Generating artificial popullations for traffic microsimulation

Hongxia Zhao, Shuming Tang, Yisheng Lv

Abstract: Travel demand is derived from people's participation in daily activities scattered in time and space. Traffic microsimulation starts by generating individuals to participate in activities. In this paper, we propose a framework called Artificial Population Systems (APS) in order to automatically generate artificial populations for traffic microsimulation. Different from the conventional approach using empirical data to generate synthetic populations for the base year, our APS framework can generate artificial populations which evolve with time and space. So, with artificial populations, we will get more reasonable traffic demand forecast and analytical results in long term traffic microsimulation.