Microscopic Traffic Flow Properties in Emergency Situations

Emergency situations (e.g., evacuations following a disaster) have been shown to affect traffic flow operations substantially. However, the best way to model the adaptation effects in longitudinal driving behavior underlying this impact had not been made clear. Furthermore, the macroscopic consequences of the adaptation effects in longitudinal driving behavior had also not been made clear. This study sought to clarify these modeling issues and macroscopic consequences by estimating parameter values and model performance of the intelligent driver model with the data obtained through a driving simulator study. In addition, this paper presents the results of a case study that used a microscopic simulation program and the parameter values obtained through the estimation of the intelligent driver model. Results show that emergency situations have a substantial influence on parameter values and performance of the intelligent driver model. Furthermore, results show that the adaptation effects represented in parameter values and model performance have a substantial influence on macroscopic flow characteristics. A discussion of results and recommendations for future research are provided.