Abstract
Through recent developments in information and communication technologies, dynamic monitoring and control of transport systems are technically possible. These technologies enable constructing more flexible and cost-effective transport services which may vary based on demand. Since passenger demand for public transports has been declining in rural regions, DRT (Demand Responsible Transport), which provides transport service in response to the requests, is expected to have an important role as new public transport system to fulfill the mobility gap between taxi and bus. The route and departure time of DRT changes according to each reservation. Therefore passenger's mode choice influences on the service level. On the other hand, the mode choice is also influenced by the experienced service level. One might not want to use the DRT service any more if travel time is too long to accept in one day. After all, one's decision making influences on others through the DRT system. To explore these phenomenon, this study attempts to develop a multi-agent social simulation considering consider passengers? mode and departure choice learning to evaluate the DRT system.
