KSII The 10th International on Internet (ICONI) 2018

Copyright © 2018 KSII 1

A New Model for Simulating and

Evaluating Congestion Cause at Signalized
Intersection
KimAng Kheang, Sokchea Kor, and Sovila Srun
Department of Information Technology Engineering, Faculty of Engineering,
Royal University of Phnom Penh
Phnom Penh, Cambodia
kimangkheang@gmail.com, kor.sokchea@rupp.edu.kh, srun.sovila@rupp.edu.kh
Sokchea Kor*Sovila Srun*

Abstract
This paper presents a simulation framework to determine congestion cause for
an isolated signalized intersection having four-approaches with through and
left-right turn movement under homogenous condition. The simulation
framework consists of various correlated models such as vehicles’ path model,
car following model, vehicles’ arrival model, and evaluation model. The
framework is then implemented to create SPSV (Special Purpose Simulation
and Visualization) software. These models are presented in mathematical terms
with specified parameters and objective function that later are interrupted and
discretized using Object-oriented methodology with programming language.
The vehicles’ path model is a piecewise function describing a driver’s position
when approaching intersection till leaving intersection in terms of time. The
vehicle arrival model is based on negative exponential distribution. The data
generated by the models will be used to suggest the optimal setting to
determine the factors for better intersection performance.

Keywords: Signalized Intersection, Homogenous Condition, Simulation Model, Congestion

Rate, Object-Oriented, Parametric equation
infrastructure and urban
1. Introduction development. The simulation-
The development of traffic before-construction approach [1]
facilities saw an enormous boost is apparently more practiced to
over the last decades with the reduce risk to
advance of automobile
technologies making the solution
to traffic issue a prominent
challenge. The computing
technology also plays a crucial
role in accelerating the
development of traffic
2 KimAng Kheang, Sokchea Kor, and Srun Sovila: A New Model
for Simulating and
Evaluating Congestion Cause at Signalized Intersection

predict the outcome. Thus, many to that interests of flow rate,

challenging construction projects vehicular headway, road density and
were carried out in computer vehicular counts of each intersection
simulation right before they had the approach with various dynamically
chance to materialize. In the last adjustable input parameters like
decades, many attempts were made vehicle arrival rate, traffic signal
in a bit to elaborate the traffic duration, and vehicle behaviors. In
behaviors scientifically through the end, the framework also enables
mathematics model and researchers as well as engineers to
programming paradigms. conduct more specifically designed
scenarios to gain the insight of
This paper presents the closely
overall traffic situation. The result
related models to be a unified
congestion occurrence will be used
simulation framework for an isolated
to suggest the optimal settings to
signalized intersection under
get the desired traffic milestone.
homogenous condition that produces
traffic data 2. Literature Review
The first insight to build the
simulation models was introduced
by A. D’Ambrogio [1] to help the
traffic engineer to quickly assess the
vehicular situation in intersection
area. This method involves defining
formal specification of vehicular and
lighting attribute derived from
informal assumption to formalize the
model. The set of input will be
provided accordingly to yield the
simulation result in queue size in
each intersection approach versus
simulation time. Later Asaithambi
[2] took an initiative to describe an
intersection model in a more
programming like approach with
Object-Oriented methodology to
implement the related mathematics
model. His model saw a leaped
improvement in terms of
heterogeneous behavior of vehicular
movement at the intersection are
and the data generated by the model
to later use for analyzing the traffic
features. Likewise, the previous
research, the traffic entities were
defined in UML form (Unified
Modelling Language) diagram based
on research interests. The
correlation between classes were
congregated programmatically and
algorithmically. The research
interests were similar to that of A.
D’Ambrogio [1] to yield the result by
comparing the observed vehicles
2 KimAng Kheang, Sokchea Kor, and Srun Sovila: A New Model
for Simulating and
Evaluating Congestion Cause at Signalized Intersection

density to the simulated one. stop on signalized intersection

Additionally, the numbers of performance.
dissipating vehicles, observed and However, the models [1,2,3,4] were
simulated, were also compared. problem-oriented and left the results
More researches were conduct by the model to the traffic engineers
narrowly to focus on a corner of the as well as researcher to later
problem. Yubin [3] introduced a perform calculate based on
microscopic model to simulate the respective field and interests. A.
traffic flow model in the urban area D’Ambrogio[1] method only provide
with highly dense vehicular ways to define simulation properties
movement. More related models to get the interested results to
were also included to realistically conduct a later study in a more
imitate the true scenarios such as sophisticated way whereas
travel demand model, and car Asaithambi [2] focus on the accuracy
following model. A more generalized of the model trying to compare the
model was introduced like [4] to observed data with the simulated
simulate the effect of bus one.
3. Simulation Framework
The core concept of this simulation
framework is to initiate the blueprint
of a computer program capable of
simulating traffic movement which
truly reflects the real world
scenario. The microscopic
simulation models will initiate a
factor to dynamically observed the
traffic performance based on
computer simulation to the field
engineer. With the advance of
detecting technologies and
satellites, the required input
parameter such as vehicular flow,
birth rate, driving behaviors, set of
rules specified to a particular area
can be offered without much
obstacle.
2 KimAng Kheang, Sokchea Kor, and Srun Sovila: A New Model
for Simulating and
Evaluating Congestion Cause at Signalized Intersection
The 10th International Conference on Internet (ICONI) 2018, December
2018
Because the model is object-
oriented, the vehicular movement is
solely responsible for its own
instance to make direct interaction
with other entities to make the
model more generalized but sill
contained the element of multi-
agent. Asaithambi model [2] was
sophisticated enough to predict
results in both stochastic and
deterministic behaviors while the
proposed model introduced hybrid
and multi behaviors to the overall
simulation framework. The model is
capable of making changes to the
simulating system as each core
component is working in parallel in
respond to changes to the input
parameters. In this scene, once the
simulation is advanced, the input
parameters can vary in times
enabling the dynamics changes to
the system. This is the case when
traffic engineers try to simulation a
system with unpredicted
phenomenon requiring model to still
simulate with conventional scheme
but additionally offers such features.

3.1 Signalized Intersection

model

A typical isolated signalized

intersection with four approaches
and vehicles detector configuration
is studied in this paper. Each
approach has through, right-turning
and left-turning. To detect vehicles,
inductive loops are installed on the
stop-lines, upstream-lines, and
corner-lines for right-turning.
Inductive loops are capable of
counting vehicles in these lines.
The 10th International Conference on Internet (ICONI) 2018, December
2018
For an approach to 4 legs A 4-phrases common approach
intersection, the number of vehicles for determining traffic phrase will be
for east, south, west, and north used.
approach is defined within the time
interval
[ t−∆ t ,t ] :
N d ( t )={N dn , … N dn−1 , n ∈[0,3]
Where:
N d ( t )=¿ the number of queue vehicles
in an
approach d at any time t.
d = direction where vehicles are
approaching. for
south approach (d = S), east (d = E),
north (d =
N), and west (d = W).
n = lanes within each approach. For
left-turn (n =
0), through (n = 1), and right-turn (n
= 2).
N S0 ( t )can be described as: the
number of leftturn
vehicles in south approach at any
time t
within interval [ t −∆ t ,t ] .
A traffic flow set can also be defined:

Q d ( t )={Q dn−1 ( t ) } , n∈[3,3]

That specific the flow rate in each
approach with its corresponding
lane.
These traffic variables can be
collected by inductive loop or other
relevant facilities on the field.
The 10th International Conference on Internet (ICONI) 2018, December
2018