突发拥堵状况下动态交通流信息预测研究  

Research on Dynamic Traffic Flow Information Prediction Under Sud⁃den Congestion

作　　者：宋静静 SONG Jingjing(Henan Communications Planning&Design Institute Co.,Ltd.,Zhengzhou 450000,China)

机构地区：[1]河南省交通规划设计研究院股份有限公司,河南郑州450000

出　　处：《河南科技》2024年第12期19-23,共5页Henan Science and Technology

摘　　要：【目的】建立能够在突发拥堵状况下准确预测交通流的模型,以便更好应对突发交通拥堵情况。【方法】采用混沌理论推导交通流的最小预测周期,并基于此,提出了CDNN预测模型。以APE、MAPE及RMSE为评价指标,结合公路案例对比分析了CDNN、FCM、DLA及NN模型的预测稳定性和精确度,归纳各类预测模型特性及机理。【结果】动态交通流预测周期应不小于80 s;CDNN模型预测性能在突发事件发生时刻最好,无突发事件时次之,突发事件持续时期相对较差;CDNN模型预测性能相较于FCM、DLA及NN模型更优。【结论】CDNN预测模型为突发拥堵状况下的交通流预测提供了新的理论和实践途径,具有更佳的预测性能,凸显了其在应对突发交通情况中的潜在应用价值,对未来的交通管理和规划具有重要的指导意义。[Purposes]This paper aims to establish a model that can accurately predict traffic flow under sudden congestion conditions,so as to better cope with sudden traffic congestion.[Methods]The mini⁃mum prediction period of traffic flow is derived from chaos theory,and based on that,the CDNN predic⁃tion model is proposed.Taking APE,MAPE and RMSE as the evaluation indexes,the prediction stability and accuracy of the CDNN,FCM,DLA and NN models are analyzed in comparison with the highway cases,and the characteristics and mechanisms of the various types of prediction models are summarized.[Findings]Dynamic traffic flow prediction period should be not less than 80s;CDNN model prediction performance is the best at the moment of emergencies,followed by no emergencies,and the duration of emergencies is relatively poor;CDNN model prediction performance is better than that of FCM,DLA and NN model.[Conclusions]The CDNN prediction model provides a new theoretical and practical way for traffic flow prediction under unexpected congestion conditions with better prediction performance,high⁃lighting its potential application value in coping with unexpected traffic situations,which is of great sig⁃nificance for future traffic management and planning.

关 键 词：突发拥堵状况 交通流 动态预测 

分 类 号：U491[交通运输工程—交通运输规划与管理]