The impacts of traffic signal timings optimization on … · The impacts of traffic signal timings optimization on reducing vehicle emissions and fuel consumption by Aimsun and Synchro

INTERNATIONAL JOURNAL OF CIVIL AND STRUCTURAL ENGINEERING

Volume 5, No 2, 2014

© Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0

Research article ISSN 0976 – 4399

Received on September, 2014 Published on November 2014 144

The impacts of traffic signal timings optimization on reducing vehicle

emissions and fuel consumption by Aimsun and Synchro software's (Case

study: Tehran intersections) Ali Mansour Khaki1, Pegah jafari Haghighat Pour2

1-Associate Professor, Department of Civil Engineering, University of Science and

Technology, Tehran, Iran.

2- Ph.D Candidate in Transportation of Tehran Payame Noor University, Tehran, Iran

[email protected]

doi: 10.6088/ijcser.2014050014

ABSTRACT

Considering the fact that in recent years the transport sector allocated considerable fuel

consumption and emissions, evaluating issues related to fuel consumption and air pollution is

one of the most important issues of transport sector. Estimate of fuel consumption models

and emissions are new issues that discussions of various models have been published in Iran

and different countries. But assessing the impact of traffic signal timing optimization on fuel

consumption and emissions is one of the new and important subjects that have significant

effect on emissions and economics. Therefore, 5 Intersections of Tehran in 5 different areas

selected for the case study and studied period in traffic simulation and optimization to address

problems related to emissions were in 2013 in this thesis. Traffic data and parameters that

related to emissions and fuel consumption is obtained as ADT in days of October in studied

year. After optimization, the validity and accuracy of project have been used by Aimsun

software and it was observed that traffic signal timing optimization have significant reduction

in emissions and fuel consumption. The considerable results of this research can be cited to

Synchro software application in traffic signal timing optimization. For example, after

optimization fuel consumption has been decreased about 0.25%, 0.17% in AM peak time and,

3.63%, 2.46%, in PM peak time at Mahalati-10 farvardin, Shariati-Dolat intersections

respectively.

Keywords: Intersections, optimization, reduction in vehicle emissions and fuel consumption,

traffic signal timings.

1. Introduction

The transportation sector in Iran accounts for about 35% of total energy consumption and

nearly 70% of total oil consumption (Energy and Economic magazine). Heavy reliance on

fossil fuels might have accelerated climate change, and threatened energy security and public

health. Ever increasing concerns on energy and emissions have led the transportation sector

to mitigate the adverse impacts on vehicle emissions and fuel consumption.

It has been widely accepted that improving traffic flow has been one of the strategies to

reduce vehicle emissions and fuel consumption. In urban areas, frequent stop-and-go driving

and excessive speed variations contribute to higher fuel consumption and emissions. While

traffic signal timing optimization can reduce the number of stops and maintain moderate

vehicle speed, little is known of the impact of direct optimization for minimizing fuel

consumption or emissions, especially using a transportation planning-level microscopic

traffic simulator. Today, improving the flow of traffic is acceptable as one of the effective

The impacts of traffic signal timings optimization on reducing vehicle emissions and fuel consumption by

Aimsun and Synchro software's (Case study: Tehran intersections)

Ali Mansour Khaki,Pegah jafari Haghighat Pour

International Journal of Civil and Structural Engineering 145

Volume5 Issue2 2014

methods of reducing emissions and fuel consumption. Therefore other methods, such as

traffic management, timing optimization is important to reduce delays. High volume of

stopped vehicles without engine operation cause to waste large amount of fuel and emissions.

So traffic signal timing optimization by using simulation and optimization software at the

microscopic level transportation planning can make a direct impact to minimize fuel

consumption and emissions.The objective of this article is to quantify the impact of traffic

signal timing optimization on fuel consumption and emissions. The proposed method consists

of the combination as traffic simulation, timing optimization using the related software. Also

comparison of different software to select the best optimization method is done.

2. Literature review

L.Adacher has been provided the article, a global optimization approach to solve the traffic

signal synchronization problem. In this study investigates the Traffic Signal Synchronization

is a traffic engineering technique of matching the green light times for a series of

intersections to enable the maximum number of vehicles to pass through, thereby reducing

stops and delays experienced by motorists. Synchronizing traffic signals ensures a better flow

of traffic and minimizes gas consumption and pollutant emissions. The objective function

used in this work is a weighted sum of the delays caused by the signalized intersections. In

this paper, they apply generalized 'surrogate problem' methodology that is based on an on-

line control scheme which transforms the problem into a 'surrogate' continuous optimization

problem and proceeds to solve the latter using standard gradient-based approaches while

simultaneously updating both actual and surrogate system states. They extend a `surrogate

problem' approach that is developed for a class of stochastic discrete optimization problems

so as to tackle the traffic signal synchronization problem to minimize the total

delay .Numerical experiments conducted on a test and a real networks show that the surrogate

method converges in a very small area (Adacher L, 2012).

Li Jie, et al have been provided the article, Calibration of a microscopic simulation model for

emission calculation. In this article they indicated that Emissions by road traffic can be

reduced by optimizing traffic control. The impact of this optimization on emission can be

analyses by simulation. The simulation programs used for this analysis should be valid with

respect to the traffic characteristics that determine the emissions. Thus calibration of the

parameters is a prerequisite. In most cases, volumes, travel times and queues are used to

calibrate simulation models, rather than detailed driving characteristics such as speed and

acceleration patterns. However, these driving behavior parameters determine the vehicular

emissions to a great extent. A study was carried out in which the driving behavior parameters

in a microscopic simulation model (VISSIM) were calibrated using real trajectories collected

by image processing at an intersection in Rotterdam. The sensitivity of the simulation results

for driving behavior parameters was investigated. The most influential parameters were

identified and adjusted to ensure that the simulation results were consistent with the observed

traffic and could provide valid estimations of the total production of emissions (Henk Van

Zuylen, 2012).

3. Methodology

Several factors affect the traffic signal timing, fuel consumption and emissions at

intersections. These parameters are increasing and decreasing of vehicle speed, the input

vehicles volume, type of traffic signal phasing, type of lane, effective green time, cycle length

and etc.





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Traffic signal timing have optimized due to Iran standards after identifying the main factors

affecting traffic signal timing and considering the simulation software. Intersection’s

information related to traffic signal has been obtained from comprehensive traffic company.

finally a comparison have done between the software and the appropriate software in terms

of time, speed and accessibility that could reduce emission and fuel consumption well.5

intersections for case study are Golbarg-Dardasht, Kamali-Karegar, Mahalati-10farvardin,

Shariati-Dolat, Zibadasht-Dehkadeh. Research process are presented in the following graph.

Figure 1: Study methodology

4. Case study

5 intersections from Tehran city in 5 different areas consist of north, south, center, east, west

have selected for giving conclusions and case study. We just introduce some information of 2

intersections because the traffic information and emission parameters for 5 intersections are

enormous and cannot propose in this study. As noted, equivalent coefficients accordance with

urban road regulations is used to convert public transport and motorcycles volumes to

passenger vehicles.

4.1 Traffic information of Shariati-Dolat intersection (north Area)

This intersection is shown in Figure 1 .at this intersection Dolat Street is sideway and from

East to West has 3 lanes and also from north to south and south to north has 3 lanes.

Emamzadeh Street as two-lane Minor Street enters to intersection. Intersection angle is 90

degrees. And has an intelligent 2 phase signal traffic. It also has separate turn right and turn

left from East to west. Cycle length in AM peak and PM peak time are 80 and 69 seconds

respectively. Traffic volume in AM peak time in main road is 2202vehicles and 1993

vehicles in lateral direction and 2128 vehicles in main road and 1502 vehicles in PM peak

hours along the lateral direction in 2013.

5.2 Second simulation with Aimsun traffic simulator

The proposed output in table 1 and 2 were obtain after optimizing and putting the traffic

information into Aimsun simulator software by second simulation in compare with first

simulation. As observed in tables with decreasing in cycle length, delay and traveled time,

fuel consumption and emissions have been decreased and traffic flow, average speed

increase. It is noteworthy that the estimated fuel consumption or emissions should be carried





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out according to the amount of traffic flow. It can be seen that the overall amount of delay,

fuel consumption and emissions have been effectively reduced with little accuracy in results

of Secondary simulation and compare them with traffic flow.

Figure 2: Shariati-Dolat Intersection

4.3 Traffic information of Mahalati-10 farvardin intersection (south area)

This intersection indicates in fig 2.at this intersection Mahalti Street from East to West has 5

lanes and 10 farvardin streets from north to south and south to north has 4 lanes. Intersection

angle is not 90 degrees. And has an intelligent 3 phase signal traffic. It also has separate turn

in 4 directions. Cycle length in AM peak and PM peak time are 85 and 98 seconds

respectively. Traffic volume in AM peak time in main road is 2936 vehicles and 1516

vehicles in lateral direction and 3628 vehicles in main road and 1414 vehicles in PM peak

hours along the lateral direction in 2013.

Figure 3: Mahalati-10 farvardin Intersection

4.4. Simulation and optimization results

4.4.1First simulation with Aimsun traffic simulator

5 intersections studied geometrical plan is the first and most important step to enter data into

the Aimsun software. In this section the background of geometric design in AutoCAD format

or the images from Google earth or Google maps put into the Aimsun software as layout

before drawing the intersections plan.





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4.4.2 Optimization with synchro software

After the initial simulation and obtain outputs such as delay time, traveled distance, traffic

flow, vehicle average speed, travel time, fuel consumption and emissions like HC, CO, NOX

by Aimsun software. Signal timing optimization is done by Synchro software.Overall the rate

of cycle length about 27.05,10 % have been decreased at Mahalti-10 farvardin and Shariati-

Dolat intersections than previous case before optimization in AM peak time and also

41.83 ,31.88 % have been decreased in PM peak time respectively.

Figure 4: Geometric plan of Mahalti-10 farvardin Intersection

Figure 5: Geometric plan of Shariati-Dolat Intersection

Figure 6: Cycle length and Geometric plan of Mahalti-10 farvardin Intersection before

optimization in AM peak time by Synchro software





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Figure 7: Cycle length and Geometric plan of Shariati-Dolat Intersection before optimization

in AM peak time by Synchro software

Figure 8: Cycle length and Geometric plan of Mahalti-10 farvardin Intersection before

optimization in PM peak time by Synchro software

Figure 9: Cycle length and Geometric plan of Shariati-Dolat Intersection before optimization

in PM peak time by Synchro software





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Figure 10: Cycle length and Geometric plan of Mahalti-10 farvardin Intersection after

optimization in AM peak time by Synchro software

Figure 11: Cycle length and Geometric plan of Shariati-Dolat Intersection after optimization

in AM peak time by Synchro software

By examining changes in tables and considering traffic flow, it can be seen that the amount of

delay, fuel consumption, emissions such as HC, CO, NOX and travel time have been

decreased with improving cycle length and the rate of traffic flow, vehicles average speed

increased in both AM and PM peak hours at each intersection. Thus providing accurate traffic

signal timing optimization algorithms at intersections in Synchro software and observing

changes in Aimsun traffic simulator could provide significant reduction in fuel consumption

and emissions.After second simulation in Aimsun software the percent of flow /capacity in

AM peak time are represent as sample in figure 13 and 14.

Figure 12: Cycle length and Geometric plan of Mahalti-10 farvardin Intersection after

optimization in PM peak time by Synchro software





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Figure 13: Cycle length and Geometric plan of Shariati-Dolat Intersection after optimization

in PM peak time by Synchro software

Table 1: Output from second simulation, compared with the first simulation at Mahalati-10

farvardin intersection by Aimsun software

Current

case unit

AM

peak time

in first

simulation

AM Peak

time in

second

simulation

PM

peak time

in first

simulation

PM Peak

time in

second

simulation

Delay

time

s/k

m 57 55.7 68.6 61.6

Traffic

flow

Veh

/hr 4614 4677 5050 5980

Average

speed

Km

/hr 35.6 35.7 33.7 34.6

Travel

time

s/k

m 124 122.6 135.2 128.4

Traveled

distance km 1573 1562 1767.6 1741.8

Fuel

consumption liter 198 197.5 225.4 217.2

CO Kg 22.4 22.3 26.2 25.1





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HC Kg 1.75 1.2 2.1 1.9

NO Kg 0.36 0.30 0.42 0.39

Table 2: Output from second simulation, compared with the first simulation at Shariati-Dolat

intersection by Aimsun software .

Current

case

uni

t

AM

peak time in

first

simulation

AM Peak

time in

second

simulation

PM peak

time in first

simulation

PM Peak

time in

second

simulation

Delay

time

s/k

m 74.6 71.9 52.4 39.7

Traffic

flow

Ve

h/hr 4332 4406 3619 3643

Average

speed

Km

/hr 31 31 35.9 37.2

Travel

time

s/k

m 142.9 140.4 120.7 108.1

Traveled

distance km 1032.6 1050.9 850.1 847.2

Fuel

consumption

lite

r 200.90 200.24 133.9 130.6

CO Kg 20.2 19.1 13.7 12.8

HC Kg 1.5 1.38 1 0.91

NO Kg 0.39 0.19 0.25 0.13

Figure 14: The percent of flow/capacity in AM peak time at Mahalati-10 farvardin

intersection





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Figure 15: The percent of flow/capacity in AM peak time at Shariati-Dolat intersection

5. Conclusions

The review of previous studies in Iran and other countries indicated that extensive research

on traffic signal timing optimization to reduce delay time, total travel time and queue length

have done. However, few of these studies regarding the traffic signal timing optimization on

reducing fuel consumption and emissions. As was pointed out during the study, traffic signal

timing optimization and simulation can influence to reduce fuel consumption and emissions,

such HC, CO, NOX. So 5 intersections as case study have selected in this article. Traffic

information, geometric design and traffic signal timing enter to Aimsun software as the first

step for simulating. After simulation primary output such as delays, traffic flow, traveled time,

traveled distance, vehicles average speed ,fuel consumption and emissions have

acheived.Then optimization has done with synchro and to observe changes, second

simulation considered in this study. For sample percentage changes of Mahalati-10 farvardin

intersection are given in table 3.

Table 3: percentage changes of Mahalati-10 farvardin intersection

Current case unit

Percentage

changes in AM

peak time

percentage

changes in

PM peak time

Delay time s/km -2.28% -10.20%

Traffic flow Veh/

hr +1.36% +18.41%

Average

speed

Km/

hr +0.28% +2.67%

Travel time s/km -1.12% -5.02%

Traveled

distance km -0.69% -1.45%

Fuel

consumption liter -0.25% -3.63%





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CO Kg -0.44% -4.19%

HC Kg -31.42% -9.52%

NO Kg -16.66% -7.14%

Acknowledgement

This research was taken from Pegah Jafari Haghighatpour thesis and supported by

Department of Engineering, Islamic Azad University South Tehran Branch of Tehran, Iran.

The authors are grateful to Tehran Traffic Control Company and Dr Ali Mansourkhaki of

Civil Engineering department, University of Science and Technology for his help with this

thesis.

6. References

1. Energy and Economic magazine, International number: 1123-15632012, Tehran. Iran.

2. Adacher L., (2012), “A global optimization approach to solve the traffic signal

synchronization problem”, Procedia - Social and Behavioral Sciences, Published by

Elsevier Ltd. 54, pp 1270-1277.

3. Henk Van Zuylen, et al, (2012), Calibration of a microscopic simulation model for

emission calculation, Published by Elsevier Ltd, Transportation Research Part C, 31

pp 172–184.

4. Tehran traffic control company, October of 2013.

5. Aimsun 6.0.5 Simulation traffic software.

6. Synchro 8, Optimization and simulation traffic software.

Documents

The impacts of traffic signal timings optimization on … · The impacts of traffic signal timings optimization on reducing vehicle emissions and fuel consumption by Aimsun and Synchro