An active transportation and demand management framework focusing on tradable mobility credits (TMC) is integrated into an agent-based modeling and simulation (ABMS) platform. In this framework, it is conceived that an auction market within which mobility credits can be transferred between buyers and sellers is constructed in general. The idea of ABMS is extensively incorporated to mimic system users’ daily route choices as well as market-related micro-economical decision making process under TMC circumstance. Users are able to form individual propensities towards available bid/ask choices by reinforcement learning principles. The integrated platform offers a brand new insight view of microscopic aspect of the daily operations of credit transfer market, which has hardly been obtained by prior analytical models. Day-to-day traffic dynamics and market dynamics can be captured. Besides, market MOEs, including convergence, stability, efficiency and relative market powers of buyers and sellers under different market policies are investigated.
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