A Driving Behavior Model for Microscopic Online Simulation based on Remote Sensing and Equipped Vehicle Data

Abstract

Mostly, microscopic simulation models are calibrated with macroscopic measurement data, like flow and speed, which says nothing about the accuracy of the individual driving behavior of the vehicle – driver combinations. Due to the fact that online simulations of traffic are more dependent on the reaction of drivers in the network as offline simulations, the microscopic online simulator MiOS is extended with a driving behavior model based on equipped vehicle and floating car data. In this behavior model a dynamic probabilistic network represents the perception of the driver. Based on this, a decision making process is modeled as a dynamic decision network. The probabilistic functions and the objective function are findings from microscopic measurement data. The research was performed with data from the Netherlands, the United States and Japan.