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About the Optimized Design of the Parking Space on the Campus of a College

About the Optimized Design of the Parking Space on the Campus of a College
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摘要 In recent years, with the large increase in the number of motor vehicles in colleges and universities and the lag in campus planning, the relative shortage of parking spaces on campus has become increasingly serious. Taking Baoding College as an example, this article analyzes the current situation of static traffic on campus and finds out the problem of parking on campus through questionnaire surveys and field surveys. Analyze the growth trend of the number of motor vehicles based on the data, use the GM (1, 1) model and the linear fitting model to predict the number of motor vehicles in the future, and determine the size and layout of the parking lot based on the campus size, functional zoning, and road layout. The big campus-based parking system planning method based on big data can effectively solve the problems of small sample data, low accuracy, and poor timeliness of traditional methods, which improves the practicability and scientificity of planning results. In recent years, with the large increase in the number of motor vehicles in colleges and universities and the lag in campus planning, the relative shortage of parking spaces on campus has become increasingly serious. Taking Baoding College as an example, this article analyzes the current situation of static traffic on campus and finds out the problem of parking on campus through questionnaire surveys and field surveys. Analyze the growth trend of the number of motor vehicles based on the data, use the GM (1, 1) model and the linear fitting model to predict the number of motor vehicles in the future, and determine the size and layout of the parking lot based on the campus size, functional zoning, and road layout. The big campus-based parking system planning method based on big data can effectively solve the problems of small sample data, low accuracy, and poor timeliness of traditional methods, which improves the practicability and scientificity of planning results.
作者 Xin Wang Yunhui Wang Chong Hu Xin Wang;Yunhui Wang;Chong Hu(School of Data Science and Software Engineering, Baoding University, Baoding, China;School of Automotive and Electronic Engineering, Baoding University, Baoding, China)
出处 《American Journal of Computational Mathematics》 2020年第2期221-229,共9页 美国计算数学期刊(英文)
关键词 Static Traffic Parking Space Planning GM (1 1) Linear Fitting Static Traffic Parking Space Planning GM (1 1) Linear Fitting
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