物联网环境下的城市道路交通事件自动检测与交通诱导

Besed on the indepth analysis on the characteristics of urban traffic flow and traffic incident, and under the enviornment of intellidrive, we study the techniques of multiple information perception and data fusion of the urban transportation system, the methods of traffic state estimation, the algorithm and models of automatic arterial incident detection, the mechanism of traffic route guidance message to travel behavior, multi-mode and personalized methods of urban traffic guidance, which is face to low carbon style. Through the above research, we want to develop the techniques and methods of traffic information collection and data fusion, and to exploit the system of urban traffic state estimation, incident detection and intelligent traffic guidance based on the IntelliDrive platform in order to support the active operation and intelligent management for the urban traffic management departments. The research results will have an important theoretical significance and application prospects on relieving traffic congestion caused by traffic incident in China's large and medium cities, promoting the urban traffic resource used reasonably and balanced, improving the urban roads' safety level, improving comprehensively transportation environment. Expected research results include academic papers, invention patent, model, system software, and research report.

深入剖析我国城市交通流和交通事件的特性，研究物联网环境下的城市交通系统的多元信息感知与数据融合技术、城市道路交通事件自动检测算法和模型、交通诱导信息对出行行为的作用机理、面向低碳的多模式个性化的城市交通诱导方法。通过上述研究，发展交通信息采集与融合的技术和方法，开发基于物联网平台的城市交通事件检测和智能交通诱导系统，支持城市道路交通管理部门的主动交通运营和智能管理。研究成果对缓解我国大中城市由交通事件引发的交通拥堵问题，促进城市交通资源合理均衡使用、提高城市道路安全水平、全面改善交通运输环境具有重要的理论意义与应用前景。 预期研究成果包括学术论文、发明专利、软件著作权、模型、系统软件、研究报告。

交通事件检测和交通诱导是用于解决交通问题的两种重要方式。基于对物联网环境下城市交通流和交通事件特性的深入剖析，本课题研究了物联网环境下城市交通系统多元信息感知与数据融合技术、城市道路交通事件自动检测算法和模型、交通诱导信息对出行行为的作用机理和多模式个性化城市交通诱导方法。通过上述研究，发展交通信息采集与融合的技术和方法，开发基于物联网平台的城市交通事件检测和智能交通诱导模型。该研究成果对缓解我国大中城市由交通事件引发的交通拥堵问题，促进城市交通资源合理均衡使用，提高城市道路安全水平，全面改善交通运输环境具有重要的理论意义与应用前景。