11-02-2013, 04:30 PM
Cloud Computing for Agent-Based Urban Transportation Systems
[attachment=50558]
History of Traffi c Control
and Management Systems
When an IBM 650 computer was fi rst introduced
to an urban traffi c-management system in 1959,
the traffi c control and management paradigm
closely aligned with the computing paradigm in IT
science.1 As Figure 1 shows, this paradigm has fi ve
distinct phases that mirror the fi ve stages in the
deployment of the traffi c control and management
paradigm.
In the fi rst phase, computers were huge and
costly, so mainframes were usually shared by
many terminals. In the 1960s, a whole traffi c
management system always shared the resources
of one computer in a centralized model.
Agent-Based Traffic
Management Systems
Agent technology was used in trafficmanagement
systems as early as
1992, while multiagent trafficmanagement
systems were presented
later.5 However, all these systems focus
on negotiation and collaboration
between static agents for coordination
and optimization.6–8 In 2004,
mobile agent technology began to attract
the attention of the transportation
field. The characteristics of
mobile agents—autonomous, mobile,
and adaptive—make them suitable
to handling the uncertainties and inconstant
states in a dynamic environment.
9 The mobile agent moves
through the network to reach control
devices and implements appropriate
strategies in either autonomous or
passive modes. In this way, traffic devices
only need to provide an operating
platform for mobile traffic agents
working in dynamic environments,
without having to contain every traffic
strategies.
Computing Power
The more typical traffic scenes used to
test a traffic-strategy agent, the more
detailed the learning about the advantages
and disadvantages of different
traffic strategy agents will be. In this
case, the initial agent-distribution
map will be more accurate. To achieve
this superior performance, however,
testing a large amount of typical traffic
scenes requires enormous computing
resources.
[attachment=50558]
History of Traffi c Control
and Management Systems
When an IBM 650 computer was fi rst introduced
to an urban traffi c-management system in 1959,
the traffi c control and management paradigm
closely aligned with the computing paradigm in IT
science.1 As Figure 1 shows, this paradigm has fi ve
distinct phases that mirror the fi ve stages in the
deployment of the traffi c control and management
paradigm.
In the fi rst phase, computers were huge and
costly, so mainframes were usually shared by
many terminals. In the 1960s, a whole traffi c
management system always shared the resources
of one computer in a centralized model.
Agent-Based Traffic
Management Systems
Agent technology was used in trafficmanagement
systems as early as
1992, while multiagent trafficmanagement
systems were presented
later.5 However, all these systems focus
on negotiation and collaboration
between static agents for coordination
and optimization.6–8 In 2004,
mobile agent technology began to attract
the attention of the transportation
field. The characteristics of
mobile agents—autonomous, mobile,
and adaptive—make them suitable
to handling the uncertainties and inconstant
states in a dynamic environment.
9 The mobile agent moves
through the network to reach control
devices and implements appropriate
strategies in either autonomous or
passive modes. In this way, traffic devices
only need to provide an operating
platform for mobile traffic agents
working in dynamic environments,
without having to contain every traffic
strategies.
Computing Power
The more typical traffic scenes used to
test a traffic-strategy agent, the more
detailed the learning about the advantages
and disadvantages of different
traffic strategy agents will be. In this
case, the initial agent-distribution
map will be more accurate. To achieve
this superior performance, however,
testing a large amount of typical traffic
scenes requires enormous computing
resources.