A K-nearest neighbor （K-NN） based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways,...A K-nearest neighbor （K-NN） based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways, a specically designed database was developed via the processes including data filtering, wavelet analysis and clustering. The relativity based weighted Euclidean distance was used as the distance metric to identify the K groups of nearest data series. Then, a K-NN nonparametric regression model was built to predict the average travel speeds up to 6 min into the future. Several randomly selected travel speed data series, collected from the floating car data （FCD） system, were used to validate the model. The results indicate that using the FCD, the model can predict average travel speeds with an accuracy of above 90%, and hence is feasible and effective.展开更多
After introducing the principle of float car data (FCD), this paper gives the primary flow of pre-handing and map- matching of the FCD. After analyzing the percentage of coverage of FCD on the road network, large quan...After introducing the principle of float car data (FCD), this paper gives the primary flow of pre-handing and map- matching of the FCD. After analyzing the percentage of coverage of FCD on the road network, large quantity of heritage database of routing status is used to estimate the routing velocity when lack of FCD on parts road segments. Multi liner regression model is then put forwarded by considering the spatial correlativity among the road network, and some model parameters are deduced when time series is classified in day and week. Besides, error of velocity probability and error of status probability are achieved based on the result from field testing while the feasibility and reliability of the velocity estimation model is obtained as well. Finally, as a case study in Shanghai center area, the whole routing velocity in the road network is estimated and published in real time.展开更多
城市快速路的车速空间波动常被认为是事故风险的重要因素,但是车速空间波动很难通过传统的固定检测器来提取。为克服传统方法的不足,本文充分利用Floating Car Data(FCD)提取快速路路段的空间车速方差等道路运行指标,并在获取快速路特...城市快速路的车速空间波动常被认为是事故风险的重要因素,但是车速空间波动很难通过传统的固定检测器来提取。为克服传统方法的不足,本文充分利用Floating Car Data(FCD)提取快速路路段的空间车速方差等道路运行指标,并在获取快速路特征指标的基础上,分别以总事故频率、追尾事故频率和侧碰事故频率为因变量建立了负二项模型。模型结果发现空间车速方差、路段行程车速对三类模型的影响呈现一致关系:空间车速方法与三类事故频率呈正相关,说明利用车速空间波动来诊断城市快速路安全风险是可行和有价值的。此外还发现路段行程车速与三类事故频率呈负相关,路段内包含平曲线对事故总频率和追尾事故都有显著正相关,但对侧碰事故的相关性不显著;立交路段与侧碰事故频率相关性显著。展开更多
基金The Project of Research on Technologyand Devices for Traffic Guidance (Vehicle Navigation)System of Beijing Municipal Commission of Science and Technology(No H030630340320)the Project of Research on theIntelligence Traffic Information Platform of Beijing Education Committee
文摘A K-nearest neighbor （K-NN） based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways, a specically designed database was developed via the processes including data filtering, wavelet analysis and clustering. The relativity based weighted Euclidean distance was used as the distance metric to identify the K groups of nearest data series. Then, a K-NN nonparametric regression model was built to predict the average travel speeds up to 6 min into the future. Several randomly selected travel speed data series, collected from the floating car data （FCD） system, were used to validate the model. The results indicate that using the FCD, the model can predict average travel speeds with an accuracy of above 90%, and hence is feasible and effective.
文摘After introducing the principle of float car data (FCD), this paper gives the primary flow of pre-handing and map- matching of the FCD. After analyzing the percentage of coverage of FCD on the road network, large quantity of heritage database of routing status is used to estimate the routing velocity when lack of FCD on parts road segments. Multi liner regression model is then put forwarded by considering the spatial correlativity among the road network, and some model parameters are deduced when time series is classified in day and week. Besides, error of velocity probability and error of status probability are achieved based on the result from field testing while the feasibility and reliability of the velocity estimation model is obtained as well. Finally, as a case study in Shanghai center area, the whole routing velocity in the road network is estimated and published in real time.
文摘城市快速路的车速空间波动常被认为是事故风险的重要因素,但是车速空间波动很难通过传统的固定检测器来提取。为克服传统方法的不足,本文充分利用Floating Car Data(FCD)提取快速路路段的空间车速方差等道路运行指标,并在获取快速路特征指标的基础上,分别以总事故频率、追尾事故频率和侧碰事故频率为因变量建立了负二项模型。模型结果发现空间车速方差、路段行程车速对三类模型的影响呈现一致关系:空间车速方法与三类事故频率呈正相关,说明利用车速空间波动来诊断城市快速路安全风险是可行和有价值的。此外还发现路段行程车速与三类事故频率呈负相关,路段内包含平曲线对事故总频率和追尾事故都有显著正相关,但对侧碰事故的相关性不显著;立交路段与侧碰事故频率相关性显著。
