WO2019241928A1

WO2019241928A1 - Methods and systems for adjusting transportation capacity

Info

Publication number: WO2019241928A1
Application number: PCT/CN2018/091975
Authority: WO
Inventors: Yongkai Zhao
Original assignee: Beijing Didi Infinity Technology And Development Co., Ltd.
Priority date: 2018-06-20
Filing date: 2018-06-20
Publication date: 2019-12-26
Also published as: CN110856452A

Abstract

A method for adjusting transportation capacity include obtaining a target region. The method may also include obtaining information associated with service providers in the target region. The method may also include determining whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region. The method may also include obtaining one or more service intentions from one or more requester terminals via a network in response to a determination that the target region is the non-busy region. The method may also include determining a special offer for at least one of the one or more service intentions. The method may also include transmitting, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.

Description

METHODS AND SYSTEMS FOR ADJUSTING TRANSPORTATION CAPACITY

TECHNICAL FIELD

The present disclosure generally relates to an online to offline service system, and more particularly, to methods and systems for adjusting transportation capacity.

BACKGROUND

In an online to offline service such as an online taxi-hailing service, the demand for the taxi-hailing service in different regions may be different. For example, the demand for the taxi-hailing service in regions (also referred to as busy regions) near subway stations or bus stations may be higher than that in remote regions (also referred to as non-busy regions) . Therefore, it is desirable to provide systems and methods for adjusting transportation capacity to increase the demand for the taxi-hailing service in a non-busy region.

SUMMARY

According to a first aspect of the present disclosure, a system for adjusting transportation capacity may include one or more storage media and one or more processors configured to communicate with the one or more storage media. The one or more storage media may include a set of instructions. When the one or more processors executing the set of instructions, the one or more processors may be directed to perform one or more of the following operations. The one or more processors may obtain a target region. The one or more processors may obtain information associated with service providers in the target region. The one or more processors may determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region. The one or more processors may obtain one or more service intentions from one or more requester terminals via a network in response to a determination that the target region is the non-busy region. Each of the one or more service intentions may indicate an interest in requesting a service an origin of which is in the target region. The one or more processors may determine a special offer for at least one of the one or more service intentions. The one or more processors may transmit, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.

In some embodiments, the information associated with the service providers in the target region may include an average idle period.

In some embodiments, the average idle period may be determined according to the following operations. The one or more processors may select one or more groups of service orders associated with the target region. The one or more processors may obtain an idle period for each of the one or more groups of service orders. The one or more processors may determine the average idle period based on the one or more idle periods of the one or more groups and a count of the one or more groups.

In some embodiments, each of the one or more groups may include two service orders. A first service order of the two service orders may be completed by a service provider at a first time point. A second service order of the two service orders may be accepted, immediately subsequent to the first service order, by the service provider at a second time point. An origin of the second service order may be in the target region. The idle period for each of the one or more groups of service orders may be from the first time point to the second time point.

In some embodiments, to determine whether the target region is the busy region or the non-busy region based on the information associated with the service providers in the target region, the one or more processors may determine whether the average idle period is greater than a time threshold. The one or more processors may determine that the target region is the busy region in response to a determination that the average idle period is less than or equal to the time threshold. The one or more processors may determine that the target region is the non-busy region in response to a determination that the average idle period is greater than the time threshold.

In some embodiments, to determine the special offer for the at least one of the one or more service intentions, the one or more processors may determine a preliminary special offer for the at least one of the one or more service intentions. The one or more processors may estimate, among the one or more service intentions, a count of service intentions that would be transformed into a service order according to the preliminary special offer. The one or more processors may determine whether the count of the service intentions that would be transformed into a service order is less than a count threshold. The one or more processors may determine the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least one of the one or more service intentions in response to a determination that the count of the service intentions that would be transformed into a service order is less than the count threshold.

In some embodiments, to estimate, among the one or more service intentions, the count of the service intentions that would be transformed into a service order according to the preliminary special offer, the one or more processors may determine, for each of the one or more service intentions, a probability that the service intention would be transformed into a service order based on the preliminary special offer. The one or more processors may determine whether the probability is greater than a probability threshold. The one or more processors may determine that the service intention would be transformed into a service order in response to a determination that the probability is greater than the probability threshold.

In some embodiments, the count threshold may be equal to a sum of a count of service providers that are providing no service and locate in the target region, and a count of service providers each of which is providing a service having a destination in the target region and within a distance threshold away from the destination.

In some embodiments, to determine the special offer for the at least one of the one or more service intentions, the one or more processors may determine a preliminary special offer for the at least one of the one or more service intentions. The one or more processors may determine a sum of values of the at least one preliminary special offer. The one or more processors may determine whether the sum of values is less than or equal to than a threshold value. The one or more processors may determine the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least of the one or more service intentions in response to a determination that the sum of values is less than or equal to the threshold value.

In some embodiments, the special offer may include a discount of a price of the service for the at least one of the one or more service intentions.

According to another aspect of the present disclosure, a method for adjusting transport capacity may include one or more of the following operations. One or more processors may obtain a target region. The one or more processors may obtain information associated with service providers in the target region. The one or more processors may determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region. The one or more processors may obtain one or more service intentions from one or more requester terminals via a network in response to a determination that the target region is the non-busy region. Each of the one or more service intentions may indicate an interest in requesting a service an origin of which is in the target region. The one or more processors may determine a special offer for at least one of the one or more service intentions. The one or more processors may transmit, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.

According to yet another aspect of the present disclosure, a system for adjusting transport capacity may include a region obtaining module configured to obtain a target region. The system may also include a provider information obtaining module configured to obtain information associated with service providers in the target region. The system may also include a region information determination module configured to determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region. The system may also include an intention obtaining module configured to obtain one or more service intentions from one or more requester terminals via a network in response to a determination that the target region is the non-busy region. Each of the one or more service intentions may indicate an interest in requesting a service an origin of which is in the target region. The system may also include a special offer determination module configured to determine a special offer for at least one of the one or more service intentions. The system may also include a transmission module configured to transmit, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.

According to yet another aspect of the present disclosure, a non-transitory computer readable medium may comprise at least one set of instructions for adjusting transportation capacity. The at least one set of instructions may be executed by one or more processors of a computer server. The one or more processors may obtain a target region. The one or more processors may obtain information associated with service providers in the target region. The one or more processors may determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region. The one or more processors may obtain one or more service intentions from one or more requester terminals via a network in response to a determination that the target region is the non-busy region. Each of the one or more service intentions may indicate an interest in requesting a service an origin of which is in the target region. The one or more processors may determine a special offer for at least one of the one or more service intentions. The one or more processors may transmit, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.

Additional features will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and the accompanying drawings or may be learned by production or operation of the examples. The features of the present disclosure may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities, and combinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplary embodiments. These exemplary embodiments are described in detail with reference to the drawings. These embodiments are non-limiting exemplary embodiments, in which like reference numerals represent similar structures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary online to offline service system according to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of a computing device according to some embodiments of the present disclosure;

FIG. 3 a schematic diagram illustrating exemplary hardware and/or software components of a mobile device according to some embodiments of the present disclosure;

FIG. 4 is a block diagram illustrating an exemplary processing engine according to some embodiments of the present disclosure;

FIG. 5 is a flowchart of an exemplary process for adjusting transportation capacity according to some embodiments of the present disclosure;

FIG. 6 is a flowchart of an exemplary process for determining an average idle period of a target region according to some embodiments of the present disclosure;

FIG. 7 is a flowchart of an exemplary process for determining a special offer according to some embodiments of the present disclosure; and

FIG. 8 is a flowchart of an exemplary process for determining a special offer according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

The following description is presented to enable any person skilled in the art to make and use the present disclosure and is provided in the context of a particular application and its requirements. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Thus, the present disclosure is not limited to the embodiments shown but is to be accorded the widest scope consistent with the claims.

The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms “a, ” “an, ” and “the” may be intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises, ” “comprising, ” “includes, ” and/or “including” when used in this disclosure, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

These and other features, and characteristics of the present disclosure, as well as the methods of operations and functions of the related elements of structure and the combination of parts and economies of manufacture, may become more apparent upon consideration of the following description with reference to the accompanying drawing (s) , all of which form part of this specification. It is to be expressly understood, however, that the drawing (s) are for the purpose of illustration and description only and are not intended to limit the scope of the present disclosure. It is understood that the drawings are not to scale.

The flowcharts used in the present disclosure illustrate operations that systems implement according to some embodiments of the present disclosure. It is to be expressly understood, the operations of the flowcharts may be implemented not in order. Conversely, the operations may be implemented in inverted order, or simultaneously. Moreover, one or more other operations may be added to the flowcharts. One or more operations may be removed from the flowcharts.

Moreover, while the systems and methods disclosed in the present disclosure are described primarily regarding online to offline service, it should also be understood that this is only one exemplary embodiment. The system or method of the present disclosure may be applied to any other kind of online to offline service. For example, the system or method of the present disclosure may be applied to different transportation systems including land, ocean, aerospace, or the like, or any combination thereof. The vehicle of the transportation systems may include a taxi, a private car, a hitch, a bus, a train, a bullet train, a high speed rail, a subway, a vessel, an aircraft, a spaceship, a hot-air balloon, a driverless vehicle, a bicycle, a tricycle, a motorcycle, or the like, or any combination thereof. The transportation system may also include any transportation system that applies management and/or distribution, for example, a system for transmitting and/or receiving an express, or a system for a take-out service. The application scenarios of the system or method of the present disclosure may include a web page, a plug-in of a browser, a client terminal, a custom system, an internal analysis system, an artificial intelligence robot, or the like, or any combination thereof.

The terms “passenger, ” “requester, ” “service requester, ” and “customer” in the present disclosure are used interchangeably to refer to an individual, an entity or a tool that may request or order a service. Also, the terms “driver, ” “provider, ” “service provider, ” and “supplier” in the present disclosure are used interchangeably to refer to an individual, an entity, or a tool that may provide a service or facilitate the providing of the service. The term “user” in the present disclosure may refer to an individual, an entity, or a tool that may request a service, order a service, provide a service, or facilitate the providing of the service. For example, the user may be a passenger, a driver, an operator, or the like, or any combination thereof. In the present disclosure, terms “passenger” and “passenger terminal” may be used interchangeably, and terms “driver” and “driver terminal” may be used interchangeably.

The term “service request” in the present disclosure refers to a request that initiated by a passenger, a requester, a service requester, a customer, a driver, a provider, a service provider, a supplier, or the like, or any combination thereof. The service request may be accepted by any one of a passenger, a requester, a service requester, a customer, a driver, a provider, a service provider, or a supplier. The service request may be chargeable, or free. The terms “service request” and “service order” in the present disclosure are used interchangeably.

The positioning technology used in the present disclosure may include a global positioning system (GPS) , a global navigation satellite system (GLONASS) , a compass navigation system (COMPASS) , a Galileo positioning system, a quasi-zenith satellite system (QZSS) , a wireless fidelity (WiFi) positioning technology, or the like, or any combination thereof. One or more of the above positioning technologies may be used interchangeably in the present disclosure.

An aspect of the present disclosure relates to systems and methods for adjusting transportation capacity relating to an online to offline service (e.g., an online taxi-hailing service) . For a region with a relatively low demand for the taxi-hailing service (e.g., a non-busy region) , an online to offline service platform may transmit a special offer to at least one passenger who intends to initiate a service order (e.g., a passenger who has input an origin that is in the region and an intended destination in his/her telephone but has not formally sent out a request for a taxi-hailing service) in the region. With the special offer, a passenger who intends to initiate a service order in the region may be more possible to send out a request for a taxi-hailing service so that the demand for the taxi-hailing service in the non-busy region may be increased.

It should be noted that online to offline service, such as online taxi-hailing service, is a new form of service rooted only in post-Internet era. It provides technical solutions to users and service providers that could raise only in post- Internet era. In pre-Internet era, a user may receive a special offer such as a discount related to a service from newspapers, television advertisements, telephone calls, or leaflets. It is difficult to inform users of the special offer related to the service in time. In addition, the coverage area of users of the traditional methods of special offer recommendation in pre-Internet era is limited. Online to offline service system, however, recommends special offers to larger numbers of users via Internet and ensure that users will not miss the special offers. Therefore, through Internet, the online to offline service systems may provide a much more efficient and accurate recommendation platform for users that may never met in pre-Internet era.

FIG. 1 is a schematic diagram illustrating an exemplary online to offline service system according to some embodiments of the present disclosure. For example, the online to offline service system 100 may be an online to offline service system for transportation services such as taxi hailing, chauffeur services, delivery service, carpool, bus service, take-out service, driver hiring and shuttle services. For brevity, the methods and/or systems described in the present disclosure may take a taxi service as an example. It should be noted that the taxi service is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, the methods and/or systems described in the present disclosure may be applied to other similar situations, such as a delivery service, etc.

The online to offline service system 100 may include a server 110, a network 120, a requester terminal 130, a provider terminal 140, a storage device 150, and a positioning system 160.

In some embodiments, the server 110 may be a single server or a server group. The server group may be centralized, or distributed (e.g., the server 110 may be a distributed system) . In some embodiments, the server 110 may be local or remote. For example, the server 110 may access information and/or data stored in the requester terminal 130, the provider terminal 140, and/or the storage device 150 via the network 120. As another example, the server 110 may be directly connected to the requester terminal 130, the provider terminal 140, and/or the storage device 150 to access stored information and/or data. In some embodiments, the server 110 may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof. In some embodiments, the server 110 may be implemented on a computing device 200 having one or more components illustrated in FIG. 2 in the present disclosure.

In some embodiments, the server 110 may include a processing engine 112. The processing engine 112 may process information and/or data relating to the online to offline service. For example, the processing engine 112 may determine a special offer for a service intention. In some embodiments, the processing engine 112 may include one or more processing engines (e.g., single-core processing engine (s) or multi-core processor (s) ) . Merely by way of example, the processing engine 112 may include one or more hardware processors, such as a central processing unit (CPU) , an application-specific integrated circuit (ASIC) , an application-specific instruction-set processor (ASIP) , a graphics processing unit (GPU) , a physics processing unit (PPU) , a digital signal processor (DSP) , a field-programmable gate array (FPGA) , a programmable logic device (PLD) , a controller, a microcontroller unit, a reduced instruction-set computer (RISC) , a microprocessor, or the like, or any combination thereof.

The network 120 may facilitate the exchange of information and/or data. In some embodiments, one or more components in the online to offline service system 100 (e.g., the server 110, the requester terminal 130, the provider terminal 140, the storage device 150, and the positioning system 160) may send information and/or data to other component (s) in the online to offline service system 100 via the network 120. For example, the server 110 may obtain/acquire a service intention from the requester terminal 130 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or a combination thereof. Merely by way of example, the network 120 may include a cable network, a wireline network, an optical fiber network, a telecommunications network, an intranet, the Internet, a local area network (LAN) , a wide area network (WAN) , a wireless local area network (WLAN) , a metropolitan area network (MAN) , a wide area network (WAN) , a public telephone switched network (PSTN) , a Bluetooth ^TM network, a ZigBee network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network 120 may include one or more network access points. For example, the network 120 may include wired or wireless network access points such as base stations and/or internet exchange points 120-1, 120-2, … , through which one or more components of the online to offline service system 100 may be connected to the network 120 to exchange data and/or information.

In some embodiments, a requester may be a user of the requester terminal 130. In some embodiments, the user of the requester terminal 130 may be someone other than the requester. For example, a user A of the requester terminal 130 may use the requester terminal 130 to send a service request for a user B, or receive service and/or information or instructions from the server 110. In some embodiments, a provider may be a user of the provider terminal 140. In some embodiments, the user of the provider terminal 140 may be someone other than the provider. For example, a user C of the provider terminal 140 may use the provider terminal 140 to receive a service request for a user D, and/or information or instructions from the server 110. In some embodiments, “requester” and “requester terminal” may be used interchangeably, and “provider” and “provider terminal” may be used interchangeably.

In some embodiments, the requester terminal 130 may include a mobile device 130-1, a tablet computer 130-2, a laptop computer 130-3, a built-in device in a motor vehicle 130-4, or the like, or any combination thereof. In some embodiments, the mobile device 130-1 may include a smart home device, a wearable device, a mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home device may include a smart lighting device, a control device of an intelligent electrical apparatus, a smart monitoring device, a smart television, a smart video camera, an interphone, or the like, or any combination thereof. In some embodiments, the wearable device may include a bracelet, footgear, glasses, a helmet, a watch, clothing, a backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the mobile device may include a mobile phone, a personal digital assistant (PDA) , a gaming device, a navigation device, a point of sale (POS) device, a laptop, a desktop, or the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, a virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glasses, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or the augmented reality device may include a Google Glass ^TM, a RiftCon ^TM, a Fragments ^TM, a Gear VR ^TM, etc. In some embodiments, a built-in device in the motor vehicle 130-4 may include an onboard computer, an onboard television, etc. In some embodiments, the requester terminal 130 may be a device with positioning technology for locating the position of a user of the requester terminal 130 (e.g., a service requester) and/or the requester terminal 130.

In some embodiments, the provider terminal 140 may be a device that is similar to or the same as the requester terminal 130. In some embodiments, the provider terminal 140 may be a device utilizing positioning technology for locating the position of a user of the provider terminal 140 (e.g., a service provider) and/or the provider terminal 140. In some embodiments, the requester terminal 130 and/or the provider terminal 140 may communicate with one or more other positioning devices to determine the position of the requester, the requester terminal 130, the provider, and/or the provider terminal 140. In some embodiments, the requester terminal 130 and/or the provider terminal 140 may send positioning information to the server 110.

The storage device 150 may store data and/or instructions. In some embodiments, the storage device 150 may store data obtained from the requester terminal 130 and/or the provider terminal 140. For example, the storage device 150 may store real-time locations of a service provider obtained from the provider terminal 140. In some embodiments, the storage device 150 may store data and/or instructions that the server 110 may execute or use to perform exemplary methods described in the present disclosure. For example, the storage device 150 may store instructions that the server 110 may execute or use to determine a special offer for a service intention. In some embodiments, the storage device 150 may include a mass storage, removable storage, a volatile read-and-write memory, a read-only memory (ROM) , or the like, or any combination thereof. Exemplary mass storage may include a magnetic disk, an optical disk, a solid-state drive, etc. Exemplary removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a zip disk, a magnetic tape, etc. Exemplary volatile read-and-write memory may include a random access memory (RAM) . Exemplary RAM may include a dynamic RAM (DRAM) , a double date rate synchronous dynamic RAM (DDR SDRAM) , a static RAM (SRAM) , a thyristor RAM (T-RAM) , and a zero-capacitor RAM (Z-RAM) , etc. Exemplary ROM may include a mask ROM (MROM) , a programmable ROM (PROM) , an erasable programmable ROM (EPROM) , an electrically-erasable programmable ROM (EEPROM) , a compact disk ROM (CD-ROM) , and a digital versatile disk ROM, etc. In some embodiments, the storage device 150 may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof.

In some embodiments, the storage device 150 may be connected to the network 120 to communicate with one or more components of the online to offline service system 100 (e.g., the server 110, the requester terminal 130, the provider terminal 140) . One or more components of the online to offline service system 100 may access the data or instructions stored in the storage device 150 via the network 120. In some embodiments, the storage device 150 may be directly connected to or communicate with one or more components of the online to offline service system 100 (e.g., the server 110, the requester terminal 130, the provider terminal 140) . In some embodiments, one or more components of the online to offline service system 100 (e.g., the server 110, the requester terminal 130, the provider terminal 140) may have permission to access the storage device 150. In some embodiments, the storage device 150 may be part of the server 110.

The positioning system 160 may determine information associated with an object, for example, the requester terminal 130, the provider terminal 140, etc. For example, the positioning system 160 may determine a current location of the requester terminal 130. In some embodiments, the positioning system 160 may be a global positioning system (GPS) , a global navigation satellite system (GLONASS) , a compass navigation system (COMPASS) , a BeiDou navigation satellite system (BDS) , a Galileo positioning system, a quasi-zenith satellite system (QZSS) , etc. The information may include a location, an elevation, a velocity, or an acceleration of the object, or a current time. The location may be in the form of coordinates, such as, latitude coordinate and longitude coordinate, etc. The positioning system 160 may include one or more satellites, for example, a satellite 160-1, a satellite 160-2, and a satellite 160-3. The satellites 160-1 through 160-3 may determine the information mentioned above independently or jointly. The positioning system 160 may send the information mentioned above to the network 120, the requester terminal 130, or the provider terminal 140 via wireless connections.

In some embodiments, information exchanging of one or more components of the online to offline service system 100 may be achieved by way of requesting or intending to request a service. The object of the service may be any product. In some embodiments, the product may be a tangible product or an immaterial product. The tangible product may include food, medicine, commodity, chemical product, electrical appliance, clothing, car, housing, luxury, or the like, or any combination thereof. The immaterial product may include a servicing product, a financial product, a knowledge product, an internet product, or the like, or any combination thereof. The internet product may include an individual host product, a web product, a mobile internet product, a commercial host product, an embedded product, or the like, or any combination thereof. The mobile internet product may be used in a software of a mobile terminal, a program, a system, or the like, or any combination thereof. The mobile terminal may include a tablet computer, a laptop computer, a mobile phone, a personal digital assistant (PDA) , a smartwatch, a point of sale (POS) device, an onboard computer, an onboard television, a wearable device, or the like, or any combination thereof. For example, the product may be any software and/or application used on the computer or mobile phone. The software and/or application may relate to socializing, shopping, transporting, entertainment, learning, investment, or the like, or any combination thereof. In some embodiments, the software and/or application relating to transporting may include a traveling software and/or application, a vehicle scheduling software and/or application, a mapping software and/or application, etc. In the vehicle scheduling software and/or application, the vehicle may include a horse, a carriage, a rickshaw (e.g., a wheelbarrow, a bike, a tricycle, etc. ) , a car (e.g., a taxi, a bus, a private car, etc. ) , a train, a subway, a vessel, an aircraft (e.g., an airplane, a helicopter, a space shuttle, a rocket, a hot-air balloon, etc. ) , or the like, or any combination thereof.

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of a computing device on which a processing engine may be implemented according to some embodiments of the present disclosure. As illustrated in FIG. 2, the computing device 200 may include a processor 210, a storage 220, an input/output (I/O) 230, and a communication port 240.

The processor 210 (e.g., logic circuits) may execute computer instructions (e.g., program code) and perform functions of the processing engine 112 in accordance with techniques described herein. For example, the processor 210 may include interface circuits 210-aand processing circuits 210-b therein. The interface circuits may be configured to receive electronic signals from a bus (not shown in FIG. 2) , wherein the electronic signals encode structured data and/or instructions for the processing circuits to process. The processing circuits may conduct logic calculations, and then determine a conclusion, a result, and/or an instruction encoded as electronic signals. Then the interface circuits may send out the electronic signals from the processing circuits via the bus.

The computer instructions may include, for example, routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions described herein. For example, the processor 210 may determine a special offer for a service intention. In some embodiments, the processor 210 may include one or more hardware processors, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC) , an application specific integrated circuits (ASICs) , an application-specific instruction-set processor (ASIP) , a central processing unit (CPU) , a graphics processing unit (GPU) , a physics processing unit (PPU) , a microcontroller unit, a digital signal processor (DSP) , a field programmable gate array (FPGA) , an advanced RISC machine (ARM) , a programmable logic device (PLD) , any circuit or processor capable of executing one or more functions, or the like, or any combinations thereof.

Merely for illustration, only one processor is described in the computing device 200. However, it should be noted that the computing device 200 in the present disclosure may also include multiple processors, thus operations and/or method steps that are performed by one processor as described in the present disclosure may also be jointly or separately performed by the multiple processors. For example, if in the present disclosure the processor of the computing device 200 executes both step A and step B, it should be understood that step A and step B may also be performed by two or more different processors jointly or separately in the computing device 200 (e.g., a first processor executes step A and a second processor executes step B, or the first and second processors jointly execute steps A and B) .

The storage 220 may store data/information obtained from the requester terminal 130, the provider terminal 140, the storage device 150, and/or any other component of the online to offline service system 100. In some embodiments, the storage 220 may include a mass storage, removable storage, a volatile read-and-write memory, a read-only memory (ROM) , or the like, or any combination thereof. For example, the mass storage may include a magnetic disk, an optical disk, a solid-state drive, etc. The removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a zip disk, a magnetic tape, etc. The volatile read-and-write memory may include a random access memory (RAM) . The RAM may include a dynamic RAM (DRAM) , a double date rate synchronous dynamic RAM (DDR SDRAM) , a static RAM (SRAM) , a thyristor RAM (T-RAM) , and a zero-capacitor RAM (Z-RAM) , etc. The ROM may include a mask ROM (MROM) , a programmable ROM (PROM) , an erasable programmable ROM (EPROM) , an electrically erasable programmable ROM (EEPROM) , a compact disk ROM (CD-ROM) , and a digital versatile disk ROM, etc. In some embodiments, the storage 220 may store one or more programs and/or instructions to perform exemplary methods described in the present disclosure. For example, the storage 220 may store a program for the processing engine 112 for determining a special offer for a service intention.

The I/O 230 may input and/or output signals, data, information, etc. In some embodiments, the I/O 230 may enable a user interaction with the processing engine 112. For example, an operator of the server 110 may input an instruction relating to determining a special offer for a service intention through the I/O 230. In some embodiments, the I/O 230 may include an input device and an output device. Examples of the input device may include a keyboard, a mouse, a touch screen, a microphone, or the like, or a combination thereof. Examples of the output device may include a display device, a loudspeaker, a printer, a projector, or the like, or a combination thereof. Examples of the display device may include a liquid crystal display (LCD) , a light-emitting diode (LED) -based display, a flat panel display, a curved screen, a television device, a cathode ray tube (CRT) , a touch screen, or the like, or a combination thereof.

The communication port 240 may be connected to a network (e.g., the network 120) to facilitate data communications. The communication port 240 may establish connections between the processing engine 112 and the requester terminal 130, the provider terminal 140, the positioning system 160, or the storage device 150. For example, the processing engine 112 may transmit a special offer to the requester terminal 130 through the communication port 240. The connection may be a wired connection, a wireless connection, any other communication connection that can enable data transmission and/or reception, and/or any combination of these connections. The wired connection may include, for example, an electrical cable, an optical cable, a telephone wire, or the like, or any combination thereof. The wireless connection may include, for example, a Bluetooth ^TM link, a Wi-Fi ^TM link, a WiMax ^TM link, a WLAN link, a ZigBee link, a mobile network link (e.g., 3G, 4G, 5G, etc. ) , or the like, or a combination thereof. In some embodiments, the communication port 240 may be and/or include a standardized communication port, such as RS232, RS485, etc.

FIG. 3 a schematic diagram illustrating exemplary hardware and/or software components of a mobile device on which a requester terminal and/or a provider terminal may be implemented according to some embodiments of the present disclosure. As illustrated in FIG. 3, the mobile device 300 may include a communication platform 310, a display 320, a graphics processing unit (GPU) 330, a central processing unit (CPU) 340, an I/O 350, a memory 360, and a storage 390. In some embodiments, any other suitable component, including but not limited to a system bus or a controller (not shown) , may also be included in the mobile device 300. In some embodiments, a mobile operating system (OS) 370 (e.g., iOS ^TM, Android ^TM, Windows Phone ^TM, etc. ) and one or more applications 380 may be loaded into the memory 360 from the storage 390 in order to be executed by the CPU 340. The applications 380 may include a browser or any other suitable mobile apps for receiving and rendering information relating to an online transportation service or other information from the processing engine 112, and sending information relating to an online transportation service or other information to the processing engine 112. User interactions with the information stream may be achieved via the I/O 350 and provided to the processing engine 112 and/or other components of the online to offline service system 100 via the network 120. For example, a service requester may input an origin and/or a destination through the I/O 350 of the requester terminal 130. The origin and the destination may be transmitted to the processing engine 112 through the communication platform 310. A special offer may be received through the communication platform 310. The special offer may be stored in the storage 390 and/or displayed on the display 320.

One of ordinary skill in the art would understand that when an element of the online to offline service system 100 performs, the element may perform through electrical signals and/or electromagnetic signals. For example, when the processing engine 112 processes a task, such as making a determination, or identifying information, the processing engine 112 may operate logic circuits in its processor to process such task. When the processing engine 112 sends out data (e.g., a special offer) to the requester terminal 130 and/or the provider terminal 140, a processor of the processing engine 112 may generate electrical signals encoding/including the data. The processor of the processing engine 112 may then send the electrical signals to an output port of the processing engine 112. If the requester terminal 130 and/or the provider terminal 140 communicate with the processing engine 112 via a wired network, the output port of the processing engine 112 may be physically connected to a cable, which may further transmit the electrical signals to an input port of the requester terminal 130 and/or the provider terminal 140. If the requester terminal 130 and/or the provider terminal 140 communicate with the processing engine 112 via a wireless network, the output port of the processing engine 112 may be one or more antennas, which may convert the electrical signals to electromagnetic signals. Within an electronic device, such as the requester terminal 130, the provider terminal 140, or the server 110, when a processor thereof processes an instruction, sends out an instruction, and/or performs an action, the instruction and/or action is conducted via electrical signals. For example, when the processor retrieves or saves data from a storage medium (e.g., the storage device 150, the storage 220, the storage 390) , it may send out electrical signals to a read/write device of the storage medium, which may read or write structured data in the storage medium. The structured data may be transmitted to the processor in the form of electrical signals via a bus of the electronic device. Here, an electrical signal may refer to one electrical signal, a series of electrical signals, and/or a plurality of discrete electrical signals.

FIG. 4 is a block diagram illustrating an exemplary processing engine according to some embodiments of the present disclosure. The processing engine 112 may include a region obtaining module 410, a provider information obtaining module 420, a region information determination module 430, an intention obtaining module 440, a special offer determination module 450, and a transmission module 460.

The region obtaining module 410 may be configured to obtain a target region. In some embodiments, the processing engine 112 may divide an area (e.g., Beijing) into a plurality of sub-areas. In some embodiments, the area may be divided into a plurality of sub-areas according to a geographical condition. For example, an area may be divided into two sub-areas by a river. In some embodiments, the area may be divided into a plurality of sub-areas according to administrative boundaries. For example, Beijing may be divided into a sub-area of Dongcheng district, a sub-area of Xicheng district, a sub-area of Chaoyang district, a sub-area of Haidian district, etc. In some embodiments, an area may be divided into a plurality of sub-areas with geometrical shapes. The geometrical shape of a sub-area may be regular or irregular. The regular geometrical shape may include a triangle, a square, a rectangle, a pentagon, an octagon, a circle, a hexagon, or the like, or any combination thereof. In some embodiments, the plurality of sub-areas may be same or different. For example, each of the plurality of target regions may be a hexagon having a side length of 300, 500, 700, 1000, or 1500 meters, etc. As another example, one of the plurality of sub-areas may be a hexagon having a side length of 300 meters, and another one of the plurality of sub-areas may be a hexagon having a side length of 500 meters. As still another example, one of the plurality of sub-areas may be a hexagon, and another one of the plurality of sub-areas may be a square.

In some embodiments, information relating to the area that is divided into a plurality of sub-areas may be stored in the storage device 150 and/or the storage 220. The region obtaining module 410 may obtain the information relating to the area that is divided into a plurality of sub-areas from the storage device 150 and/or the storage 220 and determine one of the plurality of sub-areas as the target region.

The provider information obtaining module 420 may be configured to obtain information associated with service providers in the target region (e.g., as described elsewhere in this disclosure in detail in connection with FIG. 6) . In some embodiments, the information associated with service providers in the target region may include an average idle period of the service providers associated with the target region.

In some embodiments, the requester terminal 130 and/or the provider terminal 140 may establish a communication (e.g., wireless communication) with the server 110, through an application (e.g., the application 380 in FIG. 3) installed in the requester terminal 130 and/or the provider terminal 140 via the network 120. The application may associate with the online to offline service system 100. For example, the application may be a taxi-hailing application associated with the online to offline service system 100. In some embodiments, when a service provider accepts (or completes) a service order, a terminal (e.g., the provider terminal 140) associated with the service provider may send the time point when the service provider accepts (or completes) the service order. For example, the service provider may press a button in an interface of the application in the provider terminal 140 to accept (or complete) the service order. After the service provider presses the button, the provider terminal 140 may send the time point when the service provider accepts (or completes) the service order to the processing engine 112 and/or the storage device 150. Alternatively or additionally, a service provider may send a message indicating that he/her accepts or completes a service order to the server 110 through the provider terminal 140. The server 110 (e.g., the processing engine 112) may record the time point when the server 110 receives the message indicating that the service provider accepts or completes the service order.

In some embodiments, a service order may refer to information of a transportation service that is formally requested and sent out by a service requester to the server 110 via the requester terminal 130. For example, when the service requester sends out the information of the transportation service to the server 110, the service requester may do so by pressing a button on the interface of the application installed in the requester terminal 130. Upon receiving the information of the transportation service, the server 110 may determine that the information of the transportation service is formally sent out and determine the information of the transportation service as a service order.

In some embodiments, if a service provider completes a service order (also referred to as a first service order in this example) at a time point (also referred to as a first time point in this example) , and accepts, immediately subsequent to the first service order, another service order (also referred to as a second service order in this example) of which the origin is in the target region at another time point (also referred to as a second time point in this example) , a time interval between the first time point and the second time point may be referred to as an idle period of the service provider. In some embodiments, the average idle period associated with the target region may be equal to an average value of one or more idle periods associated with the target region.

In some embodiments, for each of the one or more idle periods used to determine the average idle period, the first time point (e.g., the time point when a service provider completes a first service order) and the second time point (e.g., the time point when the service provider accepts, immediately subsequent to the first service order, a second service order of which the origin is in the target region) may be within a time period between a current time (e.g., a time point when the region obtaining module 410 obtains the target region) and a time point prior to the current time. For example, if the region obtaining module 410 obtains the target region at 10:00 a.m. on Monday, for each of the one or more idle periods used to determine the average idle period, the first time point and the second time point may be within a time period from 9: 00 a.m. to 10: 00 a.m. on Monday. As another example, if the region obtaining module 410 obtains the target region at 10: 00 a.m. on Monday, for each of the one or more idle periods used to determine the average idle period, the first time point and the second time point may be within time periods from 9: 00 a.m. to 10: 00 a.m. of one or more days in the past month.

The region information determination module 430 may be configured to determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region.

In some embodiments, the region information determination module 430 may determine whether the target region is a busy region or a non-busy region based on the average idle period of the target region. The region information determination module 430 may determine whether the average idle period is greater than a time threshold (e.g., 1, 2, 3, 5, 8, 10 minutes) . The region information determination module 430 may determine that the target region is the busy region in response to a determination that the average idle period is less than or equal to the time threshold. The region information determination module 430 may determine that the target region is the non-busy region in response to a determination that the average idle period is greater than the time threshold.

The intention obtaining module 440 may be configured to obtain one or more service intentions from one or more requester terminals (e.g., the requester terminal 130) via a network (e.g., the network 120) . Each of the one or more service intentions may indicate an interest in requesting a transportation service. The origin (e.g., the intended departure location) of each of the plurality of intentions may be in the target region.

The application installed in the requester terminal 130 may direct the requester terminal 130 to monitor, continuously or periodically, input from a service requester and transmit the input to the online to offline service system 100 via the network 120. Consequently, the requester terminal 130 may inform the service requester’s input to the online to offline service system 100 in real-time or substantially real-time. As a result, when the service requester input the origin and/or the destination, the online to offline service system 100 may receive enough information to determine an intention of the service requester. For example, when the service requester inputs the origin and the destination, and before sending out the origin and the destination to the online to offline service system 100, the online to offline service system 100 may have already received the origin and the destination, and determine that the service requester intends to request a transportation service.

In some embodiments, the origin and/or the destination may be a specified location input by a service requester through the requester terminal 130 (e.g., the I/O 350 in FIG. 3) . In some embodiments, the requester terminal 130 may automatically obtain the origin and/or the destination. For example, an event such as “A meeting at location A at 10: 00 a.m. on Wednesday” is recorded in a calendar in the requester terminal 130. The requester terminal 130 may automatically determine location A as the destination based on the event in the calendar. In some embodiments, the requester terminal 130 may obtain its location (which is referred to as the location of the service requester) herein through a positioning technology in the requester terminal 130, for example, the GPS, GLONASS, COMPASS, QZSS, BDS, WiFi positioning technology, or the like, or any combination thereof.

In some embodiments, the intention obtaining module 440 may obtain one or more service intentions of which the time points of receiving the origins and/or the destinations by the server 110 are within a time period (e.g., 10 minutes) immediately before the current time.

The special offer determination module 450 may be configured to determine a special offer for at least one of the one or more service intentions. The special offer may be used as an incentive for a service requester to transform a service intention into a service order. In some embodiments, the special offer may include a discount of a fee of a service order, a red packet, a discount coupon, a cash coupon, accumulate points, a cash refund, or the like, or any combination thereof. In some embodiments, the greater the value of the special offer is, the more possible it is for a service requester that receives the special offer to transform a service intention into a service order.

In some embodiments, the at least one special offer of the at least one of the one or more service intentions may be same or different. For example, the at least one of special offer may be a cash coupon of 1 dollar. As another example, a special offer for a service intention may be a cash coupon of 1 dollar, and a special offer for another service intention may be a cash coupon of 3 dollars. As still another example, a special offer for a service intention may be a cash coupon of 1 dollar, and a special offer for another service intention may be a 50%discount of a fee of a service order.

In some embodiments, the special offer determination module 450 may determine a preliminary special offer for at least one of the one or more service intentions. For each of the one or more service intentions, the special offer determination module 450 may determine whether to determine a preliminary special offer for the service intention and/or which kind of preliminary special offer to be determined for the service intention.

In some embodiments, the special offer determination module 450 may determine a preliminary special offer for a service intention according to the destination of the service intention. For example, when the destination of the service intention is located in a busy area (e.g., Xidan district of Beijing) , which indicates that the probability that the service intention would be transformed into a service order is relative large (e.g., 60%, 70%, 80%, 90%) even without a special offer, the special offer determination module 450 may determine a preliminary special offer with a relatively small value (e.g., a cash coupon of 1 dollar) or nothing at all for the service intention. When the destination of the service intention is located in a remote area (e.g., Yanqing district of Beijing) , which indicates that the probability that the service intention would be transformed into a service order is relatively small without a special offer, the special offer determination module 450 may determine a preliminary special offer with a relatively large value (e.g., a cash coupon of 5 dollars) .

In some embodiments, the special offer determination module 450 may determine the preliminary special offer for a service intention according to historical information associated with the service requester of a service intention. For example, if the number of historical service orders of the service requester in a time period (e.g., in the past month) , of which the destinations are same as the destination of the service intention, is greater than a threshold number, which indicates that the service requester often goes to that destination and the probability that the service intention would be transformed into a service order is relatively large (e.g., 60%, 70%, 80%, 90%) even without a special offer, the special offer determination module 450 may determine a preliminary special offer with a relatively small value (e.g., a cash coupon of 1 dollar) or nothing at all for the service intention.

The special offer determination module 450 may determine whether the at least one preliminary special offer of the at least one of the one or more service intentions satisfies a condition. The special offer determination module 450 may determine the at least one preliminary special offer as at least one special offer used to be transmitted to the requester terminal 130 associated with at least one service requester of the at least one of the one or more service intentions in response to a determination that the at least one preliminary special offer satisfies the condition. The special offer determination module 450 may re-determine a preliminary special offer for at least one of the one or more service intentions in response to a determination that the at least one preliminary special offer does not satisfy the condition.

For example, the special offer determination module 450 may determine whether the number of service intentions (or the count of service intentions) , among the one or more service intentions, that would be transformed into a service order according to the preliminary special offer is greater than a first threshold. The special offer determination module 450 may determine the at least one preliminary special offer as at least one special offer used to be transmitted to the requester terminal 130 associated with at least one service requester of the at least one of the one or more service intentions in response to a determination that the count of service intentions that would be transformed into a service order according to the preliminary special offer is greater than the first threshold. The special offer determination module 450 may re-determine a preliminary special offer for at least one of the one or more service intentions in response to a determination that the count of service intentions that would be transformed into a service order according to the preliminary special offer is less than or equal to the first threshold.

As another example, the special offer determination module 450 may determine whether the number of service intentions (also referred to as the count of service intentions) , among the one or more service intentions, that would be transformed into a service order according to the preliminary special offer is less than a second threshold (also referred to as a count threshold) (e.g., as described elsewhere in this disclosure in detail in connection with FIG. 7) . The special offer determination module 450 may determine the at least one preliminary special offer as at least one special offer used to be transmitted to the requester terminal 130 associated with at least one service requester of the at least one of the one or more service intentions in response to a determination that the count of service intentions that would be transformed into a service order according to the preliminary special offer is less than the second threshold. The special offer determination module 450 may re-determine a preliminary special offer for at least one of the one or more service intentions in response to a determination that the count of service intentions that would be transformed into a service order according to the preliminary special offer is greater than or equal to the second threshold.

Alternatively or additionally, the special offer determination module 450 may determine whether the sum of values of the at least one preliminary special offer is less than a threshold value (e.g., as described elsewhere in this disclosure in detail in connection with FIG. 8) . The special offer determination module 450 may determine the at least one preliminary special offer as at least one special offer used to be transmitted to the requester terminal 130 associated with at least one service requester of the at least one of the one or more service intentions in response to a determination that the sum of values is less than the threshold value. The special offer determination module 450 may re-determine a preliminary special offer for at least one of the one or more service intentions in response to a determination that the sum of values is greater than or equal to the threshold value.

The transmission module 460 may be configured to transmit the at least one special offer to at least one requester terminal (e.g., the requester terminal 130) from which the at least one of the one or more service intentions is obtained. In some embodiments, the transmission module 460 may transmit the special offer to the requester terminal 130 via the network 120. The received special offer may be shown on the interface of the application installed in the requester terminal 130. For example, a discount price may be shown together with an original price, which may incentivize the service requester to transform the service intention into a service order.

The modules in the processing engine 112 may be connected to or communicate with each other via a wired connection or a wireless connection. The wired connection may include a metal cable, an optical cable, a hybrid cable, or the like, or any combination thereof. The wireless connection may include a Local Area Network (LAN) , a Wide Area Network (WAN) , a Bluetooth, a ZigBee, a Near Field Communication (NFC) , or the like, or any combination thereof. Two or more of the modules may be combined as a single module, and any one of the modules may be divided into two or more units. For example, the provider information obtaining module 420 may be integrated in the region information determination module 430 as a single module which may both determine an average idle period and determine whether the target region is a non-busy region.

It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. For example, the processing engine 112 may further include a storage module (not shown in FIG. 2) . The storage module may be configured to store data generated during any process performed by any component of in the processing engine 112. As another example, each of components of the processing engine 112 may include a storage device. Additionally or alternatively, the components of the processing engine 112 may share a common storage device.

FIG. 5 is a flowchart illustrating an exemplary process for adjusting transportation capacity according to some embodiments of the present disclosure. Process 500 may be implemented in the online to offline service system 100 illustrated in FIG. 1. For example, process 500 may be stored in the storage device 150 and/or the storage 220 as a form of instructions (e.g., an application) , and invoked and/or executed by the server 110 (e.g., the processing engine 112 of the server 110, the processor 210 illustrated in FIG. 2, or one or more modules in the processing engine 112 illustrated in FIG. 4) . The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, process 500 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of process 500 as illustrated in FIG. 5 and described below is not intended to be limiting.

In 510, the region obtaining module 410 (or the processing engine 112, and/or the interface circuits 210-a) may obtain a target region. In some embodiments, the processing engine 112 may divide an area (e.g., Beijing) into a plurality of sub-areas. In some embodiments, the area may be divided into a plurality of sub-areas according to a geographical condition. For example, an area may be divided into two sub-areas by a river. In some embodiments, the area may be divided into a plurality of sub-areas according to administrative boundaries. For example, Beijing may be divided into a sub-area of Dongcheng district, a sub-area of Xicheng district, a sub-area of Chaoyang district, a sub-area of Haidian district, etc. In some embodiments, an area may be divided into a plurality of sub-areas with geometrical shapes. The geometrical shape of a sub-area may be regular or irregular. The regular geometrical shape may include a triangle, a square, a rectangle, a pentagon, an octagon, a circle, a hexagon, or the like, or any combination thereof. In some embodiments, the plurality of sub-areas may be same or different. For example, each of the plurality of target regions may be a hexagon having a side length of 300, 500, 700, 1000, or 1500 meters, etc. As another example, one of the plurality of sub-areas may be a hexagon having a side length of 300 meters, and another one of the plurality of sub-areas may be a hexagon having a side length of 500 meters. As still another example, one of the plurality of sub-areas may be a hexagon, and another one of the plurality of sub-areas may be a square.

In 520, the provider information obtaining module 420 (or the processing engine 112, and/or the processing circuits 210-b) may obtain information associated with service providers in the target region (e.g., as described elsewhere in this disclosure in detail in connection with FIG. 6) . In some embodiments, the information associated with service providers in the target region may include an average idle period of the service providers associated with the target region.

In 530, the region information determination module 430 (or the processing engine 112, and/or the processing circuits 210-b) may determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region.

The busy region may indicate that the number of service orders produced in the target region (e.g., the origins of the service orders are in the target region) corresponding to a time period is relatively large. The non-busy region may indicate that the number of service orders initiated in the target region corresponding to a time period is relatively small. In some embodiments, in response to a determination that the target region is the non-busy region, the processing engine 112 may adjust the transportation capacity of the non-busy region (e.g., increase the number of service orders initiated in the non-busy region) by executing 540-560.

In 540, the intention obtaining module 440 (or the processing engine 112, and/or the processing circuits 210-b) may obtain one or more service intentions from one or more requester terminals (e.g., the requester terminal 130) via a network (e.g., the network 120) . Each of the one or more service intentions may indicate an interest in requesting a transportation service. The origin (e.g., the intended departure location) of each of the plurality of intentions may be in the target region.

In 550, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine a special offer for at least one of the one or more service intentions. The special offer may be used as an incentive for a service requester to transform a service intention into a service order. In some embodiments, the special offer may include a discount of a fee of a service order, a red packet, a discount coupon, a cash coupon, accumulate points, a cash refund, or the like, or any combination thereof. In some embodiments, the greater the value of the special offer is, the more possible it is for a service requester that receives the special offer to transform a service intention into a service order.

In 560, the transmission module 460 (or the processing engine 112, and/or the processing circuits 210-b) may transmit the at least one special offer to at least one requester terminal (e.g., the requester terminal 130) from which the at least one of the one or more service intentions is obtained. In some embodiments, the transmission module 460 may transmit the special offer to the requester terminal 130 via the network 120. The received special offer may be shown on the interface of the application installed in the requester terminal 130. For example, a discount price may be shown together with an original price, which may incentivize the service requester to transform the service intention into a service order.

In some embodiments, the processing engine 112 may perform process 500 periodically. For example, the processing engine 112 may perform process 500 every two hours.

It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. For example, steps 520-530 may be omitted when a special offer is determined no matter the target region is busy or non-busy.

FIG. 6 is a flowchart of an exemplary process for determining an average idle period of a target region according to some embodiments of the present disclosure. Process 600 may be implemented in the online to offline service system 100 illustrated in FIG. 1. For example, process 600 may be stored in the storage device150 and/or the storage 220 as a form of instructions (e.g., an application) , and invoked and/or executed by the server 110 (e.g., the processing engine 112 of the server 110, the processor 210 illustrated in FIG. 2, or one or more modules in the processing engine 112 illustrated in FIG. 4) . The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, process 600 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of process 600 as illustrated in FIG. 6 and described below is not intended to be limiting. In some embodiment, step 520 in process 500 may be performed based on process 600.

In 610, the provider information obtaining module 420 (or the processing engine 112, and/or the processing circuits 210-b) may select one or more groups of service orders associated with a target region. In some embodiments, each of the one or more group of service orders may include two service orders. One of the two service orders (also referred to as a first service order in this example) may be completed by a service provider at a time point (also referred to as a first time point in this example) . The other one of the two service orders (also referred to as a second service order in this example) of which the origin is in the target region may be accepted, immediately subsequent to the first service order, by the service provider at another time point (also referred to as a second time point in this example) .

In some embodiments, the first time point and the second time point may be within a time period between a current time (e.g., a time point when the region obtaining module 410 obtains the target region) and a time point prior to the current time. For example, if the region obtaining module 410 obtains the target region at 10:00 a.m. on Monday, the first time point and the second time point may be within a time period from 9: 00 a.m. on Monday to 10: 00 a.m. on Monday. As another example, if the region obtaining module 410 obtains the target region at 10: 00 a.m. on Monday, the first time point and the second time point may be within time periods from 9: 00 a.m. to 10: 00 a.m. of one or more days in the past month.

In 620, the provider information obtaining module 420 (or the processing engine 112, and/or the processing circuits 210-b) may obtain an idle period for each of the one or more groups of service orders. In some embodiments, for a group of service orders, a time interval between the first time point (e.g., the time point when a service provider completes the first service order) and the second time point (e.g., the time point when the service provider accepts, immediately subsequent to the first service order, the second service order of which the origin is in the target region) may be referred to as an idle period of the service provider corresponding to the group of service orders.

In 630, the provider information obtaining module 420 (or the processing engine 112, and/or the processing circuits 210-b) may determine an average idle period of the target region based on the one or more idle time periods of the one or more groups of service orders and the number of the one or more groups (also referred to as the count of the one or more groups) . In some embodiments, the provider information obtaining module 420 may determine the average idle period of the target region by dividing a sum of the one or more idle time periods of the one or more groups of service orders by the number of the one or more groups.

FIG. 7 is a flowchart of an exemplary process for determining a special offer according to some embodiments of the present disclosure. Process 700 may be implemented in the online to offline service system 100 illustrated in FIG. 1. For example, process 700 may be stored in the storage device150 and/or the storage 220 as a form of instructions (e.g., an application) , and invoked and/or executed by the server 110 (e.g., the processing engine 112 of the server 110, the processor 210 illustrated in FIG. 2, or one or more modules in the processing engine 112 illustrated in FIG. 4) . The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, process 700 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of process 700 as illustrated in FIG. 7 and described below is not intended to be limiting. In some embodiment, step 550 in process 500 may be performed based on process 700.

In 710, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine a preliminary special offer for at least one of one or more service intentions. For each of the one or more service intentions, the special offer determination module 450 may determine whether to determine a preliminary special offer for the service intention and/or which kind of preliminary special offer to be determined for the service intention.

In some embodiments, the special offer determination module 450 may determine a preliminary special offer for a service intention according to the destination of the service intention. For example, when the destination of the service intention is located in a busy area (e.g., Xidan district of Beijing) , which indicates that the probability that the service intention would be transformed into a service order is relative large (e.g., 60%, 70%, 80%, 90%) even without a special offer, the special offer determination module 450 may determine a preliminary special offer with a relatively small value (e.g., a cash coupon of 1 dollar) or nothing at all for the service intention. When the destination of the service intention is located in a remote area (e.g., Yanqing district of Beijing) , which indicates that the probability that the service intention would be transformed into a service order is relatively small (e.g., 10%, 20%, 30%) without a special offer, the special offer determination module 450 may determine a preliminary special offer with a relatively large value (e.g., a cash coupon of 5 dollars) .

In some embodiments, the special offer determination module 450 may determine a preliminary special offer for a service intention according to historical information associated with the service requester of a service intention. For example, if the number of historical service orders of the service requester in a time period (e.g., in the past month) , of which the destinations are same as the destination of the service intention, is greater than a threshold number, which indicates that the service requester often goes to that destination and the probability that the service intention would be transformed into a service order is relatively large (e.g., 60%, 70%, 80%, 90%) even without a special offer, the special offer determination module 450 may determine a preliminary special offer with a relatively small value (e.g., a cash coupon of 1 dollar) or nothing at all for the service intention.

In 720, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may estimate, among the one or more service intentions, the number of service intentions (also referred to as the count of service intentions) that would be transformed into a service order according to the at least one preliminary special offer.

In some embodiments, for each of the one or more service intention, the special offer determination module 450 may determine a probability that the service intention would be transformed into a service order. The special offer determination module 450 may determine whether the probability is greater than a probability threshold (e.g., 40%, 50%, 60%) . In response to a determination that the probability is greater than the probability threshold, the special offer determination module 450 may determine that the service intention would be transformed into a service order. In response to a determination that the probability is less than or equal to the probability threshold, the special offer determination module 450 may determine that the service intention would not be transformed into a service order.

In some embodiments, for a service intention that corresponds no preliminary special offer, the special offer determination module 450 may determine the probability that the service intention would be transformed into a service order based on, for example, the origin of the service intention, the destination of the service intention, and/or the historical service orders of the service requester corresponding to the service intention. In some embodiments, for a service intention that corresponds a preliminary special offer, the special offer determination module 450 may determine the probability that the service intention would be transformed into a service order based on the preliminary special offer, the origin of the service intention, the destination of the service intention, and/or the historical service orders of the service requester corresponding to the service intention.

In some embodiments, for a service intention that corresponds to a preliminary special offer, the special offer determination module 450 may determine the probability that the service intention would be transformed into a service order according to historical service intentions same as the service intention. A historical service intention same as the service intention may be with an origin, a destination, and a special offer same as the origin, the destination, and the preliminary special offer of the service intention. For example, if 8 of 10 historical service intentions same as the service intention are transformed into service orders, the probability that the service intention would be transformed into a service order according to the preliminary special offer may be determined as 80%.

In 730, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine whether the count of the service intentions that would be transformed into a service order is less than a count threshold. In some embodiments, the count threshold may be equal to a sum of the number of service providers that are providing no transportation service and locate in the target region, and the number of service providers each of which is providing a transportation service having a destination in the target region and within a distance threshold (e.g., 1 kilometer) away from the destination.

In some embodiments, if the number (also referred to as the count) of the service intentions that would be transformed into a service order is less than the count threshold, process 700 may proceed to 740. If the count of the service intentions that would be transformed into a service order is greater than or equal to the count threshold, process 700 may proceed to 710 to re-determine a preliminary special offer for at least one of the one or more service intentions.

In 740, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine the at least one preliminary special offer as at least one special offer used to be transmitted to at least one requester terminal from which the at least one of the one or more service intentions is obtained.

FIG. 8 is a flowchart of an exemplary process for determining a special offer according to some embodiments of the present disclosure. Process 800 may be implemented in the online to offline service system 100 illustrated in FIG. 1. For example, process 800 may be stored in the storage device150 and/or the storage 220 as a form of instructions (e.g., an application) , and invoked and/or executed by the server 110 (e.g., the processing engine 112 of the server 110, the processor 210 illustrated in FIG. 2, or one or more modules in the processing engine 112 illustrated in FIG. 4) . The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, process 800 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of process 800 as illustrated in FIG. 8 and described below is not intended to be limiting. In some embodiment, step 550 in process 500 may be performed based on process 800.

In 810, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine a preliminary special offer for at least one of one or more service intentions. In some embodiments, the process for determining the preliminary special offer for the at least one of the one or more service intentions may be same as the corresponding description in 550 of process 500 and/or 710 of process 700.

In 820, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine a sum of values of the at least one preliminary special offer. For example, the at least one preliminary special offer may include a cash coupon of 1 dollar and two cash coupons of 5 dollars. The sum of values of the at least one preliminary special offer may be equal to 11 dollars.

In 830, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine whether the sum of values is less than or equal to a threshold value. In some embodiments, the threshold value may be set to ensure that the at least one preliminary special offer does not cause a loss of a company that operates the online to offline service system 100.

In some embodiments, if the sum of values is less than the threshold value, process 800 may proceed to 840. If the sum of values is greater than or equal to the threshold value, the process 800 may proceed to 810 to re-determine a preliminary special offer for at least one of the one or more service intentions.

In 840, the special offer determination module 450 (or the processing engine 112, and/or the processing circuits 210-b) may determine the at least one preliminary special offer as at least one special offer used to be transmitted to at least one requester terminal from which the at least one of the one or more service intentions is obtained.

Having thus described the basic concepts, it may be rather apparent to those skilled in the art after reading this detailed disclosure that the foregoing detailed disclosure is intended to be presented by way of example only and is not limiting. Various alterations, improvements, and modifications may occur and are intended to those skilled in the art, though not expressly stated herein. These alterations, improvements, and modifications are intended to be suggested by this disclosure and are within the spirit and scope of the exemplary embodiments of this disclosure.

Moreover, certain terminology has been used to describe embodiments of the present disclosure. For example, the terms “one embodiment, ” “an embodiment, ” and/or “some embodiments” mean that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, it is emphasized and should be appreciated that two or more references to “an embodiment” or “one embodiment” or “an alternative embodiment” in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics may be combined as suitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects of the present disclosure may be illustrated and described herein in any of a number of patentable classes or context including any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof. Accordingly, aspects of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc. ) or combining software and hardware implementation that may all generally be referred to herein as a “unit, ” “module, ” or “system. ” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer-readable media having computer readable program code embodied thereon.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electromagnetic, optical, or the like, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that may communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including wireless, wireline, optical fiber cable, RF, or the like, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python or the like, conventional procedural programming languages, such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN) , or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider) or in a cloud computing environment or offered as a service such as a Software as a Service (SaaS) .

Furthermore, the recited order of processing elements or sequences, or the use of numbers, letters, or other designations therefore, is not intended to limit the claimed processes and methods to any order except as may be specified in the claims. Although the above disclosure discusses through various examples what is currently considered to be a variety of useful embodiments of the disclosure, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover modifications and equivalent arrangements that are within the spirit and scope of the disclosed embodiments. For example, although the implementation of various components described above may be embodied in a hardware device, it may also be implemented as a software-only solution, e.g., an installation on an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description of embodiments of the present disclosure, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the various embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, claimed subject matter may lie in less than all features of a single foregoing disclosed embodiment.

In some embodiments, the numbers expressing quantities or properties used to describe and claim certain embodiments of the application are to be understood as being modified in some instances by the term “about, ” “approximate, ” or “substantially. ” For example, “about, ” “approximate, ” or “substantially” may indicate ±20%variation of the value it describes, unless otherwise stated. Accordingly, in some embodiments, the numerical parameters set forth in the written description and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the application are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable.

Each of the patents, patent applications, publications of patent applications, and other material, such as articles, books, specifications, publications, documents, things, and/or the like, referenced herein is hereby incorporated herein by this reference in its entirety for all purposes, excepting any prosecution file history associated with same, any of same that is inconsistent with or in conflict with the present document, or any of same that may have a limiting affect as to the broadest scope of the claims now or later associated with the present document. By way of example, should there be any inconsistency or conflict between the description, definition, and/or the use of a term associated with any of the incorporated material and that associated with the present document, the description, definition, and/or the use of the term in the present document shall prevail.

In closing, it is to be understood that the embodiments of the application disclosed herein are illustrative of the principles of the embodiments of the application. Other modifications that may be employed may be within the scope of the application. Thus, by way of example, but not of limitation, alternative configurations of the embodiments of the application may be utilized in accordance with the teachings herein. Accordingly, embodiments of the present application are not limited to that precisely as shown and describe.

Claims

A system for adjusting transportation capacity, comprising:

a storage device storing a set of instructions; and

one or more processors configured to communicate with the storage device, wherein when executing the set of instructions, the one or more processors are configured to cause the system to:

obtain a target region;

obtain information associated with service providers in the target region;

determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region;

in response to a determination that the target region is the non-busy region, obtain one or more service intentions from one or more requester terminals via a network, each of the one or more service intentions indicating an interest in requesting a service an origin of which is in the target region;

determine a special offer for at least one of the one or more service intentions; and

transmit, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.
The system of claim 1, wherein the information associated with the service providers in the target region includes an average idle period.
The system of claim 2, wherein the average idle period is determined according to a process including:

selecting one or more groups of service orders associated with the target region;

obtaining an idle period for each of the one or more groups of service orders; and

determining the average idle period based on the one or more idle periods of the one or more groups and a count of the one or more groups.
The system of claim 3, wherein each of the one or more groups includes two service orders, a first service order of the two service orders is completed by a service provider at a first time point, a second service order of the two service orders is accepted, immediately subsequent to the first service order, by the service provider at a second time point, an origin of the second service order is in the target region, and the idle period for each of the one or more groups of service orders are from the first time point to the second time point.
The system of any one of claims 2 to 4, wherein to determine whether the target region is the busy region or the non-busy region based on the information associated with the service providers in the target region, the one or more processors are configured to cause the system to:

determine whether the average idle period is greater than a time threshold;

determine that the target region is the busy region in response to a determination that the average idle period is less than or equal to the time threshold; and

determine that the target region is the non-busy region in response to a determination that the average idle period is greater than the time threshold.
The system of any one of claims 1 to 5, wherein to determine the special offer for the at least one of the one or more service intentions, the one or more processors are configured to cause the system to:

determine a preliminary special offer for the at least one of the one or more service intentions;

estimate, among the one or more service intentions, a count of service intentions that would be transformed into a service order according to the preliminary special offer;

determine whether the count of the service intentions that would be transformed into a service order is less than a count threshold; and

determine the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least one of the one or more service intentions in response to a determination that the count of the service intentions that would be transformed into a service order is less than the count threshold.
The system of claim 6, wherein to estimate, among the one or more service intentions, the count of the service intentions that would be transformed into a service order according to the preliminary special offer, the one or more processors are configured to cause the system to:

for each of the one or more service intentions,

determine a probability that the service intention would be transformed into a service order based on the preliminary special offer;

determine whether the probability is greater than a probability threshold; and

determine that the service intention would be transformed into a service order in response to a determination that the probability is greater than the probability threshold.
The system of any one of claims 6 and 7, wherein the count threshold is equal to a sum of a count of service providers that are providing no service and locate in the target region, and a count of service providers each of which is providing a service having a destination in the target region and within a distance threshold away from the destination.
The system of any one of claims 1 to 5 wherein to determine the special offer for the at least one of the one or more service intentions, the one or more processors are configured to cause the system to:

determine a preliminary special offer for the at least one of the one or more service intentions;

determine a sum of values of the at least one preliminary special offer;

determine whether the sum of values is less than or equal to than a threshold value; and

determine the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least of the one or more service intentions in response to a determination that the sum of values is less than or equal to the threshold value.
The system of any one of claims 1 to 9, wherein the special offer includes a discount of a price of the service for the at least one of the one or more service intentions.
A method for adjusting transportation capacity implemented on a computing device having at least one processor and a storage device, the method comprising:

obtaining, by the at least one processor, a target region;

obtaining, by the at least one processor, information associated with service providers in the target region;

determining, by the at least one processor, whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region;

in response to a determination that the target region is the non-busy region, obtaining, by the at least one processor, one or more service intentions from one or more requester terminals via a network, each of the one or more service intentions indicating an interest in requesting a service an origin of which is in the target region;

determining, by the at least one processor, a special offer for at least one of the one or more service intentions; and

transmitting, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.
The method of claim 11, wherein the information associated with the service providers in the target region includes an average idle period.
The method of claim 12, wherein the average idle period is determined according to a process including:

selecting one or more groups of service orders associated with the target region;

obtaining an idle period for each of the one or more groups of service orders; and

determining the average idle period based on the one or more idle periods of the one or more groups and a count of the one or more groups.
The method of claim 13, wherein each of the one or more groups includes two service orders, a first service order of the two service orders is completed by a service provider at a first time point, a second service order of the two service orders is accepted, immediately subsequent to the first service order, by the service provider at a second time point, an origin of the second service order is in the target region, and the idle period for each of the one or more groups of service orders are from the first time point to the second time point.
The method of any one of claims 12 to 14, wherein determining whether the target region is the busy region or the non-busy region based on the information associated with the service providers in the target region includes:

determining whether the average idle period is greater than a time threshold;

determining that the target region is the busy region in response to a determination that the average idle period is less than or equal to the time threshold; and

determining that the target region is the non-busy region in response to a determination that the average idle period is greater than the time threshold.
The method of any one of claims 11 to 15, wherein determining the special offer for the at least one of the one or more service intentions includes:

determining a preliminary special offer for the at least one of the one or more service intentions;

estimating, among the one or more service intentions, a count of service intentions that would be transformed into a service order according to the preliminary special offer;

determining whether the count of the service intentions that would be transformed into a service order is less than a count threshold; and

determining the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least one of the one or more service intentions in response to a determination that the count of the service intentions that would be transformed into a service order is less than the count threshold.
The method of claim 16, wherein estimating, among the one or more service intentions, the count of the service intentions that would be transformed into a service order according to the preliminary special offer includes:

for each of the one or more service intentions,

determining a probability that the service intention would be transformed into a service order based on the preliminary special offer;

determining whether the probability is greater than a probability threshold; and

determining that the service intention would be transformed into a service order in response to a determination that the probability is greater than the probability threshold.
The method of any one of claims 16 and 17, wherein the count threshold is equal to a sum of a count of service providers that are providing no service and locate in the target region, and a count of service providers each of which is providing a service having a destination in the target region and within a distance threshold away from the destination.
The method of any one of claims 11 to 15, wherein determining the special offer for the at least one of the one or more service intentions includes:

determining a preliminary special offer for the at least one of the one or more service intentions;

determining a sum of values of the at least one preliminary special offer;

determining whether the sum of values is less than or equal to than a threshold value; and

determining the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least of the one or more service intentions in response to a determination that the sum of values is less than or equal to the threshold value.
The method of any one of claims 11 to 19, wherein the special offer includes a discount of a price of the service for the at least one of the one or more service intentions.
A system for adjusting transportation capacity, comprising:

a region obtaining module configured to obtain a target region;

a provider information obtaining module configured to obtain information associated with service providers in the target region;

a region information determination module configured to determine whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region;

an intention obtaining module configured to obtain one or more service intentions from one or more requester terminals via a network in response to a determination that the target region is the non-busy region, each of the one or more service intentions indicating an interest in requesting a service an origin of which is in the target region;

a special offer determination module configured to determine a special offer for at least one of the one or more service intentions; and

a transmission module configured to transmit, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.
The system of claim 21, wherein the information associated with the service providers in the target region includes an average idle period.
The system of claim 22, wherein the average idle period is determined according to a process including:

selecting one or more groups of service orders associated with the target region;

obtaining an idle period for each of the one or more groups of service orders; and

determining the average idle period based on the one or more idle periods of the one or more groups and a count of the one or more groups.
The system of claim 23, wherein each of the one or more groups includes two service orders, a first service order of the two service orders is completed by a service provider at a first time point, a second service order of the two service orders is accepted, immediately subsequent to the first service order, by the service provider at a second time point, an origin of the second service order is in the target region, and the idle period for each of the one or more groups of service orders are from the first time point to the second time point.
The system of any one of claims 22 to 24, wherein determining whether the target region is the busy region or the non-busy region based on the information associated with the service providers in the target region includes:

determining whether the average idle period is greater than a time threshold;

determining that the target region is the busy region in response to a determination that the average idle period is less than or equal to the time threshold; and

determining that the target region is the non-busy region in response to a determination that the average idle period is greater than the time threshold.
The system of any one of claims 21 to 25, wherein determining the special offer for the at least one of the one or more service intentions includes:

determining a preliminary special offer for the at least one of the one or more service intentions;

estimating, among the one or more service intentions, a count of service intentions that would be transformed into a service order according to the preliminary special offer;

determining whether the count of the service intentions that would be transformed into a service order is less than a count threshold; and

determining the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least one of the one or more service intentions in response to a determination that the count of the service intentions that would be transformed into a service order is less than the count threshold.
The system of claim 26, wherein estimating, among the one or more service intentions, the count of the service intentions that would be transformed into a service order according to the preliminary special offer includes:

for each of the one or more service intentions,

determining a probability that the service intention would be transformed into a service order based on the preliminary special offer;

determining whether the probability is greater than a probability threshold; and

determining that the service intention would be transformed into a service order in response to a determination that the probability is greater than the probability threshold.
The system of any one of claims 26 and 27, wherein the count threshold is equal to a sum of a count of service providers that are providing no service and locate in the target region, and a count of service providers each of which is providing a service having a destination in the target region and within a distance threshold away from the destination.
The system of any one of claims 21 to 25, wherein determining the special offer for the at least one of the one or more service intentions includes:

determining a preliminary special offer for the at least one of the one or more service intentions;

determining a sum of values of the at least one preliminary special offer;

determining whether the sum of values is less than or equal to than a threshold value; and

determining the preliminary special offer for the at least one of the one or more service intentions as the special offer for the at least of the one or more service intentions in response to a determination that the sum of values is less than or equal to the threshold value.
The system of any one of claims 21 to 29, wherein the special offer includes a discount of a price of the service for the at least one of the one or more service intentions.
A non-transitory computer readable medium, comprising at least one set of instructions for adjusting transportation capacity, wherein when executed by one or more processors of a computing device, the at least one set of instructions causes the computing device to perform a method, the method comprising:

obtaining a target region;

obtaining information associated with service providers in the target region;

determining whether the target region is a busy region or a non-busy region based on the information associated with the service providers in the target region;

in response to a determination that the target region is the non-busy region, obtaining one or more service intentions from one or more requester terminals via a network, each of the one or more service intentions indicating an interest in requesting a service an origin of which is in the target region;

determining a special offer for at least one of the one or more service intentions; and

transmitting, via the network, the at least one special offer to at least one requester terminal from which the at least one of the one or more service intentions is obtained.