Modeling Task Capability in Full Velocity Differential Model

Abstract

Car following (CF) models formally explain acceleration behavior of drivers. Historically, human factors are not considered in CF models. Attention is a very critical human factor. Drug use, panic, fear, or anger may negatively affect attention and consequently driving behavior. In the recent years, researchers have focused on modeling of CF behavior considering human factors as an outcome of research by traffic psychologists and engineers. These observations make clear that integration of human factors into car following models is necessary to develop a more realistic depiction of CF maneuvers under intricate driving situations. In complex driving situations, it is important to measure the dynamic interaction of driving task demand and ability of driver to handle the task at hand. The basic idea of Task Capability Interface (TCI) model is to incorporate task difficulty and task demand within a framework which gives the detailed account of their influence on one another. Task demand and capability plays a key role in decision making. TCI model has earlier been used to improve two traditional CF models namely Gipps’ model and Intelligent Driver Model (IDM). The enhanced models are referred as TD-Gipps model and TD-IDM. There is another model namely Full Velocity Differential Model (FVDM). Unlike its predecessors, FVDM doesn’t suffer from unrealistic acceleration and deacceleration. But FVDM has not been enhanced using TCI model. In this work, FVDM has been enhanced to incorporate TCI model. The enhanced model namely TD-FVDM has been verified by comparing it with TD-Gipps using simulation-based experiments. The enhanced proposed model reproduces acceleration behavior as intended.