Simultaneous traffic count and ramp flow estimation for multilane freeways based on Markov models - 文章详情页

作者：

Ma, Yong (Ma, Yong.) | Zhang, Liguo (Zhang, Liguo.) (学者：张利国) | Zhang, Lu (Zhang, Lu.)

收录：

EI Scopus

摘要：

As　a　distributed　parameter　system,　traffic　flow　model　of　freeway　traffic　is　determined　by　the　traffic　state　on-road　and　boundary　flows　form　on-ramp　or　off-ramp　sections.　The　existing　studies　for　traffic　estimation　mainly　focus　on　the　traffic　parameter,　namely　density　(or　vehicles)　of　mainline　traffic.　In　this　paper,　Kalman　filtering　for　simultaneous　traffic　counts　and　off-ramp　flow　estimation　is　proposed　with　the　linearization　of　the　speed　density　observation　equation.　The　state-space　model　is　formulated　by　using　a　Markov　chain　to　describe　the　vehicles＇　lane-change　movements.　Numerical　studies　are　carried　out　to　investigate　the　performance　of　the　developed　approach.　©　2013　IEEE.

关键词：

Highway traffic control Kalman filters Markov processes Motor transportation State space methods Street traffic control

作者机构：

[ 1 ] [Ma, Yong]School of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Zhang, Liguo]School of Electronic and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 3 ] [Zhang, Lu]Beijing Traffic Management Bureau, Beijing 100037, China

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