  We are exploring the enhancement of models of agent behaviour with more
"human-like" decision making strategies than are presently available. Our
motivation is to developed with a view to as the decision analysis and support
for electric taxi company under the mission of energy saving and reduction of
CO2, in particular car-pool and car-sharing management policies. In order to
achieve the object of decision analysis for user, we provide a human-agents
interactive spatial behaviour to support user making decision real time. We
adopt passenger average waiting time and electric taxi average idle time as the
performance measures and decision support fro electric taxi company. Finally,
according to the analysis result, we demonstrate that our multi-agent
simulation and GUI can help users or companies quickly make a quality and
accurate decision to reduce the decision-making cost and time.
