This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forec...This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forecast of transportation nodes impendence and travel time on network links. Forecasting period is two hours and the estimation is based on historical data and real time data on traffic conditions. Travel time estimation combines multivariate regression, principal component analysis, KNN （k-nearest neighbours）, cross validation and EWMA （exponentially weighted moving average） methods. When comparing estimation methodologies, relevantly better results were achieved by KNN method than with EWMA method. This is true for every time interval considered except for evening time interval when signalized arterial roads were uncongested.展开更多
Process of optimizing coordinated control is divided into two stages. At the first stage, the study improves a robust optimal control model of single-point intersection to optimize cycle and split. At the second stage...Process of optimizing coordinated control is divided into two stages. At the first stage, the study improves a robust optimal control model of single-point intersection to optimize cycle and split. At the second stage, the study combines all links with intersections of arterial road as a complete system, and applies cell transmission model to simulate traffic flow on urban signalized arterial road. We propose a coordinated control model based on the platform to optimize offset between adjacent intersections. Genetic algorithm is executed by MATLAB to solve the model. The performance evaluations show that the model not only effectively reduces average delay and stopping rate of vehicles on arterial road and largely enhances traffic capacity of arterial road, but also lowers the sensitivity of signal control for flow fluctuations.展开更多
文摘This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forecast of transportation nodes impendence and travel time on network links. Forecasting period is two hours and the estimation is based on historical data and real time data on traffic conditions. Travel time estimation combines multivariate regression, principal component analysis, KNN （k-nearest neighbours）, cross validation and EWMA （exponentially weighted moving average） methods. When comparing estimation methodologies, relevantly better results were achieved by KNN method than with EWMA method. This is true for every time interval considered except for evening time interval when signalized arterial roads were uncongested.
基金supported by the National Natural Science Foundation of China(No.61174175)the Science & Technology Development Plan of Shandong Province(No.2011GGX10504)+4 种基金the Science Foundation of Shandong Jiaotong University(No.Z201111)the Natural Science Foundation of Shandong Province(No.ZR2009GM032)the Independent Innovation Foundation of Shandong University(No.2009TS046)the Natural Science Foundation of Shandong Province(No.ZR2010FM036)the Science & Technology Projects of Higher Education of Shangdong Province(No. J09LG55)
文摘Process of optimizing coordinated control is divided into two stages. At the first stage, the study improves a robust optimal control model of single-point intersection to optimize cycle and split. At the second stage, the study combines all links with intersections of arterial road as a complete system, and applies cell transmission model to simulate traffic flow on urban signalized arterial road. We propose a coordinated control model based on the platform to optimize offset between adjacent intersections. Genetic algorithm is executed by MATLAB to solve the model. The performance evaluations show that the model not only effectively reduces average delay and stopping rate of vehicles on arterial road and largely enhances traffic capacity of arterial road, but also lowers the sensitivity of signal control for flow fluctuations.
