A Night-time Residential Parking Demand Prediction Method Based on Survival Analysis

A survival analysis and demand forecasting technology, applied in the direction of forecasting, indicating various open spaces in the parking lot, and data processing applications, etc., can solve the problems of reducing the guiding significance of forecasting results for parking management decision-making, and mastering the changing laws of parking demand. Applying value, overcoming imprecise effects

Active Publication Date: 2021-04-30
TONGJI UNIV
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AI Technical Summary

Problems solved by technology

[0004] Although the application of artificial intelligence methods such as neural networks can theoretically obtain better prediction accuracy, because this type of method contains some unrecognizable (implicit) process methods, researchers cannot further grasp the changing law of parking demand. At the same time, it also greatly reduces the guiding significance of the prediction results for parking management decisions.

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  • A Night-time Residential Parking Demand Prediction Method Based on Survival Analysis
  • A Night-time Residential Parking Demand Prediction Method Based on Survival Analysis
  • A Night-time Residential Parking Demand Prediction Method Based on Survival Analysis

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Embodiment 1

[0055] Step 1: Parking lot survey objects

[0056] A science and technology park in Shanghai is located in Pudong New District, Shanghai, close to the central ring, and occupies the core area of ​​Zhangjiang High-tech Park Jidiangang Industry. It is a typical office building. The construction area of ​​the park is 76,000 square meters, and the office area is about 65,000 square meters. The park has its own off-street parking lot, with a total of 502 parking spaces, including 181 ground parking spaces and 321 basement parking spaces.

[0057] The selected data is the six-month continuous parking data of the Science and Technology Park from June 2016 to November 2016, of which more than 30,000 pieces of parking data in the three months from June 1 to August 31, 2016 are used as model training samples, and from September 1 to November 2016. 30 parking data are used as test samples to evaluate the performance of the model.

[0058] By synthesizing the existing research literatur...

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Abstract

The invention discloses a method for predicting parking demand at night based on survival analysis, wherein the method includes: obtaining continuous parking data and some external factor data in a parking lot; Transform the nighttime parking demand into the resident part of the daytime parking vehicle; express the parking event as a survival event, and perform corresponding data processing to make the form suitable for the survival analysis method; Influenced Cox proportional hazards model; according to the model results, the probabilities of daytime parking for different durations of vehicles under different conditions are predicted, and the predicted nighttime parking demand is further obtained. The invention proposes a new microcosmic method for forecasting parking demand at night, and has good forecasting accuracy. The method for forecasting demand for parking at night according to the present invention can provide a basis for the night demand management of the parking lot, and can be used in the pricing of refined management, the opening of shared berths, and parking zoning.

Description

technical field [0001] The invention relates to the field of static traffic and parking lot design, in particular to a method for forecasting parking demand at night based on survival analysis. Background technique [0002] With the continuous increase of the number of motor vehicles, insufficient parking facilities have become a common problem in major cities, and refined parking management has become an important means to improve the utilization efficiency of parking facilities and alleviate parking difficulties. Premise and basis, it is very important to accurately predict parking demand. With the deepening of the concept of shared parking, refined parking management is bound to distinguish between day and night parking needs according to the main building type of the parking lot, and formulate corresponding and reasonable parking space reservation capacity plans, so as to achieve full parking demand Grasp the daily changes and ensure the orderly implementation of shared...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/14G06Q10/04G06Q10/06G06F17/15G06Q50/26
CPCG06F17/15G06Q10/04G06Q10/06315G06Q50/26G08G1/14
Inventor 李林波高天爽姜屿
Owner TONGJI UNIV
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