  We present an innovative framework, Crowdsourcing Autonomous Traffic
Simulation (CATS) framework, in order to safely implement and realize orderly
traffic flows. We firstly provide a semantic description of the CATS framework
using theories of economics to construct coupling constraints among drivers, in
which drivers monitor each other by making use of transportation resources and
driving credit. We then introduce an emotion-based traffic simulation, which
utilizes the Weber-Fechner law to integrate economic factors into drivers'
behaviors. Simulation results show that the CATS framework can significantly
reduce traffic accidents and improve urban traffic conditions.
