摘要
基于交通流的时空变化特征,提出交通状态的快速识别算法以及如何实现交通状态的跃迁转变。首先,依靠视频检测技术提取交通流参数,应用模糊理论构建交通状态的快速识别模型,实现了交通状态的快速识别、态势跟踪和动态预警。然后,通过模糊认知图分析交通状态之间的跃迁转变规律,建立交通状态的跃迁转变函数,实现了交通状态下一时刻的预测评估。最后,结合实例,验证了方法的可行性。
Based on the temporal and spatial variation characteristics of traffic flow,the traffic state rapid identification algorithms and how to realize the traffic state transitions shift were put forward.Firstly,relying on the video detection technology to extract traffic flow parameters,fuzzy theory was applied to build traffic state rapid identification model,realized the traffic state identification,trend tracking and dynamic warning.Then,through the fuzzy cognitive map analysis of transitions shift law between the traffic states,the traffic state transitions shift function was realized,and the next time forecast evaluation of the traffic state was established.Finally,combining with examples,the feasibility of the method was verified.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第S1期1-5,共5页
Journal of Central South University:Science and Technology
基金
国家自然基金专项资金资助项目(F030209)
关键词
交通工程
识别
跃迁转变
模糊理论
交通状态
traffic engineering
identification
transitions shift
fuzzy theory
traffic state
