东南大学学报（英文版）2025，Vol.41Issue(3)：270-277,8.DOI:10.3969/j.issn.1003-7985.2025.03.002
基于回归建模的枢纽停车场内混合停放需求分配
Mixed parking demand assignment in hub parking lots based on regression modeling
摘要
Abstract
To adapt to the unique demand-supply features of accessory parking lots at passenger transport hubs,a mixed parking demand assignment method based on regression modeling is proposed.First,an optimal model aiming to minimize total time expenditure is constructed.It incorpo-rates parking search time,walking time,and departure time,focusing on short-term parking features.Then,the in-formation dimensions that the parking lot can obtain are evaluated,and three assignment strategies based on three types of regression models—linear regression(LR),ex-treme gradient boosting(XGBoost),and multilayer percep-tron(MLP)—are proposed.A parking process simulation model is built using the traffic simulation package SUMO to facilitate data collection,model training,and case studies.Finally,the performance of the three strategies is com-pared,revealing that the XGBoost-based strategy performs the best in case parking lots,which reduces time expendi-ture by 29.3%and 37.2%,respectively,compared with the MLP-based strategy and LR-based strategy.This method offers diverse options for practical parking manage-ment.关键词
停车区域分配/枢纽停车场/回归建模/极致梯度提升(XGBoost)Key words
parking areas assignment/hub parking lot/regression-based modeling/extreme gradient boosting(XG-Boost)分类
交通工程引用本文复制引用
张楚,陈可涵,陈峻,陈嘉毅..基于回归建模的枢纽停车场内混合停放需求分配[J].东南大学学报（英文版）,2025,41(3):270-277,8.基金项目
The National Natural Science Foundation of China(No.52302388),the Natural Science Foundation of Jiangsu Province(No.BK20230853). （No.52302388）
