Parking area recommendation method and apparatus, and medium

Patent metadata

Field	Value
Publication number	US-2024194071-A1
Application number	US-202217908789-A
Country	US
Kind code	A1
Filing date	Feb 28, 2022
Priority date	May 12, 2021
Publication date	Jun 13, 2024
Grant date	—

Abstract

Provided are a parking area recommendation method and apparatus, an electronic device, and a medium. The parking area recommendation method includes: determining parking space occupancy data of a target parking lot; and selecting a target parking area from a plurality of candidate parking areas of the target parking lot according to the parking space occupancy data, where each candidate parking area includes at least two parking spaces.

First claim

What is claimed is:

1 . A parking area recommendation method, comprising:
determining parking space occupancy data of a target parking lot; and selecting a target parking area from a plurality of candidate parking areas of the target parking lot according to the parking space occupancy data; wherein each of the plurality of candidate parking areas comprises at least two parking spaces.

2 . The method according to claim 1 , wherein the selecting a target parking area from a plurality of candidate parking areas of the target parking lot according to the parking space occupancy data comprises:
selecting the target parking area from the plurality of candidate parking areas of the target parking lot according to the parking space occupancy data and based on a parking area recommendation model; wherein the parking area recommendation model is trained in the following manner: determining a historical parking area where a user parks at one historical time instant and historical parking space occupancy data of the target parking lot corresponding to the historical time instant; and performing model training according to the historical parking space occupancy data and the historical parking area to obtain the parking area recommendation model.

3 . The method according to claim 1 , wherein the plurality of candidate parking areas are determined in the following manner:
determining a historical occupancy duration and position information of each of a plurality of parking spaces in the target parking lot; and performing area partition on the plurality of parking spaces according to the historical occupancy duration and position information of each of the plurality of parking spaces to obtain the plurality of candidate parking areas.

4 . The method according to claim 3 , wherein the performing area partition on the plurality of parking spaces according to the historical occupancy duration and position information of each of the plurality of parking spaces to obtain the plurality of candidate parking areas comprises:
clustering the plurality of parking spaces according to the historical occupancy duration of each of the plurality of parking spaces to obtain an occupancy duration clustering result of the plurality of parking spaces; and performing the area partition on the plurality of parking spaces according to the occupancy duration clustering result and the position information of each of the plurality of parking spaces to obtain the plurality of candidate parking areas.

5 . The method according to claim 4 , wherein the clustering the plurality of parking spaces according to the historical occupancy duration of each of the plurality of parking spaces to obtain an occupancy duration clustering result of the plurality of parking spaces comprises:
determining a historical average occupancy duration of each of the plurality of parking spaces in each of a plurality of time periods; constructing an occupancy duration vector of each of the plurality of parking spaces according to the historical average occupancy duration in each of the plurality of time periods; and clustering the plurality of parking spaces according to the occupancy duration vector of each of the plurality of parking spaces to obtain the occupancy duration clustering result of the plurality of parking spaces.

6 . The method according to claim 4 , wherein the performing the area partition on the plurality of parking spaces according to the occupancy duration clustering result and the position information of each of the plurality of parking spaces to obtain the plurality of candidate parking areas comprises:
constructing a spatial position vector of each of the plurality of parking spaces according to the occupancy duration clustering result and the position information of each of the plurality of parking spaces; clustering the plurality of parking spaces according to the spatial position vector of each of the plurality of parking spaces to obtain a spatial position clustering result of the plurality of parking spaces; and performing the area partition on the plurality of parking spaces according to the spatial position clustering result of the plurality of parking spaces to obtain the plurality of candidate parking areas.

7 . The method according to claim 1 , wherein the parking space occupancy data comprises at least one of a total parking space occupancy rate, a parking space occupancy rate of each floor, a parking space occupancy rate of each candidate parking area or a parking space occupancy rate of a key parking area; wherein the key parking area is determined according to identification information of each candidate parking area.

8 . The method according to claim 1 , further comprising:
determining current time information corresponding to a current time instant; wherein the current time information comprises at least one of a month, a week, a day or a time period; and selecting the target parking area from the plurality of candidate parking areas of the target parking lot according to the current time information and the parking space occupancy data.

9 . A parking area recommendation apparatus, comprising: at least one processor; and a memory, which is in a communication connection with the at least one processor; wherein
the memory stores an instruction executable by the at least one processor, and the instruction, when executed by the at least one processor, enables the at least one processor to perform steps in the following modules: a parking space occupancy data determination module, which is configured to determine parking space occupancy data of a target parking lot; and a target parking area selection module, which is configured to select a target parking area from a plurality of candidate parking areas of the target parking lot according to the parking space occupancy data; wherein each of the plurality of candidate parking areas comprises at least two parking spaces.

10 . The apparatus according to claim 9 , wherein the target parking area selection module is configured to:
select the target parking area from the plurality of candidate parking areas of the target parking lot according to the parking space occupancy data and based on a parking area recommendation model; wherein the parking area recommendation model is trained in the following manner: determining a historical parking area where a user parks at one historical time instant and historical parking space occupancy data of the target parking lot corresponding to the historical time instant; and performing model training according to the historical parking space occupancy data and the historical parking area to obtain the parking area recommendation model.

11 . The apparatus according to claim 9 , further comprising: a candidate parking area determination module, which is configured to:
determine a historical occupancy duration and position information of each of a plurality of parking spaces in the target parking lot; and perform area partition on the plurality of parking spaces according to the historical occupancy duration and position information of each of the plurality of parking spaces to obtain the plurality of candidate parking areas.

12 . The apparatus according to claim 11 , wherein the candidate parking area determination module is configured to perform the area partition on the plurality of parking spaces according to the historical occupancy duration and the position information of each of the plurality of parking spaces in the following manner to obtain the plurality of candidate parking areas:
clustering the plurality of parking spaces according to the historical occupancy duration

Assignees

• Beijing Baidu Netcom Sci & Tech Co Ltd

Inventors

• Zhang Yiming
• Tan Xiongfei
• Ge Tingting

Classifications

• G06F18/23

  Clustering techniques · CPC title

• G08G1/144 Primary

  on portable or mobile units, e.g. personal digital assistant [PDA] · CPC title

• G06V10/762

  using clustering, e.g. of similar faces in social networks · CPC title

• G06V20/52

  Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V20/69) · CPC title

• G06N20/00

  Machine learning · CPC title