Large-Scale Multi-Agent Simulations for Transportation Applications
Large-Scale Multi-Agent Simulations for Transportation Applications
复制标题
交通应用的大规模多智能体模拟
DOI：
10.1080/15472450490523892
复制
发表时间：
2004
影响因子：
3.6
通讯作者：
B. Raney
中科院分区：
文献类型：
--
作者：
M. Balmer;K. Nagel;B. Raney
在包括智能交通系统（ITS）在内的许多交通仿真应用中，个体出行者的行为响应是非常重要的。这意味着直接模拟个人旅行者可能是有用的。这样一个由许多智能粒子（=代理）组成的微观模拟是多代理模拟的一个例子。对于ITS应用程序，模拟拥有1000万或更多旅行者的大都市区将是有用的。事实上，当使用并行计算和有效的实现时，这种规模的运输系统的多智能体模拟是可行的，计算速度比真实的时间快300倍。也可以有效地实现日常基于代理的学习的模拟，并且可以使这种实现模块化并且本质上是“即插即用”。不幸的是，这些技术不能立即应用于日内重新规划，这对ITS至关重要。替代技术，允许在一天内重新规划也为大的情况下，进行了讨论。
In many transportation simulation applications including intelligent transportation systems (ITS), behavioral responses of individual travelers are important. This implies that simulating individual travelers directly may be useful. Such a microscopic simulation, consisting of many intelligent particles (= agents), is an example of a multi-agent simulation. For ITS applications, it would be useful to simulate large metropolitan areas, with ten million travelers or more. Indeed, when using parallel computing and efficient implementations, multi-agent simulations of transportation systems of that size are feasible, with computational speeds of up to 300 times faster than real time. It is also possible to efficiently implement the simulation of day-to-day agent-based learning, and it is possible to make this implementation modular and essentially “plug-and-play.” Unfortunately, these techniques are not immediately applicable for within-day replanning, which would be paramount for ITS. Alternative techniques, which allow within-day replanning also for large scenarios, are discussed.
影响因子：
2.4
作者：
BANDO, M;HASEBE, K;SUGIYAMA, Y
通讯作者：
SUGIYAMA, Y