Data processing method and device

Abstract

The embodiment of the invention discloses a data processing method and device. A driver starting point, a passenger getting-on point set, a passenger getting-off point set and a driver terminal point serve as driving nodes, candidate sequences and corresponding directed graphs are determined based on the driving nodes, and a target sequence and a target station are determined according to the directed graphs of the candidate sequences. Therefore, a better pick-up sequence and a better get-on and get-off station are obtained by considering the variable conditions of the get-on and get-off points of the passengers, so that the driving time and mileage can be reduced, and the service efficiency and the service quality are improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a data processing method and device. Background Art

[0002] In the context of the rapid development of the Internet economy, shared travel services such as carpooling have gradually become an important part of urban transportation. Carpooling services integrate the travel needs of multiple passengers, realize the effective use of resources and cost sharing, and improve the travel efficiency and experience of users. This model relies on accurate route planning and efficient matching algorithms to optimize driving routes.

[0003] In the prior art, carpooling route planning mainly adopts a method based on the shortest path principle. Given the driver's position and the passenger set, an optimal pick-up and drop-off sequence is calculated to minimize the total driving distance.

[0004] However, existing technologies only consider the nearest boarding and alighting stations, while ignoring the possible complexities in the actual road network structure, such as one-way restrictions, inconvenient turns at intersections, etc. This may result in the driver still having to take an extra detour to pick up passengers or deliver them to their destinations even if they follow the so-called "optimal" route, which increases unnecessary driving time and mileage, affecting service efficiency and quality. Summary of the invention

[0005] In view of this, an object of an embodiment of the present invention is to provide a data processing method and device, which can reduce driving time and mileage and improve service efficiency and service quality.

[0006] In a first aspect, an embodiment of the present invention provides a data processing method, the method comprising:

[0007] Determine the travel nodes of the target driver, wherein the travel nodes include the driver's starting point, a set of at least one target passenger's boarding point, a set of at least one target passenger's alighting point, and the driver's end point;

[0008] Determine at least one candidate order according to the travel nodes, the candidate order being the ranking of the travel nodes;

[0009] Determine the directed graph corresponding to each candidate order;

[0010] A target order and a target site are determined based on the directed graph of the candidate orders.

[0011] In some embodiments, determining the target driver's travel node includes:

[0012] identifying a target driver and at least one target passenger;

[0013] Determining a driver start point and a driver end point of the target driver;

[0014] Determine a set of boarding points and a set of alighting points for the target passenger.

[0015] In some embodiments, determining the target driver and at least one target passenger includes:

[0016] In response to a triggering event, determining the target driver and the target passenger;

[0017] The triggering event includes at least one of the following: the addition of passengers to be added to the group order, the cancellation of the order by passengers who have already added the group order, deviation from the route and abnormal road conditions.

[0018] In some embodiments, determining the set of boarding points and the set of alighting points of the target passenger comprises:

[0019] Generating the boarding point set according to the departure place of the target passenger, wherein the boarding point set includes at least one candidate boarding point;

[0020] The alighting point set is generated according to the destination of the target passenger, and the alighting point set includes at least one candidate alighting point.

[0021] In some embodiments, the candidate order satisfies the following conditions:

[0022] The driver’s starting point is the first driving node;

[0023] The driver's destination is the last travel node;

[0024] The same passenger's boarding point collection is before the alighting point collection.

[0025] In some embodiments, the edge weights of the directed graph are road mileage and / or estimated driving time.

[0026] In some embodiments, determining the target order and the target site based on the directed graph of each candidate order comprises:

[0027] Determine the target path corresponding to each candidate order according to the directed graph corresponding to each candidate order;

[0028] The target sequence and the target site are determined according to the target path.

[0029] In some embodiments, determining the target paths corresponding to each subsequent order according to the directed graph corresponding to each candidate order includes:

[0030] Determine the candidate paths corresponding to each subsequent order according to the directed graph corresponding to each candidate order;

[0031] The best candidate path is determined as the target path.

[0032] In some embodiments, determining the target order and the target site according to the target path comprises:

[0033] Determining the candidate order corresponding to the target path as the target order;

[0034] The candidate site corresponding to the target path is determined as the target site.

[0035] In some embodiments, the method further comprises:

[0036] A planned path is generated according to the target sequence and target sites and sent.

[0037] In some embodiments, the method further comprises:

[0038] A carpooling plan is generated and executed according to the target sequence and the target site.

[0039] In a second aspect, an embodiment of the present invention provides a data processing device, the device comprising:

[0040] A node determination unit, used to determine a travel node of a target driver, wherein the travel node includes a driver starting point, a set of at least one target passenger boarding point, a set of at least one target passenger alighting point, and a driver destination;

[0041] A candidate order determination unit, configured to determine at least one candidate order according to the travel nodes, wherein the candidate order is a ranking of the travel nodes;

[0042] A directed graph determination unit, used to determine the directed graph corresponding to each candidate order;

[0043] The result acquisition unit is used to determine the target order and the target site based on the directed graph of each candidate order.

[0044] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method described in the first aspect.

[0045] In a fourth aspect, an embodiment of the present invention provides a computer program product, wherein the computer program product includes a computer program. When the computer program runs on a computer, the computer executes the method described in the first aspect.

[0046] In a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method described in the first aspect is implemented.

[0047] The technical solution of the embodiment of the present invention takes the driver's starting point, the passenger's boarding point set, the passenger's alighting point set and the driver's destination as travel nodes, determines the candidate order and the corresponding directed graph based on the travel nodes, and determines the target order and the target station according to the directed graph of each candidate order. In this way, considering the variable situation of the passenger's boarding point and alighting point, the optimal pick-up and drop-off order and boarding and drop-off stations are obtained, which can reduce the travel time and mileage, and improve the service efficiency and service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0049] Figure 1 is a schematic diagram of a data processing system according to an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of path planning for comparison;

[0051] Figure 3 is a flow chart of a data processing method according to a first embodiment of the present invention;

[0052] Figure 4 is a flow chart of determining a travel node according to an embodiment of the present invention;

[0053] Figure 5 is a schematic diagram of a directed graph according to an embodiment of the present invention;

[0054] Figure 6 is a flow chart of target sequence and target sites of an embodiment of the present invention;

[0055] Figure 7 is a flow chart of determining a target path according to an embodiment of the present invention;

[0056] Figure 8 is a schematic diagram of a directed graph according to another embodiment of the present invention;

[0057] Fig. 9 is a schematic diagram of path planning according to an embodiment of the present invention;

[0058] Fig.10 is a flow chart of a data processing method according to a second embodiment of the present invention;

[0059] Fig.11 is a schematic diagram of a data processing device according to an embodiment of the present invention;

[0060] Fig.12 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The present application is described below based on embodiments, but the present application is not limited to these embodiments. In the detailed description of the present application below, some specific details are described in detail. It is possible for those skilled in the art to fully understand the present application without the description of these details. In order to avoid confusing the essence of the present application, known methods, processes, flows, components and circuits are not described in detail.

[0062] In addition, persons of ordinary skill in the art will appreciate that the drawings provided herein are for illustration purposes and are not necessarily drawn to scale.

[0063] Unless the context clearly requires otherwise, the words "include", "including" and similar words throughout the application should be interpreted as including rather than exclusive or exhaustive; that is, the meaning is "including but not limited to".

[0064] In the description of this application, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" is two or more.

[0065] The solutions described in this specification and in the examples, if they involve the processing of personal information, will be processed on the premise of having a legal basis (such as obtaining the consent of the subject of personal information, or being necessary for the performance of a contract, etc.), and will only be processed within the scope of regulations or agreements. If a user refuses to process personal information other than the necessary information for basic functions, it will not affect the user's use of basic functions.

[0066] Figure 1 Schematic diagram of a data processing system according to an embodiment of the present invention. Figure 1 As shown, the data processing system of the embodiment of the present invention includes a server 1, at least one driver terminal 2 and at least one passenger terminal 3. The server 1, the driver terminal 2 and the passenger terminal 3 are connected via the Internet or other communication networks to achieve information exchange and service provision.

[0067] Server 1 is responsible for managing and coordinating data and services, and can also process data tasks from multiple driver terminals and passenger terminals in real time. The server performs core functions including but not limited to matching algorithms, route planning, billing systems, etc. At the same time, the server also supports API interfaces to connect with other third-party service platforms, such as payment gateways, map service providers, etc.

[0068] The driver terminal 2 is used to receive order information from the server and display important information such as navigation instructions and passenger location to the driver. In addition, the driver can also update his status (such as whether he can accept orders), communicate with passengers, and provide feedback after completing the order through the driver terminal. The driver terminal can be implemented through a mobile device or a specially designed vehicle-mounted device, such as a smartphone, tablet computer, or dedicated hardware.

[0069] The passenger terminal 3 refers to a smart device used by passengers to initiate a ride request, such as an application on a smartphone or tablet computer. Passengers can use the passenger terminal to enter their destination, select the type of service (such as ordinary travel, carpooling, etc.), and view the estimated arrival time and fare estimate. Once the order is confirmed, the passenger terminal will also provide information about the pick-up vehicle, such as license plate number, model, color and driver information.

[0070] When a passenger submits a ride request, the passenger terminal will send relevant information to the server; the server screens qualified drivers based on a specific algorithm and pushes the order details to the driver terminal of the selected driver. During the trip, both the driver and the passenger can keep in sync with the server through their respective terminals to ensure that both parties obtain the latest trip information in a timely manner. After the trip, the driver terminal uploads the driving data to the server to complete the order settlement process.

[0071] The embodiment of the present invention is described by taking the carpooling scenario as an example. The passenger selects the "carpooling" service option through the application of the passenger terminal and enters the departure place and destination, etc. After the passenger confirms, the passenger terminal organizes these data into a structured request and sends it to the server. The driver can actively publish the willingness to accept orders in the idle state or a specific time period on the driver terminal, including information such as the number of seats that can be provided and the service area, which will also be sent to the server to better match potential passengers. After receiving the request from the passenger terminal, the server starts the matching algorithm, comprehensively considers factors such as the location, route planning, and estimated arrival time of the current active driver, and evaluates possible carpooling paths to ensure the optimal overall itinerary. Once a suitable driver and potential carpooling partner are found, the server will create a carpooling order and send a notification to the selected driver terminal, and inform the passenger of the carpooling details, including the estimated waiting time and cost estimate. The driver terminal receives the notification from the server and displays the content containing the passenger's location, boarding and alighting locations, and other necessary information. For carpooling orders, the driver can also see the information of all passengers participating in the carpooling. The driver decides whether to accept the order based on his own situation. If you accept, you need to start the trip according to the best pick-up and drop-off order recommended by the system; if you refuse, the server will continue to look for other qualified drivers. When the driver accepts the order and confirms that he is ready, the system automatically updates the status and pushes the latest trip progress information to all relevant parties, indicating that the carpooling order has officially entered the execution stage.

[0072] It should be noted that the above carpooling process is only an example provided in the embodiment of the present invention. The embodiment of the present invention does not limit the process of driver issuing orders and passenger issuing orders, which can be implemented in various ways.

[0073] In the process of matching drivers and passengers and planning routes, the server not only needs to select appropriate stations (boarding points, alighting points) for passengers, but also needs to arrange a reasonable pick-up and drop-off order for drivers to ensure the efficiency of the overall journey and user experience.

[0074] Figure 2 This is a schematic diagram of a comparative path planning. Figure 2 As shown, the departure point and the destination point are the departure point and the destination point of the passenger. In the traditional method, the server usually selects the location closest to the passenger's departure point as the boarding point (such as Figure 2 ), and select the location closest to the destination as the drop-off point. However, this strategy may cause the vehicle to make additional detours to reach these points, thereby increasing travel time and mileage. Figure 2 In the scenario shown, if the passenger is at the gate of the community and the driver is on the opposite road, then according to the traditional solution, the driver will be directed to the nearest pick-up point to pick up the passenger, which will inevitably cause the driver to turn around to pick up the passenger and then turn around again to send him to the destination, causing unnecessary detours.

[0075] To solve the above problems, the embodiment of the present invention introduces an improved route planning algorithm, which not only considers the passenger's departure and destination, but also comprehensively considers the driver's current location, driving direction, and direction of the destination. In this way, the system can identify more optimal boarding and alighting points, such as Figure 2 Channel F in the middle allows passengers to get on the bus directly from one side of the road, reducing the detour distance and time of the vehicle. In addition, when there are multiple possible boarding or alighting points, the algorithm can dynamically evaluate the cost of each option (including time and distance) and select the optimal solution based on real-time road conditions and other factors. In this way, the inefficiency problem caused by only recommending the nearest boarding and alighting points in the prior art can be overcome. While ensuring that the overall route is as short as possible, local detours can be avoided as much as possible, thereby improving the efficiency of the entire journey. At the same time, it is also suitable for dealing with the problem of optimizing the pick-up and drop-off order of multiple passengers in carpooling scenarios, ensuring that the travel experience of all participants can be significantly improved. By comprehensively considering factors such as the actual location and driving direction of both the driver and the passenger, a more reasonable and efficient path planning is achieved, ultimately achieving the purpose of saving time and reducing operating costs.

[0076] Figure 3 FIG. 1 is a flow chart of a data processing method according to a first embodiment of the present invention. Figure 3As shown, the data processing method of the embodiment of the present invention includes the following steps:

[0077] Step S110: Determine the driving node of the target driver.

[0078] In this embodiment, the travel nodes include the driver's starting point, at least one target passenger's boarding point set, at least one target passenger's alighting point set and the driver's end point. The boarding point set includes one or more candidate boarding points, and the alighting point set includes one or more candidate alighting points. The data processing method of the embodiment of the present invention mainly determines the optimal order of each travel node, determines the optimal boarding point from multiple candidate boarding points, and determines the optimal alighting point from multiple candidate alighting points. One passenger corresponds to one boarding point set and one alighting point set.

[0079] Figure 4 FIG. 1 is a flow chart of determining a driving node according to an embodiment of the present invention. Figure 4 As shown, determining the driving node of the target driver includes the following steps:

[0080] Step S111: Determine a target driver and at least one target passenger.

[0081] In this embodiment, the server determines the target driver and the target passenger in response to a triggering event, wherein the triggering event includes at least one of the following: a passenger to be added to a group order, a passenger who has already added a group order canceling an order, deviation from the route, and abnormal road conditions.

[0082] The embodiment of the present invention divides the triggering events into two order acceptance stages: the addition of passengers to be added to the order is in the driver-passenger matching stage, and the cancellation of the order, deviation from the route, and abnormal road conditions by passengers who have already added the order are in the route planning stage.

[0083] In the driver-passenger matching stage, the server determines the target driver and at least one target passenger by recalling potential carpooling relationships. Specifically, the server first receives carpooling requests from various passenger terminals, which contain the passengers' departure place, destination and other preference information. Based on these data, the server builds a passenger library containing multiple passengers to be carpooled. At the same time, the server also obtains a driver library, which includes multiple drivers who can participate in carpooling. Here, "carpooling drivers" refer to those drivers who currently have no passengers who have accepted orders or have passengers who have accepted orders but still have vacant seats. Among them, "carpooling passengers" refer to those passengers who have completed two-way confirmation with the driver and established a binding relationship. The server matches the passengers to be carpooled in the passenger library and the drivers to be carpooled in the driver library according to predetermined rules to recall the driver-passenger combination that may complete carpooling, namely the so-called "carpooling relationship". These rules can be used alone or in combination based on a variety of factors, such as the number of seats, driving route, driving direction, etc., to ensure the best matching effect. Finally, the target driver and target passenger determined from the recalled carpooling relationship will enter the next step of route planning and service arrangement.

[0084] For example, suppose there are three passengers A1, A2, and A3 waiting to ride together in the passenger database, and there are two drivers B1 and B2 available to ride together in the driver database. B1 currently does not have any passengers who have already ridden together, while B2 already has passenger C1 but still has an available seat. According to the preset matching rules, the server analyzes each passenger's destination, travel time, and preferences, as well as each driver's location, driving direction, and remaining seats, and the results are: Passenger A1 can only ride together with driver B1; Passenger A2 can ride together with drivers B1 and B2; Passenger A3 can only ride together with driver B2. In this case, the ride-to-ride relationships include:

[0085] The possible relationship R1: driver B1, passenger A1;

[0086] The possible relationship R2: driver B1, passenger A2;

[0087] Possible relationship R3: driver B1, passengers A1, A2;

[0088] Possible relationship R4: driver B2, passengers A2, C1;

[0089] Possible relationship R5: driver B2, passengers A3, C1;

[0090] The possible relationship R6: driver B2, passengers A2, A3, C1.

[0091] For each possible relationship, the target driver and the target passenger are the driver and the passenger in the possible relationship.

[0092] During the route planning stage, when triggering events such as passengers canceling the order, deviation from the route, and abnormal road conditions occur, the route needs to be replanned. At this time, the target driver is the driver corresponding to the triggering event, and the target passenger is the passenger who has shared the order with the target driver.

[0093] Step S112: Determine the driver starting point and driver ending point of the target driver.

[0094] In this embodiment, the driver starting point of the target driver can be determined according to the driver's current location or the driver's setting. Specifically, the driver starting point can be the driver's current location, and the driver's current location can be obtained by the positioning function of the vehicle or the driver's terminal. Alternatively, the driver starting point can be pre-set by the driver, for example, for the driver's planned trip, the driver can pre-set the driver starting point.

[0095] The driver's destination of the target driver can be determined by the server or according to the driver's settings. Specifically, if the driver sets the destination of the trip in advance, the destination set by the driver is determined as the driver's destination. For example, in the scenario of carpooling, the driver needs to set the destination. If the driver does not set the destination of the trip, the server determines a virtual terminal for the driver as the driver's destination. For example, in the scenario of real-time carpooling, the driver does not need to set the destination, and the server can set a hotspot area as the driver's destination.

[0096] Step S113: Determine the boarding point set and the alighting point set of the target passenger.

[0097] In this embodiment, the boarding point set includes one or more candidate boarding points, and the alighting point set includes one or more candidate alighting points.

[0098] Specifically, for each target passenger, the boarding point set is generated according to the departure place of the target passenger, and the alighting point set is generated according to the destination of the target passenger. The departure place and the destination are input by the passenger when placing an order, and the server recalls one or more candidate boarding points according to the departure place and generates the boarding point set, and recalls one or more candidate alighting points according to the destination and generates the alighting point set according to a predetermined point recall method.

[0099] Therefore, through the technical solution of the embodiment of the present invention, the passenger's boarding point is dynamically variable before the passenger order is answered (that is, the driver-passenger matching stage), and the optimal boarding point selection may be different when the current passenger is matched with different ride-sharing friends and drivers. The passenger's drop-off point is dynamically variable before it is about to arrive at the destination. If other ride-sharing friends join or cancel the ride, the passenger's optimal drop-off point will follow the change of the itinerary route to match the optimal drop-off point. During the carpooling trip, when the road conditions are congested, or there are abnormal road conditions such as temporary traffic control, construction / road closure on the planned road, the carpooling route will be changed in real time, and the passenger's drop-off point will also follow the change of the itinerary route to match the optimal drop-off point. If the driver deviates during the journey, the carpooling route will be replanned, and the passenger's drop-off point will also follow the change of the itinerary route to match the optimal drop-off point. Thus, flexible and efficient travel services can be provided. Passengers can enjoy shorter waiting time and more convenient boarding and alighting locations, which improves the overall travel experience. At the same time, the drop-off point is dynamically adjusted according to the actual situation during the trip, ensuring that passengers can reach the optimal drop-off point near the destination as quickly as possible. The server can respond quickly based on real-time traffic conditions (such as traffic congestion, road construction, etc.), automatically re-plan routes and adjust boarding and alighting points to ensure the safety and punctuality of the journey.

[0100] Step S120: determining at least one candidate order according to the travel nodes.

[0101] In this embodiment, the candidate order is the order of the travel nodes. Specifically, the candidate order satisfies the following conditions:

[0102] The driver’s starting point is the first driving node;

[0103] The driver's destination is the last travel node;

[0104] The same passenger's boarding point collection is before the alighting point collection.

[0105] For example, assume that the result of determining the driver's travel nodes is: the target driver is B3, the target passengers include A4 and A5, the driver's starting point is P1, the driver's end point is P2, the passenger A4's boarding point set is P3, the passenger A4's alighting point set is P4, the passenger A5's boarding point set is P5, and the passenger A5's alighting point set is P6.

[0106] According to the conditions that the driver's starting point is the first travel node, the driver's destination is the last travel node, and the pickup point set of the same target passenger is before the drop-off point set, the generated candidate order includes:

[0107] P1, P3, P4, P5, P6, P2;

[0108] P1, P3, P5, P4, P6, P2;

[0109] P1, P3, P5, P6, P4, P2;

[0110] P1, P5, P3, P4, P6, P2;

[0111] P1, P5, P3, P6, P4, P2;

[0112] P1, P5, P6, P3, P4, P2.

[0113] Thus, the candidate order can be obtained.

[0114] Step S130: Determine the directed graph corresponding to each candidate order.

[0115] In this embodiment, the directed graph corresponding to each candidate order is determined according to the order of each travel node in the candidate order. In the directed graph, each travel node is arranged in the order of the candidate order, and each station of the upper travel node can be connected to each station of the lower order for every two adjacent travel nodes. For the station, the station of the driver's starting point and the driver's end point of the target driver is itself, and the station of the target passenger's boarding point set and the alighting point set is the candidate boarding point and the candidate alighting point.

[0116] Furthermore, the edge weight of the directed graph is the road mileage and / or the estimated travel time. That is, the edge weight of each two connected nodes (or sites) is the corresponding mileage or estimated arrival time.

[0117] In some embodiments, the edge weight between the driver's destination and his previous travel node is set to 0 or close to 0 or a lower value.

[0118] Figure 5 is a schematic diagram of a directed graph according to an embodiment of the present invention. Figure 5 In the embodiment shown, it is assumed that the result of determining the driver's travel nodes is: the target driver is B3, the target passengers include A4 and A5, the driver's starting point is P1, the driver's end point is P2, the passenger A4's boarding point set is P3, including three candidate boarding points Q11, Q12, and Q13, the passenger A4's alighting point set is P4, including two candidate alighting points R11 and R12, the passenger A5's boarding point set is P5, including two candidate boarding points Q21 and Q22, and the passenger A5's alighting point set is P6, including three candidate alighting points R21, R22, and R23. The candidate order finally generated includes the six types shown in the above step S120. The embodiment of the present invention takes the third candidate order P1, P3, P5, P6, P4, and P2 as an example for explanation. The directed graph is as shown in FIG. Figure 5 As shown, the meaning represented is that the target driver starts from the driver's starting point P1, picks up passenger A4 first, then picks up passenger A5, then sends passenger A5, then sends passenger A4, and finally reaches the driver's end point P2.

[0119] Step S140: Determine a target order and a target site based on the directed graph of each candidate order.

[0120] In this embodiment, the corresponding target order and target site are determined based on each candidate order of the directed graph obtained above. The target site includes a target boarding point and a target alighting point.

[0121] Figure 6 FIG. 1 is a flow chart of the target sequence and target sites of an embodiment of the present invention. Figure 6 As shown, determining the target order and the target site based on the directed graph of each candidate order includes the following steps:

[0122] Step S141: Determine the target path corresponding to each candidate order according to the directed graph corresponding to each candidate order.

[0123] In this embodiment, as shown in the directed graph above, for every two adjacent driving nodes, each station of the upper driving node can be connected to each station of the lower order receiving node. In this way, there are multiple possible driving paths in a candidate sequence, and the embodiment of the present invention needs to select the best one from all possible driving paths as the target path.

[0124] Specifically, Figure 7 FIG. 1 is a flow chart of determining a target path according to an embodiment of the present invention. Figure 7 As shown, the step of determining the target paths corresponding to each subsequent order according to the directed graph corresponding to each candidate order includes the following steps:

[0125] Step S1411: Determine candidate paths corresponding to each subsequent order according to the directed graph corresponding to each candidate order.

[0126] In this embodiment, the candidate path is the optimal path among all possible driving paths in a candidate sequence. Figure 5 Taking the directed graph shown as an example, there are 3*2*3*2=36 possible driving paths. For example, P1, Q11, Q21, R21, R11, P2 is a possible driving path; for another example, P1, Q12, Q21, R22, R11, P2 is another possible driving path. After listing all possible driving paths, determine the sum of edge weights of each possible driving path, and determine the path with the smallest sum of edge weights as the candidate path. That is, for each candidate order, select the path with the smallest sum of edge weights as the candidate path.

[0127] Figure 8 It is a schematic diagram of a directed graph according to another embodiment of the present invention. Figure 8 The directed graph shown is Figure 5The directed graph shown belongs to the directed graph corresponding to the same candidate order. Figure 8 Only one possible driving path (P1, Q11, Q21, R21, R11, P2) and the corresponding edge weights (W11, W21, W31, W41, W51) are shown in the figure. Correspondingly, the sum of edge weights is W11+W21+W31+W41+W51. Based on the same principle, after obtaining the sum of edge weights corresponding to the possible driving paths, the driving path with the smallest sum of edge weights is selected as the candidate path.

[0128] Therefore, after the above steps are processed, a candidate path corresponding to each candidate order can be obtained.

[0129] Step S1412: determine the best candidate path as the target path.

[0130] In this embodiment, after the candidate paths of various candidate orders are obtained, the optimal candidate path is determined as the target path.

[0131] Step S142: Determine the target order and target site according to the target path.

[0132] In this embodiment, after the target path is determined, the candidate sequence corresponding to the target path is determined as the target sequence, and the candidate site corresponding to the target path is determined as the target site.

[0133] by Figure 5 For example, assume that the target path is P1, Q12, Q21, R22, R11, P2. Since the target path is the path corresponding to the candidate order P1, P3, P5, P6, P4, P2, the target order is P1, P3, P5, P6, P4, P2. At the same time, the stations in the target path are the target stations, that is, Q12, Q21, R22, and R11 are the target stations. Thus, the optimal pick-up and drop-off order and the optimal boarding and alighting stations can be obtained through the above steps.

[0134] Fig. 9 Schematic diagram of path planning according to an embodiment of the present invention. Fig. 9 As shown, through the data processing method of the embodiment of the present invention, the boarding point finally determined is E3. Figure 2 In comparison, the mileage and time of the entire pick-up and drop-off process can be reduced.

[0135] In order to achieve more intelligent and efficient carpooling route planning, the embodiment of the present invention not only considers the passenger's departure and destination, but also comprehensively considers the driver's current location, driving direction, and direction of the destination. Fig. 9 As shown in the figure, the boarding point finally determined by this method is E3, which is better than the traditional solution (such as Figure 2), which can significantly reduce the mileage and time of the entire pick-up and drop-off process. Specifically, before assigning an order to the driver, the platform will recommend multiple candidate pick-up and drop-off points to the passenger to ensure the best choice. Taking the pick-up point recommendation as an example, the platform may provide the current passenger with two pick-up station options: E1 and E2. Passengers can walk from one station to another through channel F. If the nearby drivers are only at the stations shown in the figure, the pick-up point E2 can be recommended, even if it means that the passenger needs to walk a little further, but this will make the total distance of the driver's pick-up and drop-off shortest, thereby achieving the most globally efficient carpooling route planning.

[0136] The technical solution of the embodiment of the present invention can overcome the problem of local detours caused by only recommending the nearest boarding and alighting points in the prior art. It can avoid unnecessary detours as much as possible while ensuring that the overall route is as short as possible, thereby improving the efficiency of the entire journey. Fig. 9 In the example, choosing E3 as the pick-up point not only reduces the driver's waiting time and mileage, but also improves the overall travel experience of passengers. In addition, this method can also handle the problem of optimizing the pick-up and drop-off order of multiple passengers in a carpooling scenario, ensuring that the travel experience of all participants can be significantly improved. Therefore, by comprehensively considering factors such as the candidate pick-up and drop-off points of the driver and each passenger, as well as the pick-up and drop-off order, a more reasonable and efficient route planning is achieved, ultimately achieving the goal of saving time and reducing operating costs, while improving user experience and service quality.

[0137] The embodiment of the present invention uses the driver's starting point, the passenger's boarding point set, the passenger's alighting point set and the driver's destination as travel nodes, determines the candidate order and the corresponding directed graph based on the travel nodes, and determines the target order and the target station according to the directed graph of each candidate order. In this way, considering the variable situation of the passenger's boarding point and alighting point, the optimal pick-up and drop-off order and boarding and drop-off stations are obtained, which can reduce the travel time and mileage, and improve the service efficiency and service quality.

[0138] Furthermore, after obtaining the target sequence and the target site, subsequent processing may be performed according to the target sequence and the target site, such as generating and executing a carpooling plan according to the target sequence and the target site.

[0139] Fig.10 FIG. 1 is a flow chart of a data processing method according to a second embodiment of the present invention. Fig.10 As shown, the data processing method includes the following steps:

[0140] Step S210: Obtain the departure place and destination input by the passenger.

[0141] In this embodiment, the passenger terminal obtains the inputted departure place and destination.

[0142] Step S220: The passenger issues a ticket.

[0143] In this embodiment, after the passenger inputs the departure place and destination in the passenger terminal, the passenger selects a carpooling travel mode and places an order.

[0144] Step S230: Recall candidate sites.

[0145] In this embodiment, the server recalls the candidate stations. Specifically, the embodiment of the present invention divides passengers into passengers who have already placed a group order and passengers to be placed a group order, wherein the passengers to be placed a group order are passengers who have placed an order through the above steps S210 and S220, and the order allocation has not been completed at this time. Passengers who have already placed a group order are passengers who have been allocated to the driver.

[0146] For passengers who are waiting to place a ride, the server will recall candidate boarding points and candidate alighting points based on the departure point and destination. For passengers who have already placed a ride, the server will obtain the stations that have been recalled for the passenger during the grouping stage as candidate stations. Candidate stations include candidate boarding points and candidate alighting points.

[0147] Step S240: Recall the possible association relationships.

[0148] In this embodiment, the server recalls the possible carpooling relationships. The server matches the passengers to be carpooled in the passenger database with the possible carpooling drivers in the driver database according to predetermined rules to recall the driver-passenger combinations that may complete the carpooling, i.e., the so-called "possible carpooling relationships". These rules can be used individually or in combination based on a variety of factors, such as the number of seats, driving route, driving direction, etc., to ensure the best matching effect. Finally, the target driver and target passenger determined from the recalled possible carpooling relationships will enter the next step of route planning and service arrangement.

[0149] For example, assuming that after passenger A7 places an order, after matching the drivers in the driver database, driver B4, driver B5, driver B6 can be matched with passenger A7, then the possible relationships include: (A7, B4), (A7, B5), (A7, B6).

[0150] Step S250, obtaining the optimal spliceable relationship, optimal sequence and optimal site.

[0151] In this embodiment, for each possible association relationship, the corresponding target sequence and target site are obtained through the above steps S110-S140. That is, each possible association relationship can obtain the corresponding target sequence and target site.

[0152] Furthermore, the travel cost corresponding to each possible relationship is determined according to the target order and target station corresponding to each possible relationship. Specifically, the travel cost can be determined based on information such as total mileage and total driving time.

[0153] According to the travel cost corresponding to each possible connection relationship, the optimal possible connection relationship is selected, and the target sequence and target station corresponding to the optimal possible connection relationship are determined as the optimal sequence and optimal station.

[0154] Step S260, execute the group order process.

[0155] In this embodiment, the order-sharing process is executed according to the optimal order-sharing relationship. For example, the server assigns the passenger in the optimal order-sharing relationship to the driver to complete the order-sharing; or, the server sends a push message to the passenger and the driver according to the passenger and the driver in the optimal order-sharing relationship, and completes the order-sharing after waiting for the driver and the passenger to confirm.

[0156] Furthermore, after the group ride is completed, a pick-up route is generated based on the optimal order and optimal stops and sent to the passengers and drivers.

[0157] The embodiment of the present invention uses the driver's starting point, the passenger's boarding point set, the passenger's alighting point set and the driver's destination as travel nodes, determines the candidate order and the corresponding directed graph based on the travel nodes, and determines the target order and the target station according to the directed graph of each candidate order. In this way, considering the variable situation of the passenger's boarding point and alighting point, the optimal pick-up and drop-off order and boarding and drop-off stations are obtained, which can reduce the travel time and mileage, and improve the service efficiency and service quality.

[0158] In some embodiments, after obtaining the target sequence and the target site, subsequent processing may be performed according to the target sequence and the target site, such as generating and sending a planned path according to the target sequence and the target site. Specifically, in the path planning stage, a planned path is generated according to the target sequence and the target site and sent to the passenger and the driver.

[0159] Fig.11 Schematic diagram of a data processing device according to an embodiment of the present invention. Fig.11 As shown, the data processing device of the embodiment of the present invention includes a node determination unit 111, a candidate order determination unit 112, a directed graph determination unit 113 and a result acquisition unit 114. Among them, the node determination unit 111 is used to determine the travel nodes of the target driver, and the travel nodes include the driver's starting point, at least one target passenger's boarding point set, at least one target passenger's alighting point set and the driver's end point. The candidate order determination unit 112 is used to determine at least one candidate order based on the travel nodes, and the candidate order is the ranking of the travel nodes. The directed graph determination unit 113 is used to determine the directed graph corresponding to each candidate order. The result acquisition unit 114 is used to determine the target order and the target site based on the directed graph of each candidate order.

[0160] In some embodiments, the node determination unit includes:

[0161] A first determination subunit, used to determine a target driver and at least one target passenger;

[0162] A second determination subunit is used to determine a driver starting point and a driver ending point of the target driver;

[0163] The third determining subunit is used to determine the boarding point set and the alighting point set of the target passenger.

[0164] In some embodiments, the first determining subunit is used to:

[0165] In response to a triggering event, determining the target driver and the target passenger;

[0166] The triggering event includes at least one of the following: the addition of passengers to be added to the group order, the cancellation of the order by passengers who have already added the group order, deviation from the route and abnormal road conditions.

[0167] In some embodiments, the third determining subunit includes:

[0168] A boarding point set determination module, configured to generate the boarding point set according to the departure place of the target passenger, wherein the boarding point set includes at least one candidate boarding point;

[0169] The alighting point set determining module is used to generate the alighting point set according to the destination of the target passenger, and the alighting point set includes at least one candidate alighting point.

[0170] In some embodiments, the candidate order satisfies the following conditions:

[0171] The driver’s starting point is the first driving node;

[0172] The driver's destination is the last travel node;

[0173] The same passenger's boarding point collection is before the alighting point collection.

[0174] In some embodiments, the edge weights of the directed graph are road mileage and / or estimated driving time.

[0175] In some embodiments, the result acquisition unit includes:

[0176] A target path determination subunit, used to determine the target path corresponding to each candidate order according to the directed graph corresponding to each candidate order;

[0177] The target result subunit is used to determine the target order and target site according to the target path.

[0178] In some embodiments, the target path determination subunit includes:

[0179] A candidate path determination module, used to determine the candidate paths corresponding to each subsequent order according to the directed graph corresponding to each candidate order;

[0180] The target path determination module is used to determine the optimal candidate path as the target path.

[0181] In some embodiments, the target result subunit comprises:

[0182] A target order determination module, used to determine the candidate order corresponding to the target path as the target order;

[0183] The target site determination module is used to determine the candidate site corresponding to the target path as the target site.

[0184] In some embodiments, the apparatus further comprises:

[0185] A path planning unit is used to generate and send a planned path according to the target sequence and target sites.

[0186] In some embodiments, the method further comprises:

[0187] The carpooling plan generating unit is used to generate and execute a carpooling plan according to the target sequence and the target station.

[0188] The embodiment of the present invention uses the driver's starting point, the passenger's boarding point set, the passenger's alighting point set and the driver's destination as travel nodes, determines the candidate order and the corresponding directed graph based on the travel nodes, and determines the target order and the target station according to the directed graph of each candidate order. In this way, considering the variable situation of the passenger's boarding point and alighting point, the optimal pick-up and drop-off order and boarding and drop-off stations are obtained, which can reduce the travel time and mileage, and improve the service efficiency and service quality.

[0189] Fig.12 Schematic diagram of an electronic device according to an embodiment of the present invention. Fig.12 As shown, Fig.12The electronic device shown is a general data processing device, which includes a general computer hardware structure, which includes at least a processor 121 and a memory 122. The processor 121 and the memory 122 are connected via a bus 123. The memory 122 is suitable for storing instructions or programs executable by the processor 121. The processor 121 can be an independent microprocessor or a collection of one or more microprocessors. Thus, the processor 121 executes the instructions stored in the memory 122, thereby executing the method flow of the embodiment of the present invention as described above to realize the processing of data and the control of other devices. The bus 123 connects the above-mentioned multiple components together, and at the same time connects the above-mentioned components to the display controller 124 and the display device and the input / output (I / O) device 125. The input / output (I / O) device 125 can be a mouse, a keyboard, a modem, a network interface, a touch input device, a somatosensory input device, a printer, and other devices known in the art. Typically, the input / output device 125 is connected to the system through an input / output (I / O) controller 126.

[0190] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, devices (equipment) or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may adopt a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0191] The present application is described with reference to flowcharts of methods, apparatuses (devices) and computer program products according to embodiments of the present application. It should be understood that each process in the flowchart can be implemented by computer program instructions.

[0192] These computer program instructions may be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device that implements the process Figure 1 A function specified in a process or multiple processes.

[0193] These computer program instructions may also be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce the instructions for implementing the process Figure 1 A device that specifies functions in a process or multiple processes.

[0194] Another embodiment of the present invention relates to a non-volatile storage medium for storing a computer-readable program, wherein the computer-readable program is used for a computer to execute part or all of the above method embodiments.

[0195] That is, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by specifying relevant hardware through a program, and the program is stored in a storage medium, including several instructions for a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0196] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A data processing method, characterized in that: The method comprises: Determine the travel nodes of the target driver, wherein the travel nodes include the driver's starting point, a set of at least one target passenger's boarding point, a set of at least one target passenger's alighting point, and the driver's end point; Determine at least one candidate order according to the travel nodes, the candidate order being the ranking of the travel nodes; Determine the directed graph corresponding to each candidate order; A target order and a target site are determined based on the directed graph of the candidate orders.

2. The method according to claim 1, characterized in that Determining the travel node of the target driver includes: identifying a target driver and at least one target passenger; Determining a driver start point and a driver end point of the target driver; Determine a set of boarding points and a set of alighting points for the target passenger.

3. The method according to claim 2, characterized in that Determining the target driver and at least one target passenger comprises: In response to a triggering event, determining the target driver and the target passenger; The triggering event includes at least one of the following: the addition of passengers to be added to the group order, the cancellation of the order by passengers who have already added the group order, deviation from the route and abnormal road conditions.

4. The method according to claim 2, characterized in that: Determining the set of boarding points and the set of alighting points of the target passenger comprises: Generating the boarding point set according to the departure place of the target passenger, wherein the boarding point set includes at least one candidate boarding point; The alighting point set is generated according to the destination of the target passenger, and the alighting point set includes at least one candidate alighting point.

5. The method according to claim 2, characterized in that: The candidate order meets the following conditions: The driver’s starting point is the first driving node; The driver's destination is the last travel node; The same passenger's boarding point collection is before the alighting point collection.

6. The method according to claim 1, characterized in that The edge weights of the directed graph are road mileage and / or estimated travel time.

7. The method according to claim 4, characterized in that The determining of the target order and the target site based on the directed graph of each candidate order comprises: Determine the target path corresponding to each candidate order according to the directed graph corresponding to each candidate order; The target sequence and the target site are determined according to the target path.

8. The method according to claim 7, characterized in that Determining the target paths corresponding to each subsequent order according to the directed graph corresponding to each candidate order includes: Determine the candidate paths corresponding to each subsequent order according to the directed graph corresponding to each candidate order; The best candidate path is determined as the target path.

9. The method according to claim 7, characterized in that: Determining the target sequence and the target site according to the target path comprises: Determining the candidate order corresponding to the target path as the target order; The candidate site corresponding to the target path is determined as the target site.

10. The method according to claim 1, characterized in that The method further comprises: A planned path is generated according to the target sequence and target sites and sent.

11. The method according to claim 1, characterized in that: The method further comprises: A carpooling plan is generated and executed according to the target sequence and the target site.

12. A data processing device, characterized in that: The device comprises: A node determination unit, used to determine a travel node of a target driver, wherein the travel node includes a driver starting point, a set of at least one target passenger boarding point, a set of at least one target passenger alighting point, and a driver destination; A candidate order determination unit, configured to determine at least one candidate order according to the travel nodes, wherein the candidate order is a ranking of the travel nodes; A directed graph determination unit, used to determine the directed graph corresponding to each candidate order; The result acquisition unit is used to determine the target order and the target site based on the directed graph of each candidate order.

13. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of claims 1-11.

14. A computer program product, comprising a computer program, characterized in that: When the computer program is executed on a computer, the computer executes the method according to any one of claims 1 to 11.

15. A computer-readable storage medium storing computer program instructions, characterized in that: The computer program instructions implement the method according to any one of claims 1 to 11 when executed by a processor.

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