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

• Applicants: Professor Dr. Michael Herty; Professor Dr.-Ing. Markus Oeser
• Subject Area: Traffic and Transport Systems, Intelligent and Automated Traffic ; Mathematics
• Term: from 2016 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 280497386

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.

• DFG Programme: Research Grants