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Integrated mainline and ramp signal control for expressway on-ramp bottleneck with unequal lane-setting
Ramp metering is a major measure to reduce traffic congestion and prevent traffic breakdown at on-ramp bottlenecks. However, its efficiency is often limited by the excessive traffic demands on either the mainline or the on-ramp. Meanwhile, unequal lane-setting, in which the number of mainline lanes...
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Published in: | Journal of intelligent transportation systems 2021-12, Vol.26 (1), p.100-115 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Ramp metering is a major measure to reduce traffic congestion and prevent traffic breakdown at on-ramp bottlenecks. However, its efficiency is often limited by the excessive traffic demands on either the mainline or the on-ramp. Meanwhile, unequal lane-setting, in which the number of mainline lanes is more than on-ramp, is a common infrastructure setup in urban expressway system. In this paper, a novel Travel time balanced Mainline and Ramp integrated Control strategy (T-MRC) is proposed for unequal lane-setting on-ramp bottlenecks, which follows the feedback control framework. The control goal is to maximize the traffic efficiency, while in view of the typical early-onset phenomenon, productivity (efficiency index) is selected to replace the conventional outflow as the optimization objective. On this basis, the balance of travel time in different types of lanes (controlled on-ramp, controlled, and uncontrolled mainline lanes) is considered, and two regulators are used in the green time allocation algorithm. A high-precision microscopic simulation model in Shanghai is set up, and five control strategy scenarios are compared. Results indicate that the T-MRC strategy outperforms all others that the productivity is improved dramatically (>85%) and the vehicle total delay (VTD) of the system is reduced significantly (>30%) compared to no-control scenario. |
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ISSN: | 1547-2450 1547-2442 |
DOI: | 10.1080/15472450.2020.1797502 |