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European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
Print ISSN: 2054-0957 (Print), Online ISSN: 2054-0965 (Online)
1
SELECTION OF A SUITABLE ELECTRONIC TOLL COLLECTION
SYSTEM
Thompson F. Aderonke, Aliu M. Folasade and Akinyokun K. Oluyomi
Department of Computer Science,
The Federal University of Technology,
Akure, Nigeria.
afthompson@futa.edu.ng sadealiu@gmail.com okakinyokun@futa.edu.ng
ABSTRACT: In this work, the AHP (Analytic Hierarchy Process) is applied to select
a most satisfactory ETC (Electronic toll collection) method. ETC is an applied science
that permits the automation of tariff collections at toll parkways. The ETC technologies
from which selection was done are based on DSRC (dedicated short-range
communication) which includes barcode, quick response (QR) code and radio
frequency identification (RFID). Each of these technologies was analyzed based on five
criteria to optimize the selection process.
KEYWORDS: AHP, ETC, Barcode, RFID, QR code, technology.
INTRODUCTION
Infrastructure is an inclusive name for principal edifices and facilities that are vital to
the growth and development of the present-day wealth of any nation (Adebusuyi, 1994).
Nations that have ensured a meaningful, organized and coordinated approach in
building these infrastructures have experienced significant development over the years
(Beesley, 1973). Consequently, countries that have failed to ensure coordinated
development of their infrastructures end up retarding their development. Toll booths
are fragments of road infrastructures necessary for the maintenance of main roads in
any territory. The major intent of toll booths is to help to bring about income that will
assist in operating and conserving the highways effectively (Lekan, 2015). In 2012, the
Nigerian government announced their plan to re-introduce toll gates on interstate roads.
However, the oddities involved in the management of the toll roads have not been dealt
with. The challenges of fraud, mismanagement, and irresponsibility have not been
addressed. Operational and financial factors are a major challenge for many road
agencies. It is therefore important to carefully consider the toll collection systems and
select the most suitable one before large-scale investment to address these anomalies.
There are many ETC structures with each having its strengths and flaws. One of the
most favorable ETC systems is DSRC which includes barcode and radio frequency
identification (RFID) (Saurabh et al., 2016). The organized implementation toll
acquisition process will lessen the chain of vehicles at the toll centers.
LITERATURE REVIEW
RFID
RFID is a general phrase for recognizing technologies that make use of frequency
waves to identify people or items spontaneously (Roberts, 2006). An absolute RFID
structure is made of a transceiver (tag), reader/writer, antenna, and computer host. The
European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
Print ISSN: 2054-0957 (Print), Online ISSN: 2054-0965 (Online)
2
transceiver, which is also referred to as the tag, is a chip that is integrated with an aerial
or a receiver in a closely-packed manner. The chip has a memory and integrated circuits
to obtain and transmit data to the reader (Ayoub et al., 2009). These tags can be either
passive or active tags. A reader is made up of an antenna that sends and receives data
from the tag. The reader also has a decoder and a radio frequency (RF) module. The
reader could be placed on a platform or could be a portable, handheld mobile device.
The computer host holds the information systems software that acts as the intermediary
between the RFID components and the end-user. The computer system converts the
information acquired from the RFID system to relevant information for the client
(Khadijah et al., 2010).
Figure 1: Working Process of RFID (Faudzi et al., 2013)
Barcode
Barcodes are made up of alternating dark and light lines of various degrees of thickness.
The dark lines are broad, moderate or tiny. When taken in pairs of dark and pairs of
light lines, they represent the digits 0 to 9. Each time a barcode is scanned, a calculation
is carried out to ascertain that it has been scanned examined correctly. Barcodes are
used in library book systems to identify both books and members. They are used in
passport and ID card systems to represent the passport number or identification number
(Leadbetter et al., 2010). A barcode reader is needed to scan a barcode. Barcode
scanners may be immovable or handy. When barcode readers are installed on the
computer, they scan one item at a time and transmit the obtained data. Barcodes are
simple to use, accurate, and quick (Deepashree et al., 2016). Figure 2 shows the image
of a barcode.
Figure 2: A barcode
European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
Print ISSN: 2054-0957 (Print), Online ISSN: 2054-0965 (Online)
3
QR Code
The QR code has black elements (square dots) laid out in a square grid on white
background, which can be read by an image capturing device such as a QR scanner.
The QR code is seen as a digital image by a microchip detector and is subsequently
scrutinized by a microprocessor. It is a two-dimensional barcode that can store more
data than a standard barcode. It has the advantage of high storage capacity, good fault
tolerance, dirt and damage resistance; and versatility (Shital et al., 2014). Figure 3
shows a sample QR code.
Figure 3: A sample QR Code
Deeprashee et al. (2016) and Rohan et al. (2013) made a comparison among barcode,
QR code and RFID. RFID does not require a line of sight to be read as compared to
barcode and QR code. RFID stores more data. However, the barcode is cheaper and
does the same work as RFID but it requires a line of sight to be read. Barcode is more
precise and competent than RFID (Chawla, 2007). RFID is susceptible to diverse
security and privacy threats when viewed from the systems dimension and the area of
information security (Chia-hung, 2009).
AHP
AHP is a multi-criteria decision approach that translates personal appraisals of the
importance of a set of factors to a set of universal scores or weights. It was initially
developed by Thomas L. Saaty (Saaty, 1980). It breaks down a difficulty in a ranking
of criteria and alternatives. The goal must be clear, the criteria must be well-expressed
and the alternatives should be sorted out discreetly. The data may be acquired from
attested values like weight and height; or individual judgment such as belief and
fondness (Kardi, 2006). AHP permits some level of irregularity in judgment since
people are not always stable in their choices. The scale of preferences is extracted from
the concept of principal eigenvectors; and the consistency index is obtained from the
principle of principal eigenvalue. AHP is based on a fixed scale that transforms
subjective feelings into unbiased values and changes qualitative difficulties into
numeric values.
The initial step in the AHP process is to make pair-wise comparisons (judgment
matrix) between each criterion. It is as shown in equation 1.
(1)
European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
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4
Where A = comparison pair-wise matrix,
w1 = weight of component 1,
w2 = weight of component 2,
wn = weight of component n.
To ascertain the comparative values for two elements in the substructure of a matrix A,
pair-wise comparisons are done based on a standard table of comparison (Ming-Chang,
2014). Table 1 shows the comparison scale.
Table 1: Scales for pair-wise comparisons
Level
Degree of Importance
1
Equal value
3
Modest significance of one factor over another
5
The strong or crucial importance
7
Very crucial importance
9
Utmost importance
2, 4, 6, 8
Values for unsure comparison
Bring about a normalized pair-wise matrix by adding the values in each column of the
pair-wise matrix and then dividing each element in the matrix by its column total.
(2)
To generate the weighted matrix, the average of the normalized matrix is calculated by
dividing each row by the number of criteria used. It is given as:
(3)
Furthermore, the consistency vector (λmax) is computed by multiplying the pair-wise
matrix by the weights vector and then dividing the sum of row entries by the correlated
criterion weight.
The regularity of the judgment is checked by calculating the consistency Index (CI) as
seen in equation 4.
λ
(4)
where n is the order of the matrix.
Finally, the consistency ratio is calculated by comparing the CI with the random index
(RI). As a general rule, the judgments are consistent if CR is less than 0.1. The formula
of CR is:
(5)
where the value of RI (Random Index) is shown in the Random Index Table 2.
Table 2: Random Index
n
1
2
3
4
5
6
7
8
9
10
RI
0
0
0.58
0.9
1.12
1.24
1.32
1.41
1.45
1.49
If then the judgment is acceptable, else the judgment should be re-assessed.
European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
Print ISSN: 2054-0957 (Print), Online ISSN: 2054-0965 (Online)
5
RELATED WORKS
Xinpei et al. (2007) examined eco-campus using fuzzy AHP but the method of
evaluation used to acquire fuzzy integration factors was based on assumption. Fang et
al. (2010) applied AHP and Fuzzy Comprehensive Evaluation (FCE) to measure the
harmonious relationship between humans and water to recommend the decision-making
standard for the water resources management of their region. Jin-qui et al. (2014) made
use of AHP and FCE to discover the best coaches from several sports and to grade these
excellent coaches. Saurabh et al. (2014) also presented a subjective-fuzzy decision-
making approach to determine the choicest ETC system for India. Thirteen pivotal
factors were surveyed for the selection of a proper ETC system. It was discovered that
cost was the most crucial yardstick for the selection in India. Furthermore, Zhou et al.
(2017) presented a ubiquitous approach for usability assessment by combining AHP
and the FCE. Waris et al. (2019) used AHP to develop a multi-criteria substructure for
the durable acquisition of construction appliances in Malaysia. AHP method helps in
making decisions based on several criteria.
METHODOLOGY
The toll collection system was analyzed based on five criteria (Reliability, Security of
data, Cost, Maturity and Implementation) and three alternatives (RFID, Barcode and
QR code). This information is arranged in a hierarchical tree as shown in figure 4.
Figure 4: Hierarchical Structure for Toll Collection Method
Decision Factors
A. Reliability (C1): This refers to the ability of the system to work as expected
without creating any delay or confusion.
B. Data Security (C2): This is the ability of the system to protect customers’ data
without posing any malicious threat.
C. Cost (C3): It is the major factor to consider when putting money in new
technology. It includes the cost of acquisition, implementation and
maintenance. It is important to evaluate the financial implication before
embracing recently-acquired technology
D. Maturity (C4): One should make sure that the technology is well known for its
positive as well as negative aspects. If the benefits and shortcomings are not
Toll Collection
Maturity
Implementation
Reliability
Cost
Data Security
RFID
Barcode
QR Code
European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
Print ISSN: 2054-0957 (Print), Online ISSN: 2054-0965 (Online)
6
properly weighed, it may later lead to a total break-down of the entire system,
which will eventually result in a waste of time and resources.
E. Implementation (C5): This determines the workability or the practicability of
the technology based on the country’s financial strength and level of
development. It will be tragic to force a new technology on the citizens if the
system has not been investigated.
RESULTS
In this work, the judgment matrix is determined by an expert decision based on related
research. The implementation was done using Yaahp, software for AHP. Yaahp
provides help to model construction; calculation and analysis for the decision-making
process using AHP. The judgment matrices are shown.
Toll Collection
λmax =5.3639 CR = 0.0812
Reliability
λmax = 3.0649 CR = 0.0624
Data Security
λmax = 3.0649 CR = 0.0624
Cost
λmax = 3.0999 CR = 0.0961
Maturity
European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
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7
λmax = 3.1004 CR = 0.0966
Implementation
λmax = 3.1013 CR = 0.0974
The judgments are consistent since the values of CR are less than 0.1. Table 3 shows
the overall weights for the toll selection.
Table 3: Final Weights for Toll Collection
Element
Weight
Alternatives
Barcode
0.6275
RFID
0.2723
QR Code
0.1002
The Criterion Layer
Data Security
0.5709
Maturity
0.1877
Reliability
0.1365
Cost
0.0588
Implementation
0.0460
Combined Consistency: 0.0724
DISCUSSION
The result indicates Barcode as the highest-ranking toll collection technology with a
percentage of 62.75%. The result also shows that data security is the most pivotal
criterion with a percentage of 57.09%. Figure 5 shows the graphical representation of
the toll collection weights.
European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
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8
Figure 5: Graph showing Toll Collection Weights
CONCLUSION
This work proposes the use of AHP to decide on the most suitable toll collection
technology. The work was structured into a hierarchy based on five criteria and three
alternatives. Data security was found to be the most important criterion for the selection
of the toll collection technology, while barcode technology emerged as the most
appropriate technology. The result can provide an intelligent guide for the selection of
an ETC method for use in Nigeria. Our future work will combine Fuzzy Comprehensive
Evaluation (FCE) with AHP to capture some uncertainties.
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European Journal of Computer Science and Information Technology
Vol.8, No.2, pp.1-9, April 2020
Published by ECRTD- UK
Print ISSN: 2054-0957 (Print), Online ISSN: 2054-0965 (Online)
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