基于大数据关联分析的城市公交建设与改善决策支持研究

项目名称： 基于大数据关联分析的城市公交建设与改善决策支持研究

项目编号： No.51478350

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 建筑科学

项目作者： 杨东援

作者单位： 同济大学

项目金额： 80万元

中文摘要： 针对公交系统建设与改善具有系统架构控制与渐进式线路和运行调整的特点，以消除相应决策判断模糊性和促进共识为目标，基于城市交通大数据环境，展开公交系统与城市空间联系结构、居民活动空间与公交系统、居民主导交通方式与公交服务区位三方面的关联分析，在此基础上提出大数据环境下公交整体架构决策分析、公交服务水平精细化诊断评估分析技术方法，并依托实测数据进行技术验证。针对需解决的三个关键技术问题：大数据环境下的信息融合和关联分析、居民活动空间的表征与分析、系统瓶颈诊断与评估，提出基于采样和搜索引导的关联分析方法，基于居民活动空间的公交需求分析方法；基于决策问题层次化结构技术组织框架等技术解决方案。本项目将在基于居民活动空间的区域交通需求强度分析、决策问题层次化框架引导下的信息关联分析、针对公交系统对策研究的信息融合分析等方面取得创新性突破，研究成果将形成与基于模型的分析技术的相互支持。

中文关键词： 公共交通；决策分析；大数据；关联分析；数据融合

英文摘要： The construction of public transport system has the characteristics of system architecture control and progressive adjustment of routes and operations. In order to eliminate the fuzziness of corresponding decision-makings and promote consensus as the goal, this project will conduct the association analysis in three aspects: public transport system and urban space structure, residents' activity space and public transport system, the main transport mode of residents and transit service locations. Based on the big data environment, approaches of decision-making analysis of public transport system architecture and fine diagnostic evaluation analysis of transit service levels will be proposed and then verified by the measured data. Three key technical issues need to be resolved under big data environment: information fusion and association analysis, characterization and analysis of the residents' activity space, diagnosis and evaluation of the system bottleneck. Related technical solutions will be proposed, such as association analysis method based on sampling and search guide, public transport demand analysis method based on the residents' activity space; hierarchical structure of decision-making based on organizational framework technology. Besides, in this research innovative breakthroughs will be achieved in aspects such as the analysis of area traffic demand intensity based on residents' activity space, information association analysis guided by the hierarchical framework of decision-making, information fusion analysis on the countermeasure of public transport system. The research results can be associated with model-based analysis technology and offer mutual support.

英文关键词： Public Transport;Decision Support;Big Data;Association Analysis;Data Fusion