CN118195191A

CN118195191A - Automatic driving vehicle mixed dispatching system and automatic driving vehicle

Info

Publication number: CN118195191A
Application number: CN202211615152.3A
Authority: CN
Inventors: 黄一挥; 方知言; 刘运运; 齐昕阳; 王大陆; 杨晋青; 黄昊
Original assignee: Beijing Sankuai Online Technology Co Ltd
Current assignee: Beijing Sankuai Online Technology Co Ltd
Priority date: 2022-12-14
Filing date: 2022-12-14
Publication date: 2024-06-14

Abstract

The application discloses an automatic driving vehicle mixed dispatching system and an automatic driving vehicle, and belongs to the technical field of computers. The system comprises a dispatch module and an automatic driving vehicle; the dispatching module is used for determining orders which are being distributed by the automatic driving vehicle, and the orders correspond to an order delivery point and a destination; the scheduling module is further configured to reassign a target delivery capacity from a plurality of candidate delivery capacities based on delivery condition information of the system, the target delivery capacity being used for delivering the order from the order delivery point to the destination, the delivery condition information being used for indicating delivery conditions of the order and the delivery capacity in the system. The system has the advantages that the information considered during order scheduling is more time-efficient, and the distribution capacity is more accurate, so that the order distribution efficiency is improved.

Description

Automatic driving vehicle mixed dispatching system and automatic driving vehicle

Technical Field

The application relates to the technical field of computers, in particular to a hybrid dispatching system for an automatic driving vehicle and the automatic driving vehicle.

Background

With the development of online shopping, takeaway and other businesses, the number of orders is increasing, and how to distribute the capacity for the orders to improve the order distribution efficiency is becoming more and more important.

Disclosure of Invention

The embodiment of the application provides an automatic driving vehicle mixed dispatching system and an automatic driving vehicle, which improve the accuracy of order dispatching and further improve the order dispatching efficiency. The technical scheme is as follows:

In one aspect, an autonomous vehicle hybrid dispatch system is provided, the system including a dispatch module and an autonomous vehicle;

the dispatching module is used for determining orders which are being distributed by the automatic driving vehicle, and the orders correspond to an order delivery point and a destination;

The scheduling module is further configured to reassign a target delivery capacity from a plurality of candidate delivery capacities based on delivery condition information of the system, the target delivery capacity being used for delivering the order from the order delivery point to the destination, the delivery condition information being used for indicating delivery conditions of the order and the delivery capacity in the system.

In one aspect, there is provided an order dispatch method performed by an autonomous vehicle hybrid dispatch system, the system including a dispatch module and an autonomous vehicle, the method comprising:

The dispatching module determines orders being distributed by the automatic driving vehicle, wherein the orders correspond to an order delivery point and a destination;

the scheduling module re-assigns a target delivery capacity from a plurality of candidate delivery capacities for the order based on delivery condition information of the system, the target delivery capacity being used to deliver the order from the order delivery point to the destination, the delivery condition information being used to indicate delivery conditions of the order and delivery capacity in the system.

In one possible implementation, the delivery condition information includes at least one of the following:

the current location of the autonomous vehicle;

A region to which a destination of the order belongs;

The promised time of delivery of the order;

order information for the plurality of candidate delivery capacity incomplete orders;

Current locations of the plurality of candidate shipping capacities;

a latest schedule time for the plurality of candidate delivery capacities, the latest schedule time representing a time when an order was last allocated to the candidate delivery capacities;

An upper limit of a single load of the plurality of candidate shipping capacities;

the length of time that the plurality of candidate shipping capacities reach the order point of intersection of the order.

In one possible implementation manner, the order is multiple, and the distribution condition information includes an area to which a destination of the order belongs;

The scheduling module reassigns the target delivery capacity from a plurality of candidate delivery capacities based on the delivery condition information of the system, comprising:

The scheduling module aggregates a plurality of orders according to the area of the destination to obtain at least one order group, wherein the destinations of the orders in the order group belong to the same area;

the scheduling module assigns a target delivery capacity for each order group from the plurality of candidate delivery capacities, the target delivery capacity assigned for any order group being used to deliver each order in the order group.

In one possible implementation, the method further includes:

if the number of orders of any order group is larger than the target number, splitting the order group into at least two order groups, wherein the number of orders of each split order group is not larger than the target number.

In one possible implementation, the delivery situation information includes a promised delivery time of the plurality of orders and a delivery status of the plurality of candidate delivery capacities;

The scheduling module assigns a target delivery capacity for each order group from the plurality of candidate delivery capacities, the target delivery capacity assigned for any order group for delivering each order in the order group, comprising:

the scheduling module determines, for each order group, an earliest promised delivery time among 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;

The scheduling module selects a target delivery capacity for each order group from the plurality of candidate delivery capacities in turn according to the priority of each order group based on the delivery states of the plurality of candidate delivery capacities.

In one possible implementation, the delivery status of the candidate delivery capacity includes a number of outstanding orders for the candidate delivery capacity;

the scheduling module selects a target delivery capacity for each order group from the plurality of candidate delivery capacities in turn according to the priority of each order group based on the delivery states of the plurality of candidate delivery capacities, including:

The scheduling module determining a priority of the plurality of candidate delivery capacity based on a number of outstanding orders for the plurality of candidate delivery capacity, the priority being inversely related to the number of outstanding orders;

And 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 candidate delivery capacities.

In one possible implementation, the delivery case information includes order information of the plurality of candidate delivery capacity incomplete orders and a current location of the plurality of candidate delivery capacities;

The scheduling module determines a plurality of candidate delivery capacities of which the current position belongs to a target area and/or destinations of each unfinished order belong to the target area based on order information and the current position of the plurality of candidate delivery capacities of unfinished orders, and redistributes the target delivery capacity to the orders from the determined plurality of candidate delivery capacities, wherein the target area is an area to which the order intersection belongs.

In one possible implementation, the delivery case information includes order information for the plurality of candidate delivery capacity outstanding orders;

the scheduling module determines a number of the plurality of candidate delivery capacity incomplete orders based on order information of the plurality of candidate delivery capacity incomplete orders;

the scheduling module selects candidate delivery capacities meeting the priority condition as target delivery capacities of the orders.

In one possible implementation, the delivery situation information includes a latest schedule time of the plurality of candidate delivery capacities and a length of time the plurality of candidate delivery capacities reach an order intersection of the order;

The scheduling module determining a priority of the plurality of candidate delivery capacities based on a number of outstanding orders for the plurality of candidate delivery capacities, comprising:

The scheduling module determines a priority of at least two candidate delivery capacities based on a latest scheduling time of each candidate delivery capacity of the at least two candidate delivery capacities when a number of outstanding orders of the at least two candidate delivery capacities is 0, the priority being inversely related to the latest scheduling time, the scheduling time representing a time of allocation of orders to the candidate delivery capacities;

The scheduling module determines a priority of at least two candidate delivery capacities based on a time period for each candidate delivery capacity of the at least two candidate delivery capacities to reach the order delivery point when the number of outstanding orders of the at least two candidate delivery capacities is the same and is not 0, wherein the priority is inversely related to the time period.

In one aspect, an autonomous vehicle is provided for delivering a collected order from a first location to an order delivery point of the order when the order meets a departure condition, the order being delivered from the order delivery point to a destination of the order by other delivery capabilities, the order corresponding to one order delivery point and one destination, the first location being a pick-up location for the order.

In one aspect, a computer readable storage medium having stored therein at least one program code loaded and executed by a processor to perform operations performed by an order dispatch method as any one of the possible implementations described above is provided.

In one aspect, there is provided a computer program or computer program product comprising: computer program code which, when executed by a computer, causes the computer to perform the operations performed by the order dispatch method as described above in any one of the possible implementations.

According to the automatic driving vehicle mixed dispatching system and the automatic driving vehicle, the distribution capacity is distributed for the orders distributed by the automatic driving vehicle after the automatic driving vehicle starts according to the mode of relay distribution of the automatic driving vehicle and the distribution capacity, at the moment, distribution condition information considered by the order distribution is more time-efficient, and the distribution capacity is more accurate, so that the order distribution efficiency is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic structural diagram of a hybrid scheduling system for an autonomous vehicle according to an embodiment of the present application;

FIG. 2 is a flow chart of an order scheduling method provided by an embodiment of the present application;

FIG. 3 is a flow chart of an order scheduling method provided by an embodiment of the present application;

FIG. 4 is a flow chart of an order scheduling method provided by an embodiment of the present application;

fig. 5 is a schematic structural view of an autonomous vehicle according to an embodiment of the present application;

Fig. 6 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.

It is to be understood that the terms "first," "second," and the like, as used herein, may be used to describe various concepts, but are not limited by these terms unless otherwise specified. These terms are only used to distinguish one concept from another. For example, a first order may be referred to as a second order and a second order may be referred to as a first order without departing from the scope of the present application.

The terms "at least one", "a plurality", "each", "any" as used herein, at least one includes one, two or more, a plurality includes two or more, and each refers to each of a corresponding plurality, any one refers to any one of a plurality, for example, a plurality of orders includes 3 orders, and each refers to each of the 3 orders, any one refers to any one of the 3 orders, either the first, the second, or the third.

It should be noted that, the information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data for analysis, stored data, presented data, etc.), and signals related to the present application are all authorized by the user or are fully authorized by the parties, and the collection, use, and processing of the related data is required to comply with the relevant laws and regulations and standards of the relevant countries and regions. For example, orders, distribution information, etc. referred to in the present application are acquired with sufficient authorization. And the information and the data are processed and then used in big data application scenes, and can not be identified to any natural person or generate specific association with the natural person.

The automatic driving vehicle mixed scheduling system provided by the embodiment of the application can be applied to delivery scenes, such as take-away delivery scenes, express delivery scenes, warehouse delivery scenes and the like, is not limited, and only the following two delivery scenes are taken as examples for illustration.

For example, warehouse delivery scenarios:

Taking the storage as a vegetable storage example (the vegetable storage can be regarded as a vegetable site), a user can purchase vegetables on the internet, an automatic driving vehicle distributes the vegetables purchased by the user to an order delivery point (such as a district gate of the user), and other distribution capacity distributes the vegetables from the order delivery point to an order destination.

As another example, express delivery scenario:

The autonomous vehicle may deliver the express from the delivery station to an order delivery point (e.g., a user's cell gate, etc.), from where the express is delivered to the order destination by other delivery capabilities.

In some embodiments, the autonomous vehicle hybrid dispatch system includes a dispatch module and an autonomous vehicle. The autonomous vehicle includes vehicles that travel on the ground (e.g., automobiles, trucks, buses, etc.), vehicles that travel in the air (e.g., drones, planes, helicopters, etc.), and vehicles that travel on or in water (e.g., boats, submarines, etc.). The autonomous vehicle may or may not accommodate one or more passengers. In addition, the autonomous vehicle can be applied to the unmanned distribution field, such as the express logistics field, the take-away meal delivery field, and the like.

The scheduling module may be a complete device or may be a component module of a device, which is not limited in the embodiment of the present application. Optionally, the scheduling module is a scheduling server, and the scheduling server may be a server, a server cluster formed by a plurality of servers, or a cloud computing service center.

Fig. 1 is a schematic structural diagram of a hybrid dispatching system for an automatic driving vehicle, which is provided in an embodiment of the present application, and as shown in fig. 1, the system includes an automatic driving vehicle 101 and a dispatching module 102, where the automatic driving vehicle 101 and the dispatching module 102 are connected through a wireless or wired network.

In some embodiments, the dispatch module 102 receives an order submitted by a user, assigns the order to the automated driving vehicle 101, and the automated driving vehicle 101 dispatches the order to an order-interchange based on the order-interchange of the order.

The system further comprises a terminal 103, which terminal 103 is the terminal of the dispenser. The dispatch module 102 receives an order submitted by a user, distributes the order to the automated driving vehicle 101, distributes the order to a dispatcher through the terminal 103, dispatches the order to an order delivery point by the automated driving vehicle 101, and dispatches the order from the order delivery point to a destination of the order by a dispatcher holding the terminal 103.

It should be noted that, the automatic driving vehicle hybrid scheduling system provided by the embodiment of the application schedules orders to a vehicle and a dispatcher, and the orders are distributed by human-vehicle relay. After receiving the order, the dispatch module determines a dispatch result for the order based on a status of the candidate autonomous vehicle (e.g., a location of the autonomous vehicle, etc.), a status of the candidate dispatcher (e.g., a location of the candidate dispatcher, an incomplete order of the candidate dispatcher, etc.), and order information for the order, the dispatch result including the autonomous vehicle and the dispatcher assigned to the order, the order being dispatched by the autonomous vehicle to an order delivery point, the order being dispatched by the dispatcher from the order delivery point to an order destination.

Since the dispatch module dispatches orders to the autonomous vehicle, the autonomous vehicle will typically not pick up immediately, but will pick up after the order to be dispatched of the autonomous vehicle reaches a target number or reaches a time constraint. And the automatic driving vehicle and the dispatcher may be allocated to a new order within a period from determining the dispatching result of the order to the time when the automatic driving vehicle starts, and the state of the dispatcher may also be changed, so that the determined dispatching result may not be reasonable when the automatic driving vehicle starts, and the dispatching efficiency of the order is lower.

Therefore, in order to improve the order distribution efficiency, the embodiment of the application distributes the target distribution capacity for the order being distributed by the automatic driving vehicle after the automatic driving vehicle gets out. In some embodiments, the scheduling module, upon receiving an order, performs an order schedule, determining a first order scheduling result, the first order scheduling result including an autonomous vehicle and a dispatcher assigned for the order; after the automatic driving vehicle starts, secondary order scheduling is performed, and a second order scheduling result is determined, wherein the second order scheduling result comprises a dispatcher allocated for the order. The scheduling method provided by the embodiment of the application is a scheduling method for secondary order scheduling. After the second order scheduling result is obtained, the allocation relation between the order and the dispatcher in the first order scheduling result is not used as the reference, but the allocation relation between the order and the dispatcher in the second order scheduling result is used as the reference.

In other embodiments, the dispatch module, upon receiving an order, first assigns an autonomous vehicle to the order, and after the autonomous vehicle proceeds, assigns a dispatcher to the order that the autonomous vehicle is dispatching. The scheduling method provided by the embodiment of the application is a method for distributing a dispatcher for an order being dispatched by an automatic driving vehicle.

Fig. 2 is a flowchart of an order scheduling method according to an embodiment of the present application. The embodiment of the application is exemplified by taking a mixed dispatching system of an automatic driving vehicle as an executing main body, wherein the system comprises a dispatching module and the automatic driving vehicle, and the embodiment comprises the following steps:

201. The dispatch module determines an order being dispatched by the autonomous vehicle, the order corresponding to an order delivery point and a destination.

In some embodiments, an autonomous vehicle is used to distribute orders for users in an area. The user's orders in the area are all picked from the first location, so that the autonomous vehicle can stop at the first location, and after the dispatching module distributes the orders to the autonomous vehicle, the autonomous vehicle picks the orders at the first location and distributes the orders to the order delivery points.

It should be noted that, after the automatic driving vehicle may receive an order, the order may be immediately distributed; multiple orders may be received and then distributed together, as the embodiments of the present application are not limited in this regard. That is, in the step 201, the order that the autonomous vehicle is delivering may be one or more, which is not limited in the embodiment of the present application.

In some embodiments, the autonomous vehicle starts from the first location when the collected orders satisfy the start condition. The orders collected by the automatic driving vehicles are orders distributed to the automatic driving vehicles by the dispatching module and waiting for distribution of the automatic driving vehicles. The departure condition may be that the number of orders collected by the autonomous vehicle reaches a first number, which is any number, e.g., 5, 8, 10, etc. The first number is not limited in the embodiment of the present application. The departure condition may be that a time difference between a current time of the automatic driving vehicle and a collection time (which may also be regarded as an allocation time) of the collected first order reaches a first time, where the first time may be any time, for example, 20 minutes, 30 minutes, and the embodiment of the present application does not limit the first time. Alternatively, the first duration may be determined by the promised delivery time of the first order to avoid completing delivery of the first order beyond the promised delivery time.

In addition, the order contact point may be any point between the first location and the destination. In some embodiments, the order-crossing point is the gate of the cell in which the destination is located. The autonomous vehicle starts from a first location and delivers the order to a cell gate of the user, from which the dispatcher delivers the order to the user.

202. The scheduling module reassigns a target delivery capacity for the order from the plurality of candidate delivery capacities based on delivery condition information of the system, the target delivery capacity being for delivering the order from the order delivery point to the destination, the delivery condition information being indicative of delivery conditions of the order and the delivery capacity in the system.

In the embodiment of the application, the dispatch module distributes the target delivery capacity for the order being delivered by the automatic driving vehicle after the automatic driving vehicle starts. In order to more accurately distribute the target delivery capacity, the delivery efficiency of the order is improved, and the scheduling module distributes the target delivery capacity for the order based on the delivery condition information of the system. Because the distribution condition information of the system is used for indicating the distribution conditions of the orders and the distribution capacity in the system, when the target distribution capacity is distributed for the orders, the dispatching system considers the overall distribution condition of the system and can distribute the optimal distribution capacity for the orders.

In some embodiments, the shipping capacity is any type of shipping capacity. Such as a dispenser, a dispensing robot, etc. In some embodiments, the shipping capacity is a dispatcher. The system distributes the order to the district gate through the automatic driving vehicle, and the distributor distributes the order from the district gate to the user, so that the distribution cost is reduced because the automatic driving vehicle completes the main distribution path, and the distributor completes the final distribution, thereby ensuring the distribution accuracy and the user experience.

In some embodiments, the plurality of candidate shipping capacities is a shipping capacity in a system. In other embodiments, the plurality of candidate shipping capacities is a shipping capacity in the system that satisfies a condition. Optionally, the distribution capacity has a correspondence with the area. If a shipping capacity corresponds to a region, the shipping capacity is indicated for use in shipping orders for users in the region. Accordingly, the plurality of candidate delivery capacities in the step 202 may be delivery capacities corresponding to the areas to which the order delivery points belong.

According to the order scheduling method provided by the embodiment of the application, aiming at the modes of the automatic driving vehicle and the delivery capacity relay delivery, the delivery capacity is distributed for the order being delivered by the automatic driving vehicle after the automatic driving vehicle starts, at the moment, the information considered by the order distribution is more time-efficient, and the distributed delivery capacity is more accurate, so that the order delivery efficiency is improved.

Fig. 3 is a flowchart of an order scheduling method according to an embodiment of the present application. The embodiment of the application is exemplified by taking a mixed dispatching system of an automatic driving vehicle as an executing main body, wherein the system comprises a dispatching module and the automatic driving vehicle, and the embodiment comprises the following steps:

301. The dispatch module determines a plurality of orders being dispatched by the autonomous vehicle, the orders corresponding to an order delivery point and a destination.

The embodiment of the present application is merely illustrative of the timing of the scheduling module determining the plurality of orders that the autonomous vehicle is delivering, and the rest of the embodiments of the present application may refer to step 201 described above, which is not described in detail herein.

In some embodiments, after the autonomous vehicle starts, a first message notification is sent to the dispatch module indicating that the autonomous vehicle has started from the first location, and the dispatch module performs step 301 described above in response to receiving the first message notification.

In other embodiments, the dispatch module obtains the delivery status information of the system once every a first time period, the delivery status information including a current location of the autonomous vehicle. The dispatch module determines whether the autonomous vehicle is to be launched based on the current location of the autonomous vehicle. For example, the current location does not belong to a first location, and it is determined that the autonomous vehicle has departed from the first location. It should be noted that, the scheduling module may not only determine the timing of "the scheduling module determining a plurality of orders being distributed by the automated driving vehicle" according to the distribution situation information, but also may distribute the target distribution capacity for the plurality of orders according to the distribution situation information.

Optionally, the delivery status information includes at least one of: (1) automatically driving the current location of the vehicle. (2) an area to which the destination of the order belongs. The order is an order in the system. (3) promised time of delivery of order. The order may be an order in the system or an order that the autonomous vehicle is delivering. (4) Order information for a plurality of candidate shipping capacity outstanding orders. The candidate delivery capacity is a delivery capacity in the system or a delivery capacity in the system that satisfies a condition, for example, an autonomous vehicle is used to deliver an order to a user in the target area, and the candidate delivery capacity is a delivery capacity used to deliver an order to a user in the target area. (5) the current location of the plurality of candidate shipping capacities. (6) A latest schedule time for a plurality of candidate delivery capacities, the latest schedule time representing a time when an order was last allocated to the candidate delivery capacity. (7) An upper limit on the single volume load for the plurality of candidate delivery capacities, the upper limit on the single volume load referring to the maximum number of outstanding orders for the candidate delivery capacity, or the maximum number of orders that the candidate delivery capacity can deliver from the order delivery point at a time. (8) The length of time that the plurality of candidate shipping capacities reach the order point of intersection of the order.

302. And the scheduling module aggregates the orders according to the area to which the destination belongs to obtain at least one order group, wherein the destinations of the orders in the order group belong to the same area.

In the embodiment of the present application, the order intersection of the orders is related to the area to which the destination belongs, and if the areas to which the two orders belong are the same area, the order intersection of the two orders is the same order intersection. In some embodiments, the area to which the destination belongs is a cell in which the user is located, and the order-contact point of the order is a cell gate in which the user is located.

Since orders belonging to the same area correspond to the same order delivery point, a plurality of orders belonging to the same area can be assigned to the same delivery capacity, so that the delivery capacity can be delivered to a plurality of orders at one order delivery point and the plurality of orders can be delivered to the same area.

In order to allocate orders belonging to the same area to the same delivery capacity, the embodiment of the application aggregates a plurality of orders being delivered by the automatic driving vehicle according to the area to which the destination belongs, so as to obtain at least one order group, and then the order group can be allocated to the target delivery capacity.

In some embodiments, the order is destined for an xxx urban xxx street xxx cell xxx unit xxx floor xxx gate number. When the scheduling module aggregates a plurality of orders according to the area to which the destination belongs, the scheduling module can directly acquire the xxx cell from the destination of the orders and aggregate a plurality of orders belonging to the same cell.

Because the scheduling module can distribute the orders into the target delivery capacity, the tolerance of the target delivery capacity can be considered, so that excessive orders in the order group are avoided, larger pressure is caused to the target delivery capacity, and the conditions of untimely delivery of the target delivery capacity and overtime of the orders caused by excessive orders are also avoided. Optionally, after the scheduling module aggregates the plurality of orders according to the area to which the destination belongs to obtain at least one order group, if the number of orders of any order group is greater than the target number, splitting the order group into at least two order groups, wherein the number of orders of each split order group is not greater than the target number.

Wherein the target number may be any number. E.g., 3, 5, etc. The embodiment of the application does not limit the target quantity. In some embodiments, the target number is a single load upper limit for shipping capacity. The upper limit of the order load may be the maximum number of orders that the shipping capacity can transfer from the order transfer point at a time.

In step 201, the autonomous vehicle is mentioned as being used to distribute an order to a user in a certain area, and it should be noted that the area targeted by the autonomous vehicle and the area to which the destination belongs are areas in different ranges. Taking the region in the step 201 as a first region, taking the region in the step 302 as a second region as an example, the second region is a sub-region of the first region.

303. The scheduling module determines, for each order group, an earliest promised arrival time of promised arrival times of each order in the order group.

The important points of order delivery are: delivery of the order is completed before the promised time of delivery of the order. Thus, order allocation needs to be as guaranteed as possible that orders are completed before the promised time. In order to make the order complete before the promised delivery time as much as possible, the embodiment of the application can preferentially allocate the target delivery capacity for the order with the earliest promised delivery time, so that the target delivery capacity allocated by the order is the optimal delivery capacity in the candidate delivery capacities, and the order can be delivered as soon as possible.

Because the scheduling module in the embodiment of the application distributes the delivery capacity by taking the order group as the unit, in order to distribute the order of the earliest promised delivery time preferentially, the scheduling module acquires the promised delivery time of each order in the order group for each order group, and determines the earliest promised delivery time from the promised delivery time of each order in the order group. The degree of urgency of the order group is represented by the earliest promised time of delivery.

304. The scheduling module determines a priority for each order group based on the earliest promised time of delivery in each order group.

In the embodiment of the application, the earlier the earliest promised delivery time of the order group is, the higher the priority of the order group is. The priority of the order group is expressed as the order of the order group distribution target distribution capacity, so that the higher the priority of the order group is, the more preferentially the scheduling module distributes the target distribution capacity for the order group, so that the order group is distributed to the high-quality target distribution capacity, the order of the order group is distributed as soon as possible, and the order distribution efficiency is improved.

305. The scheduling module determines, based on the order information of the outstanding orders of the candidate delivery capacities and the current position, that the current position belongs to a target area and/or that the destination of each outstanding order belongs to the candidate delivery capacities of the target area, wherein the target area is an area to which an order intersection of the orders belongs.

In some embodiments, the plurality of candidate shipping capacities is a shipping capacity in a system. In other embodiments, the plurality of candidate shipping capacities is a shipping capacity in the system that satisfies a condition. Optionally, the distribution capacity has a correspondence with the area. Wherein the delivery capacity corresponding to a region is used to deliver orders for that region. Accordingly, the plurality of candidate shipping capacities in step 305 may be shipping capacities corresponding to the areas to which the order delivery points belong. Optionally, the scheduling module determines a region to which the order-delivery points of the plurality of orders belong, and determines the delivery capacity corresponding to the region to which the delivery capacity belongs as the candidate delivery capacity based on the correspondence between the delivery capacity and the region.

Although the delivery capacity corresponding to the area is used to deliver the order of the user in the area, there may be some delivery capacities corresponding to the area that are not currently located in the area or some delivery capacities that need to be delivered to other areas away from the area. These delivery capacities may not be considered when assigning the order to the target delivery capacities. That is, the scheduling module determines, based on the order information and the current location of the plurality of candidate delivery capacity incomplete orders, a plurality of delivery capacities of which the current location belongs to a target area and/or of which the destination of each incomplete order belongs to the target area, and selects a target delivery capacity for the order group from the plurality of delivery capacities.

306. The scheduling module determines a priority of the plurality of candidate delivery capacities based on the determined number of outstanding orders for the plurality of candidate delivery capacities, the priority being inversely related to the number of outstanding orders.

If an order is assigned to a delivery capacity that does not currently have an order to be delivered, the delivery capacity may deliver the order immediately after handing over to the order, resulting in a higher delivery efficiency for the order. If an order group is assigned to a delivery capacity with more outstanding orders, the delivery capacity may not be able to deliver the order immediately after the automated driving vehicle reaches the order delivery point, nor may the order be able to be delivered immediately, making delivery of the order less efficient. Thus, in an embodiment of the present application, the scheduling module determines a priority of the plurality of delivery capacity based on a number of outstanding orders for the plurality of delivery capacity, the priority being inversely related to the number of outstanding orders.

In addition, considering that the number of outstanding orders with at least two delivery capacities may be the same, the embodiment of the present application further provides a manner of determining the priority of the at least two delivery capacities when the number of outstanding orders with at least two delivery capacities is the same. Optionally, the scheduling module determines a priority of the plurality of candidate delivery capacities based on the determined number of outstanding orders for the plurality of candidate delivery capacities, comprising: the scheduling module determines a priority of at least two candidate delivery capacities based on a latest scheduling time of each candidate delivery capacity of the at least two candidate delivery capacities, where the priority is inversely related to the latest scheduling time, and the scheduling time indicates a time to allocate an order to the delivery capacity, in a case where the number of outstanding orders of the at least two candidate delivery capacities is 0.

For example, the number of outstanding orders for both delivery capacity 1 and delivery capacity 2 is 0, but the latest schedule time for delivery capacity 1 (the time when the order was last allocated to the delivery capacity) is 2022, 1, 11, and the latest schedule time for delivery capacity 1 (the time when the order was last allocated to the delivery capacity) is 2022, 1, 11, 40, and the idle time for delivery capacity 1 is longer, and therefore, the priority of delivery capacity 1 is higher than that of delivery capacity 2, thereby preferentially allocating orders for delivery capacity 1.

Optionally, the scheduling module determines a priority of the plurality of candidate delivery capacities based on the determined number of outstanding orders for the plurality of candidate delivery capacities, comprising: in the event that the number of outstanding orders for the at least two candidate delivery capacities is the same and is not 0, determining a priority of the at least two candidate delivery capacities based on a time period for each of the at least two candidate delivery capacities to reach the order intersection, the priority being inversely related to the time period.

When the number of outstanding orders of at least two candidate delivery capacities is the same, if one candidate delivery capacity can reach the order intersection in advance, the candidate delivery capacity can deliver the orders in the order group in advance, and delivery of the order group is completed earlier, so that the shorter the time period that the candidate delivery capacity reaches the order intersection, the higher the priority.

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 the plurality of candidate delivery capacities.

When the scheduling module selects the target delivery capacity for each order group according to the priority of each order group and the priority of a plurality of candidate delivery capacities, the higher the priority of the order group is, the higher the target delivery capacity is selected for the order group; the higher the priority of a candidate delivery capacity, the higher the candidate delivery capacity is selected as the target delivery capacity. Optionally, 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 plurality of delivery capacities, including: and sequentially arranging a plurality of order groups according to the order of the priority from high to low, and determining the delivery capacity with the highest priority as the target delivery capacity of the order group from candidate delivery capacities with the number of incomplete orders smaller than the target number.

That is, after the ordered order group and the delivery capacity are obtained, the order group is assigned to the delivery capacity with the highest priority as sequentially as possible when the delivery capacity load constraint is satisfied. For example, consider first assigning the highest priority order group to the highest priority shipping capacity and consider then assigning the next highest priority order group to the highest priority shipping capacity. If the highest priority delivery capacity has reached the upper single load limit, the next highest priority delivery capacity is considered, and so on.

It should be noted that, in the embodiment of the present application, only "determining the priority of the plurality of order groups and the priority of the plurality of candidate delivery capacities", selecting the target delivery capacity for each order group according to the priority of each order group and the priority of the plurality of candidate delivery capacities "is taken as an example, and" how to allocate the target delivery capacity for the order "is described as an example, and in another embodiment, after aggregating the orders being delivered by the automated driving vehicle, the order allocation may be directly performed. In one possible implementation manner, the scheduling module aggregates a plurality of orders according to the area to which the destination belongs to obtain at least one order group, wherein the destinations of the orders in the order group belong to the same area; a target delivery capacity is allocated for each order group from a plurality of candidate delivery capacities, the target delivery capacity allocated for any one order group being used to deliver each order in the order group.

The scheduling module may use any scheduling method (such as greedy algorithm, etc.), and the scheduling method is not limited in the embodiment of the present application, where the target delivery capacity is allocated to each order group from the plurality of candidate delivery capacities, and the target delivery capacity allocated to any order group is used for delivering each order in the order group.

In some embodiments, the scheduling module may further sort the plurality of order groups, and sequentially select the target shipping capacity for the plurality of order groups in the order of the plurality of order groups. For example, the scheduling module determines, for each order group, an earliest promised arrival time of promised arrival times of each order in the order group; the scheduling module determines a priority of each order group based on an earliest promised delivery time in the order group, and sequentially selects a target delivery capacity for each order group from the plurality of candidate delivery capacities according to the priority of each order group based on the delivery states of the plurality of candidate delivery capacities.

In some embodiments, the candidate delivery capacity is screened prior to selecting the target delivery capacity for each order group from the candidate delivery capacities. Optionally, the scheduling module is configured to determine, based on order information of the plurality of candidate delivery capacities of incomplete orders and the current location, a plurality of candidate delivery capacities of which the current location belongs to a target area and/or of which destinations of each incomplete order belong to a target area, and select, according to a priority of each order group, a target delivery capacity for each order group from the determined plurality of candidate delivery capacities, where the target area is an area to which an order intersection of the plurality of orders belongs.

It should be noted that, in the embodiment of the present application, only "determining the priority of a plurality of order groups and the priority of a plurality of candidate delivery capacities", selecting the target delivery capacity for each order group according to the priority of each order group and the priority of a plurality of candidate delivery capacities "and" determining the priority of a plurality of order groups ", selecting the target delivery capacity for each order group according to the priority of each order group" are taken as examples, and "how to allocate the target delivery capacity for an order" is described as an example. In yet another embodiment, a priority of a plurality of candidate delivery capacities is determined, and a target delivery capacity is selected for the order according to the priority of the plurality of candidate delivery capacities.

Optionally, the scheduling module determines a number of the plurality of candidate delivery capacity incomplete orders based on order information of the plurality of candidate delivery capacity incomplete orders; the scheduling module determining a priority of the plurality of candidate delivery capacity based on a number of outstanding orders for the plurality of candidate delivery capacity, the priority being inversely related to the number of outstanding orders; the scheduling module selects a candidate delivery capacity meeting the priority condition as a target delivery capacity for the order.

For example, the scheduling module selecting a candidate delivery capacity that satisfies the priority condition as the target delivery capacity for the order includes: the scheduling module takes the candidate delivery capacity with the highest priority as the target delivery capacity of the order.

In addition, when the number of outstanding orders of the plurality of delivery capacities is 0, the embodiment of the application determines the priority of the plurality of delivery capacities based on the latest scheduling time of the plurality of delivery capacities, so that the delivery capacity with the longest idle time is preferentially allocated to the orders, and the dispatch fairness of the scheduling module is improved.

In addition, the embodiment of the application also describes an order scheduling method by using fig. 4 as an example. In some embodiments, the delivery condition information of the system is input to the scheduling module every preset time period, where the delivery condition information includes: (1) A status of the autonomous vehicle, such as a current location of the autonomous vehicle; (2) Status of the rider, such as order information of the rider not completed order, current position, latest scheduling time, etc.; (3) Order status, such as the area to which the order destination belongs, the time of delivery promised, etc.

The scheduling module makes a decision based on the input delivery situation information: for orders being distributed by the automatic driving vehicle, packaging the orders suitable for being distributed by a rider through order aggregation, and sequencing the order packages according to the promised delivery time of the orders; for candidate riders, the candidate riders are first screened to exclude riders that cannot be scheduled. On this basis, candidate riders are ranked by integrating the candidate rider incomplete order, the current position, and the latest scheduling time (i.e., last scheduling time). Finally, order scheduling is performed to gradually distribute the order package to the rider.

The following details the individual steps in the decision:

(1) Order aggregation

Orders from the same cell should be distributed to the same rider as much as possible to avoid that different riders need to go to a standing point (the same order delivery point as above) for order delivery after the automated driving vehicle reaches the standing point. However, the upper limit of the single-volume load of the rider is also needed to be considered in the process, so that the application firstly aggregates orders according to the area to which the orders belong, and if the single-volume of the same area is larger than the load of the rider, the order package is split according to the upper limit of the single-volume load.

(2) Order ordering

For the aggregated order package, ordering is required according to the urgency of the order. The application compares the minimum value of the promised delivering time in each order package (namely the promised delivering time of the most urgent order), and sorts the order packages according to the minimum value.

(3) Rider screening

For the rider, the rider who cannot distribute the orders needs to be screened out according to the screening rule first. The screening rules include: (1) Riders not disposed at standing points corresponding to the orders are screened out. Wherein, the rider configured at the standing point corresponding to the order means: the rider has a correspondence with the area to which the stay point belongs, and the rider is used for distributing the rider of the order in the area. (2) And the current position of the rider configured at the standing point corresponding to the orders is not in the area of the standing point, or the destination of the unfinished order does not belong to the area of the standing point.

(4) Rider sequencing

To be able to distribute the most urgent orders to the most likely to return to the standing spot as early as possible, the riders may be ordered. First, a rider with a decision time order of 0 (i.e., a rider not completing an order) is prioritized. The rider can reach the standing point before the automatic driving vehicle reaches the standing point, so that the order distribution efficiency is improved. If a plurality of 0-order riders exist, the rider with earlier scheduling time is prioritized, so that the problem that the order is not shared by a certain rider due to long-time non-allocation of the order can be avoided. When the rider's single volume is greater than 0, the riders may be ordered according to the rider's single volume. When there are a plurality of riders with the same amount, the time length for the rider to reach the standing point can be estimated according to the position of the rider and the incomplete order of the rider, and the order is sorted according to the time length.

(5) Order scheduling

After the ordered order packages and the riders are obtained, the order packages are sequentially assigned to the delivery capacity with high priority as much as possible under the condition that the load constraint of the riders is met. For example, consider first assigning the highest priority order package to the top ranked rider and then the highest priority order package to the top ranked rider. If the rider has reached the upper single load limit, the rider is considered to be assigned to the next-to-front rider, and so on.

The embodiment of the application also provides a hybrid dispatching system of the automatic driving vehicle, which comprises a dispatching module and the automatic driving vehicle;

The dispatching module is used for determining an order which is being distributed by the automatic driving vehicle, wherein the order corresponds to an order delivery point and a destination;

The scheduling module is further configured to reassign a target delivery capacity from a plurality of candidate delivery capacities based on delivery condition information of the system, the target delivery capacity being configured to deliver the order from the order delivery point to the destination, the delivery condition information being configured to indicate delivery conditions of the order and the delivery capacity in the system.

In one possible implementation, the delivery status information includes at least one of:

the current position of the autonomous vehicle;

the area to which the destination of the order belongs;

The promised time of delivery of the order;

order information for the plurality of candidate delivery capacity outstanding orders;

The current location of the plurality of candidate shipping capacities;

A latest schedule time for the plurality of candidate delivery capacities, the latest schedule time representing a time when an order was last allocated to the candidate delivery capacity;

an upper single load limit for the plurality of candidate shipping capacities;

the length of time the plurality of candidate shipping capacities reach the order point of intersection of the order.

In one possible implementation, the order is plural, and the distribution condition information includes an area to which a destination of the order belongs;

The scheduling module is used for aggregating a plurality of orders according to the area of the destination to obtain at least one order group, wherein the destinations of the orders in the order group belong to the same area;

The scheduling module is configured to allocate a target delivery capacity for each order group from the plurality of candidate delivery capacities, the target delivery capacity allocated for any order group being used to deliver each order in the order group.

In one possible implementation manner, the scheduling module is configured to split the order group into at least two order groups if the number of orders in any order group is greater than the target number, and the number of orders in each split order group is not greater than the target number.

The scheduling module is used for determining the earliest promised delivery time in the promised delivery time of each order in the order group for each order group;

The scheduling module is used for determining the priority of each order group based on the earliest promised delivery time in each order group;

The scheduling module is used for selecting a target delivery capacity from the plurality of candidate delivery capacities according to the priority of each order group in turn based on the delivery states of the plurality of candidate delivery capacities.

The scheduling module is used for determining the priority of the candidate delivery capacity based on the number of outstanding orders of the candidate delivery capacity, and the priority is inversely related to the number of outstanding orders;

the scheduling module is used for selecting a target delivery capacity for each order group according to the priority of each order group and the priorities of the candidate delivery capacities.

In one possible implementation, the delivery situation information includes order information for the plurality of candidate delivery capacity outstanding orders and a current location of the plurality of candidate delivery capacities;

The scheduling module is configured to determine, based on order information and a current location of the plurality of candidate delivery capacities of outstanding orders, a plurality of candidate delivery capacities of which the current location belongs to a target area and/or of which destinations each outstanding order belongs to the target area, and reallocate the target delivery capacity for the order from the determined plurality of candidate delivery capacities, where the target area is an area to which the order delivery point belongs.

The scheduling module is used for determining the quantity of the plurality of candidate delivery capacity incomplete orders based on the order information of the plurality of candidate delivery capacity incomplete orders;

The scheduling module is used for selecting candidate delivery capacity meeting the priority condition as the target delivery capacity of the order.

In one possible implementation, the delivery situation information includes a latest schedule time of the plurality of candidate delivery capacities and a time period for the plurality of candidate delivery capacities to reach an order intersection of the order;

The scheduling module is used for determining the priority of at least two candidate delivery capacities based on the latest scheduling time of each candidate delivery capacity in the at least two candidate delivery capacities when the number of outstanding orders of the at least two candidate delivery capacities is 0, wherein the priority is in negative correlation with the latest scheduling time, and the scheduling time represents the time for distributing orders to the candidate delivery capacities;

the scheduling module is configured to determine, based on a time period for each of the at least two candidate delivery capacities to reach the order delivery point, a priority of the at least two candidate delivery capacities, where the priority is inversely related to the time period, in a case where the number of outstanding orders for the at least two candidate delivery capacities is the same and is not 0.

Fig. 5 is a block diagram of an autonomous vehicle 500 according to an embodiment of the present application. The autonomous vehicle 500 includes: a processor 501 and a memory 502.

Processor 501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 501 may be implemented in at least one hardware form of DSP (DIGITAL SIGNAL Processing), FPGA (Field-Programmable gate array), PLA (Programmable Logic Array ). The processor 501 may also include a main processor and a coprocessor, where the main processor is a processor for processing data in an awake state, and is also called a CPU (Central Processing Unit ); a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 501 may integrate a GPU (Graphics Processing Unit, image processor) for rendering and drawing of content required to be displayed by the display screen. In some embodiments, the processor 501 may also include an AI (ARTIFICIAL INTELLIGENCE ) processor for processing computing operations related to machine learning.

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

In some embodiments, autonomous vehicle 500 may optionally further include: a peripheral interface 503 and at least one peripheral. The processor 501, memory 502, and peripheral interface 503 may be connected by buses or signal lines. The individual peripheral devices may be connected to the peripheral device interface 503 by buses, signal lines or circuit boards. Specifically, the peripheral device includes: at least one of radio frequency circuitry 504, a display 505, a camera 506, audio circuitry 507, a positioning component 508, and a power supply 509.

Peripheral interface 503 may be used to connect at least one Input/Output (I/O) related peripheral to processor 501 and memory 502. In some embodiments, processor 501, memory 502, and peripheral interface 503 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 501, memory 502, and peripheral interface 503 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.

The Radio Frequency circuit 504 is configured to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuitry 504 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 504 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 504 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuit 504 may communicate with other autonomous vehicles via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (WIRELESS FIDELITY ) networks. In some embodiments, the radio frequency circuit 504 may further include NFC (NEAR FIELD Communication) related circuits, which is not limited by the present application.

The display 505 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display 505 is a touch display, the display 505 also has the ability to collect touch signals at or above the surface of the display 505. The touch signal may be input as a control signal to the processor 501 for processing. At this time, the display 505 may also be used to provide virtual buttons and/or virtual keyboards, also referred to as soft buttons and/or soft keyboards. In some embodiments, the display 505 may be one, providing a front panel of the autonomous vehicle 500; in other embodiments, the display 505 may be at least two, respectively disposed on different surfaces of the autonomous vehicle 500 or in a folded design; in still other embodiments, the display 505 may be a flexible display disposed on a curved surface or a folded surface of the autonomous vehicle 500. Even more, the display 505 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The display 505 may be made of LCD (Liquid CRYSTAL DISPLAY), OLED (Organic Light-Emitting Diode), or other materials.

The camera assembly 506 is used to capture images or video. Optionally, the camera assembly 506 includes a front camera and a rear camera. The front camera is arranged on the front panel of the automatic driving vehicle, and the rear camera is arranged on the back of the automatic driving vehicle. In some embodiments, the at least two rear cameras are any one of a main camera, a depth camera, a wide-angle camera and a tele camera, so as to realize that the main camera and the depth camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize a panoramic shooting and Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments, camera assembly 506 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The dual-color temperature flash lamp refers to a combination of a warm light flash lamp and a cold light flash lamp, and can be used for light compensation under different color temperatures.

The audio circuitry 507 may include a microphone and a speaker. The microphone is used for collecting sound waves of users and environments, converting the sound waves into electric signals, and inputting the electric signals to the processor 501 for processing, or inputting the electric signals to the radio frequency circuit 504 for voice communication. For purposes of stereo acquisition or noise reduction, a plurality of microphones may be provided at different portions of the autonomous vehicle 500, respectively. The microphone may also be an array microphone or an omni-directional pickup microphone. The speaker is used to convert electrical signals from the processor 501 or the radio frequency circuit 504 into sound waves. The speaker may be a conventional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only the electric signal can be converted into a sound wave audible to humans, but also the electric signal can be converted into a sound wave inaudible to humans for ranging and other purposes. In some embodiments, audio circuitry 507 may also include a headphone jack.

The locating component 508 is used to locate the current geographic location of the autonomous vehicle 500 for navigation or LBS (Location Based Service, location-based services). The positioning component 508 may be a positioning component based on the United states GPS (Global Positioning System ), the Beidou system of China, the Granati system of Russia, or the Galileo system of the European Union.

The power supply 509 is used to power the various components in the autonomous vehicle 500. The power supply 509 may be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 509 comprises a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, autonomous vehicle 500 also includes one or more sensors 510. The one or more sensors 510 include, but are not limited to: an acceleration sensor 511, a gyro sensor 512, a pressure sensor 513, a fingerprint sensor 514, an optical sensor 515, and a proximity sensor 516.

The acceleration sensor 511 may detect the magnitudes of accelerations on three coordinate axes of the coordinate system established in the autonomous vehicle 500. For example, the acceleration sensor 511 may be used to detect components of gravitational acceleration on three coordinate axes. The processor 501 may control the display 505 to display a user interface in a landscape view or a portrait view according to a gravitational acceleration signal acquired by the acceleration sensor 511. The acceleration sensor 511 may also be used for acquisition of motion data of a game or a user.

The gyro sensor 512 may detect the body direction and the rotation angle of the autonomous vehicle 500, and the gyro sensor 512 may collect the 3D motion of the user on the autonomous vehicle 500 in cooperation with the acceleration sensor 511. The processor 501 may implement the following functions based on the data collected by the gyro sensor 512: motion sensing (e.g., changing UI according to a tilting operation by a user), image stabilization at shooting, game control, and inertial navigation.

The pressure sensor 513 may be disposed on a side frame of the autonomous vehicle 500 and/or on an underside of the display 505. When the pressure sensor 513 is provided at a side frame of the autonomous vehicle 500, a grip signal of the user on the autonomous vehicle 500 may be detected, and the processor 501 performs a left-right hand recognition or a quick operation according to the grip signal collected by the pressure sensor 513. When the pressure sensor 513 is disposed at the lower layer of the display screen 505, the processor 501 controls the operability control on the UI interface according to the pressure operation of the user 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.

The fingerprint sensor 514 is used for collecting the fingerprint of the user, and the processor 501 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 514 or the fingerprint sensor 514 identifies the identity of the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the user is authorized by the processor 501 to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying for and changing settings, etc. The fingerprint sensor 514 may be provided on the front, back, or side of the autonomous vehicle 500. When a physical key or vendor Logo is provided on the autonomous vehicle 500, the fingerprint sensor 514 may be integrated with the physical key or vendor Logo.

The optical sensor 515 is used to collect the ambient light intensity. In one embodiment, the processor 501 may control the display brightness of the display screen 505 based on the intensity of ambient light collected by the optical sensor 515. Specifically, when the intensity of the ambient light is high, the display brightness of the display screen 505 is turned up; when the ambient light intensity is low, the display brightness of the display screen 505 is turned down. In another embodiment, the processor 501 may also dynamically adjust the shooting parameters of the camera assembly 506 based on the ambient light intensity collected by the optical sensor 515.

A proximity sensor 516, also referred to as a distance sensor, is provided at 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 a gradual decrease in the distance between the user and the front of the autonomous vehicle 500, the processor 501 controls the display screen 505 to switch from the bright screen state to the off screen state; when the proximity sensor 516 detects that the distance between the user and the front face of the autonomous vehicle 500 gradually increases, the display screen 505 is controlled by the processor 501 to switch from the off-screen state to the on-screen state.

Those skilled in the art will appreciate that the configuration shown in fig. 5 is not limiting of the autonomous vehicle 500 and may include more or fewer components than shown, or may combine certain components, or may employ a different arrangement of components.

Fig. 6 is a schematic structural diagram of a server according to an embodiment of the present application, where the server 600 may have a relatively large difference due to different configurations or performances, and may include one or more processors (Central Processing Units, CPUs) 601 and one or more memories 602, where at least one program code is stored in the memories 602, and the at least one program code is loaded and executed by the processors 601 to implement the methods provided in the foregoing method embodiments. Of course, the server may also have a wired or wireless network interface, a keyboard, an input/output interface, and other components for implementing the functions of the device, which are not described herein.

The server 600 is configured to perform the steps performed by the server in the method embodiment described above.

In an exemplary embodiment, a computer readable storage medium, e.g. a memory comprising program code, executable by a processor in a computer device to perform the order scheduling method of the above-described embodiments, is also provided. For example, the computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

In an exemplary embodiment, a computer program or a computer program product is also provided, which comprises computer program code which, when executed by a computer, causes the computer to implement the order scheduling method in the above-described embodiments.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the above storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

The foregoing description of the preferred embodiments of the present application is not intended to limit the application, but rather, the application is to be construed as limited to the appended claims.

Claims

1. An autonomous vehicle hybrid dispatch system, the system comprising a dispatch module and an autonomous vehicle;

2. The system of claim 1, wherein the delivery status information comprises at least one of:

the current location of the autonomous vehicle;

A region to which a destination of the order belongs;

The promised time of delivery of the order;

Current locations of the plurality of candidate shipping capacities;

3. The system of claim 1 or 2, wherein the order is plural, and the delivery case information includes an area to which a destination of the order belongs;

The scheduling module is used for distributing target delivery capacity to each order group from the plurality of candidate delivery capacities, and the target delivery capacity distributed to any order group is used for delivering each order in the order group.

4. The system of claim 3, wherein the scheduling module is configured to split the order group into at least two order groups if the number of orders in any one order group is greater than the target number, and the number of orders in each split order group is not greater than the target number.

5. The system of claim 3, wherein the delivery situation information includes a promised delivery time of the plurality of orders and a delivery status of the plurality of candidate delivery capacities;

The scheduling module is used for selecting target delivery capacity from the plurality of candidate delivery capacities according to the priority of each order group in turn based on the delivery states of the plurality of candidate delivery capacities.

6. The system of claim 5, wherein the delivery status of the candidate delivery capacity includes a number of outstanding orders for the candidate delivery capacity;

And the scheduling module is used for selecting a target delivery capacity for each order group according to the priority of each order group and the priorities of the plurality of candidate delivery capacities.

7. The system of claim 1, wherein the delivery case information includes order information for the plurality of candidate delivery capacity outstanding orders and a current location of the plurality of candidate delivery capacities;

The scheduling module is configured to determine, based on order information and a current location of the plurality of candidate delivery capacities of outstanding orders, a plurality of candidate delivery capacities of which the current location belongs to a target area and/or destinations of each outstanding order belong to the target area, and reallocate the target delivery capacity for the order from the determined plurality of candidate delivery capacities, where the target area is an area to which the order intersection belongs.

8. The system of claim 1, wherein the delivery case information includes order information for the plurality of candidate delivery capacity outstanding orders;

And the scheduling module is used for selecting the candidate delivery capacity meeting the priority condition as the target delivery capacity of the order.

9. The system of claim 8, wherein the delivery situation information includes a latest schedule time of the plurality of candidate delivery capacities and a length of time the plurality of candidate delivery capacities reach an order intersection of the order;

The scheduling module is used for determining the priority of at least two candidate delivery capacities based on the latest scheduling time of each candidate delivery capacity in the at least two candidate delivery capacities under the condition that the number of outstanding orders of the at least two candidate delivery capacities is 0, wherein the priority is inversely related to the latest scheduling time, and the scheduling time represents the time for distributing orders to the candidate delivery capacities;

The scheduling module is configured to determine, when the number of outstanding orders of at least two candidate delivery capacities is the same and is not 0, a priority of the at least two candidate delivery capacities based on a time period for each candidate delivery capacity of the at least two candidate delivery capacities to reach the order intersection, where the priority is inversely related to the time period.

10. An autonomous vehicle, characterized in that,

The automatic driving vehicle is used for starting from a first place when the collected orders meet the starting condition, distributing the orders to the order delivery points of the orders, distributing the orders from the order delivery points to the destinations of the orders by other distribution capacity, wherein the orders correspond to one order delivery point and one destination, and the first place is a picking place of the orders.