大数据在交通规划和管理中实践探索——以广州为例

Exploration of Big Data in Transportation Planning and Management: Guangzhou as an Example

大数据条件下的交通系统分析不是将大数据技术简单套用或者移植到交通领域,而是将大数据技术融入到交通体系中,将数据挖掘成为有效信息,从价值信息中提炼特征,从特征变化中发现规律,从特征规律中提出措施.首先,梳理大数据的特征、发展阶段以及交通大数据3大类别;其次,分析手机数据、IC卡数据、GPS数据和道路卡口数据的基本原理和应用领域,以广州市为例进行实证研究,并从单类数据深入挖掘、数据质量评估和验证以及多元数据融合等提出研究3点展望,为下一步城市交通大数据的应用提供参考.

In recent years,with the development of new technologies such as big data,cloud computing,internet,artificial intelligence,the research and application of transportation big data has been become the focus.Big data has been gradually applied to transportation planning,policy development and industry management.However,the traffic system analysis in the era of big data is not simply applying or transplanting big data technology into the transportation system,making data mining effective information,and extracting features from value information.Meanwhile,the pattern is found in the change of characteristics,and the measures are proposed.First,the characteristics and development stage of big data and categories in the transport sector were explored.Secondly,basic principles and application areas of mobile phone data,IC card data,GPS data and road bayonet data were analyzed.Finally,some cases of Guangzhou city were analyzed,and three research perspectives are proposed from single-class data mining,data quality assessment and validation,and multivariate data fusion,the purpose is to provide a reference for the application of urban traffic big data.