Mitigating the impact of light rail on urban traffic networks using mixed-integer linear programming

As urban traffic congestion is on the increase worldwide, many cities are increasingly looking to inexpensive public transit options such as light rail that operate at street-level and require coordination with conventional traffic networks and signal control. A major concern in light rail installat...

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Bibliographic Details
Published in:	IET intelligent transport systems Vol. 14; no. 6; pp. 523 - 533
Main Authors:	Guilliard, Iain, Trevizan, Felipe, Sanner, Scott
Format:	Journal Article
Language:	English
Published:	The Institution of Engineering and Technology 01.06.2020
Subjects:	58.7% versus optimal fixed‐time control adaptive signal control method authors study conventional traffic networks conventional vehicle traffic capacity fixed‐time control schedules increase worldwide inexpensive public transit options integer programming light rail constraints light rail installation light rail presence light rail schedule constraints linear programming mixed‐integer linear programming framework optimisation optimised traffic signal control Research Article resulting decrease road traffic road traffic control scheduling street‐level traffic control traffic engineering computing urban traffic congestion urban traffic networks urban traffic congestion integer programming road traffic control linear programming 58.7% versus optimal fixed-time control street-level increase worldwide optimisation traffic control optimised traffic signal control scheduling urban traffic networks resulting decrease authors study road traffic light rail presence conventional traffic networks adaptive signal control method mixed-integer linear programming framework traffic engineering computing light rail constraints inexpensive public transit options conventional vehicle traffic capacity light rail installation fixed-time control schedules light rail schedule constraints
ISSN:	1751-956X, 1751-9578
Online Access:	Get full text
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