Modeling intermodal travel behavior in an agent-based travel demand model

The topic of intermodal passenger mobility has become more important during the last 20 years. As options increase in number and flexibility, it gets attractive to combine multiple modes on single trips. In addition, travel behavior is expected contribute less car dependent transport sector’s reduction greenhouse gas emissions. Creating improving conditions for such a requires planning with knowledge about influencing factors highest resistances. Empirical evidence behavioral models can support decisions measures supply. This work presents an agent-based model approach containing regard its most decisions. It enables combination multitude be extended even modes. By combining many influences comprehensible adaptable different surveys circumstances. We show that results are realistic impacts valid able forecast effects potential measures.