Real‐time coordination of connected vehicles at intersections using graphical mixed integer optimization

Abstract Management of connected vehicles at unsignalised intersections is a large‐scale complex problem with safety constraints and time‐varying unsolved variables, which is crucial but hard to solve online. A faster coordination system, however, not only benefits from smaller time granularity to f...

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Bibliographic Details
Main Authors: Qiang Ge, Qi Sun, Zhen Wang, Shengbo Eben Li, Ziqing Gu, Sifa Zheng, Lyuchao Liao
Format: Article
Language:English
Published: Wiley 2021-06-01
Series:IET Intelligent Transport Systems
Online Access:https://doi.org/10.1049/itr2.12061
Description
Summary:Abstract Management of connected vehicles at unsignalised intersections is a large‐scale complex problem with safety constraints and time‐varying unsolved variables, which is crucial but hard to solve online. A faster coordination system, however, not only benefits from smaller time granularity to find optimum, but also has more robustness towards a scenario with fast‐moving vehicle nodes. This paper proposes a real‐time coordination scheme consisting of three stages. (a) Target velocity optimisation: collision‐free passage is formulated as a mixed integer linear programming problem, each approaching lane corresponding to an independent variable; (b) vehicle subgraph extraction: a directed graph is built and pruned based on the optimisation result, determining a subgraph wherein vehicle nodes pass without redundant time slot; (c) velocity profile synchronisation: velocity profile of the selected vehicles is planned synchronously, respecting inter‐subgraph constraints. The main contribution of this study is to propose a fast hierarchical optimization‐based coordination method, of which the complexity is invariant with the traffic density. Simulation has verified the effectiveness of the scheme from both microscopic behaviour and statistical characteristics, reducing single‐step computation time to 0.02 s, and saving average driving delay by 59.83% compared to the benchmark method.
ISSN:1751-956X
1751-9578