基于粒计算的智能交通系统信息融合与共享研究

项目名称： 基于粒计算的智能交通系统信息融合与共享研究

项目编号： No.61473108

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 自动化技术、计算机技术

项目作者： 僧德文

作者单位： 杭州电子科技大学

项目金额： 70万元

中文摘要： 智能交通系统的建设在当前智慧城市浪潮中占有至关重要的地位。要想充分发挥智能交通系统的作用，需具备两大条件：充足的交通数据和有效的数据分析手段。随着各种数据采集设备的使用，交通数据从量到质都有了很大的提升，为有效解决交通问题提供了可能。多源、异构、模糊、不确定交通数据的融合与共享，是当前智能交通系统研究与应用的重点与难点。粒计算对海量、模糊、不确定、不完整信息的分析和处理表现出独特的优势，基于粒计算的交通信息融合尚缺乏完整的理论体系和实践案例。本项目对交通信息粒计算理论进行研究，构建交通信息融合的粒计算模型、框架及实施方案，提出基于粒计算理论的不确定信息约简算法、交通流预测及拥堵识别算法，为处理交通系统中复杂不确定性决策问题提供新的思路和方法；构建基于交通信息云的智能交通系统架构,使智能交通系统从封闭的静态演进系统转变为开放的动态演进系统。因此，本项目的研究具有重要的理论价值和社会意义。

中文关键词： 智能交通；数据挖掘；信息融合；数据融合

英文摘要： The construction of Intelligent Transportation Systems (ITS) occupies a crucial position in the current wave of smart city. Effective and efficiency ITS needs two important conditions: plenty of traffic data and effective means of data analysis. With the use of a variety of data acquisition equipments, traffic data from quantity to quality has been greatly improved, which may provide effective solutions for the traffic problems. Multi-source, heterogeneous, vague, uncertain traffic data fusion and sharing is the focus and difficulty of current research and application of ITS. The granular computing in the information analysis and processing of massive, vague, uncertain and incomplete data demonstrates a unique advantage. Traffic information fusion based on granular computing is still a lack of a complete theoretical system and practical examples. We will study the on traffic information granular computing theory and build traffic information fusion model, framework and implementation program based on granular computing. In our research, we will raise uncertainty reduction algorithms, traffic flow forecasting and congestion recognition algorithms based on granular computing theory, which will provide new ideas and methods to deal with the transport system in the complex decision making under uncertainty problems. Our project will build ITS architecture based on traffic information cloud, which will make ITS from closed static evolution system into open dynamic evolution system. Therefore, our research has important theoretical value and social significance.

英文关键词： intelligent transportation systems;data mining;Information fusion;data fusion