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contributor authorMahmoud Pourmehrab
contributor authorPatrick Emami
contributor authorMarilo Martin-Gasulla
contributor authorJabari Wilson
contributor authorLily Elefteriadou
contributor authorSanjay Ranka
date accessioned2022-01-30T21:24:06Z
date available2022-01-30T21:24:06Z
date issued9/1/2020 12:00:00 AM
identifier otherJTEPBS.0000409.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4268136
description abstractSignal control devices have been continuously evolving to make green assignments more responsive to traffic. Recent advances in connected and automated vehicles (CAVs) provide new opportunities to achieve higher performance levels for signalized intersections through an increased coordination level between vehicles and control devices. This study compares two state-of-the-art intersection management algorithms (IMAs) for CAVs and conventional vehicles (CNVs) to an actuated signal control system (ASCS). The two IMAs, the intelligent intersection control algorithm (IICA) and hybrid autonomous intersection management (H-AIM), are designed to enhance the efficiency of intersections by leveraging vehicle automation and connectivity. Our results show that the performance of both IICA and H-AIM improves as the CAV penetration rate increases. H-AIM attains lower average travel times than the state-of-the-practice ASCS only at a CAV penetration rate of 90% and greater. IICA, which jointly optimizes signal phase and timing (SPaT) and CAV trajectories, achieves the best average travel times and throughput for a wide range of CAV ratios. H-AIM yields lower average travel time and higher throughput compared to IICA at penetration rates close to 100%.
publisherASCE
titleSignalized Intersection Performance with Automated and Conventional Vehicles: A Comparative Study
typeJournal Paper
journal volume146
journal issue9
journal titleJournal of Transportation Engineering, Part A: Systems
identifier doi10.1061/JTEPBS.0000409
page9
treeJournal of Transportation Engineering, Part A: Systems:;2020:;Volume ( 146 ):;issue: 009
contenttypeFulltext


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