The Markov-Gap CA Model for Entering Gaps and Departure Headways at Signalized Intersections

Modeling gaps/headways has many applications in traffic theory and transportation operations. Recently, many researchers begin to show interests in microscopic simulation based interpretations on the formulation of gap and headway distributions. However, there are few cellular automata (CA) model proposed in this area, since most current CA models focus on phase transitions of freeway traffic only. In this paper, a so called Markov-Gap CA models is proposed, aiming on fitting the empirical gap/headway distributions collected. The model treats gap variations between consecutive vehicles approaching or leaving signalized intersections as different Markov processes and provides a concise and uniform method to describe the observed traffic flow phenomena. The agreement between the simulation results and empirical data suggests the soundness of the Markov-Gap CA model.