基于关联规则的居民公共交通依赖性致因分析  

A Cause Analysis of Residents'Dependence on Public Transportation Based on Association Rules

作　　者：胡松 杨贝 翁剑成[3] 周伟[4] HU Song;YANG Bei;WENG Jiancheng;ZHOU Wei(Research Institute of Highway Ministry of Transport,Beijing 100088,China;Zhonglu Gongke(Beijing)Consulting Co.,Ltd.,Beijing 100088,China;Faculty of Urban Construction,Beijing University of Technology,Beijing 100124,China;Ministry of Transport of the People's Republic of China,Beijing 100736,China)

机构地区：[1]交通运输部公路科学研究所,北京100088 [2]中路公科(北京)咨询有限公司,北京100088 [3]北京工业大学城市建设学部,北京100124 [4]中华人民共和国交通运输部,北京100736

出　　处：《交通信息与安全》2023年第3期147-156,共10页Journal of Transport Information and Safety

基　　金：中央级公益性科研院所基本科研业务费专项资金项目(2021-9017b);国家自然科学基金重大项目(U1811463);国家自然科学基金项目(52072011);交通运输部公路科学研究所(院)交通强国试点项目(QG2022-2-8-4)资助。

摘　　要：鉴别不同出行者对公共交通的依赖程度,并分析其形成的致因差异,有助于从规划设计、政策制定等维度针对性地改善公共交通服务质量。设计并实施了居民出行的行为调查(revealed preference,RP)线上问卷,在数据质量检验的基础上引入关联匹配技术,通过融合出行调查数据与公共交通出行交易数据实现了个体公共交通出行链提取。提出了公共交通依赖性度量指标与关键致因指标,构建了AGNES-Apriori模型开展公共交通依赖性分级与不同层级群体强关联规则挖掘,并据此提出了公共交通依赖性层级提升的“两阶段”框架及出行激励策略集。结果表明:①居民公共交通依赖性可被划分为低、较低、较高和高依赖性4个层级,不同层级对应的强关联规则间具有显著差异性;②关联规则包含的指标数量与3个参数值呈负相关关系,高依赖性强关联规则出现的概率为低依赖性的2.1倍;③家和目的地到站点总距离、收入、小汽车可用性等客观条件是影响居民公共交通依赖性的关键致因,而公共交通出行低自由度是导致居民公共交通依赖性降低的重要原因;④较低的客观条件指标值通常促使居民形成较高的公共交通依赖性;⑤小汽车低可用性变量主要出现在公共交通低、高依赖性群体对应的强关联规则中,而高依赖性群体随其小汽车可用性增强可能出现公共交通依赖性降低的趋势。Identifying the magnitude of travelers'dependence on public transit(PT)and analyzing the differences in its underlying causes can contribute to targeted improvements in the level of PT services from the perspectives of planning,design and policy making.In this study,an online revealed preference(RP)survey for residents'travel is designed and carried out.The data quality is examined,based on which the correlation matching technique is adopted to extract individual PT-trip chains by integrating travel survey data and PT transaction data.Measurement indicators and key causation indicators of PT dependence are proposed,and an AGNES-Apriori model is developed to classify travelers'PT dependence and strong association rules for different groups.Further,a two-stage framework and a set of travel incentive strategies to enhance travelers'PT dependence levels are proposed.The results show that①residents'PT dependence can be classified into four categories(low,relatively low,relatively high,and high dependences),and significant differences are found among the different categories regarding the strong association rules;②the number of indicators contained in association rules is negatively correlated with three parameters,and the probability of strong association rules with high dependence level is 2.1 times higher than that with low dependence level;③objective factors such as total distance from home and destination to the PT stations,income,and car availability are identified as key indicators affecting residents'PT dependence,and the low freedom for traveling by PT is an important reason for the reduction of travelers'dependence on PT;④the low values of the objective factors usually cause the travelers to form a relatively high PT dependence;⑤the low availability of cars mainly related to the strong association rules corresponding to the low and high PT dependence groups,while the high dependence group may show the tendency of reducing PT dependence with increased car availability.

关 键 词：城市交通 公共交通依赖性 出行链 AGNES-Apriori算法 关联规则 

分 类 号：U491.1[交通运输工程—交通运输规划与管理]