车辆自组织网络(VANET)是构建现代交通"人-车-路"协同信息平台的关键，可以通过车车/车路通信实现动态交通信息的感知、共享和有效利用。但是在城市交通环境下，如何设计以车辆为主体的分布式交通态势感知和高效信息传输机制成为新的挑战性课题。本项目以满足用户对交通态势信息的需求为核心，围绕VANET对复杂动态环境的认知性和信息传输的适变性两个基本问题，探索实时多尺度交通态势估计的有效解决方案，发展面向用户交通态势信息需求的适变传输技术，重点开展三方面研究:1.构建车辆"情境"模型，基于多源信息融合和压缩感知技术，研究复杂动态环境下VANET的合作感知算法;2.基于情境构建用户信息需求量化模型和信息效用模型，开展用户信息需求量化与分析;3.提出信息需求发布和响应策略，设计适变传输机制。本项目有望在基础理论和网络技术方面实现突破，为VANET如何在复杂交通环境中实现高效信息共享提出科学的解决方案。

Vehicular Ad Hoc Network (VANET) is vital for the information platform integrated with "Human-Vehicle-Road" cooperation. It can realize sensing, sharing and effective utilization of dynamic traffic information with V2V and V2I communication. However, it is a new challenge in urban traffic environment that how to design car-based distributed traffic sensing and efficient transmission mechanism. This project aims at meeting car users'demands on traffic information. In order to solve the two fundamental problems on cognition of complex dynamic environment and adaption of information transmission, we are to explore the real-time multi-scale traffic situation estimation, and to develop demand oriented adaptive transmission mechanism.The contents are as follows: 1. To build the context model for VANET, and to propose cooperative sensing based on the multi-sensor fusion and compressive sensing for complex and dynamic environment; 2. To present the context-aware quantitative model and utility model of users' information demands, and develop the quantification and analysis methods; 3. To design the demand release and response scheme, and propose adaptive transmission mechanism. This project is expected to achieve a breakthrough in the theory and networking technology. It is desired to provide an effective solution of VANET on how to achieve efficient information sharing in complex traffic environment.