基于蒙特卡洛马尔可夫链的无信号t型交叉口交通流模拟

Wong Xin Ci, Syed Khaleel Ahmed, F. Zulkifli, A. Ramasamy
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引用次数: 6

摘要

拥挤的交通状况是现代生活的日常烦恼。减少这些拥堵将会带来更少的压力和更健康的通勤。在获得缓解方案之前,需要对问题进行理解和分析。即使是中等复杂的系统,也很难得到基于概率论和排队系统的精确解。此外,对于复杂系统,对系统行为的洞察不是很清楚。本文将基于蒙特卡罗马尔可夫链的仿真技术应用于无信号t型交叉口。值得注意的是,“少量”的模拟足以理解系统的行为。这种简单而强大的方法提供了多种选择,因此非常吸引人。该方法也可以很容易地扩展到其他类型的系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic flow simulation at an unsignalized T-junction using Monte Carlo Markov Chains
Congested traffic conditions are a daily nuisance of modern life. Reduction of these congestions will lead to a less stressful and healthier commute. Before mitigating solutions can be obtained, the problem needs to be understood and analyzed. Exact solutions based on probability theory and queuing systems are difficult to obtain for even moderately complex systems. Further for complex systems, insight into system behaviour is not very clear. In this paper, a simulation technique based on the Monte Carlo Markov Chain is applied to an unsignalized T-junction. It is noticed that a “small” number of simulations are sufficient to understand the behavior of the system. This simple yet powerful method offers several options and hence, is very appealing. The method can be easily extended to other types of systems as well.
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