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Corridor capacity analysis with mesoscopic simulation: Erzincanprovince sample
AHMET OGUZ DEMIRIZ1,* , OSMAN UNSAL BAYRAK2 and HALIM FERIT BAYATA1
1Department of Civil Engineering, Faculty of Engineering, Erzincan Binali Yildirim University, Erzincan,
Turkey2Department of Civil Engineering, Faculty of Engineering, Ataturk University, Erzurum, Turkey
e-mail: [email protected]
MS received 9 June 2020; revised 7 October 2020; accepted 1 November 2020
Abstract. Today, the existing traffic networks cannot cope-up with the increasing transportation demands and
traffic volume and fail to meet the demands. This causes economic and social losses. Increasing transportation
demands and traffic volume in Erzincan city center of Turkey cause the main arteries and junctions to be insufficient.
In such problems, solutions are generally produced using parameters such as trip and delay durations and exhaust
emissions. Another point to be considered is to ensure the improved intersections towork as a whole. In this study, the
main arteries and the junctions on these in Erzincan city center were discussed. In this context, totally 14 intersections
were tried to be improved. Suggestions were offered regarding delay time, travel time, queue lengths, NOx and CO2
emissions, and average speed values as the design criteria. Simulations were made in AIMSUN program for the
current situation and four different scenarios. Analytical Hierarchy Process (AHP), which is one of the multi-criteria
decision-making methods for the network was employed to determine which scenario was more appropriate. At the
end of the study, decrease of up to 23% for travel time, 47% for delays, 48% for queue lengths, 11% forNOx, and 13%
for CO2 and increase of up to 30% in average speed were obtained. According to AHP, Scenario 4 had the highest
priority value among all alternatives. Moreover, the reliability of the results was ensured by supporting the meso-
scopic simulation with AHP which is a multi-criteria decision-making method.
Keywords. Intersection; traffic management; mesoscopic simulation; road network; AIMSUN.
1. Introduction
Transportation is one of the most important factors
embedded with any stages in people’s life. Transportation
demands have increased day by day along with factors such
as population growth, growth of cities and increase at
industrialization. As a result of the increasing transportation
demands, densities appear in transportation networks, and
congestion starts locally. As traffic density increases, the
parameters that negatively affect human life such as fuel
consumption, travel time, and risk of accidents increase.
The road section where the most traffic accident occurs in
our country is the intersections. According to the traffic
accident data announced by the General Directorate of
Highways, there were 186.532 accidents involving death or
personal injuries [1].
Intersections are one of the factors that mostly affect the
risk of accident, travel time, fuel consumption, and road
performance. For these reasons, along with the increasing
traffic density, an intersection is one of the factors that
needs to be improved first. Traffic simulations are used
when designing intersections. In addition to being safe and
economical, simulation is a very effective instrument for
model production and evaluation of produced models [2–5].
The researchers who have recently carried out studies on
transportation have benefited from mesoscopic simulations
to compare large-scale traffic networks and assessed their
performances [5–7]. Various mesoscopic simulation pro-
grams such as AIMSUN, VISUM, SATURN, TRACKS,
DYNAMEQ, DYNAMIT, etc. offer the opportunity of
evaluating and comparing traffic networks [7–10] (traffic
modelling guidelines). In this study, AIMSUN mesoscopic
model was used to assess and compare the current situation
and alternative scenarios of Erzincan central traffic net-
work. AIMSUN mesoscopic model is ideal for simulating
and evaluating large-scale traffic networks. Although
alternative scenarios are analyzed and assessed with AIM-
SUN, the researcher decides which alternative is the opti-
mum solution. Because simulation programs cannot
determine the parameters such as security or benefit/cost.
In engineering applications, some criteria are determined
to assess alternatives, and the alternatives are compared
with each other in terms of these determined criteria. Multi-
criteria decision-making methods are used when comparing*For correspondence
Sådhanå (2021) 46:10 � Indian Academy of Sciences
https://doi.org/10.1007/s12046-020-01533-9Sadhana(0123456789().,-volV)FT3](0123456789().,-volV)
alternatives in terms of pre-determined criteria. The most
frequently used multiple-criteria decision-making methods
are Analytic Hierarchy Process (AHP), Analytic Network
Process (ANP), Electre, Promethee, and Technique for the
Order of Prioritization by Similarity to Ideal Solution
(TOPSIS). The Analytical Hierarchy Process (AHP)
developed by Saaty [11] has become one of the most
effective multi-criteria evaluation methods that have been
used in a wide range of practical applications for various
decision-making processes. Since its introduction, the AHP
has shown a broad impact in the field of multi-criteria or
multi-attribute decision making and has been recognized
with its numerous applications such as choices, prioritiza-
tion/evaluation, resource allocation, benchmarking, and
quality management [12]. In this study, AHP was used to
determine the optimum option among the alternatives.
One of the most important issues to design effective road
networks is the junction type selection. For example, if a
junction where traffic regulatory signs can be used is
designed as signalized, the values such as delay time, travel
time, and fuel consumption increase [4]. Or if a grade-
separated junction is to be replaced by a modern junction
with high-level service, the level of service does not change
and only the cost of construction increases. Thus, an ana-
lytical approach that considers assessing multi-criteria is
essential as well as the cost-benefit analysis that assesses
the consequences of different intersection design types in
monetary terms [13].
In recent years, several studies have been carried out on
simulation applications for traffic control and management
[6, 14–16]. Some researchers have calibrated mesoscopic
simulation parameters according to their study area
[5, 7, 8, 10, 17–20]. Some others have used AHP to dis-
cover the optimum option among the alternatives they have
created [13, 14, 21–23]. However, it was observed that very
few of these studies were large-scale, and therefore, most of
them were not assessed as a whole using mesoscopic sim-
ulation. Therefore, in this article, all the corridors in a city
were investigated as a whole, the scenarios with different
types of junctions were created, and the optimum option
was revealed using the AHP method. For these purposes,
the 14 intersections with the highest density in Erzincan
city center and the link roads of these intersections were
considered as a corridor. The total corridor had a length of
about 25 km and a heavy traffic volume during working
hours. In order to increase corridor performance, the current
situation and 4 scenarios (Scenario 1: Current Situation;
Scenario 2: Optimization with Webster method, Scenario 3:
Modern Roundabout Applications; Scenario 4: Optimiza-
tion with Webster method along with roundabout applica-
tion and signalized roundabout application; Scenario 5:
Grade Separated Junction Application) were assessed and 4
alternative scenarios were created to increase the perfor-
mance. During the decision-making process, the criteria of
delay time, travel time, queue length, NOx emission, CO2
emission, speed and cost of construction were taken into
consideration. All criteria except from the cost of con-
struction were determined using the AIMSUN program.
Then, AHP was used to determine the optimum scenario
considering all the criteria.
2. Material and method
2.1 Case study- an Erzincan city
Fourteen junctions with the highest traffic density and on
the main arteries were discussed as the study areas. These
junctions were Bahcesaray, Isikpinar, Milli Egemenlik,
Esentepe, Mengucek Gazi, Adnan Menderes, Cumartesi,
Ataturk, Halit Pasa, Yildiz, Izzet Pasa, Menguceli, Terz-
ibaba, and Sumer. The whole network was regarded as a
single corridor (figure 1). In the study area, there were 13
signalized and 1 unsigned junction (figure 2).
It was observed that traffic density and traffic jams
occurred at the current intersections especially in the
morning and evening hours. At least one of these inter-
sections has been used for any transportation demands in
Erzincan. There are an average of 6 junctions within the
city bus (public transport) routes. Each of the junctions
used in the study had a different importance and cannot be
ignored. In addition to the aforementioned reasons, the
corridors that were selected covered the entire Erzincan city
center, the importance of the corridor increased with any
increasing transportation demands.
2.2 Data collection
Data collection and data analysis are very important for
traffic engineers in terms of traffic control and manage-
ment. Various preliminary investigations such as traffic
volume counts in the corridor, signaling times of intersec-
tions, and travel time were carried out during peak hours of
morning, lunchtime, and evening. In this study, the sig-
naling phase times were obtained from Erzincan Munici-
pality’s Signaling unit. Vehicle counts were made manually
for some intersections according to vehicle types (bus and
Figure 1. Test area.
10 Page 2 of 12 Sådhanå (2021) 46:10
automobile), and via video camera recordings for the oth-
ers. The vehicles were counted on Monday, Wednesday,
Friday and Sunday between 7:45 and 8:45 a.m., 12:00
and1:00 p.m. 4:45 and 5:45 p.m. In-vehicle counts, the
highest traffic volume was determined between 7:45 and
8:45 a.m. on Monday. The data were analyzed and used as
input data for AIMSUN’s mesoscopic simulation software.
The traffic composition showed that 94% of total vehicles
were private cars, and 6% were public transport vehicles
(buses). Private vehicles and public transport buses were
counted separately according to their routes [24]. For
example, the traffic volumes of the Yildiz junction were
presented in figure 3.
Here, it was observed that there were 448 cars and 49
buses coming from the East-West direction (indicated as 1
numbered road) and going straight (to 4 numbered road),
170 cars and 18 buses turning to the left (to 6 numbered
road), 28 cars making a U-turn (to 8 numbered road) 52
cars and 6 buses turning to the right (to 2 numbered road). It
was also observed that there were 462 cars and 43 buses
coming from West-East direction (from 5 numbered road)
and going straight (to 8 numbered road), 243 cars and 23
buses turning to the left (to 2 numbered road), 66 cars
turning to the right (to 6 numbered road), and 31 cars
making a U-turn (to 4 numbered road). From the North-
South direction (from 3 numbered road) to the left (to 4
numbered road) 71 cars 28 buses, to the straight (to 6
numbered road) 313 cars and 20 buses, to the right (to 8
numbered road) 186 cars, U-turn. There were 43 cars that
made (to 2 numbered road). Also, there were 71 cars and 28
buses coming from the North-South direction (from 3
numbered road) turning to the left (to 4 numbered road), to
313 cars and 20 buses going straight (to 6 numbered road),
186 cars turning to the right (to 8 numbered road), and 43
cars making U-turn (to 2 numbered road). Moreover, it was
also observed that there were 123 cars and 4 buses coming
from South-North direction (from 7 numbered road) and
turning to the left (to 4 numbered road), 229 cars and 20
buses going straight (to 2 numbered road), 68 cars and 16
buses turning to the right (to 8 numbered road) and 8 cars
making U-turn (to 6 numbered road).
In figure 4, the phase durations of the signaling system at
the Terzibaba junction were presented. At Terzibaba junc-
tion, the duration lasted for 62 s, the yellow light time
between red and green light was 2 s, and protection red (all
red) was 2 s. The starting point of the arrows shown in red
indicated the point where the traffic lights were located, and
the direction of the arrow indicated the permissible transi-
tion phases.
Different speed limits are applied in Erzincan city center
as 50 km/h, 60 km/h, and 70 km/h. The speed limits
administered in the traffic network were presented in fig-
ure 5. Lane using is reduced in some streets as parking is
permitted in many arteries of the city. For example, in
figure 6, the sections of the lanes in the arteries connected
to the safety junction that cannot be used due to parking
were marked in red. In simulation modeling to be created,
the current situation will be reflected as it is regarding the
speed limits and parking conditions of the arteries in the
traffic network.
2.3 Model building and calibration
The image of Erzincan City Center taken using the Google
Earth program was transferred to the AIMSUN software on
Figure 2. The intersections in the test area (Reference: Googles
Maps).
Sådhanå (2021) 46:10 Page 3 of 12 10
a scale, and the accuracy of the road lengths was measured
by car. The collected data were entered into the software,
and the current situation was modeled. The models created
with simulation software are needed to be calibrated to
reflect the real situation. The default parameter values are
changed till the error between actual and simulated mea-
sures such as flow or travel time less than the required
threshold value [3, 25]. However, in current traffic
engineering, no accepted standards exist to determine when
a model can be considered to be suitably validated or cal-
ibrated [26]. Different methods such as GEH formula
[15, 27–29], relative error [25, 30], etc. used for calibration.
In this study, traffic volumes were used for the calibration
parameter. Traffic volumes were counted according to their
routes (figure 3) and simulation values were obtained from
data collection points. Counted values and simulated values
were assessed according to the GEH formula in Table 1.
2.4 Webster method
The Webster method is a method used to regulate the phase
duration and period of the signals at junctions controlled by
signalization and is also known as the British method.
Signalization optimization was provided in several studies
using Webster method [31–33]. Through the Webster
method, signal optimization was separately applied to each
junction with signalization, and the most successful among
them were used in this study. These junctions were Ataturk,
Halit Pasa, Menguceli, Cumartesi, Terzibaba and Izzet
Pasa. The new phases created with the Webster method for
one of these intersections was presented in figure 7. In
figure 7, the phase durations and rights of ways in the
phases were shown in details.
Figure 3. Yildiz intersection, traffic volumes of directions [24].
Figure 4. Terzibaba intersection phase durations [24].
10 Page 4 of 12 Sådhanå (2021) 46:10
In figure 7, the new phases of Ataturk Junction created
with the Webster method were presented. In the upper part
of the figure, the permitted transitions in Signal 1 and
Signal 2 phases were shown. Signal 1 and Signal 2 phase
diagrams were given in the middle part, and traffic light
durations in the phases were presented in the lower part.
According to figure; Signal 1 had 26-second red light
duration, 4-second yellow light duration, and 46-second
green light duration. Signal 2 had 50-second red light
duration, 3-second yellow light duration and 23-second
green light duration.
Since the physical conditions of the Yıldız Junction
which locates at the midpoint of the entire road network
and has the highest traffic density are insufficient, green
wave application could not be applied. Hence, Webster
signal optimization has been done instead of the green
wave.
Figure 5. Speed limits of road sections in the traffic network.
Figure 6. Lanes to be parked in Ataturk junction.
Table 1. GEH values.
Yildiz Junction
GEH
WEST-EAST EAST-WEST NORTH-SOUTH SOUTH-NORTH
TOTALCar Bus Car Bus Car Bus Car Bus
Observed values 802 66 698 73 613 48 428 40 2768
Simulation values 806 62 684 98 599 44 386 41 2720
GEH value 0.14 0.50 0.53 2.70 0.57 0.59 2.08 0.16 0.92
Criteria GEHT\ 5 YES YES YES YES YES YES YES YES YES
Sådhanå (2021) 46:10 Page 5 of 12 10
2.5 AHP method
In many engineering applications, the final decision is
based upon the assessment of a number of alternatives in
terms of a set of criteria. Multi-criteria decision-making
methods help decision-makers to find solutions that best
corresponds to their goals. Different methods have been
developed to solve multi-criteria analysis problems. One of
these developed methods is the AHP method
[12–14, 21, 23, 34]. The Analytic Hierarchy Process (AHP)
is a multi-criteria decision-making approach developed by
Saaty [11, 35, 36], and used for solving the complex
decision problems [13, 34, 37]. Many researchers have
come to the final conclusion using AHP in their studies
[14, 23, 38, 39].
The criteria determined to be used for the comparison
and assessment of the scenarios were given below. The
definitions of the criteria were given as used for mesoscopic
simulation network results in AIMSUN software.
1. Delay Time: The delay time in the software is the
average delay time of vehicles per kilometer. The
average of the delay times for all vehicles is calculated
and then converted to time per kilometer. The unit is
second/kilometer.
2. Travel time: It is the ratio of the total travel time of all
vehicles from the beginning of the simulation to the total
trip distance, and is expressed in second/km.
3. Average Queue Length: It is the average queue length
that occurs in the whole traffic network during the
simulation in the program and is expressed in vehicles.
4. NOx Emission: Nitrogen Oxide emission is the amount
of NOx emitted by all vehicles leaving the traffic
network in kilometers and expressed in gram/kilometer
in the software.
5. CO2 Emission: Carbon Monoxide emission is the
amount of CO2 emitted by all vehicles leaving the
traffic network in kilometers and expressed in gram/
kilometer in the software.
6. Speed: It is the average speed of all vehicles leaving the
traffic network in AIMSUN Software and expressed in
kilometer/hour.
7. Cost of Construction: The costs of the regulations to be
created at junctions are as important as the benefits. For
this reason, the construction cost was included as a
criterion since the benefit/cost ratio should also be
regarded while making regulations.
In order to weigh the determined criteria, decision-
makers compared the criteria with the paired comparison
method. In the comparison process, 1-9 scale was used.
After creating a paired comparison matrix, the criteria
weights were calculated. The paired comparison matrix was
presented in Table 2.
In Table 2, indicating the paired comparison matrix, the
superiority of the criteria in the rows against the criteria in
the column were given at the junction points. For example,
when the Table was analyzed, it was possible to notice that
the travel time and cost of construction were slightly more
significant than the delay time, and the other criteria were
less significant. The weights calculated as result of the
paired comparison matrix were given in the last column of
the Table. According to the calculated weights, the most
significant criterion was the cost of construction and the
least significant one was the queue length.
3. Alternative preference
Junctions are road sections where traffic flow coming from
more than one direction intersects, joins and separates.
Planning is made regarding the factors of comfort, safety
and capacity. Here, the safety factor means preventing a
vehicle from colliding with a pedestrian or a vehicle
coming from a different direction and eliminating the ele-
ments that may create an accident hazard. The comfort
factor means having no situations that may require sudden
braking or acceleration and minimizing the time lost
between braking and acceleration. And capacity is a desired
situation for junction planning.
The junctions are grouped under two main types as at-
grade junctions and grade-separated junctions. After the
traffic volume in junctions exceeds a certain level, the
capacity of the at-grade junctions becomes insufficient.
This can increase delay times and queue lengths at junc-
tions as well as causing serious traffic accidents. Grade
separated junctions are constructed in cases when at-grade
junctions remain insufficient. At-grade junctions are the
ones that appear as a result of the intersection of traffic
flows from different directions on the same plane. The
majority of traffic accidents or problems occur in at-grade
junctions. For this reason, much attention should be paid to
its design. At-grade junctions are grouped under 4 as
Figure 7. Ataturk intersection, the phases created with the
Webster method.
10 Page 6 of 12 Sådhanå (2021) 46:10
uncontrolled, signalized, modern roundabouts, and signal-
ized roundabouts. Uncontrolled junctions are the ones
where there is no control mechanism. Traffic flow depends
on factors such as the behavior, knowledge, and initiative of
the drivers. The signalized junctions are the ones where
traffic movements are controlled with traffic signals. In
these junction types, various methods such as the Webster
method are used to calculate signal times to prevent
excessive delay, queue length, and fuel consumption.
Modern roundabouts, on the other hand, are the ones where
traffic flows regularly and continuously around a traffic
island without signalization and with specific rules with
traffic regulatory signs. Signalized roundabouts do not have
enough space on the traffic island and have signalization to
evacuate the traffic on the island and prevent traffic jams to
appear.
In the light of the above information, 5 scenarios together
with the current situation were regarded for the junctions in
Erzincan city center. These are:
• Current situation of all junctions (Scenario 1).
• Signal optimization of some junctions with Webster
method (Scenario 2).
• Design of some junctions as modern roundabouts
(Scenario 3).
• Design of some junctions as modern roundabouts,
signaling optimization of some junctions with Webster
method, and signalization of a junction adding a traffic
island (Scenario 4).
• Design of some junctions as the subway (Scenario 5).
The details of the scenarios were presented in Table3.
3.1 Modern roundabout applications
In the current traffic network, all junctions that provided
necessary geometrical conditions and had high traffic
density were modeled as modern roundabouts. The junc-
tions converted into modern roundabouts were Ataturk,
Yildiz, Bahcesaray, Isikpinar, Izzet Pasa, and Menguceli.
Created modern roundabouts were separately presented in
the figures, and the maximum possible radius was used in
all. The roundabout with a radius of 50 m was modelled at
Table 2. Paired comparison matrix.
Criteria
Delay
time
Travel
time
Queue
length
NOx
emission
CO2
emission Speed
Cost of
construction Weight
Delay time 1 1/2 5 4 4 2 1/2 0.186
Travel time 2 1 3 5 4 2 1/3 0.212
Queue length 1/5 1/3 1 1/2 1/2 1/2 1/4 0.047
NOx emission 1/4 1/5 2 1 1/2 1/3 1/6 0.048
CO2 emission 1/4 1/4 2 2 1 1/3 1/4 0.064
Speed 1/2 1/2 2 3 3 1 1/3 0.116
Cost of construction 2 3 4 6 4 3 1 0.327
Lambda (max):
7.396
CI: 0.066 RI: 1.32 CR: 0.05 (\ 0.10)
Table 3. The scenarios to be created.
Junctions Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5
Bahcesaray Current Situation Current Situation Roundabout Roundabout Current Situation
Isikpinar Current Situation Current Situation Roundabout Roundabout Current Situation
Milli Egemenlik Current Situation Webster Method Current Situation Webster Method Current Situation
Mengucek Gazi Current Situation Current Situation Current Situation Signalized Roundabout Current Situation
Adnan Menderes Current Situation Current Situation Current Situation Current Situation Current Situation
Cumartesi Current Situation Webster Method Current Situation Webster Method Current Situation
Ataturk Current Situation Webster Method Roundabout Roundabout Grade Separated
Halit Pasa Current Situation Webster Method Current Situation Webster Method Grade Separated
Yildiz Current Situation Current Situation Roundabout Roundabout Grade Separated
Izzet Pasa Current Situation Current Situation Roundabout Roundabout Grade Separated
Menguceli Current Situation Webster Method Roundabout Roundabout Current Situation
Terzibaba Current Situation Webster Method Current Situation Webster Method Current Situation
Sumer Current Situation Current Situation Current Situation Current Situation Current Situation
Sådhanå (2021) 46:10 Page 7 of 12 10
Ataturk, 20 m at Yildiz, Bahcesaray, and Isikpinar junc-
tions, and 26 m at Izzet Pasa and Menguceli junctions were
modeled.
In figure 8, an example of a modern roundabout model
for the Ataturk junction was presented. The flow inside the
roundabout was prioritized, and a ‘‘give way’’ regulatory
sign was added to the arteries.
3.2 Signalized roundabout applications
It was observed that the waiting times in the Hospital
junction with four legs four-phase signaling are higher
rather than other junctions. Webster’s method was tried at
the junctions that needed improvement, but no satisfactory
results were obtained. It was also observed that the existing
geometry was not sufficient for making modern round-
abouts. For these reasons, the signaling system with 4
phases was reduced to 2 phases adding a traffic island to the
junction. The new signaling with 2 phases was created
using Webster’s method. There was no signalization in the
designed traffic island and there was a ‘‘give way’’ traffic
regulatory sign.
As shown in figure 9, the two opposed legs on Signal 1
operated in the same phase and two other legs in Signal 2
operated on the same phase. Traffic lights were located at
the beginning of the red arrows. The red arrows indicated
permitted transitions. Signal 1 had a 27-second red light
duration, 3-second yellow light duration, and 30-second
green light duration. Signal 2 had a 33-second red light
Figure 8. Modern roundabout application in Ataturk junction.
Figure 9. Mengucek Gazi signalized roundabout phase
durations.
Figure 10. Ataturk grade-separated junction application.
60
70
80
90
100
110
120
130
140
Scenari
o 1
Scenari
o 2
Scenari
o 3
Scenari
o 4
Scenari
o 5
Ave
rage
Que
ue L
engt
h
3600
3700
3800
3900
4000
4100
4200
Scenari
o 1
Scenari
o 2
Scenari
o 3
Scenari
o 4
Scenari
o 5
NO
x (G
ram
) (a)
(b)
Figure 11. a Delay time. b Travel tim.
10 Page 8 of 12 Sådhanå (2021) 46:10
duration, 3-second yellow light duration, and 24-second
green light duration.
3.3 Grade separated junction application
In Turkey, if the volume of traffic in a junction is more than
1800 vehicle/hour/lane, grade-separated junctions should
be considered (46). For that reason, in this study, the sub-
way application was carried out in the east-west direction
where the traffic volume was the highest in Ataturk, Halit
Pasa, Yildiz, and Izzet Pasa junctions in Erzincan city
center. The junction models created were presented in
figure 10.
In figure 10, the 3-dimensional view of the Ataturk
junction was presented on the left and the view from the top
was presented on the right. As the existing geometry at
Ataturk junction permitted, two-lane subways designing. A
single-lane subway was designed according to the existing
geometry at Halit Pasa junction. At Yildiz junction, a sin-
gle-lane subway was designed according to the existing
geometry. At Izzet Pasa junction, a two-lane subway was
designed according to the current geometry.
4. Results
For current conditions and alternative scenarios, delay time,
travel time, queue length, CO2 and NOx emissions, and
speed were obtained and assessed using AIMSUN meso-
scopic simulation. Subsequently, AHP was used as a multi-
criteria decision-making method to determine the appro-
priate solution scenario.
4.1 Assessment of mesoscopic simulation outputs
Scenarios were modeled separately in AIMSUN software,
and the results were obtained in accordance with pre-de-
termined criteria. The scenarios created were revealed
comparatively in terms of the criteria. The graphics of delay
time, travel time, queue length, NOx emission, CO2 emis-
sion, and speed criteria were separately presented below.
According to the values presented in the delay time
chart in figure 11a and b, Scenario 4 had the lowest delay
value, and Scenario 1 was indicated the case with the
highest delay time. According to the values shown in the
10
15
20
25
30
Scenari
o 1
Scenari
o 2
Scenari
o 3
Scenari
o 4
Scenari
o 5
Del
ay T
ime
(Sec
ond)
707580859095
100
Scenari
o 1
Scenari
o 2
Scenari
o 3
Scenari
o 4
Scenari
o 5
Trav
el T
ime
(Sec
ond)
(a)
(b)
Figure 12. a Queue length. b NOx emission.
3384000
3484000
3584000
3684000
3784000
3884000
Scenari
o 1
Scenari
o 2
Scenari
o 3
Scenari
o 4
Scenari
o 5
CO
2 (G
ram
)
3537394143454749515355
Scenari
o 1
Scenari
o 2
Scenari
o 3
Scenari
o 4
Scenari
o 5
Spee
d (K
m/h
)
(a)
(b)
Figure 13. a CO2 emission. b speed.
Sådhanå (2021) 46:10 Page 9 of 12 10
travel time graph, Scenario 4 had the lowest travel time
value, and Scenario 1 had the highest.
According to the values presented in the queue length
chart in figure 12a and b, it seemed that the highest queuing
value appeared in Scenario 1, and the lowest queuing
appeared in Scenario 4. According to the values shown in
the NOx emission graph, it was noticed that the maximum
NOx emission appeared in Scenario 1 and the lowest in
Scenario 4.
According to the values shown in the CO2 emission
graph in figure 13a, it was noticed that the highest CO2
emission appeared in Scenario 1, and the lowest in Scenario
4. According to the values presented in the speed graph in
figure 13b, Scenario 1 was the one with the lowest average
speed and Scenario 5 had the highest average speed.
4.2 Assessment of AHP results
In order to weigh the pre-determined criteria, decision-
makers compared the criteria with the paired comparison
method. In the comparison process, 1-9 scale was used. The
criteria weights were calculated after creating a paired
comparison matrix. The combined weight of all criteria, in
other words, the result matrix, was given in Table 4.
The combined weight of all criteria, in other words the
result matrix, was given in Table 4. According to this
Table, the weights of the criteria as delay time, travel time,
NOx emission, and cost of construction were noticed to be
highest in Scenario 4. Moreover, the highest weights in
terms of CO2 emission and queue length criteria were
obtained in Scenario 4 and Scenario 5. When the AHP
method was employed, it was revealed that Scenario 4 with
the highest combined weight was the optimum option.
Besides, Scenario 1, in other words, the current situation,
was revealed as the most inappropriate scenario.
5. Conclusion
The purpose of this study was to investigate all main
arteries and the junctions of Bahcesaray, Isikpinar, Milli
Egemenlik, Esentepe, Mengucek Gazi, Adnan Menderes,
Cumartesi, Ataturk, Halit Pasa, Yildiz, Izzet Pasa, Men-
guceli, Terzibaba, and Sumer intersections in Erzincan city
center and to offer suggestions to improve delay time,
travel time, queue length, NOx emission, CO2 emission,
and speed values. In accordance with this purpose, the
current situation of the corridors in Erzincan city center and
4 different alternative scenarios were offered and investi-
gated. According to the APS method, the most suit-
able junction type related to the parameters given above
were determined among the alternatives. The results
obtained from the study are presented below.
• In simulations, ‘‘Scenario 1’’ decreased delay time to
9%, ‘‘Scenario 3’’ to 34%, ‘‘Scenario 4’’ to 47%, and
‘‘Scenario 5’’ to 41%.
• In simulations, ‘‘Scenario 2’’ decreased travel time to
11%, ‘‘Scenario 3’’ to 19%, ‘‘Scenario 4’’ to 23%, and
‘‘Scenario 5’’ to 21%.
• In simulations, ‘‘Scenario 2’’ decreased queue length to
7%, ‘‘Scenario 3’’ to 36%, ‘‘Scenario 4’’ to 48%, and
‘‘Scenario 5’’ to 47%.
• In simulations, ‘‘Scenario 2’’ decreased NOx emission
to 5%, ‘‘Scenario 3’’ to 9%, ‘‘Scenario 4’’ to 11%, and
‘‘Scenario 5’’ to 9%.
• In simulations, ‘‘Scenario 2’’ decreased CO2 emission
to 6%, ‘‘Scenario 3’’ to 10%, ‘‘Scenario 4’’ and
‘‘Scenario 5’’ to 13%.
• In simulations, ‘‘Scenario 2’’ increased average speed
to 15%, ‘‘Scenario 3’’ to 26%, ‘‘Scenario 4’’ to 30%,
and ‘‘Scenario 5’’ to 31%.
• The most appropriate alternative according to the AHP
method was obtained in Scenario 4. The improvements
in Scenario 4 were reconstructed for Bahcesaray,
Isikpinar, Ataturk, Yildiz, Izzet Pasa, and Menguceli
junctions as modern roundabouts, optimization of Milli
Egemenlik, Cumartesi, Halit Pasa, and Terzibaba
junctions with the Webster method, and construction
of a signalized roundabout to Mengucek Gazi junction.
• The employability of the AIMSUN software meso-
scopic simulation model was noticed to be possible in
corridor analysis.
In this study, the number and routes of pedestrians on the
corridors and public transportation demands were not
Table 4. Combined weight of all criteria.
Criteria Criteria weights Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5
Delay time 0.186 0.044 0.062 0.213 0.351 0.330
Travel time 0.212 0.043 0.095 0.203 0.343 0.316
Queue length 0.047 0.042 0.062 0.199 0.349 0.349
NOx emission 0.048 0.041 0.102 0.219 0.398 0.240
CO2 emission 0.064 0.037 0.093 0.203 0.333 0.333
Speed 0.116 0.037 0.099 0.207 0.319 0.338
Cost of construction 0.327 0.381 0.350 0.147 0.085 0.037
Combined weights 0.152 0.171 0.188 0.263 0.225
10 Page 10 of 12 Sådhanå (2021) 46:10
modeled. Further research is possible to be carried out
including passenger demands, stops, and passenger routes
for public transportation. Also, in this study, only the peak
hours on days without precipitation were regarded. On
snowy and rainy days, capacity changes at junctions and
roads as a result of the changing characteristic features such
as reducing drivers’ acceleration-deceleration and increas-
ing the following distance. For this reason, it is also rec-
ommended to carry out further researches for peak hours on
rainy days.
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