时空大数据驱动的新型智慧城市交通规划决策支持框架

A Decision Support Framework for Transportation Planning in the New Smart City Driven by Spatiotemporal Big Data

时空大数据由于其人本、精细、海量等优点已经融入到我国城市交通规划的各个环节之中,然而仍然存在数据利用相对割裂、辅助决策逻辑不清等问题。针对这些问题,首先将我国新型智慧城市交通规划工作的需求归纳为重点关注城市居民出行需求、着重提升城市交通服务能力、全面构建城市交通复合网络3个方面,进而梳理了支撑交通规划的5种时空大数据的特征及应用方向,在此基础上提出面向3个需求的新型智慧城市交通规划决策支持框架,从交通需求精准预测、出行过程全面感知、综合网络系统分析3个层面阐述利用时空大数据支持新型智慧城市交通规划各环节的思路。决策支持框架总体上实用性较强,其中机动化出行方式相关数据的应用相较于慢行交通相关数据更成熟,而精确到居民个体层面的微观数据的采集技术与应用方法仍需进一步开发完善。

The spatiotemporal big data has been widely used for urban transportation planning in China because of its advantages such as human-based,refined,and massive.However,it has drawbacks including the relatively independent use of data,unclear logic of decision support,etc..This article firstly summarizes the new requirements of the intelligent urban transportation planning in China,that is,special focus on travel demands,the improvement of transportation service quality,and the construction of a comprehensive transportation network.Then,the characteristics and applications of five types of spatiotemporal data supporting transportation planning are reviewed.A decision support framework for intelligent transportation planning is proposed to meet three kinds of requirements,including precise prediction of transportation demands,comprehensive traffic chain monitoring,and integrated network analysis.In general,this decision support framework is very useful.At the macro-scale,there have been more and more applications of the motorized travel data,while at the micro-scale,the collection and applications of non-motorized travel data still need to be improved.