Logistics monitoring method and device

• US 10,446,023 B2
• Filed: 09/28/2017
• Issued: 10/15/2019
• Est. Priority Date: 04/03/2015
• Status: Active Grant

• Current Assignee: Alibaba Group Holding Ltd.
• Original Assignee: Alibaba Group Holding Ltd.
• Inventors: Liang, Simiao, Wang, Yu, Pang, Baohui, Min, Wanli, Ren, Jidong
• Primary Examiner(s): Beaulieu, Yonel
• Application Number:
  US15/718,733
• Publication Number:
  US 20180018868A1
• Time in Patent Office: 747 Days
• CPC Class Codes: G01W 1/00 Meteorology
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/0838 Historical data
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/015 with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
• CPC Class Codes: G08G 1/052 with provision for determining speed or overspeed speed measuring in general G01P

Abstract

A logistics monitoring method and device are disclosed. The method comprises: obtaining an estimated speed of a vehicle at a road section according to the weather and speed data of the road section, and then acquiring logistics monitoring data according to the estimated speed of the vehicle. Weather information can be structured into a pattern that can be applied to logistics monitoring, and precise logistics monitoring and prediction data is acquired by combining weather factors with information about a road section. Due to the large time and space span in long-distance logistics, weather factors have a great impact on long-distance logistics, making the logistics monitoring method and device applicable for monitoring of intercity long-distance logistics.

Claims

1. A method of logistics monitoring, comprising:

determining, remotely from a vehicle, a road section that the vehicle is travelling on and a time segment;

obtaining historical vehicle speed data on the road section associated with historical meteorological data of the road section and time segment, wherein the historical vehicle speed data comprises an average standard vehicle speed of each of a plurality of vehicle types;

obtaining current meteorological data;

obtaining an estimated vehicle speed of the vehicle on the road section based on the current meteorological data, historical meteorological data, and historical vehicle speed data, wherein obtaining an estimated vehicle speed of the vehicle on the road section based on the current meteorological data, historical meteorological data, and historical vehicle speed data comprises obtaining an average standard vehicle speed corresponding to a vehicle type of the vehicle;

determining, after obtaining the average standard vehicle speed corresponding to the vehicle'"'"'s vehicle type, whether the time for the vehicle to travel on a remaining portion of the road section with an average vehicle speed for the portion of the road section that the vehicle has traveled is smaller than a preset threshold;

in response to determining that the time is smaller than the preset threshold, taking the average vehicle speed for the portion of the road section that the vehicle has traveled to be the estimated vehicle speed for the remaining portion of the vehicle on the road section; and

in response to determining that the time is not smaller than the preset threshold, identifying a matched average standard vehicle speed that is associated to the road section, the matched average standard vehicle speed being identified from the historical meteorological data and the historical vehicle speed, and obtaining the estimated vehicle speed of the remaining portion of the vehicle on the road section according to the matched average standard vehicle speed that is associated to the road section;

determining, remotely from the vehicle, a real time speed of the vehicle; and

if the real time speed is less than the estimated vehicle speed, and the difference between the real time speed and the estimated vehicle speed is greater than a threshold, determining that the road section is congested.

2. The method according to claim 1, wherein matching with the average standard vehicle speed that is associated to the road section from the relationship data of the historical meteorological data and the historical vehicle speed comprises one of the following:

seeking, from the historical meteorological data and the historical vehicle speed, a vehicle speed for the same road section and same time segment with the same weather as the matched average standard vehicle speed that is associated to the road section;

seeking, from the historical meteorological data and the historical vehicle speed, a vehicle speed for the same road section and another similar time segment with the same weather as the matched average standard vehicle speed that is associated to the road section; and

seeking, from the historical meteorological data and the historical vehicle speed, a vehicle speed for another road section as the matched average standard vehicle speed that is associated to the road section.

3. A method of logistics monitoring, comprising:

obtaining an estimated vehicle speed of a vehicle on a road section according to meteorological and vehicle speed data of the road section, wherein the meteorological and vehicle speed data of the road section comprises real time meteorological data of the road section, real time vehicle speed of the vehicle, and relationship data between historical meteorological data and vehicle speed of the road section, wherein the relationship data between the historical meteorological data and the vehicle speed of the road section comprises an average standard vehicle speed of each vehicle type of a plurality of vehicle types based on the historical meteorological data according to the road section and a time segment, and wherein obtaining the estimated vehicle speed of the vehicle on the road section obtained based on the meteorological and the vehicle speed data of the road section comprises obtaining an average standard vehicle speed corresponding to a vehicle type of the vehicle based on the historical meteorological data of the road section and time segment, according to the meteorological data of the vehicle on the road section and the average standard vehicle speed of each vehicle type based on the historical meteorological data of the road section and time segment;

determining, after obtaining the average standard vehicle speed corresponding to the vehicle type of the vehicle, whether the time for the vehicle to travel on a remaining portion of the road section with an average of the real time vehicle speed for a portion of the road section that the vehicle has traveled is smaller than a preset threshold;

in response to determining that the time is smaller than the preset threshold, taking the average of the real time vehicle speed for the road section'"'"'s portion that the vehicle has traveled to be the estimated vehicle speed of the remaining portion of the road section; and

in response to determining that the time is not smaller than the preset threshold, identifying a matched average standard vehicle speed that is associated to the road section, the matched average standard vehicle speed being identified from the relationship data of the historical meteorological data and the vehicle speed, and obtaining the estimated vehicle speed of the remaining portion of the road section according to the matched average standard vehicle speed that is associated to the road section;

acquiring logistics monitoring data according to the estimated vehicle speed, wherein acquiring the logistics monitoring data according to the estimated vehicle speed comprises determining whether the road section is congested according to a vehicle flow rate on the road section, the real time vehicle speed, and a corresponding average standard vehicle speed.

4. The method according to claim 3, wherein matching with the average standard vehicle speed that is associated to the road section from the relationship data of the historical meteorological data and the vehicle speed comprises one of the following:

seeking, from the relationship data between the historical meteorological data and vehicle speed, a vehicle speed for the same road section and same time segment with the same weather as the matched average standard vehicle speed that is associated to the road section;

seeking, from the relationship data between the historical meteorological data and vehicle speed, a vehicle speed for the same road section and another time segment with the same weather as the matched average standard vehicle speed that is associated to the road section; and

seeking, from the relationship data between the historical meteorological data and vehicle speed, a vehicle speed for another road section as the matched average standard vehicle speed that is associated to the road section.

5. The method according to claim 3, wherein matching with the average standard vehicle speed that is associated to the road section from the relationship data of the historical meteorological data and the vehicle speed comprises:

seeking, from the relationship data between the historical meteorological data and vehicle speed, a vehicle speed for the same road section and same time segment with the same weather, and if there is such a vehicle speed, using the vehicle speed as the matched average standard vehicle speed that is associated to the road section;

in response to determining the vehicle speed for the same road section and same time segment with the same weather, using the vehicle speed as the matched average standard vehicle speed that is associated to the road section;

in response to determining no vehicle speed for the same road section and same time segment with the same weather, seeking, from the relationship data between the historical meteorological data and vehicle speed, a vehicle speed for the same road section and another time segment with the same weather, and;

in response to determining the vehicle speed for the same road section and another time segment with the same weather, using the vehicle speed as the matched average standard vehicle speed that is associated to the road section; and

in response to determining no vehicle speed for the same road section and another time segment with the same weather, seeking, from the relationship data between the historical meteorological data and vehicle speed, a vehicle speed for another road section as the matched average standard vehicle speed that is associated to the road section.

6. The method according to claim 3, wherein after determining whether the road section is congested, further comprising:

acquiring a congestion duration time for the road section according to the vehicle flow rate on the road section and the estimated vehicle speed of the remaining portion.

7. The method according to claim 6, wherein after the congestion duration time for the road section is acquired, further comprising:

adjusting the route of the vehicle that passes through the road section when the congestion duration time is larger than the preset threshold.

8. The method according to claim 3, further comprising:

acquiring the estimated vehicle speeds of each subsequent road section of a route of the vehicle according to the estimated vehicle speed for the remaining portion of the vehicle on the road section; and

wherein acquiring logistics monitoring data according to the estimated vehicle speed comprises;

estimating a travel time of the vehicle on each road section according to the remaining portion of the vehicle on the road section and the estimated vehicle speed for each road section; and

estimating the time for the vehicle to reach one node according to the travel time of each road section prior to the node.

9. The method according to claim 8, wherein before estimating the time for the vehicle to reach one node according to the travel time of each road section prior to the node, further comprising:

establishing a correspondence relationship between the vehicle and a waybill.

10. The method according to claim 9, wherein the waybill comprises an already generated waybill and an estimated waybill obtained based on sale forecast.

11. The method according to claim 9, wherein estimating the time for the vehicle to reach the one node according to the travel time of each road section prior to the node comprises:

estimating the time for the vehicle to reach one node according to the travel time of each road section prior to a current node according to a waybill processing speed of a preceding node and travel time for each road section prior to the road section.

12. The method according to claim 11, wherein after the time for the vehicle to reach one node is estimated according to the travel time of each road section prior to the current node according to the waybill processing speed of the preceding node and the travel time for each road section prior to the road section, further comprising:

estimating a quantity of waybills to be processed for each time segment in future for the node based on the time for the vehicle to reach the node.

13. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor of a logistics monitoring system, cause the system to perform a method, the method comprising:

obtaining an estimated vehicle speed of a vehicle on a road section according to meteorological and vehicle speed data of the road section, wherein the meteorological and vehicle speed data of the road section comprises real time meteorological data of the road section, real time vehicle speed of the vehicle, and relationship data between historical meteorological data and vehicle speed of the road section, wherein the relationship data between the historical meteorological data and the vehicle speed of the road section comprises an average standard vehicle speed of each vehicle type of a plurality of vehicle types based on the historical meteorological data according to the road section and a time segment, and wherein obtaining the estimated vehicle speed of the vehicle on the road section obtained based on the meteorological and the vehicle speed data of the road section comprises obtaining an average standard vehicle speed corresponding to a vehicle type of the vehicle based on the historical meteorological data of the road section and time segment, according to the meteorological data of the vehicle on the road section and the average standard vehicle speed of each vehicle type based on the historical meteorological data of the road section and time segment;

determining, after obtaining the average standard vehicle speed corresponding to the vehicle type of the vehicle, whether the time for the vehicle to travel on a remaining portion of the road section with an average of the real time vehicle speed for a portion of the road section that the vehicle has traveled is smaller than a preset threshold;

in response to determining that the time is smaller than the preset threshold, taking the average of the real time vehicle speed for the road section'"'"'s portion that the vehicle has traveled to be the estimated vehicle speed of the remaining portion of the road section;

in response to determining that the time is not smaller than the preset threshold, identifying a matched average standard vehicle speed that is associated to the road section, the matched average standard vehicle speed being identified from the relationship data of the historical meteorological data and the vehicle speed, and obtaining the estimated vehicle speed of the remaining portion of the road section according to the matched average standard vehicle speed that is associated to the road section;

acquiring logistics monitoring data according to the estimated vehicle speed, wherein acquiring the logistics monitoring data according to the estimated vehicle speed comprises determining whether the road section is congested according to a vehicle flow rate on the road section, the real time vehicle speed, and a corresponding average standard vehicle speed.