基于群智感知技术的车联网路径优化问题研究

Research on Path Optimization of Internet of Vehicle Based on Crowd Sensing Technology

无线网络、云计算以及智能终端等研究推进了车联网(Internet Of Vehicle,IOV)应用的发展,如在车辆防盗、定位、紧急救援等方面,而群智感知技术为车联网的应用提供了精确、实时的兴趣数据,为解决路径选择提供了数据基础。论文首先分析介绍了IOV的关键技术,并且回顾了传统的用于解决路径选择的两类流量模型—车辆到基站(V2I,Vehicle ToInfrastructure)以及车辆到车辆(Vehicle To Vehicle,V2V),论文引入了新的感知节点—人,利用基于人自身的群智感知数据,动态地创建路由选择过程,并通过试验对策略进行验证,结论证明本策略在实验环境下降低实际交通过程中的拥塞问题,最后提出了可靠性较高的交通预测。

The research of wireless network, cloud computing and intelligent terminal to promote the development of the application of Internet of Vehicle （IOV）, such as in vehicle anti-theft, positioning, emergency rescue, however the application of the crowd sensing technology have provided accurate, interesting data in real time for IOV, which provides the basic data for the solu- tion the key technology of IOV is analyzed firstly and the traditional traffic models for two vehicles to solve the flow model of the Vehicle To Infrastructure （V2I） and vehicle to vehicle （V2V） are reviewed, a new perception node-person is also introduced, using crowd sourcing data based on their own, a dynamic routing process is created, and through the test the conclusion that the strategies to reduce the actual traffic congestion problem in the process of the experimental environment is validated, and finally the reliability high traffic forecast is put forward.