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...
保存先:
| 主要な著者: | , , , |
|---|---|
| その他の著者: | |
| フォーマット: | Conference paper |
| 出版事項: |
2023
|
| 主題: | |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
| 要約: | 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. |
|---|