Development and Evaluation of Statistical and Machine-Learning Models for Queue-Length Estimation for Lane Closures in Freeway Work Zones-Reference-Cited by-同舟云学术

Development and Evaluation of Statistical and Machine-Learning Models for Queue-Length Estimation for Lane Closures in Freeway Work Zones

Author:

Biswas Pronab Kumar¹^ORCID,Khan Sakib Mahmud²^ORCID,Piratla Kalyan³,Chowdhury Mashrur⁴

Affiliation:

1. Master’s Student, Glenn Dept. of Civil Engineering, Clemson Univ., Clemson, SC 29634 (corresponding author). ORCID: .

2. Assistant Research Professor, Glenn Dept. of Civil Engineering, Clemson Univ., Clemson, SC 29634. ORCID: .

3. Liles Associate Professor, Glenn Dept. of Civil Engineering, Clemson Univ., Clemson, SC 29634.

4. Professor, Glenn Dept. of Civil Engineering, Clemson Univ., Clemson, SC 29634.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

Reference31 articles.

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1. Using Deep Neural Networks and Big Data to Predict Microscopic Travel Time in Work Zones;Transportation Research Record: Journal of the Transportation Research Board;2024-03-27