This thesis investigated the effect of human factors on car-following behavior and developed a novel methodology to incorporate those in car-following models. Application of the new method enables the car-following models to realistically reproduce the human factor induced behavior which can help researchers to better understand complex traffic problems caused by human errors, for example, road crashes and traffic jams. The method contains an innovative task difficulty formula, which captures the motivation behind driving decisions. The task difficulty offers a better explanation of human behavior in complex traffic conditions than the conventional measures, such as speed and headway.
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