کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
311637 534028 2008 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Real-time freeway traffic state estimation based on extended Kalman filter: Adaptive capabilities and real data testing
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
Real-time freeway traffic state estimation based on extended Kalman filter: Adaptive capabilities and real data testing
چکیده انگلیسی

This paper reports on real data testing of a real-time freeway traffic state estimator, with a particular focus on its adaptive capabilities. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic macroscopic traffic flow modeling and extended Kalman filtering. One major innovative feature of the traffic state estimator is the online joint estimation of important model parameters (free speed, critical density, and capacity) and traffic flow variables (flows, mean speeds, and densities), which leads to three significant advantages of the estimator: (1) avoidance of prior model calibration; (2) automatic adaptation to changing external conditions (e.g. weather and lighting conditions, traffic composition, control measures); (3) enabling of incident alarms. These three advantages are demonstrated via suitable real data testing. The achieved testing results are satisfactory and promising for subsequent applications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part A: Policy and Practice - Volume 42, Issue 10, December 2008, Pages 1340–1358
نویسندگان
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