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LOGAN#039;s Run: Lane optimisation using genetic algorithms based on NSGA-II

机译:LOGAN的Run:使用基于NSGA-II的遗传算法进行车道优化

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Whilst bus lanes are an important tool to ensure bus time reliability their presence can be detrimental to urban traffic. In this paper a Non-dominated Sorting Genetic Algorithm (NSGA-II) has been adopted to study the effect of bus lanes on urban traffic in terms of location and time of operation. Due to the complex nature of this problem traditional search would not be feasible. An artificial arterial route has been modelled from real data to evaluate candidate solutions. The results confirm this methodology for the purpose of studying and identifying bus lane locations and times of operation. Additionally it is shown that bus lanes can exist on an arterial link without exclusively occupying a continuous lane for large periods of time. Furthermore results indicate a use for this methodology over a larger scale and potential near real-time operation.
机译:尽管公交专用道是确保公交时间可靠性的重要工具,但公交专用道的存在可能会对城市交通造成不利影响。本文采用非主导排序遗传算法(NSGA-II)来研究公交专用道对城市交通的影响,包括位置和运营时间。由于此问题的复杂性质,传统搜索将不可行。人造动脉路线已从真实数据建模,以评估候选解决方案。结果证实了这种方法论的目的,是为了研究和确定公交专用道的位置和运行时间。另外,显示了公交专用道可以存在于动脉链路上,而不会长时间专门占据连续的专用道。此外,结果表明该方法已在更大规模的范围内使用,并且可能会接近实时运行。

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