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Simple and fast trip generation for large scale traffic simulation

机译:简单快速的行程生成,可进行大规模交通模拟

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A large-scale traffic simulator with microscopic model requires trip generation for millions of vehicles. To achieve a realistic result, the trip generation should provide a variety of trips between pairs of locations from Origin-Destination (OD) table reflecting the choices of drivers. Shortest paths take long time to generate and often differ from the choices of drivers. We propose a simple and fast tree-based algorithm in this paper. Our algorithm mixes shortest path trees starting from some location nodes in each subarea of the OD table as preprocessing and then generates trips by probabilistically traversing the mixed shortest path trees. Experiments reveal that the tree-based algorithm runs much faster than the naive one. We also confirm that, under certain conditions on the granularity of the OD table, the results of simulation using trips generated by our algorithm do not differ much from traffic conditions observed in the real world.
机译:具有微观模型的大型交通模拟器需要生成数百万辆汽车的行程。为了获得切合实际的结果,行程生成应在起源-目的地(OD)表中的成对位置之间提供各种行程,以反映驾驶员的选择。最短的路径需要很长时间才能生成,并且通常与驱动程序的选择有所不同。在本文中,我们提出了一种简单而快速的基于树的算法。我们的算法将从OD表的每个子区域中的某些位置节点开始的最短路径树进行混合,作为预处理,然后通过概率遍历混合的最短路径树来生成行程。实验表明,基于树的算法比单纯的算法运行速度快得多。我们还确认,在OD表粒度的特定条件下,使用由我们的算法生成的行程的模拟结果与现实世界中观察到的交通状况相差不大。

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