contributor author | Liuhui Zhao; Steven I. Chien; Bo Du | |
date accessioned | 2019-03-10T11:54:36Z | |
date available | 2019-03-10T11:54:36Z | |
date issued | 2019 | |
identifier other | JTEPBS.0000202.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4254475 | |
description abstract | Work zones have become the second largest contributor to the nonrecurring delay disruptions of traffic on US highways. The development of a sound model to minimize the total cost (i.e., road user cost and agency cost) by implementing effective traffic management strategies (i.e., traffic diversion or shoulder use) is desirable. The objective of this study was to optimize work-zone schedules and associated characteristics (e.g., maintenance crew, work-zone lengths, and diversion rates) that yield the minimum total cost. Floating car data enable traffic engineers and planners to obtain accurate and reliable traffic measures, such as speed, travel time, and delay. By considering prevailing road and time-varying traffic conditions, the proposed model evaluated the efficiency and effectiveness of traffic management strategies for freeway work zones. A case study was conducted in which the developed model was applied to optimize the work schedule for a road maintenance project on Interstate 80 (I-80) in New Jersey, in which the relationships among the decision variables and model parameters were explored. The findings of this study can assist traffic management decision making to mitigate congestion caused by freeway work zones. | |
publisher | American Society of Civil Engineers | |
title | Optimizing Work-Zone Schedule with Floating Car Data Considering Traffic Diversion and Managed Lanes | |
type | Journal Paper | |
journal volume | 145 | |
journal issue | 1 | |
journal title | Journal of Transportation Engineering, Part A: Systems | |
identifier doi | 10.1061/JTEPBS.0000202 | |
page | 04018076 | |
tree | Journal of Transportation Engineering, Part A: Systems:;2019:;Volume ( 145 ):;issue: 001 | |
contenttype | Fulltext | |