Autonomous driving vehicle hybrid dispatching system and autonomous driving vehicle

Abstract

The present application discloses a hybrid dispatching system for autonomous driving vehicles and an autonomous driving vehicle, and belongs to the field of computer technology. The system includes a dispatching module and an autonomous driving vehicle; the dispatching module is used to determine the order that the autonomous driving vehicle is delivering, and the order corresponds to an order handover point and a destination; the dispatching module is also used to re-allocate the target delivery capacity for the order from multiple candidate delivery capacities based on the delivery information of the system, and the target delivery capacity is used to deliver the order from the order handover point to the destination, and the delivery information is used to indicate the delivery status of the order and delivery capacity in the system. The information considered by the system when scheduling orders is more timely, and the allocated delivery capacity is more accurate, thereby improving the efficiency of order delivery.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an autonomous driving vehicle hybrid scheduling system and an autonomous driving vehicle. Background Art

[0002] With the development of online shopping, food delivery and other businesses, the number of orders continues to increase. How to allocate transportation capacity to orders to improve order delivery efficiency is becoming increasingly important. Summary of the invention

[0003] The embodiment of the present application provides a hybrid dispatching system for autonomous driving vehicles and an autonomous driving vehicle, which improves the accuracy of order dispatching and thus improves the efficiency of order delivery. The technical solution is as follows:

[0004] In one aspect, a hybrid dispatching system for autonomous driving vehicles is provided, the system comprising a dispatching module and an autonomous driving vehicle;

[0005] The dispatch module is used to determine the order that the autonomous driving vehicle is delivering, and the order corresponds to an order handover point and a destination;

[0006] The scheduling module is also used to reallocate target delivery capacity for the order from multiple candidate delivery capacities based on the delivery status information of the system. The target delivery capacity is used to deliver the order from the order handover point to the destination. The delivery status information is used to indicate the delivery status of the orders and delivery capacity in the system.

[0007] In one aspect, an order scheduling method is provided, which is performed by a hybrid scheduling system for autonomous driving vehicles, the system comprising a scheduling module and an autonomous driving vehicle, the method comprising:

[0008] The dispatch module determines the order that the autonomous driving vehicle is delivering, the order corresponding to an order handover point and a destination;

[0009] The scheduling module reallocates target delivery capacity for the order from a plurality of candidate delivery capacities based on the delivery status information of the system. The target delivery capacity is used to deliver the order from the order handover point to the destination. The delivery status information is used to indicate the delivery status of the orders and delivery capacity in the system.

[0010] In a possible implementation, the delivery information includes at least one of the following:

[0011] the current location of the autonomous vehicle;

[0012] The region to which the order is destined;

[0013] the promised delivery time of the order;

[0014] Order information of uncompleted orders of the multiple candidate delivery capabilities;

[0015] The current locations of the plurality of candidate delivery transport capabilities;

[0016] The latest scheduling time of the multiple candidate delivery transport capabilities, where the latest scheduling time indicates the time when an order is last allocated to the candidate delivery transport capabilities;

[0017] The upper limit of the single load of the multiple candidate delivery transport capabilities;

[0018] The time taken for the multiple candidate delivery transport capabilities to arrive at the order handover point of the order.

[0019] In a possible implementation, there are multiple orders, and the delivery information includes the area to which the destination of the order belongs;

[0020] The scheduling module reassigns a target delivery capacity for the order from a plurality of candidate delivery capacities based on the delivery status information of the system, including:

[0021] The scheduling module aggregates multiple orders according to the area to which the destinations belong, to obtain at least one order group, where the destinations of the orders in the order group belong to the same area;

[0022] The scheduling module allocates a target delivery capacity to each order group from the multiple candidate delivery capacities, and the target delivery capacity allocated to any order group is used to deliver each order in the order group.

[0023] In a possible implementation, the method further includes:

[0024] If the order quantity of any order group is greater than the target quantity, the order group is split into at least two order groups, and the order quantity of each order group after the split is not greater than the target quantity.

[0025] In a possible implementation, the delivery status information includes the promised delivery time of the multiple orders and the delivery status of the multiple candidate delivery transport capacities;

[0026] The scheduling module allocates a target delivery capacity to each order group from the plurality of candidate delivery capacities, and the target delivery capacity allocated to any order group is used to deliver each order in the order group, including:

[0027] The scheduling module determines, for each order group, the earliest promised delivery time among the promised delivery times of each order in the order group;

[0028] The scheduling module determines the priority of each order group based on the earliest promised delivery time in each order group;

[0029] The scheduling module selects a target delivery capacity for each order group from the multiple candidate delivery capacities in turn based on the delivery status of the multiple candidate delivery capacities and according to the priority of each order group.

[0030] In a possible implementation, the delivery status of the candidate delivery transport capacity includes the number of uncompleted orders of the candidate delivery transport capacity;

[0031] The scheduling module selects a target delivery capacity for each order group from the multiple candidate delivery capacities in sequence according to the delivery status of the multiple candidate delivery capacities and the priority of each order group, including:

[0032] The scheduling module determines the priority of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, wherein the priority is negatively correlated with the number of uncompleted orders;

[0033] The scheduling module selects a target delivery capacity for each order group according to the priority of each order group and the priorities of the multiple candidate delivery capacities.

[0034] In a possible implementation, the delivery status information includes order information of uncompleted orders of the multiple candidate delivery transport capacities and current locations of the multiple candidate delivery transport capacities;

[0035] The scheduling module re-allocates target delivery capacity for the order from a plurality of candidate delivery capacities based on the delivery status information of the system, including:

[0036] The scheduling module determines, based on the order information and current location of the unfinished orders of the multiple candidate delivery capacities, multiple candidate delivery capacities whose current location belongs to a target area and / or whose destinations of each unfinished order belong to the target area, and reallocates the target delivery capacity to the order from the determined multiple candidate delivery capacities, where the target area is the area to which the order handover point belongs.

[0037] In a possible implementation, the delivery status information includes order information of uncompleted orders of the multiple candidate delivery transport capacities;

[0038] The scheduling module re-allocates target delivery capacity for the order from a plurality of candidate delivery capacities based on the delivery status information of the system, including:

[0039] The scheduling module determines the number of uncompleted orders of the multiple candidate delivery transport capacities based on the order information of the uncompleted orders of the multiple candidate delivery transport capacities;

[0040] The scheduling module determines the priority of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, wherein the priority is negatively correlated with the number of uncompleted orders;

[0041] The scheduling module selects candidate delivery capacity that meets the priority conditions as the target delivery capacity for the order.

[0042] In a possible implementation, the delivery status information includes the latest scheduling time of the multiple candidate delivery transport capacities and the time it takes for the multiple candidate delivery transport capacities to arrive at the order handover point of the order;

[0043] The scheduling module determines the priorities of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, including:

[0044] The scheduling module determines the priority of the at least two candidate delivery transport capacities based on the latest scheduling time of each of the at least two candidate delivery transport capacities when the number of uncompleted orders of the at least two candidate delivery transport capacities is 0, wherein the priority is negatively correlated with the latest scheduling time, and the scheduling time represents the time for allocating orders to the candidate delivery transport capacities;

[0045] When the number of uncompleted orders of at least two candidate delivery capacities is the same and not zero, the scheduling module determines the priority of the at least two candidate delivery capacities based on the time it takes for each of the at least two candidate delivery capacities to arrive at the order handover point, and the priority is negatively correlated with the time it takes.

[0046] On the one hand, an autonomous driving vehicle is provided, which is used to depart from a first location and deliver the order to an order handover point of the order when the collected orders meet the departure conditions. Other delivery capacity then delivers the order from the order handover point to the destination of the order. The order corresponds to an order handover point and a destination, and the first location is the pickup location for the order.

[0047] On the one hand, a computer-readable storage medium is provided, in which at least one program code is stored, and the at least one program code is loaded and executed by a processor to implement the operations performed by the order scheduling method in any possible implementation manner as described above.

[0048] On the one hand, a computer program or a computer program product is provided, wherein the computer program or the computer program product comprises: a computer program code, wherein when the computer program code is executed by a computer, the computer implements the operations performed by the order scheduling method in any possible implementation manner as described above.

[0049] The autonomous driving vehicle hybrid scheduling system and autonomous driving vehicle provided in the embodiments of the present application are for a mode of relay delivery between autonomous driving vehicles and delivery capacity. After the autonomous driving vehicle sets off, delivery capacity is allocated to the orders that the autonomous driving vehicle is delivering. At this time, the delivery information considered for order allocation is more timely and the allocated delivery capacity is more accurate, thereby improving order delivery efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 It is a structural schematic diagram of a hybrid dispatching system for autonomous driving vehicles provided in an embodiment of the present application;

[0052] Figure 2 is a flow chart of an order scheduling method provided by an embodiment of the present application;

[0053] Figure 3 is a flow chart of an order scheduling method provided by an embodiment of the present application;

[0054] Figure 4 is a flow chart of an order scheduling method provided by an embodiment of the present application;

[0055] Figure 5 is a structural schematic diagram of an autonomous driving vehicle provided in an embodiment of the present application;

[0056] Figure 6 It is a structural diagram of a server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0058] It is understood that the terms "first", "second", etc. used in this application can be used in this article to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, a first order can be called a second order, and a second order can be called a first order without departing from the scope of this application.

[0059] The terms "at least one", "multiple", "each" and "any" used in this application, at least one includes one, two or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple. For example, multiple orders include 3 orders, and each refers to each of the 3 orders, and any refers to any one of the 3 orders, which can be the first, the second or the third.

[0060] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions. For example, the order and delivery information involved in this application are all obtained with full authorization. And the above information and data are processed and used in big data application scenarios, and cannot be identified to any natural person or have a specific association with him.

[0061] The hybrid dispatching system for autonomous driving vehicles provided in the embodiments of the present application can be applied to delivery scenarios, such as food delivery scenarios, express delivery scenarios, warehousing delivery scenarios, etc. The embodiments of the present application do not limit this, and only use the following two delivery scenarios as examples for illustrative explanation.

[0062] For example, in the warehousing and distribution scenario:

[0063] Taking the warehouse as a vegetable warehouse as an example (the vegetable warehouse can be regarded as a vegetable station), users can purchase vegetables online, and the self-driving vehicle delivers the vegetables purchased by the user to the order handover point (such as the user's community gate), and other delivery capabilities deliver the vegetables from the order handover point to the order destination.

[0064] Another example is the express delivery scenario:

[0065] Autonomous driving vehicles can deliver express packages from express delivery stations to order handover points (such as the user’s community gate, etc.), and other delivery capabilities will deliver the express packages from the order handover point to the order destination.

[0066] In some embodiments, the autonomous driving vehicle hybrid dispatching system includes a dispatching module and an autonomous driving vehicle. The autonomous driving vehicle includes vehicles traveling on the ground (e.g., cars, trucks, buses, etc.), and may also include vehicles traveling in the air (e.g., drones, airplanes, helicopters, etc.), and may also include vehicles traveling on or in the water (e.g., ships, submarines, etc.). The autonomous driving vehicle may or may not accommodate one or more passengers. In addition, the autonomous driving vehicle can be applied to unmanned delivery fields, such as express logistics, takeout delivery, etc.

[0067] The scheduling module may be a complete device or a component module of a device, and the embodiments of the present application do not limit the scheduling module. Optionally, the scheduling module is a scheduling server, which may be a server, a server cluster composed of several servers, or a cloud computing service center.

[0068] Figure 1 is a structural diagram of a hybrid dispatching system for autonomous driving vehicles provided in an embodiment of the present application, such as Figure 1 As shown, the system includes an autonomous driving vehicle 101 and a dispatching module 102, and the autonomous driving vehicle 101 and the dispatching module 102 are connected via a wireless or wired network.

[0069] In some embodiments, the scheduling module 102 receives an order submitted by a user, assigns the order to the autonomous driving vehicle 101, and the autonomous driving vehicle 101 delivers the order to the order handover point based on the order handover point of the order.

[0070] The system also includes a terminal 103, which is a terminal for the delivery person. The dispatch module 102 receives the order submitted by the user, assigns the order to the autonomous driving vehicle 101, and assigns the order to the delivery person through the terminal 103. The autonomous driving vehicle 101 delivers the order to the order handover point, and the delivery person holding the terminal 103 delivers the order from the order handover point to the destination of the order.

[0071] It should be noted that the hybrid dispatching system for autonomous driving vehicles provided in the embodiment of the present application dispatches orders to one vehicle and one delivery person, and the delivery is carried out by people and vehicles. After receiving the order, the dispatching module determines the dispatching result of the order based on the status of the candidate autonomous driving vehicle (such as the location of the autonomous driving vehicle, etc.), the status of the candidate delivery person (such as the location of the candidate delivery person, the unfinished orders of the candidate delivery person, etc.) and the order information of the order. The dispatching result includes the autonomous driving vehicle and delivery person assigned to the order. The autonomous driving vehicle delivers the order to the order handover point, and the delivery person delivers the order from the order handover point to the order destination.

[0072] After the dispatch module dispatches an order to an autonomous vehicle, the autonomous vehicle usually does not start immediately, but waits until the number of orders to be delivered by the autonomous vehicle reaches the target number or the time constraint is met before it starts to dispatch. During the period from when the dispatch result of the order is determined to when the autonomous vehicle dispatches, the autonomous vehicle and the delivery person may be assigned to a new order, and the status of the delivery person may also change, causing the dispatch result to look unreasonable when the autonomous vehicle dispatches, which in turn leads to low order delivery efficiency.

[0073] Therefore, in order to improve the delivery efficiency of orders, the embodiments of the present application allocate target delivery capacity for the orders being delivered by the autonomous driving vehicle after the autonomous driving vehicle is dispatched. In some embodiments, when the scheduling module receives an order, it performs an order scheduling and determines the first order scheduling result, and the first order scheduling result includes the autonomous driving vehicle and the delivery person assigned to the order; after the autonomous driving vehicle departs, a secondary order scheduling is performed to determine the second order scheduling result, and the second order scheduling result includes the delivery person assigned to the order. The scheduling method provided in the embodiments of the present application is a scheduling method for secondary order scheduling. After obtaining the second order scheduling result, the allocation relationship between the order and the delivery person in the first order scheduling result is no longer based on the allocation relationship between the order and the delivery person, but on the allocation relationship between the order and the delivery person in the second order scheduling result.

[0074] In other embodiments, when the dispatch module receives an order, it first assigns an autonomous driving vehicle to the order, and after the autonomous driving vehicle sets off, it assigns a delivery person to the order that the autonomous driving vehicle is delivering. The dispatch method provided in the embodiment of the present application is a method for assigning a delivery person to the order that the autonomous driving vehicle is delivering.

[0075] Figure 2 This is a flow chart of an order scheduling method provided by an embodiment of the present application. This embodiment of the present application is exemplified by taking an autonomous driving vehicle hybrid scheduling system as an example, the system includes a scheduling module and an autonomous driving vehicle. The embodiment includes:

[0076] 201. The dispatch module determines the order that the autonomous driving vehicle is delivering, and the order corresponds to an order handover point and a destination.

[0077] In some embodiments, the autonomous driving vehicle is used to deliver orders to users in a certain area. All orders of users in the area are picked up from a first location, so the autonomous driving vehicle can stop at the first location. After the scheduling module assigns an order to the autonomous driving vehicle, the autonomous driving vehicle picks up the order at the first location and delivers the order to the order handover point.

[0078] It should be noted that the autonomous driving vehicle can deliver an order immediately after receiving it, or it can deliver multiple orders together after receiving multiple orders, which is not limited in the present embodiment. In other words, the order being delivered by the autonomous driving vehicle in the above step 201 can be one or more orders, which is not limited in the present embodiment.

[0079] In some embodiments, the autonomous driving vehicle departs from the first location when the collected orders meet the departure conditions. Among them, the orders collected by the autonomous driving vehicle are the orders assigned to the autonomous driving vehicle by the scheduling module and waiting for the autonomous driving vehicle to deliver. The departure condition may be that the number of orders collected by the autonomous driving vehicle reaches a first number, and the first number is any number, for example, 5, 8, 10, etc. The first number is not limited in the embodiment of the present application. The departure condition may also be that the time difference between the current moment of the autonomous driving vehicle and the collection moment of the first collected order (which can also be regarded as the distribution moment) reaches a first duration, and the first duration can be any duration, for example, 20 minutes, 30 minutes, etc. The embodiment of the present application does not limit the first duration. Optionally, the first duration can be determined by the promised delivery time of the first order to avoid completing the delivery of the first order beyond the promised delivery time.

[0080] In addition, the order handover point can be any location between the first location and the destination. In some embodiments, the order handover point is the gate of the community where the destination is located. The autonomous driving vehicle departs from the first location and delivers the order to the user's community gate, and the delivery person delivers the order from the community gate to the user.

[0081] 202. The dispatching module reallocates target delivery capacity for the order from a plurality of candidate delivery capacities based on the delivery status information of the system. The target delivery capacity is used to deliver the order from the order handover point to the destination. The delivery status information is used to indicate the delivery status of the order and the delivery capacity in the system.

[0082] In the embodiment of the present application, after the autonomous driving vehicle sets off, the dispatching module allocates target delivery capacity for the order being delivered by the autonomous driving vehicle. In order to more accurately allocate the target delivery capacity and improve the delivery efficiency of the order, the dispatching module allocates target delivery capacity for the order based on the delivery status information of the system. Since the delivery status information of the system is used to indicate the delivery status of the order and delivery capacity in the system, when allocating target delivery capacity for the order, the dispatching system takes into account the overall delivery status of the system and can allocate the optimal delivery capacity for the order.

[0083] In some embodiments, the delivery capacity is any type of delivery capacity. For example, a delivery person, a delivery robot, etc. In some embodiments, the delivery capacity is a delivery person. The system delivers the order to the gate of the community through an autonomous driving vehicle, and the delivery person delivers the order from the gate of the community to the user. Since the autonomous driving vehicle completes the main delivery path, the delivery cost is reduced. The final delivery is completed by the delivery person, which can ensure the accuracy of delivery and user experience.

[0084] In some embodiments, the multiple candidate delivery capacities are delivery capacities in the system. In other embodiments, the multiple candidate delivery capacities are delivery capacities that meet the conditions in the system. Optionally, there is a corresponding relationship between the delivery capacity and the region. If a certain delivery capacity corresponds to a certain region, it means that the delivery capacity is used to deliver orders to users in the region. Therefore, the multiple candidate delivery capacities in the above step 202 can be the delivery capacity corresponding to the region to which the order handover point belongs.

[0085] The order scheduling method provided in the embodiment of the present application is aimed at the mode of relay delivery between autonomous driving vehicles and delivery capacity. After the autonomous driving vehicle sets off, delivery capacity is allocated to the orders that the autonomous driving vehicle is delivering. At this time, the information considered in order allocation is more timely and the allocated delivery capacity is more accurate, thereby improving the order delivery efficiency.

[0086] Figure 3 This is a flow chart of an order scheduling method provided by an embodiment of the present application. This embodiment of the present application is exemplified by taking an autonomous driving vehicle hybrid scheduling system as an example, the system includes a scheduling module and an autonomous driving vehicle. The embodiment includes:

[0087] 301. The dispatch module determines a plurality of orders that the autonomous driving vehicle is delivering, and the orders correspond to an order handover point and a destination.

[0088] The embodiment of the present application is only an illustrative explanation of the timing of "the scheduling module determining that the autonomous driving vehicle is delivering multiple orders". For the rest, please refer to the above step 201, and the embodiment of the present application will not be described one by one here.

[0089] In some embodiments, after the autonomous driving vehicle departs, a first message notification is sent to the scheduling module. The first disappearance notification is used to indicate that the autonomous driving vehicle has departed from the first location. In response to receiving the first message notification, the scheduling module executes the above step 301.

[0090] In other embodiments, the scheduling module obtains the system's delivery information every first period of time, and the delivery information includes the current position of the autonomous driving vehicle. The scheduling module determines whether the autonomous driving vehicle has departed based on the current position of the autonomous driving vehicle. For example, if the current position does not belong to the first location, it is determined that the autonomous driving vehicle has departed from the first location. It should be noted that the scheduling module can not only determine the timing of "multiple orders that the scheduling module determines that the autonomous driving vehicle is delivering" based on the delivery information, but also allocate target delivery capacity for the multiple orders based on the delivery information.

[0091] Optionally, the delivery information includes at least one of the following: (1) the current location of the autonomous driving vehicle. (2) the area to which the destination of the order belongs. The order is an order in the system. (3) the promised delivery time of the order. The order can be an order in the system or an order that the autonomous driving vehicle is delivering. (4) order information of multiple candidate delivery capabilities that have not completed orders. The candidate delivery capabilities are delivery capabilities in the system or delivery capabilities that meet the conditions in the system. For example, the autonomous driving vehicle is used to deliver orders to users in the target area, and the candidate delivery capabilities are delivery capabilities used to deliver orders to users in the target area. (5) the current locations of multiple candidate delivery capabilities. (6) the latest scheduling time of multiple candidate delivery capabilities, which indicates the time when the order was last assigned to the candidate delivery capabilities. (7) the upper limit of the order load of multiple candidate delivery capabilities, which refers to the maximum number of uncompleted orders of the candidate delivery capabilities, or the maximum number of orders that the candidate delivery capabilities can deliver from the order handover point at one time. (8) the time it takes for multiple candidate delivery capabilities to reach the order handover point of the order.

[0092] 302. The scheduling module aggregates multiple orders according to the regions to which the destinations belong, and obtains at least one order group, in which the destinations of the orders in the order group belong to the same region.

[0093] In an embodiment of the present application, the order handover point of the order is related to the area to which the destination belongs. If the areas to which the two orders belong are the same area, then the order handover points of the two orders are the same order handover point. In some embodiments, the area to which the destination belongs is the community where the user is located, and the order handover point of the order is the entrance of the community where the user is located.

[0094] Since orders belonging to the same area correspond to the same order handover point, multiple orders belonging to the same area can be assigned to the same delivery capacity. In this way, the delivery capacity can hand over multiple orders at one order handover point and deliver the multiple orders to the same area.

[0095] In order to allocate orders belonging to the same area to the same delivery capacity, the embodiment of the present application aggregates multiple orders being delivered by the autonomous driving vehicle according to the area to which the destination belongs, and obtains at least one order group, which can then be allocated to the target delivery capacity.

[0096] In some embodiments, the destination of the order is xxx street, xxx community, xxx unit, xxx floor, xxx door number, xxx city. When the dispatch module aggregates multiple orders according to the area to which the destination belongs, it can directly obtain xxx community from the destination of the order and aggregate multiple orders belonging to the same community.

[0097] Since the scheduling module will assign order groups to the target delivery capacity, the target delivery capacity can also be considered to avoid too many orders in the order group, which will cause great pressure on the target delivery capacity, and avoid the situation where the target delivery capacity is not delivered in time and the orders are overdue due to too many orders. Optionally, the scheduling module aggregates multiple orders according to the area to which the destination belongs, and after obtaining at least one order group, if the number of orders in any order group is greater than the target number, the order group is split into at least two order groups, and the number of orders in each order group after the split is not greater than the target number.

[0098] The target quantity may be any number. For example, 3, 5, etc. The embodiment of the present application does not limit the target quantity. In some embodiments, the target quantity is the upper limit of the single load of the delivery capacity. The upper limit of the single load may be the maximum number of orders that the delivery capacity can deliver from the order delivery point at one time.

[0099] In the above step 201, it is mentioned that the autonomous driving vehicle is used to deliver orders to users in a certain area. It should be noted that the area targeted by the autonomous driving vehicle and the area to which the destination belongs are areas of different ranges. For example, the area in the above step 201 is the first area, and the area in the above step 302 is the second area. The second area is a sub-area of ​​the first area.

[0100] 303. The scheduling module determines, for each order group, the earliest promised delivery time among the promised delivery times of each order in the order group.

[0101] A very important point in order delivery is to complete the delivery of the order before the promised delivery time. Therefore, order allocation needs to ensure that the order is completed before the promised delivery time as much as possible. In order to complete the order before the promised delivery time as much as possible, the embodiment of the present application will give priority to allocating target delivery capacity to the order with the earliest promised delivery time. In this way, the target delivery capacity allocated to the order is the best delivery capacity among the candidate delivery capacities, so that the order can be delivered as soon as possible.

[0102] Since the scheduling module in the embodiment of the present application allocates delivery capacity to orders based on order groups, in order to give priority to the orders with the earliest promised delivery time, the scheduling module obtains the promised delivery time of each order in each order group, and determines the earliest promised delivery time from the promised delivery time of each order in the order group. The earliest promised delivery time indicates the urgency of the order group.

[0103] 304. The scheduling module determines the priority of each order group based on the earliest promised delivery time in each order group.

[0104] In the embodiment of the present application, the earlier the earliest promised delivery time of an order group, the higher the priority of the order group. The priority of an order group represents the order in which the target delivery capacity is allocated to the order group. Therefore, the higher the priority of an order group, the higher the priority of the scheduling module in allocating the target delivery capacity to the order group, so that the order group is allocated to the high-quality target delivery capacity, and the orders of the order group are delivered as soon as possible, thereby improving the efficiency of order delivery.

[0105] 305. The scheduling module determines, based on the order information and current location of the uncompleted orders of the multiple candidate delivery capacities, that the current location belongs to a target area and / or the destination of each uncompleted order belongs to multiple candidate delivery capacities of the target area, where the target area is the area to which the order handover points of the multiple orders belong.

[0106] In some embodiments, multiple candidate delivery capacities are delivery capacities in the system. In other embodiments, multiple candidate delivery capacities are delivery capacities that meet the conditions in the system. Optionally, there is a correspondence between delivery capacity and region. Among them, the delivery capacity corresponding to a certain region is used to deliver orders in that region. Therefore, the multiple candidate delivery capacities in the above step 305 can be the delivery capacity corresponding to the region to which the order handover point belongs. Optionally, the scheduling module determines the region to which the order handover points of multiple orders belong, and based on the correspondence between the delivery capacity and the region, determines the delivery capacity corresponding to the region to which it belongs as the candidate delivery capacity.

[0107] It should be noted that although the delivery capacity corresponding to the area is used to deliver the orders of users in the area, some of the delivery capacity corresponding to the area may not be in the area at present, or some delivery capacity may need to leave the area to deliver to other areas. These delivery capacities can be ignored when allocating target delivery capacity to the order group. That is, the scheduling module determines multiple delivery capacities whose current location belongs to the target area and / or whose destinations of each unfinished order belong to the target area based on the order information and current location of multiple candidate delivery capacities for unfinished orders, and selects the target delivery capacity for the order group from the multiple delivery capacities.

[0108] 306. The scheduling module determines the priorities of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, and the priority is negatively correlated with the number of uncompleted orders.

[0109] If the order group is assigned to a delivery capacity that currently has no orders to deliver, then the delivery capacity can deliver the order immediately after receiving the order, making the delivery efficiency of the order higher. If the order group is assigned to a delivery capacity with many unfinished orders, the delivery capacity may not be able to immediately hand over the order after the autonomous driving vehicle reaches the order handover point, nor can it deliver the order immediately, making the delivery efficiency of the order lower. Therefore, in an embodiment of the present application, the scheduling module determines the priority of multiple delivery capacities based on the number of unfinished orders of the multiple delivery capacities, and the priority is negatively correlated with the number of unfinished orders.

[0110] In addition, considering that there may be at least two delivery transport capacities with the same number of unfinished orders, the embodiment of the present application also provides a method for determining the priority of at least two delivery transport capacities when the number of unfinished orders of at least two delivery transport capacities is the same. Optionally, the scheduling module determines the priority of the multiple candidate delivery transport capacities based on the number of unfinished orders of the multiple candidate delivery transport capacities, including: when the number of unfinished orders of at least two candidate delivery transport capacities is 0, the scheduling module determines the priority of the at least two candidate delivery transport capacities based on the latest scheduling time of each candidate delivery transport capacity among the at least two candidate delivery transport capacities, and the priority is negatively correlated with the latest scheduling time, and the scheduling time represents the time when the order is assigned to the delivery transport capacity.

[0111] For example, the number of unfinished orders for delivery capacity 1 and delivery capacity 2 are both 0, but the latest scheduling time of delivery capacity 1 (the last time an order was assigned to the delivery capacity) is 11:35 on January 1, 2022, and the latest scheduling time of delivery capacity 1 (the last time an order was assigned to the delivery capacity) is 11:40 on January 1, 2022. The idle time of delivery capacity 1 is longer. Therefore, the priority of delivery capacity 1 is higher than that of delivery capacity 2, and orders are assigned to delivery capacity 1 first.

[0112] Optionally, the scheduling module determines the priority of the multiple candidate delivery capacities based on the number of uncompleted orders of the multiple candidate delivery capacities, including: when the number of uncompleted orders of at least two candidate delivery capacities is the same and not zero, determining the priority of the at least two candidate delivery capacities based on the time it takes for each of the at least two candidate delivery capacities to arrive at the order handover point, and the priority is negatively correlated with the time it takes.

[0113] When at least two candidate delivery capabilities have the same number of uncompleted orders, if one candidate delivery capability can arrive at the order handover point in advance, then the candidate delivery capability can deliver the orders in the order group in advance and complete the delivery of the order group earlier. Therefore, the shorter the time it takes for the candidate delivery capability to arrive at the order handover point, the higher its priority.

[0114] 307. The scheduling module selects a target delivery capacity for each order group according to the priority of each order group and the priorities of multiple candidate delivery capacities.

[0115] Among them, when the scheduling module selects the target delivery capacity for each order group according to the priority of each order group and the priorities of multiple candidate delivery capacities, the higher the priority of the order group, the priority of selecting the target delivery capacity for the order group; the higher the priority of the candidate delivery capacity, the priority of selecting the candidate delivery capacity as the target delivery capacity. Optionally, the scheduling module selects the target delivery capacity for each order group according to the priority of each order group and the priorities of multiple delivery capacities, including: in descending order of priority, for multiple order groups, from the candidate delivery capacities whose number of unfinished orders is less than the target number, determine the delivery capacity with the highest priority as the target delivery capacity for the order group.

[0116] That is to say, after obtaining the sorted order groups and delivery capacity, if the delivery capacity load constraint is met, the order groups are assigned to the delivery capacity with the highest priority in sequence as much as possible. For example, first consider assigning the highest priority order group to the delivery capacity with the highest priority, and then consider assigning the second highest priority order group to the delivery capacity with the highest priority. If the delivery capacity with the highest priority has reached the upper limit of the order load, consider assigning it to the delivery capacity with the second highest priority, and so on.

[0117] It should be noted that the embodiment of the present application only takes "determining the priorities of multiple order groups and the priorities of multiple candidate delivery capacities, and selecting target delivery capacity for each order group according to the priority of each order group and the priority of multiple candidate delivery capacities" as an example to exemplify "how to allocate target delivery capacity to orders", while in another embodiment, after aggregating the orders being delivered by the autonomous driving vehicle, the orders can be directly allocated. In one possible implementation, the scheduling module aggregates multiple orders according to the area to which the destinations belong to obtain at least one order group, and the destinations of the orders in the order group belong to the same area; the target delivery capacity is allocated to each order group from multiple candidate delivery capacities, and the target delivery capacity allocated to any order group is used to deliver each order in the order group.

[0118] Among them, the scheduling module can adopt any scheduling method (such as greedy algorithm, etc.) to allocate target delivery capacity for each order group from multiple candidate delivery capacities. The target delivery capacity allocated to any order group is used to deliver each order in the order group. The embodiment of the present application does not limit the scheduling method.

[0119] In some embodiments, the scheduling module may further sort multiple order groups, and select target delivery capacity for the multiple order groups in sequence according to the sequence of the multiple order groups. For example, for each order group, the scheduling module determines the earliest promised delivery time among the promised delivery times of each order in the order group; the scheduling module determines the priority of each order group based on the earliest promised delivery time in each order group, and selects target delivery capacity for each order group from the multiple candidate delivery capacities in sequence according to the priority of each order group based on the delivery status of the multiple candidate delivery capacities.

[0120] In some embodiments, before selecting a target delivery capacity for each order group from a plurality of candidate delivery capacities, the plurality of candidate delivery capacities are first screened. Optionally, the scheduling module is used to determine, based on the order information and current locations of the uncompleted orders of the plurality of candidate delivery capacities, a plurality of candidate delivery capacities whose current locations belong to a target area and / or whose destinations of each uncompleted order belong to a target area, and select a target delivery capacity for each order group from the determined plurality of candidate delivery capacities according to the priority of each order group, wherein the target area is the area to which the order handover points of the plurality of orders belong.

[0121] It should be noted that the embodiments of the present application only take "determining the priorities of multiple order groups and the priorities of multiple candidate delivery transport capacities, and selecting a target delivery transport capacity for each order group according to the priority of each order group and the priority of multiple candidate delivery transport capacities" and "determining the priorities of multiple order groups, and selecting a target delivery transport capacity for each order group according to the priority of each order group" as examples to illustrate "how to allocate target delivery transport capacity to an order". In another embodiment, the priorities of multiple candidate delivery transport capacities are determined, and the target delivery transport capacity is selected for the order according to the priorities of the multiple candidate delivery transport capacities.

[0122] Optionally, the scheduling module determines the number of uncompleted orders of the multiple candidate delivery capacities based on the order information of the uncompleted orders of the multiple candidate delivery capacities; the scheduling module determines the priority of the multiple candidate delivery capacities based on the number of uncompleted orders of the multiple candidate delivery capacities, and the priority is negatively correlated with the number of the uncompleted orders; the scheduling module selects the candidate delivery capacity that meets the priority condition as the target delivery capacity for the order.

[0123] For example, the scheduling module selects the candidate delivery capacity that meets the priority condition as the target delivery capacity for the order, including: the scheduling module selects the candidate delivery capacity with the highest priority as the target delivery capacity for the order.

[0124] The order scheduling method provided in the embodiment of the present application is aimed at the mode of relay delivery between autonomous driving vehicles and delivery capacity. After the autonomous driving vehicle sets off, delivery capacity is allocated to the orders that the autonomous driving vehicle is delivering. At this time, the information considered in order allocation is more timely and the allocated delivery capacity is more accurate, thereby improving the order delivery efficiency.

[0125] In addition, when the number of unfinished orders of multiple delivery capabilities is 0, the embodiment of the present application will determine the priority of the multiple delivery capabilities based on the latest scheduling time of the multiple delivery capabilities, so that the delivery capabilities with the longest idle time are assigned to orders first, thereby improving the fairness of order dispatching by the scheduling module.

[0126] In addition, the embodiment of the present application also Figure 4 The order scheduling method is exemplified. In some embodiments, at preset intervals, the system's delivery information is input into the scheduling module, and the delivery information includes: (1) the status of the autonomous driving vehicle, such as the current location of the autonomous driving vehicle; (2) the status of the rider, such as the order information, current location, and latest scheduling time of the rider's uncompleted orders; (3) the order status, such as the region to which the order destination belongs, the promised delivery time, etc.

[0127] The scheduling module makes decisions based on the input delivery information: for orders being delivered by autonomous vehicles, the orders suitable for delivery by a rider are first packaged through order aggregation, and then the order packages are sorted according to the promised delivery time of the order; for candidate riders, the candidate riders are first screened to exclude riders who cannot be scheduled. On this basis, the candidate riders are sorted based on their unfinished orders, current location, and latest scheduling time (that is, the last scheduling time). Finally, order scheduling is performed to gradually allocate order packages to riders.

[0128] The following is a detailed description of each step in the decision-making process:

[0129] (1) Order aggregation

[0130] Orders from the same community should be assigned to the same rider for delivery as much as possible to avoid different riders having to go to the station to hand over orders after the autonomous vehicle arrives at the station (the same as the order handover point mentioned above). However, this process also needs to consider the rider's order load limit. Therefore, this application first aggregates the orders according to the area to which the orders belong. If the order volume in the same area is greater than the rider's load, the order package will be split according to the order load limit.

[0131] (2) Order Sorting

[0132] The aggregated order packages need to be sorted according to the urgency of the orders. This application first compares the minimum value of the promised delivery time in each order package (that is, the promised delivery time of the most urgent order), and sorts the order packages according to the minimum value.

[0133] (3) Rider screening

[0134] For the riders, first of all, they need to filter out the riders who cannot assign these orders according to the screening rules. The screening rules include: (1) Filter out the riders who are not assigned to the stations corresponding to these orders. Among them, the riders assigned to the stations corresponding to the orders refer to: there is a corresponding relationship between the rider and the area to which the station belongs, and the rider is used to deliver the orders in the area. (2) Among the riders assigned to the stations corresponding to these orders, the current location is not in the area to which the station belongs, or there are unfinished orders whose destinations do not belong to the area to which the station belongs.

[0135] (4) Rider ranking

[0136] In order to assign the most urgent orders to the riders who are most likely to return to the station as soon as possible, the riders can be sorted. First, priority is given to riders whose order quantity is 0 at the decision-making moment (that is, riders who have no unfinished orders). This rider can arrive at the station before the autonomous driving vehicle reaches the station, thereby improving the efficiency of order delivery. If there are multiple riders with 0 order quantities, priority will be given to riders whose last scheduling time was earlier. This way, unfair order dispatching caused by not assigning orders to a certain rider for a long time can be avoided. When the rider's order quantity is greater than 0, the riders can be sorted according to the rider's order quantity. When there are multiple riders with the same order quantity, the time it takes for the rider to arrive at the station can be estimated based on the rider's position and the rider's unfinished orders, and sorted accordingly.

[0137] (5) Order Scheduling

[0138] After getting the sorted order packages and riders, if the rider load constraints are met, the order packages are dispatched to the delivery capacity with high priority as much as possible. For example, first consider dispatching the highest priority order package to the rider with the highest ranking, and then consider dispatching the second highest priority order package to the rider with the highest ranking. If the rider has reached the upper limit of the order load, consider dispatching it to the rider with the second highest ranking, and so on.

[0139] The embodiment of the present application also provides a hybrid dispatching system for autonomous driving vehicles, the system comprising a dispatching module and an autonomous driving vehicle;

[0140] The dispatch module is used to determine the order that the autonomous driving vehicle is delivering, and the order corresponds to an order handover point and a destination;

[0141] The scheduling module is also used to reallocate target delivery capacity for the order from multiple candidate delivery capacities based on the delivery status information of the system. The target delivery capacity is used to deliver the order from the order handover point to the destination. The delivery status information is used to indicate the delivery status of the order and delivery capacity in the system.

[0142] In a possible implementation, the delivery information includes at least one of the following:

[0143] the current location of the autonomous vehicle;

[0144] The region to which the order is destined;

[0145] The promised delivery time of the order;

[0146] Order information of the multiple uncompleted orders of the candidate delivery capabilities;

[0147] The current positions of the multiple candidate delivery transport capabilities;

[0148] The latest scheduling time of the multiple candidate delivery transport capabilities, where the latest scheduling time indicates the time when an order is last allocated to the candidate delivery transport capability;

[0149] The upper limit of the single load of the multiple candidate delivery transport capacities;

[0150] The time it takes for the multiple candidate delivery capabilities to arrive at the order handover point of the order.

[0151] In a possible implementation, the order is multiple, and the delivery information includes the area to which the destination of the order belongs;

[0152] The scheduling module is used to aggregate multiple orders according to the area to which the destinations belong, to obtain at least one order group, where the destinations of the orders in the order group belong to the same area;

[0153] The scheduling module is used to allocate a target delivery capacity to each order group from the multiple candidate delivery capacities, and the target delivery capacity allocated to any order group is used to deliver each order in the order group.

[0154] In a possible implementation, the scheduling module is used to split any order group into at least two order groups if the order quantity of the order group is greater than the target quantity, and the order quantity of each order group after the split is not greater than the target quantity.

[0155] In a possible implementation, the delivery status information includes the promised delivery time of the multiple orders and the delivery status of the multiple candidate delivery transport capacities;

[0156] The scheduling module is used to determine, for each order group, the earliest promised delivery time among the promised delivery times of each order in the order group;

[0157] The scheduling module is used to determine the priority of each order group based on the earliest promised delivery time in each order group;

[0158] The scheduling module is used to select a target delivery capacity for each order group from the multiple candidate delivery capacities in turn based on the delivery status of the multiple candidate delivery capacities and according to the priority of each order group.

[0159] In a possible implementation, the delivery status of the candidate delivery transport capacity includes the number of uncompleted orders of the candidate delivery transport capacity;

[0160] The scheduling module is used to determine the priority of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, and the priority is negatively correlated with the number of the uncompleted orders;

[0161] The scheduling module is used to select a target delivery capacity for each order group according to the priority of each order group and the priorities of the multiple candidate delivery capacities.

[0162] In a possible implementation, the delivery status information includes order information of uncompleted orders of the multiple candidate delivery transport capacities and current locations of the multiple candidate delivery transport capacities;

[0163] The scheduling module is used to determine, based on the order information and current location of the unfinished orders of the multiple candidate delivery capacities, multiple candidate delivery capacities whose current location belongs to the target area and / or the destination of each unfinished order belongs to the target area, and reallocate the target delivery capacity for the order from the determined multiple candidate delivery capacities, and the target area is the area to which the order handover point belongs.

[0164] In a possible implementation, the delivery status information includes order information of the multiple uncompleted orders of the candidate delivery transport capacities;

[0165] The scheduling module is used to determine the number of uncompleted orders of the multiple candidate delivery transport capacities based on the order information of the uncompleted orders of the multiple candidate delivery transport capacities;

[0166] The scheduling module is used to determine the priority of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, and the priority is negatively correlated with the number of the uncompleted orders;

[0167] The scheduling module is used to select candidate delivery capacity that meets the priority conditions as the target delivery capacity for the order.

[0168] In a possible implementation, the delivery status information includes the latest scheduling time of the multiple candidate delivery transport capacities and the time it takes for the multiple candidate delivery transport capacities to arrive at the order handover point of the order;

[0169] The scheduling module is used to determine the priority of the at least two candidate delivery transport capacities based on the latest scheduling time of each of the at least two candidate delivery transport capacities when the number of uncompleted orders of the at least two candidate delivery transport capacities is 0, wherein the priority is negatively correlated with the latest scheduling time, and the scheduling time represents the time for allocating orders to the candidate delivery transport capacities;

[0170] The scheduling module is used to determine the priority of the at least two candidate delivery capacities based on the time it takes for each of the at least two candidate delivery capacities to arrive at the order handover point when the number of uncompleted orders of at least two candidate delivery capacities is the same and not zero, and the priority is negatively correlated with the time it takes.

[0171] Figure 5 5 is a block diagram of an autonomous driving vehicle 500 provided in an embodiment of the present application. The autonomous driving vehicle 500 includes: a processor 501 and a memory 502.

[0172] The processor 501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 501 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 501 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 501 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 501 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0173] The memory 502 may include one or more computer-readable storage media, which may be non-transitory. The memory 502 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 502 is used to store at least one program code, which is used to be executed by the processor 501 to implement the order scheduling method provided in the method embodiment of the present application.

[0174] In some embodiments, the autonomous driving vehicle 500 may also optionally include: a peripheral device interface 503 and at least one peripheral device. The processor 501, the memory 502 and the peripheral device interface 503 may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface 503 via a bus, a signal line or a circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 504, a display screen 505, a camera 506, an audio circuit 507, a positioning component 508 and a power supply 509.

[0175] The peripheral device interface 503 may be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 501 and the memory 502. In some embodiments, the processor 501, the memory 502, and the peripheral device interface 503 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 501, the memory 502, and the peripheral device interface 503 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[0176] The radio frequency circuit 504 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 504 communicates with communication networks and other communication devices through electromagnetic signals. The radio frequency circuit 504 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency circuit 504 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and the like. The radio frequency circuit 504 can communicate with other autonomous driving vehicles through at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: a metropolitan area network, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 504 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0177] The display screen 505 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 505 is a touch display screen, the display screen 505 also has the ability to collect touch signals on the surface or above the surface of the display screen 505. The touch signal can be input to the processor 501 as a control signal for processing. At this time, the display screen 505 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 505 can be one, and the front panel of the autonomous driving vehicle 500 is set; in other embodiments, the display screen 505 can be at least two, which are respectively set on different surfaces of the autonomous driving vehicle 500 or are folded; in some other embodiments, the display screen 505 can be a flexible display screen, which is set on the curved surface or folded surface of the autonomous driving vehicle 500. Even, the display screen 505 can also be set as a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 505 can be made of materials such as LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode, organic light-emitting diode).

[0178] The camera assembly 506 is used to capture images or videos. Optionally, the camera assembly 506 includes a front camera and a rear camera. The front camera is arranged on the front panel of the autonomous driving vehicle, and the rear camera is arranged on the back of the autonomous driving vehicle. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 506 may also include a flash. The flash can be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0179] The audio circuit 507 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals and input them into the processor 501 for processing, or input them into the RF circuit 504 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the autonomous driving vehicle 500. The microphone may also be an array microphone or an omnidirectional acquisition microphone. The speaker is used to convert the electrical signal from the processor 501 or the RF circuit 504 into sound waves. The speaker may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 507 may also include a headphone jack.

[0180] The positioning component 508 is used to locate the current geographic location of the autonomous driving vehicle 500 to achieve navigation or LBS (Location Based Service). The positioning component 508 can be a positioning component based on the US GPS (Global Positioning System), China's Beidou system, Russia's Grenas system, or the European Union's Galileo system.

[0181] The power supply 509 is used to power various components in the autonomous driving vehicle 500. The power supply 509 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 509 includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0182] In some embodiments, the autonomous driving vehicle 500 further includes one or more sensors 510. The one or more sensors 510 include, but are not limited to, an acceleration sensor 511, a gyroscope sensor 512, a pressure sensor 513, a fingerprint sensor 514, an optical sensor 515, and a proximity sensor 516.

[0183] The acceleration sensor 511 can detect the magnitude of acceleration on the three coordinate axes of the coordinate system established by the autonomous driving vehicle 500. For example, the acceleration sensor 511 can be used to detect the components of gravity acceleration on the three coordinate axes. The processor 501 can control the display screen 505 to display the user interface in a horizontal view or a vertical view according to the gravity acceleration signal collected by the acceleration sensor 511. The acceleration sensor 511 can also be used to collect motion data of games or users.

[0184] The gyro sensor 512 can detect the body direction and rotation angle of the autonomous driving vehicle 500. The gyro sensor 512 can cooperate with the acceleration sensor 511 to collect the user's 3D actions on the autonomous driving vehicle 500. The processor 501 can implement the following functions based on the data collected by the gyro sensor 512: motion sensing (such as changing the UI according to the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0185] The pressure sensor 513 can be set on the side frame of the autonomous driving vehicle 500 and / or the lower layer of the display screen 505. When the pressure sensor 513 is set on the side frame of the autonomous driving vehicle 500, it can detect the user's grip signal of the autonomous driving vehicle 500, and the processor 501 performs left and right hand recognition or quick operation according to the grip signal collected by the pressure sensor 513. When the pressure sensor 513 is set on the lower layer of the display screen 505, the processor 501 controls the operability controls on the UI interface according to the user's pressure operation on the display screen 505. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0186] The fingerprint sensor 514 is used to collect the user's fingerprint, and the processor 501 identifies the user's identity based on the fingerprint collected by the fingerprint sensor 514, or the fingerprint sensor 514 identifies the user's identity based on the collected fingerprint. When the user's identity is identified as a trusted identity, the processor 501 authorizes the user to perform relevant sensitive operations, which include unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings. The fingerprint sensor 514 can be set on the front, back, or side of the autonomous driving vehicle 500. When a physical button or manufacturer logo is set on the autonomous driving vehicle 500, the fingerprint sensor 514 can be integrated with the physical button or manufacturer logo.

[0187] The optical sensor 515 is used to collect the ambient light intensity. In one embodiment, the processor 501 can control the display brightness of the display screen 505 according to the ambient light intensity collected by the optical sensor 515. Specifically, when the ambient light intensity is high, the display brightness of the display screen 505 is increased; when the ambient light intensity is low, the display brightness of the display screen 505 is reduced. In another embodiment, the processor 501 can also dynamically adjust the shooting parameters of the camera component 506 according to the ambient light intensity collected by the optical sensor 515.

[0188] The proximity sensor 516, also called a distance sensor, is disposed on the front panel of the autonomous vehicle 500. The proximity sensor 516 is used to collect the distance between the user and the front of the autonomous vehicle 500. In one embodiment, when the proximity sensor 516 detects that the distance between the user and the front of the autonomous vehicle 500 is gradually decreasing, the processor 501 controls the display screen 505 to switch from the screen-on state to the screen-off state; when the proximity sensor 516 detects that the distance between the user and the front of the autonomous vehicle 500 is gradually increasing, the processor 501 controls the display screen 505 to switch from the screen-off state to the screen-on state.

[0189] Those skilled in the art will understand that Figure 5 The structure shown in does not constitute a limitation on the autonomous driving vehicle 500, and may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0190] Figure 6 6 is a schematic diagram of the structure of a server provided in an embodiment of the present application. The server 600 may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) 601 and one or more memories 602, wherein at least one program code is stored in the memory 602, and the at least one program code is loaded and executed by the processor 601 to implement the methods provided in the above-mentioned various method embodiments. Of course, the server may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output, and the server may also include other components for implementing device functions, which will not be described in detail here.

[0191] The server 600 is used to execute the steps executed by the server in the above method embodiment.

[0192] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including a program code, and the program code can be executed by a processor in a computer device to complete the order scheduling method in the above embodiment. For example, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0193] In an exemplary embodiment, a computer program or a computer program product is also provided. The computer program or the computer program product includes a computer program code. When the computer program code is executed by a computer, the computer implements the order scheduling method in the above embodiment.

[0194] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0195] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. An autonomous driving vehicle hybrid dispatching system, characterized in that: The system includes a dispatch module and an autonomous driving vehicle; The scheduling module is configured to perform an order scheduling upon receiving an order, and determine a first order scheduling result, wherein the first order scheduling result includes the autonomous driving vehicle and target delivery capacity allocated to the order; the autonomous driving vehicle departs from the first location when the collected orders meet the departure conditions, and goes to the order handover point, and after the autonomous driving vehicle departs, determines the order being delivered by the autonomous driving vehicle, wherein the order corresponds to an order handover point and a destination; After the autonomous driving vehicle sets off, the scheduling module is also used to reallocate target delivery capacity for the order from multiple candidate delivery capacities based on the delivery status information of the system. The target delivery capacity is used to deliver the order from the order handover point to the destination. The delivery status information is used to indicate the delivery status of the orders and delivery capacity in the system.

2. The system according to claim 1, characterized in that The delivery information includes at least one of the following: the current location of the autonomous vehicle; The region to which the order is destined; the promised delivery time of the order; Order information of uncompleted orders of the multiple candidate delivery capabilities; The current locations of the plurality of candidate delivery transport capabilities; The latest scheduling time of the multiple candidate delivery transport capabilities, where the latest scheduling time indicates the time when an order is last allocated to the candidate delivery transport capabilities; The upper limit of the single load of the multiple candidate delivery transport capabilities; The time taken for the multiple candidate delivery transport capabilities to arrive at the order handover point of the order.

3. The system according to claim 1 or 2, characterized in that: There are multiple orders, and the delivery information includes the area to which the destination of the order belongs; The scheduling module is used to aggregate multiple orders according to the area to which the destinations belong, to obtain at least one order group, where the destinations of the orders in the order group belong to the same area; The scheduling module is used to allocate a target delivery capacity to each order group from the multiple candidate delivery capacities, and the target delivery capacity allocated to any order group is used to deliver each order in the order group.

4. The system according to claim 3, characterized in that The scheduling module is used to split the order group into at least two order groups if the order quantity of any order group is greater than the target quantity, and the order quantity of each order group after the split is not greater than the target quantity.

5. The system according to claim 3, characterized in that The delivery status information includes the promised delivery time of the multiple orders and the delivery status of the multiple candidate delivery transport capabilities; The scheduling module is used to determine, for each order group, the earliest promised delivery time among the promised delivery times of each order in the order group; The scheduling module is used to determine the priority of each order group based on the earliest promised delivery time in each order group; The scheduling module is used to select a target delivery capacity for each order group from the multiple candidate delivery capacities in turn based on the delivery status of the multiple candidate delivery capacities and according to the priority of each order group.

6. The system according to claim 5, characterized in that The delivery status of the candidate delivery transport capacity includes the number of uncompleted orders of the candidate delivery transport capacity; The scheduling module is used to determine the priority of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, wherein the priority is negatively correlated with the number of uncompleted orders; The scheduling module is used to select a target delivery capacity for each order group according to the priority of each order group and the priorities of the multiple candidate delivery capacities.

7. The system according to claim 1, characterized in that The delivery status information includes order information of uncompleted orders of the multiple candidate delivery transport capacities and current locations of the multiple candidate delivery transport capacities; The scheduling module is used to determine, based on the order information and current location of the unfinished orders of the multiple candidate delivery capacities, multiple candidate delivery capacities whose current location belongs to a target area and / or whose destinations of each unfinished order belong to the target area, and reallocate the target delivery capacity to the order from the determined multiple candidate delivery capacities, wherein the target area is the area to which the order handover point belongs.

8. The system according to claim 1, characterized in that The delivery status information includes order information of uncompleted orders of the multiple candidate delivery transport capacities; The scheduling module is used to determine the number of uncompleted orders of the multiple candidate delivery transport capacities based on the order information of the uncompleted orders of the multiple candidate delivery transport capacities; The scheduling module is used to determine the priority of the multiple candidate delivery transport capacities based on the number of uncompleted orders of the multiple candidate delivery transport capacities, wherein the priority is negatively correlated with the number of uncompleted orders; The scheduling module is used to select candidate delivery capacity that meets the priority conditions as the target delivery capacity for the order.

9. The system according to claim 8, characterized in that The delivery status information includes the latest scheduling time of the multiple candidate delivery transport capabilities and the time it takes for the multiple candidate delivery transport capabilities to arrive at the order handover point of the order; The scheduling module is used to determine the priority of the at least two candidate delivery transport capacities based on the latest scheduling time of each of the at least two candidate delivery transport capacities when the number of uncompleted orders of the at least two candidate delivery transport capacities is 0, wherein the priority is negatively correlated with the latest scheduling time, and the scheduling time represents the time for allocating orders to the candidate delivery transport capacities; The scheduling module is used to determine the priority of the at least two candidate delivery capacities based on the time it takes for each of the at least two candidate delivery capacities to arrive at the order handover point when the number of uncompleted orders of at least two candidate delivery capacities is the same and not zero, and the priority is negatively correlated with the time it takes.

10. An autonomous driving vehicle, characterized in that: The autonomous driving vehicle is applied in the autonomous driving vehicle hybrid dispatching system according to any one of claims 1 to 9; The autonomous driving vehicle is used to depart from a first location and deliver the order to an order handover point of the order when the collected orders meet the departure conditions. Other delivery capacity then delivers the order from the order handover point to the destination of the order. The order corresponds to an order handover point and a destination. The first location is the pickup location for the order. The autonomous driving vehicle is dispatched when the dispatching module receives the order. The other delivery capacity is dispatched for the order by the dispatching module after the autonomous driving vehicle departs.

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