APOD Abstract for presentation (Poster or Podium) with a Paper in the Conference Proceedings
Public Transport
Oliver F. Shyr, PhD (he/him/his)
Professor
National Cheng Kung University
Tainan, Taiwan (Republic of China)
Oliver F. Shyr, PhD (he/him/his)
Professor
National Cheng Kung University
Tainan, Taiwan (Republic of China)
Shao-Jun Chiang, BA
Master Student
National Cheng Kung University
Tainan, Tainan, Taiwan (Republic of China)
Shao-Jun Chiang, BA
Master Student
National Cheng Kung University
Tainan, Tainan, Taiwan (Republic of China)
Oliver F. Shyr, PhD (he/him/his)
Professor
National Cheng Kung University
Tainan, Taiwan (Republic of China)
The integration of on-demand services, autonomous driving, and carpooling technologies in automated transit systems (ATN) is becoming a highly feasible option for future urban travel. ATN also echoes with the environmental awareness to reduce carbon emissions in response to climate change. Nevertheless, a dynamic systems simulation is needed to fully understand the effectiveness of ATN to alleviate traffic congestion caused by urban sprawl. With limited exploration on how ATN can impact urban commuting behavior, we attempt to apply a real option approach to measure and analyze the comparative impacts of ATN versus Monorail systems based on data collected from future project of Dark Green Line in the Tainan Metro System. We collect cost data and questionnaires from potential passengers to understand user’s acceptance and preference towards the two systems. This data is then integrated and calibrated so as to formulate equations for system dynamics simulation to obtain predicted patronage. By incorporating these predictions, we then apply the real option method to calculate future payoffs for ATN and Monorail systems to determine the most preferable alternative for Dark Green Line.