New traffic models considering complex geometries and data

考虑复杂几何形状和数据的新交通模型

• 批准号: 461365406
• 负责人: Professor Dr. Michael Herty
• 金额: --
• 依托单位: Lehrstuhl und Institut für Straßenwesen
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/461365406?language=en
• 关键词: New; traffic; models; considering; complex

The traditional approach of traffic safety analysis – based on historical accident data – is subject to the restriction that a sufficient number of accidents must have occurred in order to be able to identify accident black spots and take appropriate measures. The predictive possibilities of the traditional approach are therefore limited and should be extended by other possibilities such as model-based predictions or replaced by road safety analyses with safety indicators. Traffic modelling offers the possibility of predicting the number of accidents on a road section based on models. While traffic models of motorway sections are well advanced, models for more complex geometries (e.g. junctions), which are more risky due to changed driving behaviour, are not yet available to the same extent.The goal of this project is therefore to transfer the previous results and data on traffic behaviour on motorway sections to complex geometries of motorway junctions. The newly developed models and numerical methods will be combined with the results obtained to date and supplemented by stochastic approaches (uncertainty) in order to obtain a multi-scale stochastic traffic forecast model for the entire motorway. In addition, the safety indicators will be transferred to weaving traffic and complemented by uncertain parameters.

传统的交通安全分析方法-基于历史事故数据-受到一个限制，即必须发生足够数量的事故，才能确定事故黑点并采取适当措施。因此，传统方法的预测可能性是有限的，应通过其他可能性，如基于模型的预测加以扩展，或由具有安全指标的道路安全分析取代。交通建模提供了基于模型预测路段上事故数量的可能性。虽然高速公路路段的交通模型已经非常先进，但由于驾驶行为的改变，更复杂的几何形状（例如交叉口）的模型还没有达到同样的程度。因此，本项目的目标是将以前关于高速公路路段交通行为的结果和数据转移到高速公路交叉口的复杂几何形状。新开发的模型和数值方法将与迄今为止获得的结果相结合，并辅以随机方法（不确定性），以获得整个高速公路的多尺度随机交通预测模型。此外，安全指标将被转移到交织交通，并补充不确定的参数。