Use of advanced traffic control systems ranks as one of the most
cost-effective actions for urban transportation improvements to mitigate
total delay and alleviate fuel consumption and air pollution.
Nonetheless, Adaptive Signal System, the most advanced type of traffic
control designed for real-time traffic responsive operations, is not
widely accepted in field implementation. Benefits of such systems are
not fully realized yet, mainly because of the large cost for installment
and maintenance of required sensor systems for traffic forecast.
Moreover, even with the sensor systems, the performance still suffers
due to inaccurate prediction caused by the limitation of data sources
and deficiencies in the control algorithms.
Based on these observations, this study developed the applications of
emerging data sources in traffic control system. Traffic parameters are
collected under the new traffic information system such as a Persistent
Traffic Cookies (PTC) system conceptually proposed at UC Irvine using
wireless communication between a vehicle and a roadside hardware. With
the preliminary study results under the system, this study develops
traffic control schemes with the traffic forecast resulting from the PTC
system. Initially, general methods are presented to generate required
input, that is path-based traffic variables such as the turning flows
and travel time from PTC data. The inputs were implemented in two
different traffic control schemes; subnetwork definition for
area-control and signal optimization scheme in network-level. The
relevant spatial boundary for area-control is determined by a systematic
approach on the basis of traffic dynamics estimated by the PTC data.
Basically, the approach is to group multiple interconnected
intersections with strong control dependencies on each other, which can
be measured by the path flow among the intersections. Another
application is a signal optimization scheme at the network-level under
the assumption of fully decentralized control embedded with indirect
signal coordination consideration. Local optimization was accomplished
by a Dynamic Programming approach incorporating with a modified Rolling
Horizon Scheme and network-wide coordination was indirectly achieved by
iterative approach with repeated local optimizations.
For an evaluation of proposed control scheme, a simulation study was
presented using Irvine Triangular Network constructed in microscopic
simulation software. Results show that the proposed scheme is capable
of reducing total delays in a network, in comparison to Actuated Signal
Control already installed in the study network. It is also shown that
the scheme that incorporates certain modified rolling horizon methods
performs better than that with a more conventional rolling horizon method.
