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Predicting Freeway Work Zone Capacity Distribution Based on Logistic Speed-Density Models

Authors :
Chaoru Lu
Jing Dong
Anuj Sharma
Tingting Huang
Skylar Knickerbocker
Source :
Journal of Advanced Transportation, Vol 2018 (2018)
Publication Year :
2018
Publisher :
Wiley, 2018.

Abstract

Speed-volume-density relationship and capacity are key elements in modelling traffic operations, designing roadways, and evaluating facility performance. This paper uses a modified five-parameter logistic model to describe the speed-density relationship. The calibrated speed-density models show that the stop-and-go speed (Vb) and shape parameters (θ1 and θ2) are similar for work zones and the nonwork zone site. Accordingly, an operational capacity prediction method is proposed. To demonstrate the effectiveness of the proposed method, the predicted operational capacities are compared with the field data, Highway Capacity Manual method, the output of WorkZoneQ software, and the ensemble tree approach under different work zone scenarios. Furthermore, a lifetime distribution prediction framework for stochastic capacity of work zones is proposed. The predicted lifetime distribution can well capture the tendency of the observed work zone capacities.

Details

Language :
English
ISSN :
01976729 and 20423195
Volume :
2018
Database :
Directory of Open Access Journals
Journal :
Journal of Advanced Transportation
Publication Type :
Academic Journal
Accession number :
edsdoj.5b667680df74b368ba5db311fe1df19
Document Type :
article
Full Text :
https://doi.org/10.1155/2018/9614501