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

Joint Authors

Dong, Jing
Lu, Chaoru
Sharma, Anuj
Huang, Tingting
Knickerbocker, Skylar

Source

Journal of Advanced Transportation

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-11-01

Country of Publication

Egypt

No. of Pages

15

Main Subjects

Civil Engineering

Abstract EN

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.

American Psychological Association (APA)

Lu, Chaoru& Dong, Jing& Sharma, Anuj& Huang, Tingting& Knickerbocker, Skylar. 2018. Predicting Freeway Work Zone Capacity Distribution Based on Logistic Speed-Density Models. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1181899

Modern Language Association (MLA)

Lu, Chaoru…[et al.]. Predicting Freeway Work Zone Capacity Distribution Based on Logistic Speed-Density Models. Journal of Advanced Transportation No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1181899

American Medical Association (AMA)

Lu, Chaoru& Dong, Jing& Sharma, Anuj& Huang, Tingting& Knickerbocker, Skylar. Predicting Freeway Work Zone Capacity Distribution Based on Logistic Speed-Density Models. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1181899

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1181899