an empty vehicle can be confirmed by whether the driver has an ongoing order currently, if some vehicle still has the order ongoing, the vehicle is a passenger vehicle, and if no order ongoing, the vehicle is an empty vehicle.
In some preferred embodiments, it is preferable to search for an empty vehicle, and the specific search manner is as follows: and if the vehicles in the preset linear distance are searched for and are all non-empty vehicles, the preset linear distance is expanded until the empty vehicles are searched for. For example, searching is performed according to a preset linear distance of 1km, that is, all empty vehicles are searched in a circular area with the starting position as a center and the radius of 1km as a radius, if any vehicle is not searched, the preset linear distance is expanded, for example, the range is expanded to 2km, and the like until the empty vehicle is searched.
Step S13: generating a planned path for each of the vehicles from its current location to the origin location; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position, and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order.
It should be noted that, in the existing network taxi appointment order matching method, only the empty taxi is usually located, and the nearest empty taxi is arranged to go to the pickup. However, in actual operation, firstly, the empty vehicles do not necessarily reach the order destination position faster than the non-empty vehicles, and secondly, the empty vehicles cannot be located in busy time, so that in order to expand the vehicle base number, the vehicle matching method and the vehicle matching system can locate the vehicles from the empty vehicles to the non-empty vehicles, so that the vehicle matching efficiency and the matching quality are improved.
In some examples, for a non-empty vehicle, the actual travel path refers to the actual travel path from its current location to the destination location of the in-progress order and then to the departure location. Taking fig. 2A as an example, the starting position of the order in progress of the non-empty vehicle is S1, the destination position is S2, and the broken line between S1 and S2 represents the planned path of the order in progress; position C represents the current position of the non-empty vehicle; the starting position of the travel order to be matched is S3, the destination position is S4, and the broken line between S3 and S4 represents the planned path of the travel order. Therefore, the actual travel route of the non-empty vehicle is the actual travel route from the current position C1 to S2, and then from S2 to S3.
In some examples, the actual travel path of the non-empty vehicle refers to an actual travel path from the current position of the non-empty vehicle to the departure location of the in-progress order, to the destination location of the in-progress order, and to the departure location. This situation is generally applicable to a very short travel path for an ongoing order for a non-empty vehicle, which takes very little time, although in a passenger. Taking fig. 2B as an example, the starting position of the order in progress of the non-empty vehicle is S5, the destination position is S6, and the current position is C2, and the vehicle is driving on the road of S5; the starting position of the travel order to be matched is S7, the destination position is S8, and the broken line between S7 and S8 represents the planned path of the travel order. Therefore, the actual travel route of the non-empty vehicle is the actual travel route from the current position C1 to S5, and then from S5 to S6, and from S6 to S7.
Step S14: and calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path, and selecting the vehicle with the shortest time consumption to match the travel order.
It is worth noting that the invention changes the path comparison commonly used in the prior art into time-consuming comparison, because the path is far and the actual time consumption is less, the user can receive orders more quickly in the actual experience; on the contrary, some routes are short but actually take a long time, and a bad experience is brought to the user.
Meanwhile, the total distance and the speed information of the planned route, which are expected to consume time, are calculated, the speed information can be obtained from the average speed of the historical orders in the planned route, but the average speed of the historical orders is obviously not accurate enough, and in practical application, the time-consuming data obtained through final calculation is most consistent with the practical application scene because of great deviation caused by various factors and influence on the accuracy of vehicle matching.
Specifically, the process of calculating the predicted time consumption for each vehicle to reach the departure location according to the planned route includes: acquiring the average speed limit of the planned path, and correcting the average speed limit according to a vehicle speed correction coefficient to obtain the actual driving speed of each vehicle; and calculating to obtain average consumed time according to the total distance length of the planned path and the actual running speed, and correcting the average consumed time according to a time correction coefficient to obtain the predicted consumed time of each vehicle.
The method for acquiring the average speed limit of the planned path comprises the following steps: and acquiring speed limit data of each component road section of the planned path, and calculating the average speed limit of the planned path according to the length of each component road section and the speed limit data. For example, if the planned route is composed of an A link and a B link, the total length of the A link is 10km, the speed limit is 80km/h, the total length of the B link is 20km, and the speed limit is 100km/h, then the average speed limit is 92.3km/h ((10+20)/(10/80+ 20/100)). In addition, since the calculated average speed limit is biased to the theoretical value, in consideration of the difference between reality and theory, the embodiment performs a certain conversion downward after calculating the average speed limit, for example: and the calculated average theoretical speed limit value is V1 ', and the actual value of the average speed limit is V1-0.8V 1'.
In the embodiment, the vehicle speed correction coefficient is related to a weather factor and/or a trip period factor; the time correction factor is related to the traffic light quantity factor and/or the passenger carrying factor, and the specific relation is as follows.
The vehicle speed correction coefficient is in positive correlation with the degree of downward correction of the vehicle speed and the degree of adverse effect of weather factors on vehicle traveling and/or the road congestion degree in a traveling time period. That is, the worse the weather is, the more the vehicle speed is corrected downward; conversely, the more favorable the weather is for travel, the less the vehicle speed is corrected downwards.
For example, if the weather is heavy rainstorm (snow), the corrected speed is 0.4 × V1; if the weather is heavy rainstorm (snow), the correction speed is 0.5 × V1; if the weather is medium rain (snow), the correction speed is 0.6 × V1; if the weather is light rain (snow), the corrected speed is 0.7 × V1. It should be noted that the above examples are provided for illustrative purposes and should not be construed as limiting.
The time correction coefficient positively correlates the predicted time consumption upward correction degree with the number of left-turn intersections, the number of right-turn intersections controlled by traffic lights and the number of single-lane intersections; the time correction factor corrects the predicted elapsed time upward in the case of a passenger in the vehicle. That is, the more the left-turn intersections in the planned path are, the more time-consuming upward correction is expected, and otherwise, the less correction is expected; the more the number of right-turn intersections controlled by traffic lights in the planned path is, the more time is predicted to be consumed, the more upward correction is performed, and otherwise, the less correction is performed; the more the number of the single-lane intersections in the planned path is, the more upward correction is expected to be consumed, otherwise, the less correction is expected; in addition, if the matching vehicle is currently in the passenger carrying state, the predicted time consumption also needs to be corrected correspondingly.
For example, the number of left-turn intersections in the planned path is counted as a, and if 7 seconds are consumed for each intersection needing a left turn, the predicted consumed time needs to be corrected upwards by 7 × a seconds. Counting the number of intersections with right-turn red lights in the planned path as B, and if each intersection with right-turn red lights takes 6 seconds more, correcting the predicted time consumption upwards for 6 seconds. Counting that the number of the single-lane intersections in the planned path is C, and if each single-lane intersection takes 5 seconds more, correcting the predicted time consumption upwards by 5 × C seconds. If the vehicle is currently in the passenger carrying state, the predicted elapsed time needs to be corrected upward for 10 seconds.
For convenience of understanding, it is assumed that the total length of the planned path is S, the average calculated speed limit value is V1', the actual driving speed is 0.8 of the average calculated speed limit value, the current weather is light rain, a total of a left-turn intersection, B intersections controlled by traffic lights for right turning, and C single-lane intersections all consume 5 seconds, and the driver is carrying passengers, and the estimated consumed time correction calculation process is as follows:
the actual driving speed may be calculated as V1' × 0.8 ═ V1; and if the current weather is light rain, the corresponding value of the vehicle speed correction coefficient is 0.7, and the corrected actual vehicle speed is 0.7 × V1. Thus, the expected elapsed time t before correction can be expressed as: t ═ S/(0.7 × V1).
According to A left-turn intersections, B intersections controlled by traffic lights and C single-lane intersections, each intersection takes 5 seconds, and the driver is carrying passengers, so the corrected estimated time consumption t can be expressed as: t ═ t' + (a + B + C) × 5+ 10.
In some examples, considering that there may be two or more vehicles that match the criteria at the same time, this may be the case where the predicted elapsed times for these vehicles are exactly equal, or the predicted elapsed times are very small. In this case, the current passenger carrying state of these vehicles needs to be further analyzed.
And if the matched vehicles are all empty vehicles, selecting the optimal vehicle according to the driver image. The driver representation is to abstract each concrete information of the driver into labels based on the network application and big data, and to embody the driver image by using the labels, thereby providing a targeted service. The driver portrait in this embodiment at least includes basic driver information (such as name, gender, age, driving age, etc.), driver score (score based on historical orders, and the score items usually include service attitude, whether to be on time, whether to detour, whether to be tired of driving, whether to be in emergency stop and emergency open, etc.); the embodiment matches the highest ranking driver with the trip order in the top priority to form a virtuous circle.
If the empty vehicles and the non-empty vehicles are matched, judging whether the current travel order quantity is sufficient; if the travel orders are not sufficient, matching the travel orders to empty vehicles; and if the distance between the destination position of the order and the departure position of the travel order during the non-empty vehicle running is less than a preset threshold value, matching the travel order to the non-empty vehicle. That is, under the condition that the order quantity is insufficient, the travel order is preferentially matched with the empty vehicle; under the condition that the order quantity is sufficient, whether the destination position of the order in the process of the non-empty vehicle is close to the starting position of the travel order can be considered, if so, the travel order is matched with the non-empty vehicle, so that the travel order can be managed with the maximum efficiency, the condition that the vehicle needs to travel for a long distance to receive the order is avoided, and travel resources are greatly wasted.
As shown in fig. 3, a flow chart of a travel order initiating method according to an embodiment of the present invention is shown, which includes steps S31-S33. It should be noted that the travel order initiating method of the embodiment is applied to a user terminal, such as a smart phone, a tablet computer, a smart bracelet, a smart watch, a smart helmet, and the like.
Step S31: and responding to a travel request sent by the user, and generating a corresponding travel order.
Taking a touch-controlled mobile phone as an example, a user initiates a travel request through controlling a touch screen, and a user terminal generates a corresponding travel order corresponding to the travel request sent by the user. The travel order should at least include the following basic information: departure location, destination location information, passenger portrait information (such as passenger name, gender, contact information, reputation), travel people information, and the like.
Step S32: sending the travel order to a server for the server to determine the starting position of the travel order and search for vehicles within a preset linear distance; generating a planned path for each of the vehicles from its current location to the origin location; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order; and calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path, and selecting the vehicle with the shortest time consumption to match the travel order.
In some examples, the predicted elapsed time for each vehicle to reach the origin location is calculated from the planned path by a process comprising: acquiring the average speed limit of the planned path, and correcting the average speed limit according to a vehicle speed correction coefficient to obtain the actual driving speed of each vehicle; and calculating to obtain average consumed time according to the total distance length of the planned path and the actual running speed, and correcting the average consumed time according to a time correction coefficient to obtain the predicted consumed time of each vehicle.
In some examples, the vehicle speed correction factor is associated with a weather factor and/or a travel period factor; the time correction factor is related to a traffic light quantity factor and/or a passenger carrying factor. The vehicle speed correction coefficient positively correlates the downward correction degree of the vehicle speed with the degree of adverse vehicle travel caused by weather factors and/or the road congestion degree in travel time.
Furthermore, the time correction coefficient positively correlates the predicted time-consuming upward correction degree with the number of left-turn intersections, the number of right-turn intersections controlled by traffic lights and the number of single-lane intersections; the time correction factor corrects the predicted elapsed time upward in the case of a passenger in the vehicle.
Step S33: and receiving the matched vehicle information sent by the server.
Because the implementation of the method for initiating a travel order in this embodiment is similar to that of the method for allocating a travel order in the foregoing embodiment, further description is omitted.
Fig. 4 is a schematic structural diagram illustrating a travel order distribution apparatus according to an embodiment of the present invention. The travel order distribution device 400 of the present embodiment includes an order module 401, a search module 402, a path module 403, and a matching module 404.
The order module 401 is configured to receive a travel order; the searching module 402 is configured to determine the departure location and search for a vehicle within a preset linear distance; the path module 403 is configured to generate a planned path from the current location to the departure location of each vehicle; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order; the matching module 404 is configured to calculate expected time consumption for each vehicle to reach the departure location according to the planned path, and select a vehicle with the shortest time consumption to match the travel order.
It should be understood that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the path module may be a processing element separately set up, or may be implemented by being integrated in a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the processing element of the apparatus calls and executes the functions of the path module. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when one of the above modules is implemented in the form of a Processing element scheduler code, the Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Fig. 5 is a schematic structural diagram of a service terminal according to an embodiment of the present invention. The service terminal of the present embodiment includes a processor 51 and a memory 52; the memory 52 is used for storing computer programs; the processor 51 is configured to execute the computer program stored in the memory, so as to enable the terminal to execute the travel order allocation method.
Fig. 6 shows a schematic structural diagram of a user terminal according to an embodiment of the present invention. The user terminal of the present embodiment includes a processor 61 and a memory 62; the memory 62 is used for storing a computer program; the processor 61 is configured to execute the computer program stored in the memory, so as to make the terminal execute the travel order initiating method.
The above-mentioned system bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
The present invention also provides a computer readable storage medium having stored thereon a first computer program and/or a second computer program, the first computer program, when executed by a processor, implementing the travel order allocation method; the second computer program, when executed by a processor, implements the travel order initiating method.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the above method embodiments may be performed by hardware associated with a computer program. The aforementioned computer program may be stored in a computer readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
In the embodiments provided herein, the computer-readable and writable storage medium may include read-only memory, random-access memory, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, a USB flash drive, a removable hard disk, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable-writable storage media and data storage media do not include connections, carrier waves, signals, or other transitory media, but are intended to be non-transitory, tangible storage media. Disk and disc, as used in this application, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.
In summary, the present application provides a travel order allocation and initiation method, device, terminal, and storage medium, which can promote order pushing from an empty vehicle to a non-empty vehicle, increase the cardinality of matched drivers, and select the most appropriate driver with the best vehicle for a travel order. According to the method, a shortest route selection method is abandoned, a shortest expected time consumption selection method is used instead, a speed sampling method adopted for calculating the expected time consumption is used for limiting the speed of the road, calculation is carried out by combining weather, intersection number, passenger carrying conditions and the like, more accurate time consumption calculation is achieved, and the matching efficiency and the matching quality of travel orders are greatly improved. Therefore, the application effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (13)
1. A travel order distribution method is characterized by being applied to a server; the method comprises the following steps:
receiving a travel order;
determining the starting position of the travel order and searching for vehicles within a preset straight-line distance;
generating a planned path for each of the vehicles from its current location to the origin location; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order;
and calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path, and selecting the vehicle with the shortest time consumption to match the travel order.
2. A travel order allocation method as claimed in claim 1, wherein said calculating a predicted time taken for each said vehicle to reach said origin location from said planned path comprises:
acquiring the average speed limit of the planned path, and correcting the average speed limit according to a vehicle speed correction coefficient to obtain the actual driving speed of each vehicle;
calculating to obtain average consumed time according to the total distance length of the planned path and the actual running speed, and correcting the average consumed time according to a time correction coefficient to obtain the predicted consumed time of each vehicle.
3. A travel order distribution method as claimed in claim 2, wherein said vehicle speed correction factor is associated with a weather factor and/or a travel period factor; the time correction factor is related to a traffic light quantity factor and/or a passenger carrying factor.
4. A travel order allocation method according to claim 3, wherein said vehicle speed correction factor positively correlates the degree of downward correction of said actual driving speed with the degree of adverse weather effects on vehicle travel and/or the degree of road congestion during a travel period.
5. A travel order allocation method according to claim 3, wherein said time correction factor positively correlates the degree of upward correction of said predicted elapsed time with the number of left-turn intersections, the number of right-turn intersections controlled by traffic lights, and the number of single-lane intersections; the time correction factor corrects the estimated elapsed time upward in the case of a passenger in the vehicle.
6. A travel order distribution method as claimed in claim 1, wherein said actual travel path to said origin location after completion of said in-flight order by said non-empty vehicle comprises: the actual driving path from the current position of the non-empty vehicle to the place of departure after the non-empty vehicle reaches the target position of the order in progress; and/or the non-empty vehicle goes to the destination position of the order in progress from the current position of the non-empty vehicle to the departure place of the order in progress and then to the actual driving path of the departure place position.
7. A travel order allocation method according to claim 1, wherein if all vehicles within a predetermined straight-line distance are searched for as non-empty vehicles, said predetermined straight-line distance is extended until an empty vehicle is searched for.
8. A travel order allocation method according to claim 1, wherein if a plurality of vehicles are matched, the following is done:
if the matched vehicles are all empty vehicles, selecting the optimal vehicle according to the driver image;
if the empty vehicles and the non-empty vehicles are matched, judging whether the current travel order quantity is sufficient; if the travel orders are not sufficient, matching the travel orders to empty vehicles; and if the distance between the destination position of the order and the departure position of the travel order during the non-empty vehicle running is less than a preset threshold value, matching the travel order to the non-empty vehicle.
9. A travel order initiating method is characterized in that the method is applied to a user terminal; the method comprises the following steps:
responding to a travel request sent by a user, and generating a corresponding travel order;
sending the travel order to a server for the server to determine the starting position of the travel order and search for vehicles within a preset linear distance; generating a planned path for each of the vehicles from its current location to the origin location; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order; calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path, and selecting the vehicle with the shortest time consumption to match the travel order;
and receiving the matched vehicle information sent by the server.
10. A travel order dispensing apparatus, comprising:
the order module is used for receiving a travel order;
the searching module is used for determining the starting position of the travel order and searching for vehicles within a preset linear distance;
the path module is used for generating a planned path from the current position of each vehicle to the departure place position; the planned path comprises an actual driving path from the current position of the empty vehicle to the departure place position and/or an actual driving path from the non-empty vehicle to the departure place position after the non-empty vehicle finishes the in-progress order;
and the matching module is used for calculating the predicted time consumption of each vehicle reaching the place of departure according to the planned path and selecting the vehicle with the shortest time consumption to match the travel order.
11. A service terminal, comprising: a processor and a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory to cause the service terminal to execute the travel order allocation method according to any one of claims 1 to 8.
12. A user terminal, comprising: a processor and a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory to cause the user terminal to execute the travel order initiating method according to claim 9.
13. A computer-readable storage medium, on which a first computer program and/or a second computer program are stored, which when executed by a processor implements the travel order allocation method of any one of claims 1 to 8; said second computer program, when executed by a processor, implements the method of travel order initiation of claim 9.
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