中山大学学报（自然科学版）（中英文）2025，Vol.64Issue(3)：129-138,10.DOI:10.13471/j.cnki.acta.snus.ZR20240357
基于高速公路交易数据的出行模式分析与差异化收费策略
Travel pattern analysis and differentiated tolling strategies based on highway transaction data
摘要
Abstract
Highway transaction data were utilized to select 10 indicators representing user-specific characteristics and the spatiotemporal features of travel,forming the basis for constructing a user characteristic model.To classify highway user characteristics,the K-means,fuzzy C-means,and self-organizing map algorithms were applied to ETC data from a specific road segment.The results indicate that,compared to K-means and fuzzy C-means,the SOM model performs better in classifying user travel patterns and supports the reasonable classification of highway users into six categories.Based on these classification results,a personalized differential tolling strategy is proposed,and its feasibility is validated through numerical simulation.关键词
ETC数据/聚类算法/出行模式分析/差异化收费Key words
ETC data/clustering algorithm/travel mode analysis/differentiated charges分类
交通工程引用本文复制引用
吕能超,董新雨,罗如意,曾岳凯,徐达,周新聪..基于高速公路交易数据的出行模式分析与差异化收费策略[J].中山大学学报（自然科学版）（中英文）,2025,64(3):129-138,10.基金项目
国家重点研发计划(2023YFB4302600) （2023YFB4302600）
国家自然科学基金(52472366,52072290) （52472366,52072290）
湖北省重点研发计划(2024BAB051) （2024BAB051）
