Welcome to the National Transport Library Catalogue

Normal view MARC view

Experiment to Improve Estimation of Vehicle Queue Length at Metered On-Ramps Wu, Jingcheng ; Jin, Xia ; Horowitz, Alan J ; Gong, Daqing

By: Contributor(s): Series: ; 2099Publication details: Washington DC Transportation Research Record: Journal of the Transportation Research Board, 2009Description: s. 30-38ISBN:
  • 9780309126151
Subject(s): Bibl.nr: VTI P8167:2099Location: Abstract: Two types of algorithms for on-ramp queue estimation are discussed: a Kalman filter and a conservation model. A volume-balancing ratio is introduced to both models to account for unavoidable detector miscounting behavior. Estimation results are compared with queue data observed in the field. The volume-balancing ratio improves both models. Although the conservation model may provide more accurate prediction with balanced volumes, the Kalman filter tends to provide better estimation when the volume-balancing ratio deviates from 1. Generally the Kalman filter provides a better prediction, but the conservation model is simpler to implement. Attempts to improve the Kalman filter further are also explored.
Item type: Reports, conferences, monographs
Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Statens väg- och transportforskningsinstitut Available

Two types of algorithms for on-ramp queue estimation are discussed: a Kalman filter and a conservation model. A volume-balancing ratio is introduced to both models to account for unavoidable detector miscounting behavior. Estimation results are compared with queue data observed in the field. The volume-balancing ratio improves both models. Although the conservation model may provide more accurate prediction with balanced volumes, the Kalman filter tends to provide better estimation when the volume-balancing ratio deviates from 1. Generally the Kalman filter provides a better prediction, but the conservation model is simpler to implement. Attempts to improve the Kalman filter further are also explored.