28-05-2014, 02:58 PM
HYBRID PETRI NET MODELING OF TRAFFIC FLOW AND SIGNAL CONTROL
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Abstract:
Traffic control systems of signalized intersections are
naturally hybrid systems, in which vehicle flow behavior can
be described by a time-driven model and the traffic light
dynamics are modeled as a discrete event system. In this paper,
we use hybrid Petri nets (HPNs) to specify traffic and traffic
control at an intersection and use a second-order macroscopic
model to model the motion of vehicles in a road stretch
between two successive intersections. The traffic control
system of an arterial street is thus modeled as a composition of
individual intersection models and road stretch models. Such a
structure is suitable to perform traffic optimization by
changing the length of the offset between two adjacent
intersections with the common cycle.
Introduction
Traffic signal control is the regulation, warning and
guidance of traffic for the purpose of improving the safety
and efficiency of transportation that has great impact on the
life in urban areas. The control strategies consist of
changing the intersection's stage specification, the relative
green duration of each stage, the intersection's cycle time,
and the offset between cycles for successive intersections,
while requiring the well-planned synchronization, schedule
and control to achieve satisfactory performance.
The synchronization issues related to resource sharing
and conflict solving, which make the synthesis of an
adequate model of the traffic behavior of paramount
importance. A variety of mathematical programming
methodologies and artificial intelligence (AI) techniques
have been used to model the traffic flow and control logic
[2], [12], [13], with the aim of optimizing transportation
network performances. However, it is worth noting that an
effective responsiveness cannot be achieved by implement-
ing off-line methods [9].
Traffic control of an arterial street
An arterial street (Fig.1) control system is modeled as
a composition of two adjacent signalized intersection
models and a connected stretch model. The key issue
involved in arterial street control is to establish a time
relationship between the beginning of the green at one
intersection and beginning of the green at the next
intersection so that traffic platoons may receive a green
indication just as they approach a signalized intersection,
which is captured by the concept of offset. This relationship
permits the continuous flow of traffic along a street and aids
in reducing delay.
HPN model of a two-phase intersection
The HPN model of the intersection in Fig.2 is depicted
in Fig.5. Such a net is composed of three parts. The part
inside is a discrete PN modeling the changing rule of traffic
light. Note that where there is a token in place GA-A1, the
traffic lights for directions EW/WE are green or amber, and
those for SN/NS are red. The left part is composed by
continuous PNs modeling the vehicle flows entering and
leaving the intersection and the downstream roads. The
marking of the continuous part of the net represents the
number of vehicles that are in each place. The right part
models the behavior of vehicles in direction NS passing
through or turning in the intersection. Tab.1 and 2 give the
description of place and transitions in this model.
Conclusions
In this paper, the hybrid modeling approach based on
HPNs has been adopted to represent an arterial street of
signalized intersections, and a second-order macroscopic
model to model the motion of vehicles in a road stretch
between two successive intersections. Such a structure is
suitable to perform traffic optimization by changing the
length of the offset between two adjacent intersections with
the common cycle.