CN114254825A - Distribution path determining method and device, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure provides a method and a device for determining a distribution route, electronic equipment, a readable storage medium and a computer program product, and relates to the field of smart cities and intelligent transportation. The specific implementation scheme is as follows: determining historical vehicle operation information among distribution blocks, wherein the distribution blocks are obtained by partitioning distribution areas; determining estimated vehicle operation information among the distribution blocks in a target time period according to estimated road traffic conditions and the historical vehicle operation information, wherein the estimated road traffic conditions are road traffic abnormal conditions existing in the distribution areas in the target time period, and the vehicle operation information comprises traffic flow of third-party vehicles among the distribution blocks and driving time among the distribution blocks; and determining logistics distribution paths among the distribution blocks according to the estimated vehicle operation information. The scheme can enable the planned logistics distribution path to better meet the real situation of the distribution area in the target time period.
Description
Technical Field
The utility model relates to an artificial intelligence field, concretely relates to wisdom city and intelligent transportation technique, scene such as specifically can be used to wisdom city, intelligent transportation.
Background
The public transport system is as the important component part in wisdom city, and the rational public transport that utilizes carries out logistics distribution, not only can improve the effective utilization of public transport resource, but also can reduce logistics distribution's distribution cost, alleviates urban traffic pressure. In the process of logistics distribution by using public transport means, the logistics distribution path is reasonably planned, and the method becomes an important link for improving the logistics distribution success rate and the distribution efficiency.
Disclosure of Invention
The present disclosure provides a method, an apparatus, an electronic device, a readable storage medium, and a computer program product for determining a distribution path, so that a planned logistics distribution path can better conform to the reality of a distribution area within a target time period.
According to an aspect of the present disclosure, there is provided a method of determining a delivery path, which may include the steps of:
determining historical vehicle operation information among distribution blocks, wherein the distribution blocks are obtained by partitioning distribution areas;
determining estimated vehicle operation information among distribution blocks in a target time period according to the estimated road traffic condition and historical vehicle operation information, wherein the estimated road traffic condition is a road traffic abnormal condition existing in a distribution area in the target time period, and the vehicle operation information comprises the traffic flow of third-party vehicles among the distribution blocks and the driving time among the distribution blocks;
and determining logistics distribution paths among the distribution blocks according to the estimated vehicle operation information.
According to a second aspect of the present disclosure, there is provided a distribution path determination apparatus, which may include:
the historical vehicle operation information determining unit is used for determining historical vehicle operation information among distribution blocks, and the distribution blocks are obtained by partitioning distribution areas;
the estimated vehicle operation information determining unit is used for determining estimated vehicle operation information among the distribution blocks in the target time period according to the estimated road traffic condition and the historical vehicle operation information, the estimated road traffic condition is the road traffic abnormal condition existing in the distribution area in the target time period, and the vehicle operation information comprises the traffic flow of third-party vehicles among the distribution blocks and the driving time among the distribution blocks;
and the distribution path determining unit is used for determining the logistics distribution paths among the distribution blocks according to the estimated vehicle running information.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method according to any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform a method in any of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the method in any of the embodiments of the present disclosure.
The technology disclosed by the invention can determine the estimated vehicle operation information among the distribution blocks in the target time period according to the road traffic abnormal conditions existing in the distribution area in the target time period and the historical vehicle operation information, and then determine the logistics distribution path among the distribution blocks based on the estimated vehicle operation information. When the logistics distribution path is planned, the road traffic abnormal condition existing in the distribution area in the target time period is fully considered, so that the planned logistics distribution path can better accord with the real condition of the distribution area in the target time period. Therefore, the logistics distribution success rate and the distribution efficiency are improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a flowchart of a method for determining a delivery route according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of a method of determining historical vehicle operation information provided in an embodiment of the present disclosure;
FIG. 3 is a flow chart of a method for adjusting historical vehicle operation information provided in an embodiment of the present disclosure;
FIG. 4 is a flow chart of another method of adjusting historical vehicle operation information provided in an embodiment of the present disclosure;
fig. 5 is a flowchart of a method for determining a logistics distribution path provided in an embodiment of the present disclosure;
fig. 6 is a flowchart of another method for determining a logistics distribution path provided in an embodiment of the present disclosure;
FIG. 7 is a schematic diagram of a weighted directed graph provided in an embodiment of the present disclosure;
FIG. 8 is a schematic diagram of a distribution path determining apparatus according to an embodiment of the present disclosure;
fig. 9 is a schematic view of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The present disclosure provides a method for determining a distribution route, and specifically, referring to fig. 1, a flowchart of a method for determining a distribution route is provided for an embodiment of the present disclosure. The method may comprise the steps of:
step S101: historical vehicle operation information among distribution blocks is determined, and the distribution blocks are obtained by partitioning distribution areas.
Step S102: according to the estimated road traffic condition and the historical vehicle operation information, the estimated vehicle operation information between the distribution blocks in the target time period is determined, the estimated road traffic condition is the road traffic abnormal condition existing in the distribution area in the target time period, and the vehicle operation information comprises the traffic flow of third-party vehicles between the distribution blocks and the driving time between the distribution blocks.
Step S103: and determining logistics distribution paths among the distribution blocks according to the estimated vehicle operation information.
According to the embodiment of the disclosure, the estimated vehicle operation information among the distribution blocks in the target time period can be determined according to the road traffic abnormal condition existing in the distribution area in the target time period and the historical vehicle operation information. And then determining logistics distribution paths among distribution blocks based on the estimated vehicle operation information.
When the logistics distribution path planning is carried out, the road traffic abnormal conditions existing in the distribution area in the target time period are fully considered. The planned logistics distribution path can better meet the real situation of a distribution area in a target time period. Therefore, the logistics distribution success rate and the distribution efficiency are improved.
In the embodiment of the present disclosure, the distribution area refers to an area into which the logistics distribution unit is divided in advance according to the logistics distribution demand, for example: the distribution areas are divided according to the administrative areas of the people's republic of China. In this case, one distribution area may be a province, a city under the direct jurisdiction, an autonomous region, or the like, or may be a city under the jurisdiction of a certain province, or a jurisdiction of a certain city, or the like.
The delivery block is a plurality of areas obtained by further dividing the delivery area, and the plurality of areas obtained by dividing the delivery area are referred to as delivery blocks for distinguishing them from the delivery area.
The historical vehicle operation information is vehicle operation information of a third-party vehicle in a certain historical time period. The estimated vehicle operation information is vehicle operation information of a third-party vehicle in a target time period.
The vehicle operation information is information for describing vehicle operation conditions of the third-party vehicle among different distribution blocks, and the vehicle operation conditions at least comprise traffic flow of the third-party vehicle among the distribution blocks, driving time of the third-party vehicle among the distribution blocks and direct conditions of the third-party vehicle among the distribution blocks.
The third-party vehicle is a vehicle which can be used for logistics distribution besides the logistics distribution special vehicle, and includes but is not limited to buses, taxis and taxi appointments.
In an embodiment of the present disclosure, the traffic flow of the third-party vehicle between the distribution blocks is: traffic volume of third party vehicles operating between different distribution blocks. May be represented by the arrival interval of third party vehicles between different distribution blocks.
For the bus, because the running mode of the bus is relatively fixed, the arrival intervals of the bus among different blocks can be directly calculated through the historical driving track of the bus.
For taxis or net appointments, although the operation mode of the taxis or the net appointments is relatively random, the arrival intervals of the taxis or the net appointments among different distribution blocks are subject to exponential distribution X to lambda, and the exponential distribution parameter lambda can be obtained by fitting according to the historical driving track of the taxi.
The driving time between the distribution blocks is as follows: the average length of time required to pass from one delivery block to another by a third party vehicle. Specifically, the vehicle driving track can be directly calculated through the historical vehicle driving track.
The direct situation of the third-party vehicle among the distribution blocks refers to that: whether a third party vehicle can reach directly between different distribution blocks. I.e., whether there are direct third party vehicles between different distribution blocks.
In the actual logistics distribution process, logistics distribution sites are often set for distribution blocks. The physical distribution between the distribution blocks is reflected in the actual logistics distribution process, which is often the logistics distribution between the distribution sites. The logistics distribution station of each distribution block is often disposed in a central area of the block, and specifically may refer to an area where the traffic flow in the distribution block meets a preset condition, for example: the region with the highest traffic flow.
Therefore, in order to make the final logistics distribution path more fit to the actual logistics distribution situation, the following steps are taken in the embodiment of the present disclosure to determine the historical vehicle operation information. Referring to fig. 2, a flowchart of a method for determining historical vehicle operation information according to an embodiment of the disclosure is shown. The method comprises the following steps:
step S201: and dividing the distribution area into a plurality of distribution blocks.
Step S202: and determining a central area of the distribution block, wherein the central area is an area in which the traffic flow in the distribution block meets a preset condition.
Step S203: and determining historical vehicle running information according to the historical vehicle running track passing through the central area, wherein the historical vehicle running track is the vehicle running track of the third-party vehicle.
The specific implementation manner of dividing the distribution area into blocks to obtain a plurality of distribution blocks may be as follows: firstly, a target parking point in a historical vehicle driving track is obtained, and the target parking point is a parking point for a third-party vehicle to get on and off a passenger. And then clustering the target parking points to obtain a plurality of clustering areas. And finally, determining the clustering area as a distribution block.
And clustering the parking points of the third-party vehicles for passengers to get on and off as clustering points to obtain corresponding clustering areas, and determining the clustering areas as distribution blocks. The parking points for passengers to get on and off the bus are used as clustering points to perform clustering, the fact that the main task of the third-party vehicle is to provide passenger carrying service is fully considered, and the third-party vehicle is used for logistics distribution only for the purpose of more fully and reasonably utilizing the third-party vehicle under the condition that the third-party vehicle provides the passenger carrying service. And then can make the distribution block that divides out more reasonable, and can satisfy the operation demand of local vehicle.
Many stopping points may be included in the so-called historical vehicle travel track. Therefore, in order to select the parking spots for passengers to get on and off, it is necessary to select the parking spots corresponding to parking due to red street lamps, road congestion, and the like among all the parking spots of the third-party vehicle.
In embodiments of The present disclosure, a density-based Clustering algorithm (OPTICS) may be employed, which is capable of reducing The sensitivity of input parameters. However, when clustering is performed using the OPTICS algorithm, the entire data set still needs to be returned for each clustering point, which is time-consuming.
Therefore, in order to reduce the time consumed to obtain the clustered regions. The distribution area may be first gridded and then the entire data set may be mapped into the grid. When each cluster point is searched later, only the contained points in the grid can be traversed, and the whole data set does not need to be traversed. Therefore, the time consumption of the OPTICS algorithm can be reduced, and the query efficiency of the clustering points can be improved.
The method for dividing the region in the embodiment of the present disclosure is not specifically limited, and the region may be divided by using an OPTICS algorithm and other methods, for example: the division is directly carried out according to administrative regions. Specifically, when a certain city is taken as a delivery area, a plurality of jurisdictions of the city may be taken as delivery blocks.
In addition, a K-means clustering algorithm (K-means clustering algorithm, K-means) can be adopted to cluster all blocks of the city into K blocks; the K-means clustering algorithm adopts the vehicle running distance between two streets when calculating the distance.
According to the embodiment of the disclosure, the historical vehicle operation information can reflect the vehicle operation condition between the distribution blocks in the past time period, and the vehicle operation condition between the distribution blocks can be well represented. However, since the distribution area often has an abnormal condition of sudden or abnormal road traffic, the historical vehicle operation information often cannot truly and effectively reflect the vehicle operation condition between the distribution blocks in the target time period.
If the logistics distribution paths among the distribution blocks are determined according to the historical vehicle operation information, the determined logistics distribution paths can be applicable to the condition that the road traffic of the distribution areas is normal. However, once a sudden or abnormal road traffic abnormality occurs in the distribution area within the target time period, the logistics distribution path is often no longer a requirement for logistics distribution.
Therefore, in order to enable the vehicle operation information to more accurately reflect the vehicle operation conditions between the distribution blocks in the target time period, the determined logistics distribution path can better accord with the real conditions of the distribution areas in the target time period, and therefore the logistics distribution success rate and the distribution efficiency are improved. In the embodiment of the present disclosure, the historical vehicle operation information needs to be adjusted based on the estimated road traffic condition to obtain new vehicle operation information. The specific implementation mode is as follows: and obtaining historical vehicle operation information, and adjusting the historical vehicle operation information according to the estimated road traffic condition to obtain the estimated vehicle operation information.
In an embodiment of the present disclosure, the abnormal road traffic condition in the distribution area may include: the distribution blocks have a condition that the road cannot pass through. In this case, the traffic flow of the third-party vehicle between the distribution blocks inevitably decreases due to the influence of the road not being able to pass. At this time, the traffic flow of the affected third-party vehicle needs to be excluded from the traffic flow in the historical vehicle operation information, so that the traffic flow of the third-party vehicle can be ensured to better meet the real traffic flow of the third-party vehicle in the target time period.
In the embodiment of the disclosure, in the case that the predicted road traffic condition includes that the impassable road exists between the distribution blocks, please refer to fig. 3, which is a flowchart of a method for adjusting historical vehicle operation information provided in the embodiment of the disclosure.
Step S301: and determining the traffic flow of the third-party vehicle on the road which cannot pass through according to the historical vehicle operation information.
Step S302: and adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of the third-party vehicle on the road which cannot be passed through.
For example, one delivery area may be divided into 10 delivery blocks (i.e., delivery block 1 to delivery block 10), and if there is a partially impassable road between the delivery block 1 and the delivery block 2, the traffic flow of a third-party vehicle on the partially impassable road is determined according to the traffic flow between the delivery block 1 and the delivery block 2 in the historical vehicle operation information. And adjusting the traffic flow between the distribution block 1 and the distribution block 2 in the historical vehicle operation information according to the traffic flow of the third-party vehicle on the part of the road which cannot pass through, so as to obtain the new traffic flow between the distribution block 1 and the distribution block 2, and further obtain the estimated vehicle operation information. At this time, the traffic flow between the distribution block 1 and the distribution block 2 in the estimated vehicle operation information is the traffic flow between the new distribution block 1 and the new distribution block 2.
In addition, if all the distribution blocks 1 and 2 are impassable roads, the traffic flow between the distribution block 1 and the distribution block 2 in the historical vehicle operation information is adjusted to be 0, and the distribution block 1 and the distribution block 2 are set to be impassable, so that the estimated vehicle operation information is obtained.
The reasons for the impassable road between the distribution blocks include: roads require or are being serviced, road management, etc. In this case, all the third-party vehicles cannot pass through, and therefore, a part of the vehicles cannot arrive with delay. And therefore, the corresponding delay time length of the third-party vehicle does not need to be further considered.
In an embodiment of the present disclosure, the road traffic abnormal condition existing in the distribution area may further include: there is only a partial delay in the arrival of third party vehicles between distribution blocks. Since only part of the third-party vehicles arrive with delay between different areas, the traffic flow of the third-party vehicles between distribution blocks is necessarily reduced. In this case, the traffic flow in the historical vehicle operation information needs to be adjusted according to the traffic flow of the part of the third-party vehicles that have arrived later. The specific implementation mode is as follows: and determining third-party vehicles which cannot arrive between different areas, and excluding the traffic flow of the third-party vehicles which cannot arrive between the different areas from the traffic flow in the historical vehicle operation information. Therefore, the traffic flow of the third-party vehicle among different distribution blocks in the estimated vehicle operation information can be ensured to be more consistent with the real traffic flow of the third-party vehicle in the target time period.
In addition, since only part of the third-party vehicles arrive at different distribution blocks in a delayed manner, the traveling time of the third-party vehicles among the distribution blocks is correspondingly prolonged. Therefore, the driving time between the distribution blocks in the historical vehicle operation information needs to be further adjusted, so that the estimated driving time in the vehicle operation information can be more consistent with the real driving time between the distribution blocks in the target time period.
Therefore, in the case that the predicted road traffic condition includes that the impassable road exists between the distribution blocks, please refer to fig. 4, which is a flowchart of another historical vehicle operation information adjusting method provided in the embodiment of the present disclosure.
Step S401: and determining the traffic flow of part of third-party vehicles when the estimated road traffic condition is that only part of the third-party vehicles are delayed to arrive between the distribution blocks.
Step S402: and adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of part of the third-party vehicles.
Step S403: and determining the corresponding delay time length of part of the third-party vehicles.
Step S404: and adjusting the driving time length in the historical vehicle operation information according to the delay time length.
In the embodiments of the present disclosure, the reasons why only some third-party vehicles arrive late between different distribution blocks include, but are not limited to: the road between different distribution blocks reaches a road congestion condition of "special congestion" and "general congestion". Under the condition that roads among different distribution blocks are congested, such as 'special congestion' and 'general congestion', taxis and network appointments in third-party vehicles generally select detours, and due to the fact that running routes of buses are fixed, detours cannot be selected in most cases. Thus, there is only a bus delay arrival between different delivery blocks in this case.
In the case of a road congestion where the road between the different distribution blocks is "particularly congested", the arrival of the bus is delayed even if there is a traffic jam between the different distribution blocks. In consideration of the timeliness requirement of actual logistics distribution, although the traffic flow corresponding to the bus is reserved when the traffic flow in the historical vehicle operation information is adjusted, the driving time in the historical vehicle operation information can be adjusted to be infinite.
In the actual logistics distribution process, distribution demands corresponding to different logistics objects may be different. For example: the distribution requirements of some logistics objects are quickly reached, and at the moment, the time consumption of a distribution path is shortest; the distribution demand of some logistics objects does not have such high time requirements, and in this case, the logistics distribution cost is required to be minimum.
Therefore, in the embodiment of the present disclosure, the following steps are taken to determine the logistics distribution path, and specifically, refer to fig. 5, which is a flowchart of a method for determining the logistics distribution path provided in the embodiment of the present disclosure. The determining step of the logistics distribution path comprises the following steps:
step S501: a starting block and an ending block for the logistics distribution are selected in the distribution area.
Step S502: and determining an optimal distribution path according with the distribution requirement according to the traffic flow in the estimated vehicle operation information and the driving time in the estimated vehicle operation information, wherein the optimal distribution path is a path from the initial distribution block to the final distribution block.
Step S503: the preferred distribution path is determined as the logistics distribution path.
According to the logistics distribution route determining method and device, when the logistics distribution route is determined, not only can the traffic flow in the estimated vehicle operation information and the driving time in the estimated vehicle operation information be considered, but also the distribution demand can be considered at the same time, so that the determined distribution route can meet the real situation of a distribution area in a target time period, and the distribution demand can be met.
In the embodiment of the disclosure, after the central area of the distribution block is distributed, a logistics distribution station is further arranged in the central area of the distribution block. In the embodiments of the present disclosure, the path from the starting block to the ending block actually means: a path from the logistics distribution site of the starting distribution block to the logistics distribution site of the ending distribution block.
In the early stage of logistics distribution, the sender may first distribute the logistics objects to the logistics distribution site of the initial distribution block, or after the logistics distribution personnel pick up the logistics objects, the logistics objects are distributed to the logistics distribution site of the initial distribution block and then distributed from the logistics distribution site of the initial distribution block. In the later period of logistics distribution, after the distribution object reaches the logistics distribution site of the distribution block, the logistics distribution personnel can distribute the logistics object from the logistics distribution site to the pickup person, or the pickup person can pick up the pickup by itself from the logistics distribution site.
In the embodiments of the present disclosure, the delivery requirements include, but are not limited to: the logistics distribution consumes the shortest time, the distribution path of the logistics distribution is the shortest, and the logistics distribution cost does not exceed a specified cost threshold.
In the embodiment of the disclosure, the optimal distribution path meeting the distribution demand is conveniently and quickly determined, a weighted directed graph for distribution blocks can be constructed based on the estimated vehicle operation information, and then the optimal distribution path meeting the distribution demand is determined based on the weighted directed graph. Fig. 6 is a flowchart of another method for determining a logistics distribution route according to an embodiment of the present disclosure. The determining step of the logistics distribution path comprises the following steps:
step S601: and constructing a weighted directed graph aiming at the distribution blocks by utilizing the estimated vehicle operation information, wherein nodes in the weighted directed graph are used for representing the distribution blocks, edges in the weighted directed graph are used for representing third-party vehicles which can reach the distribution blocks, and weights in the weighted directed graph are pre-configured according to distribution requirements.
Step S602: and determining the optimal distribution path which meets the distribution demand by using the weighted directed graph.
Step S603: and determining the optimal distribution path as the preferred distribution path.
The specific implementation manner of constructing the weighted directed graph for the distribution blocks by using the estimated vehicle operation information is as follows:
firstly, a vehicle transfer directed topology map for distribution blocks is constructed according to the traffic flow of third-party vehicles among different central blocks. Wherein the nodes in the vehicle transfer directed topology graph are used for representing distribution blocks; the edges in the vehicle transfer directed topology graph are used for indicating that reachable third-party vehicles exist between different distribution areas (namely reachable paths exist between different distribution areas); the arrow of the vehicle-transferred directed topology is used to indicate the direction of travel of the third party vehicle (i.e., the direction of travel of the reachable path between different delivery areas).
Then, respectively constructing a traffic flow transfer matrix, a driving time matrix and a reachable matrix according to the traffic flow of third-party vehicles among different central blocks and the driving time among distribution blocks; the elements in the traffic flow transfer matrix are used for representing the traffic flow of third-party vehicles among different distribution areas, the elements in the driving time length matrix are used for representing the driving time lengths among the different distribution areas, and the elements in the reachable matrix are used for representing whether third-party vehicles capable of directly reaching the different distribution areas exist or not.
In the embodiment of the present disclosure, after obtaining the weighted directed graph, the weighted directed graph may be stored in a adjacency matrix manner G ═ v, e, and ω. Wherein G represents a priority weighting graph, upsilon represents a node, epsilon represents an edge, and omega represents a weight. And finally, according to distribution requirements, giving weights to edges in the vehicle transfer directed topological graph according to the traffic flow transfer matrix, the driving time matrix and the reachable matrix to obtain a weighted directed graph. Taking 7 distribution areas as an example, the weighted directed graph for the 7 distribution areas can be
Please refer to fig. 7, which is a schematic diagram of a weighted directed graph according to an embodiment of the present disclosure.
In the process of giving weights to the edges in the vehicle transfer directed topology map according to the traffic flow transfer matrix, the driving time matrix and the reachable matrix aiming at the distribution demands, if the distribution demands are that the time consumed by logistics distribution is shortest, the weights can be given to the edges in the vehicle transfer directed topology map only according to the reachable matrix. In addition, in general, the weight ratio of the traffic flow transition matrix when determining the side weight is 2/3, and the weight ratio of the traffic time length matrix when determining the side weight is 1/3. However, in the embodiment of the present disclosure, the weight ratio of the three matrices in determining the weight of the edge is not specifically limited, and the weight ratio of the different matrices in determining the weight of the edge may be specifically adjusted according to different distribution requirements.
After determining the weight ratio of the different matrices when determining the weight of the edge, normalization processing may be performed on all values corresponding to the elements in the matrices. And then obtaining the corresponding normalized element value of different distribution blocks connected with each edge in the matrix and the weight ratio of different matrices to calculate the weight of the edge.
After determining the weighted directed graph, Dijkstra (shortest path) algorithm may be applied to the weighted directed graph to obtain an optimal distribution path.
For example: the shortest time-consuming logistics distribution path from distribution block 1 to distribution block 6 is: the method includes distributing blocks 1 to 2, distributing blocks 2 to 5, distributing blocks 5 to 6.
In addition to using a directed weighted graph to determine preferred logistics, embodiments of the present disclosure may also use other ways to determine preferred logistics. For example: fast search random tree (RRT) algorithm, etc. That is, in the embodiment of the present disclosure, the determination method of the preferred logistics distribution is not particularly limited.
It should be noted that, in order to be able to characterize the vehicle operation conditions between the distribution blocks more accurately, the historical vehicle operation information may also be determined according to the time period. That is, historical vehicle operation information corresponding to different time periods is determined. Specifically, the day may be divided into 6 different candidate time periods according to 4 hours, and the historical vehicle operation information corresponding to each candidate time period may be determined respectively.
When determining the logistics distribution path, a candidate time period corresponding to the target time period needs to be determined, and the estimated vehicle operation information is determined according to the historical vehicle operation information of the candidate time period, so that the logistics distribution path is determined.
Specifically, if the target time period belongs to one of the candidate time periods, the estimated vehicle operation information is determined according to the historical vehicle operation information of the candidate time period, and then the logistics distribution path is determined. And if the target time period spans a plurality of candidate time periods, determining estimated vehicle operation information according to historical vehicle operation information of the candidate time periods in sequence, and further determining the logistics distribution path in the current candidate time period. Namely, every time a new candidate time period comes, the estimated vehicle operation information is determined according to the historical vehicle operation information of the candidate time period, and then the logistics distribution path in the candidate time period is determined.
As shown in fig. 8, an embodiment of the present disclosure provides a distribution path determining apparatus, including:
a historical vehicle operation information determining unit 801 configured to determine historical vehicle operation information between distribution blocks, where the distribution blocks are obtained by partitioning distribution areas;
the estimated vehicle operation information determining unit 802 is configured to determine estimated vehicle operation information between distribution blocks in a target time period according to an estimated road traffic condition and historical vehicle operation information, where the estimated road traffic condition is a road traffic abnormal condition existing in a distribution area in the target time period, and the vehicle operation information includes traffic flow of a third-party vehicle between the distribution blocks and driving time between the distribution blocks;
the distribution path determining unit 803 is configured to determine a logistics distribution path between distribution blocks according to the predicted vehicle operation information.
In one embodiment, the historical vehicle operation information determining unit 801 may further include:
the block dividing subunit is used for carrying out block division on the distribution area to obtain a plurality of distribution blocks;
the central area determining subunit is used for determining a central area of the distribution block, and the central area is an area where the traffic flow in the distribution block meets a preset condition;
and the historical vehicle running information determining subunit is used for determining the historical vehicle running information according to the historical vehicle running track passing through the central area, wherein the historical vehicle running track is the vehicle running track of the third-party vehicle.
In one embodiment, the partitioning the sub-unit may further include:
the system comprises a target parking point obtaining subunit, a target parking point obtaining subunit and a control unit, wherein the target parking point obtaining subunit is used for obtaining a target parking point in a historical vehicle driving track, and the target parking point is a parking point for a third-party vehicle to get on and off a passenger;
the clustering region obtaining subunit is used for clustering the target parking points to obtain a plurality of clustering regions;
and the distribution block determining subunit is used for determining the clustering area as a distribution block.
In one embodiment, the predicted vehicle operation information determining unit 802 may further include:
a historical vehicle operation information obtaining subunit, configured to obtain historical vehicle operation information;
and the vehicle operation information adjusting subunit is used for adjusting the historical vehicle operation information according to the estimated road traffic condition to obtain the estimated vehicle operation information.
In one embodiment, the vehicle operation information adjusting subunit may further include:
the first traffic flow determining subunit is used for determining the traffic flow of a third-party vehicle on the impassable road according to the historical vehicle operation information under the condition that the estimated road traffic condition comprises impassable roads among distribution blocks;
and the first traffic flow adjusting subunit is used for adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of the third-party vehicle on the impassable road.
In one embodiment, the vehicle operation information adjusting subunit may further include:
the second traffic flow determining subunit is used for determining the traffic flow of part of third-party vehicles under the condition that the estimated road traffic condition is that only part of third-party vehicles among the distribution blocks are delayed to arrive;
the second traffic flow adjusting subunit is used for adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of part of the third-party vehicles;
the delay time length determining subunit is used for determining the delay time length corresponding to part of the third-party vehicles;
and the driving time adjusting subunit is used for adjusting the driving time in the historical vehicle operation information according to the delay time.
In one embodiment, the delivery path determining unit 803 may further include:
a distribution block selection subunit, configured to select a starting distribution block and an ending distribution block for logistics distribution in the distribution area;
the preferred distribution path determining subunit is used for determining a preferred distribution path which meets the distribution requirement according to the traffic flow in the predicted vehicle operation information and the driving time in the predicted vehicle operation information, wherein the preferred distribution path is a path from the starting distribution block to the ending distribution block;
a logistics distribution path determination subunit for determining the preferred distribution path as the logistics distribution path.
In one embodiment, the preferred delivery path determining subunit may further include:
the weighted directed graph building subunit is used for building a weighted directed graph aiming at the distribution blocks by utilizing the estimated vehicle operation information, wherein nodes in the weighted directed graph are used for representing the distribution blocks, edges in the weighted directed graph are used for representing third-party vehicles which can reach the distribution blocks, and weights in the weighted directed graph are pre-configured according to distribution requirements;
the optimal distribution path determining subunit is used for determining an optimal distribution path which meets the distribution requirements by using the weighted directed graph;
and the preferred distribution path determining subunit is used for determining the optimal distribution path as the preferred distribution path.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.
According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.
FIG. 9 illustrates a schematic block diagram of an example electronic device 900 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 9, the apparatus 900 includes a computing unit 901, which can perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)902 or a computer program loaded from a storage unit 908 into a Random Access Memory (RAM) 903. In the RAM903, various programs and data required for the operation of the device 900 can also be stored. The calculation unit 901, ROM 902, and RAM903 are connected to each other via a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.
A number of components in the device 900 are connected to the I/O interface 905, including: an input unit 906 such as a keyboard, a mouse, and the like; an output unit 907 such as various types of displays, speakers, and the like; a storage unit 908 such as a magnetic disk, optical disk, or the like; and a communication unit 909 such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 909 allows the device 900 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 901 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 901 performs the respective methods and processes described above, such as the determination method of the distribution path. For example, in some embodiments, the method of determining the delivery path may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 900 via ROM 902 and/or communications unit 909. When the computer program is loaded into the RAM903 and executed by the computing unit 901, one or more steps of the method of determining a distribution path described above may be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to perform the method of determining the delivery path by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable distribution path determining apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (19)
1. A method of determining a delivery path, comprising:
determining historical vehicle operation information among distribution blocks, wherein the distribution blocks are obtained by partitioning distribution areas;
determining estimated vehicle operation information among the distribution blocks in a target time period according to estimated road traffic conditions and the historical vehicle operation information, wherein the estimated road traffic conditions are road traffic abnormal conditions existing in the distribution areas in the target time period, and the vehicle operation information comprises traffic flow of third-party vehicles among the distribution blocks and driving time among the distribution blocks;
and determining logistics distribution paths among the distribution blocks according to the estimated vehicle operation information.
2. The method of claim 1, wherein the determining historical vehicle operation information between delivery zones comprises:
dividing the distribution area into a plurality of distribution blocks;
determining a central area of the distribution block, wherein the central area is an area in which the traffic flow in the distribution block meets a preset condition;
and determining the historical vehicle running information according to the historical vehicle running track passing through the central area, wherein the historical vehicle running track is the vehicle running track of the third-party vehicle.
3. The method of claim 2, wherein the block partitioning the delivery area comprises:
obtaining a target parking point in the historical vehicle driving track, wherein the target parking point is a parking point for passengers to get on or off the vehicle of the third party;
clustering the target parking points to obtain a plurality of clustering areas;
and determining the clustering area as the distribution block.
4. The method of claim 1, wherein the determining of the predicted vehicle operation information comprises:
obtaining the historical vehicle operation information;
and adjusting the historical vehicle operation information according to the estimated road traffic condition to obtain the estimated vehicle operation information.
5. The method of claim 4, wherein said adjusting said historical vehicle operation information comprises:
determining the traffic flow of the third-party vehicle on the impassable road according to the historical vehicle operation information under the condition that the estimated road traffic condition comprises impassable roads among the distribution blocks;
and adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of the third-party vehicle on the road which cannot be passed through.
6. The method of claim 4 or 5, wherein said adjusting said historical vehicle operation information comprises:
determining the traffic flow of part of the third-party vehicles when the estimated road traffic condition is that only part of the third-party vehicles are delayed to arrive between the distribution blocks;
adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of part of the third-party vehicles;
determining a delay time length corresponding to part of the third-party vehicles;
and adjusting the driving time length in the historical vehicle operation information according to the delay time length.
7. The method of any of claims 1 to 5, wherein the determining the logistics distribution path between the distribution blocks comprises:
selecting a starting distribution block and an ending distribution block of logistics distribution in the distribution area;
determining a preferred distribution path which meets the distribution demand according to the traffic flow in the estimated vehicle operation information and the driving time in the estimated vehicle operation information, wherein the preferred distribution path is a path from the initial distribution block to the final distribution block;
determining the preferred distribution path as the logistics distribution path.
8. The method of claim 7, wherein said determining a preferred delivery path that meets delivery requirements comprises:
utilizing the estimated vehicle operation information to construct a weighted directed graph for the distribution blocks, wherein nodes in the weighted directed graph are used for representing the distribution blocks, edges in the weighted directed graph are used for representing the third-party vehicles which can reach the distribution blocks, and weights in the weighted directed graph are pre-configured according to the distribution requirements;
determining an optimal distribution path which accords with the distribution demand by using the weighted directed graph;
and determining the optimal distribution path as the preferred distribution path.
9. A delivery path determination apparatus comprising:
the system comprises a historical vehicle operation information determining unit, a distribution area determining unit and a distribution area determining unit, wherein the historical vehicle operation information determining unit is used for determining historical vehicle operation information among distribution areas which are obtained by partitioning distribution areas;
the estimated vehicle operation information determining unit is used for determining estimated vehicle operation information among the distribution blocks in a target time period according to an estimated road traffic condition and the historical vehicle operation information, wherein the estimated road traffic condition is a road traffic abnormal condition existing in the distribution area in the target time period, and the vehicle operation information comprises the traffic flow of third-party vehicles among the distribution blocks and the driving time among the distribution blocks;
and the distribution path determining unit is used for determining the logistics distribution paths among the distribution blocks according to the predicted vehicle running information.
10. The apparatus of claim 9, wherein the historical vehicle operation information determination unit comprises:
a block dividing subunit, configured to perform block division on the distribution area to obtain a plurality of distribution blocks;
a central area determining subunit, configured to determine a central area of the distribution block, where a traffic flow rate in the distribution block meets a preset condition;
and the historical vehicle running information determining subunit is used for determining the historical vehicle running information according to a historical vehicle running track passing through the central area, wherein the historical vehicle running track is the vehicle running track of the third-party vehicle.
11. The apparatus of claim 10, wherein the tile-dividing unit comprises:
the target parking point obtaining subunit is used for obtaining a target parking point in the historical vehicle driving track, wherein the target parking point is a parking point for passengers to get on or off the vehicle from the third-party vehicle;
a clustering region obtaining subunit, configured to cluster the target parking points to obtain multiple clustering regions;
a delivery block determination subunit, configured to determine the clustering area as the delivery block.
12. The apparatus of claim 9, wherein the predicted vehicle operation information determining unit comprises:
a historical vehicle operation information obtaining subunit, configured to obtain the historical vehicle operation information;
and the vehicle operation information adjusting subunit is used for adjusting the historical vehicle operation information according to the estimated road traffic condition to obtain the estimated vehicle operation information.
13. The apparatus of claim 12, wherein the vehicle operation information adjusting subunit includes:
the first traffic flow determining subunit is configured to determine, according to the historical vehicle operation information, a traffic flow of the third-party vehicle on the impassable road when the estimated road traffic condition includes impassable roads existing between the distribution blocks;
and the first traffic flow adjusting subunit is used for adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of the third-party vehicle on the impassable road.
14. The apparatus of claim 12 or 13, wherein the vehicle operation information adjusting subunit includes:
the second traffic flow determining subunit is used for determining the traffic flow of part of the third-party vehicles when the estimated road traffic condition is that only part of the third-party vehicles arrive in a delayed manner between the distribution blocks;
the second traffic flow adjusting subunit is used for adjusting the traffic flow in the historical vehicle operation information according to the traffic flow of part of the third-party vehicles;
the delay time length determining subunit is used for determining a delay time length corresponding to part of the third-party vehicles;
and the driving time length adjusting subunit is used for adjusting the driving time length in the historical vehicle operation information according to the delay time length.
15. The apparatus according to any one of claims 9 to 13, wherein the delivery path determining unit includes:
a distribution block selection subunit, configured to select a starting distribution block and an ending distribution block for logistics distribution in the distribution area;
a preferred distribution path determining subunit, configured to determine a preferred distribution path that meets a distribution demand according to the traffic flow in the predicted vehicle operation information and the driving time duration in the predicted vehicle operation information, where the preferred distribution path is a path from the initial distribution block to the final distribution block;
a logistics distribution path determination subunit, configured to determine the preferred distribution path as the logistics distribution path.
16. The apparatus of claim 15, wherein the preferred delivery path determining subunit comprises:
a weighted directed graph construction subunit, configured to construct a weighted directed graph for the distribution blocks by using the estimated vehicle operation information, where nodes in the weighted directed graph are used to represent the distribution blocks, edges in the weighted directed graph are used to represent the third-party vehicles that are reachable between the distribution blocks, and weights in the weighted directed graph are pre-configured according to the distribution requirements;
the optimal distribution path determining subunit is used for determining an optimal distribution path which meets the distribution requirement by using the weighted directed graph;
and the preferred distribution path determining subunit is used for determining the optimal distribution path as the preferred distribution path.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1 to 8.
19. A computer program product comprising computer programs/instructions, wherein the computer programs/instructions, when executed by a processor, implement the steps of the method of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115330318A (en) * | 2022-10-12 | 2022-11-11 | 广州一链通互联网科技有限公司 | Logistics distribution method and system based on block chain technology |
| CN116451897A (en) * | 2023-06-14 | 2023-07-18 | 吉林大学 | Crowd-sourced logistics distribution path planning system and method based on artificial intelligence |
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2021
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115330318A (en) * | 2022-10-12 | 2022-11-11 | 广州一链通互联网科技有限公司 | Logistics distribution method and system based on block chain technology |
| CN115330318B (en) * | 2022-10-12 | 2023-02-10 | 广州一链通互联网科技有限公司 | Logistics distribution method and system based on block chain technology |
| CN116451897A (en) * | 2023-06-14 | 2023-07-18 | 吉林大学 | Crowd-sourced logistics distribution path planning system and method based on artificial intelligence |
| CN116451897B (en) * | 2023-06-14 | 2023-08-18 | 吉林大学 | Crowd-sourced logistics distribution path planning system and method based on artificial intelligence |
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