There is recent increase in the use of private providers’ digital map
and traffic information systems that have evolved mostly without much
public sector influence. Some paradigm shift is needed for thinking
about the directions of future developments that will show societal
benefits also open up private-sector opportunities. In this context, we
develop a multi-agent advanced traffic management and information
systems (ATMIS) framework with day-to-day dynamics where private
agencies are included as traffic information service providers (ISPs)
together with public agencies handling the traffic control and the users
(drivers) as the decision-makers.
The emergence of private ISPs makes it possible to obtain path-based
data via retrieval of individual trajectory diaries and current position
information from their subscribers. This can bring about the
development of new path-based ATMIS algorithms that are capable of
taking into account the routing effects of advanced traveler information
systems (ATIS). Under the assumption that the traffic management center
(TMC) has some (even approximate) knowledge of the ISPs’ optimal
strategies, it is possible to design optimal route guidance and control
strategies (ORGCS) taking into account the anticipated ISP reactions in
terms of route-level flows. In light of these issues, we develop a
routing-based real-time cycle-free network-wide signal control scheme
(R2CFNet) that uses path-based data. Another theoretical advance in
the research is in the development of a modeling scheme that uses a new
optimization algorithm for a convergent simulation-based dynamic traffic
assignment (DTA) model. This model incorporates a Gradient Projection
(GP) algorithm, as opposed to the traditionally-used Method of
Successive Averages (MSA), and it displays significantly better
convergence characteristics. A consistent day-to-day dynamic framework
is also developed, incorporating an elaborate microscopic simulation
model to capture traffic network performance, to study network dynamics.
The results of parametric simulations have shown that the proposed
framework is capable of effectively capturing the effects of the
interplay of urban traffic route guidance, network control and user
response. An appropriate combination of ATIS market penetration rate
and signal control settings could divert some portion of travel demand
to different routes. This is achieved by constraining the signal
settings to conform to certain longer-term strategies. The performance
and efficiency of the components of the proposed framework such as the
DTA model, the day-to-day dynamics model and the R2CFNet control scheme
have been investigated through various numerical experiments that show
promising results. Lastly, several future topics of relevance to the
framework are discussed.
