Date of Award
Spring 2015
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Civil & Environmental Engineering
Program/Concentration
Civil Engineering
Committee Director
Mecit Cetin
Committee Member
Filmon Habtemichael
Committee Member
Rajesh Paleti
Call Number for Print
Special Collections LD4331.E542 A45 2015
Abstract
The Hampton Roads Bridge Tunnel (HRBT) is a major link for activity in Hampton Roads. The eastbound direction also suffers from congestion during both morning and peak hours. During these periods of congestion, the flow rate varies in regards to the location of the congestion. This study focuses on investigating driver behavior during these different conditions and briefly investigates the cost of delay due to the different capacities. To accomplish this, per vehicle record data (PVR) is used. This data, collected at the exit of the tunnel, provides information on arrival time, speed, lane location, vehicle class, and time headway. Using this data allows an in-depth look at the differences between the two lanes and considers whether heavy goods vehicles (HGV) have a significant impact on the flow. Taking the inverse of the average headway in the study times to obtain flow shows that, in Lane 2, the flow when congestion is prior to the tunnel entrance is 19% higher than when the congestion is within the tunnel itself. In Lane 1, the difference is 16%. Over the study period, the percentage of HGV was lower during the morning peak when congestion was outside the tunnel.
This report concluded that it is not the presence of HGV that results in the location change of congestion and the resulting drop in flow rate. This thesis also determined that there is a difference of around 12,000 vehicle hours of delay, producing a delay cost increase of $375,000 annually. Further study into the feasibility of Active Traffic Management {ATM) applications could identify methods to control the location of the congestion and prevent congestion from occurring within the tunnel. This would increase the queue discharge flow rate and overall capacity.
Rights
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DOI
10.25777/efy8-1t62
Recommended Citation
Allen, Michelle L..
"Analyzing Driver Behavior and Traffic Flow Breakdowns at the Hampton Roads Bridge Tunnel"
(2015). Master of Science (MS), Thesis, Civil & Environmental Engineering, Old Dominion University, DOI: 10.25777/efy8-1t62
https://digitalcommons.odu.edu/cee_etds/193