一种应用协同导航技术的交通拥堵度计算与危险预测方法  

A Method for Computing Congestion Degree and Dangerous Prediction Using Cooperative Navigation Technology

作　　者：崔鹏雨 刘锐[1] 王方超 CUI Pengyu;LIU Rui;WANG Fangchao(Information Engineering University, Zhengzhou 450001, China)

机构地区：[1]信息工程大学,河南郑州450001

出　　处：《测绘科学技术学报》2021年第5期441-447,共7页Journal of Geomatics Science and Technology

摘　　要：多源数据融合下的多目标协同导航是提高目标导航定位精度和稳定性的有效途径。通过导航数据传感器的实时观测以及位置、速度和目标间测距值等协同信息的共享,基于相关模型实现了协同导航系统中交通拥堵度和交通危险性的预判。模拟实验结果表明,协同导航技术不仅能降低传感器部署成本,还能提高交通拥堵计算和危险性预判的效率。The multi-target collaborative navigation based on multi-source data fusion is an effective way to improve the accuracy and stability of target navigation and positioning.Through the real-time observation of navigation data sensors and the sharing of collaborative information such as position,speed,and ranging value between targets,the prediction of traffic congestion degree and traffic risk in the collaborative navigation system based on the relevant model is realized in the paper.The simulation results show that the collaborative navigation technology can not only reduce the sensor deployment cost,but also improve the efficiency of traffic congestion calculation and risk prediction.

关 键 词：协同导航技术 交通拥堵度 危险预判 精度分析 多源数据融合 

分 类 号：P228[天文地球—大地测量学与测量工程]