Massively parallelizable approach for evaluating signalized arterial performance using probe-based data
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2022-05-03
Authors
Poddar, Subhadipto
Chakraborty, Pranamesh
Sharma, Anuj
Knickerbocker, Skylar
Hawkins, Neal
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Sharma, Anuj
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Institute for Transportation
InTrans administers 14 centers and programs, and several other distinct research specialties, and a variety of technology transfer and professional education initiatives. More than 100 Iowa State University faculty and staff work at InTrans, and from 200 to 250 student assistants from several ISU departments conduct research while working closely with university faculty. InTrans began in 1983 as a technical assistance program for Iowa’s rural transportation agencies.
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Civil, Construction and Environmental EngineeringInstitute for Transportation
Abstract
Effective performance of arterial corridors is essential to community safety and vitality. Considering the dynamic nature of traffic demand, efficient management of these corridors require frequent updating of the traffic signal timings through various strategies. Agency resources for these activities are commonly scarce and are primarily by public complaints.
This study provides a workflow using probe-based data to measure and compare different segments on arterial corridors in terms of the traffic signal performance measures that can capture travel time dynamics across signalized intersections. The proposed methodology identifies a group of dynamic days followed by evaluation of travel rate based upon remaining non-dynamic days. Dynamic days represent the variability of traffic on a segment. Consequently, a corridor having high number of dynamic segments along with poor performance during normal days would be a candidate for adaptive control. Further, to handle the large-scale data source collected from city-wide or statewide traffic signals, the study adopts parallel computation-based strategy using MapReduce technique. A case study was conducted on 11 corridors within Des Moines, Iowa, to demonstrate the efficacy of the proposed approach, which identified two arterial corridors, Merle Hay Road and University Avenue, to be suitable for adaptive traffic signal control.
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This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Intelligent Transportation Systems: Technology, Planning, and Operations on 03 May 2022.
It is available online at DOI: 10.1080/15472450.2022.2069497.
Copyright 2022 Taylor and Francis.
Posted with permission.
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Wed Jan 01 00:00:00 UTC 2020