基于多源异构大数据的出行特征分析——以苏州工业园区为例

Analysis of Travel Characteristics Based on Multi-source Heterogeneous Big Data

融合交通相关的多源异构大数据,持续推进年度交通需求特征分析,是提升交通数字化治理能力的重要工作。基于苏州工业园区连续3年交通出行特征研究工作,形成构建多源数据融合分析的工作体系,建立17类多源异构数据库,形成综合特征分析指标体系,并改进多源数据融合分析算法。连续3年在长三角区域、都市圈和市域市区视角下,研究疫情下苏州工业园区人口岗位、职住和出行特征变化,区域跨市出行需求变化和综合交通枢纽出行需求特征,及时响应和支撑苏州工业园区城市交通发展决策工作。

Integrating multi-source heterogeneous big data related to transportation and continuously promoting the analysis of annual transportation demand characteristics is an important work to improve the ability of transportation digital governance.Based on three consecutive years of research work on traffic and travel characteristics in Suzhou Industrial Park,a work system for constructing multi-source data fusion analysis has been formed,17 types of multi-source heterogeneous databases have been established,a comprehensive feature analysis indicator system has been formed,and the multi-source data fusion analysis algorithm has been improved.For three consecutive years,from the perspective of the Yangtze River Delta region,metropolitan area,and metropolitan area,research has been conducted on the changes in the population,job,residence,and travel characteristics of Suzhou Industrial Park under the epidemic situation,as well as the changes in regional intercity travel demand and comprehensive transportation hub travel demand characteristics,in order to timely respond to and support the urban transportation development decision-making work of Suzhou Industrial Park.