Modeling driver behavior in the dilemma zone based on stochastic model predictive control

MANFIS Based Modeling and Prediction of the Driver-Vehicle Unit Behavior in Overtaking Scenarios

Overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. In this study, two novel prediction models for overtaking behavior are proposed. These models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (MANFIS). They are validated at microscopic level and are able to simulate and predict the fut...

Stochastic Model Predictive Control

Model Predictive Control (MPC) is a control strategy that has been used successfully in numerous and diverse application areas. The aim of the present article is to discuss how the basic ideas of MPC can be extended to problems involving random model uncertainty with known probability distribution. We discuss cost indices, constraints, closed loop properties and implementation issues.

Microscopic Modeling of Driver Behavior Based on Modifying Field Theory for Work Zone Application

Fuzzy sets to describe driver behavior in the dilemma zone of high-speed signalized intersections

The Type II dilemma zone describes a segment of road on the approach to a signalized intersection where, if occupied by a motorist presented with the circular yellow indication, is likely to result in a motorist having difficulty deciding to stop at the stop line or proceed through the intersection. This phenomenon results in increased frequency of three failure conditions: rear-end collision a...

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...