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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Vydáno v:	IET intelligent transport systems Ročník 14; číslo 6; s. 523 - 533
Hlavní autoři:	Guilliard, Iain, Trevizan, Felipe, Sanner, Scott
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 01.06.2020
Témata:	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
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Popis
Shrnutí:	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 installation is whether enough commuters will switch to it to offset the additional constraints it places on traffic signal control and the resulting decrease in conventional vehicle traffic capacity. In this study, the authors study this problem and ways to mitigate it through a novel model of optimised traffic signal control subject to light rail schedule constraints solved in a mixed-integer linear programming (MILP) framework. The authors’ key results show that while this MILP approach provides a novel way to optimise fixed-time control schedules subject to light rail constraints, it also enables a novel optimised adaptive signal control method that virtually nullifies the impact of the light rail presence, reducing average delay times in microsimulations by up to 58.7% versus optimal fixed-time control.
ISSN:	1751-956X 1751-9578
DOI:	10.1049/iet-its.2019.0277