Basic evaluation for simulation-based crash-risk-models - multiscale modelling regarding dynamic traffic flow states

基于模拟的碰撞风险模型的基本评估 - 关于动态交通流状态的多尺度建模

基本信息

批准号：
280497386
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
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/280497386?language=en
关键词：
Basic evaluation simulation based crash

项目摘要

Crash risk estimation is an important task in the area of infrastructure planning, which nowadays is realized by statistical modeling. The group of models however until now does not result in reliable predictions depending on dynamic states of traffic flow. The aim of the actual research proposal is, to create the basis for a mathematical model and analytic consideration for a coming simulation-assisted estimate of crash risk. Methodically, this will be achieved by an extension of the existing and validated traffic flow models by inhomogeneous dynamic state of traffic flow. Therefore the responsible drivers behavior is analyzed as an inhomogeneous state of traffic and so integrated into the model. The driving behavior in dynamic traffic states identified in real traffic and in laboratory driving simulator experiments is incorporated into a microscopic traffic model. From this small-scale system rigorously mathematically a large scale model is derived. Model-based predictions of possible crash risks are then derived on the basis of large-scale macroscopic traffic flow model. The derived models are calibrated and validated based on the obtained data. By the research project a substantial input to mathematical traffic modeling is expected. From this findings risk-based decision models for individual vehicle guidance or collective traffic influencing can be developed in future.

崩溃风险估计是基础架构计划领域的重要任务，如今，这是通过统计建模实现的。然而，到目前为止，一组模型并未根据交通流动的动态状态产生可靠的预测。实际研究建议的目的是为即将到来的模拟辅助崩溃风险估计值创建基础和分析考虑。有条理地，这将通过通过不均匀的动态流量流量来扩展现有和经过验证的交通流量模型来实现。因此，负责任的驱动因素行为被分析为不均匀的流量状态，并将其整合到模型中。在实际流量和实验室驾驶模拟器实验中确定的动态交通状态的驾驶行为已纳入微观交通模型。从这个小规模的系统中，在数学上严格地得出了大规模模型。然后，基于模型的崩溃风险预测基于大规模的宏观交通流模型。根据获得的数据对衍生模型进行校准和验证。通过研究项目，预计将对数学交通建模有实质性的投入。从这一发现中，基于风险的单个车辆指导或集体交通影响的决策模型将来可以开发出来。