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European Journal of Applied Sciences – Vol. 12, No. 6
Publication Date: December 25, 2024
DOI:10.14738/aivp.126.18149.
Guidana, G. F., Kali, A., & Tanone, D. (2024). Using the ELECTRE Tri Method to Categorize Roads: The Case of the Ngaoundéré
Town in Cameroun. European Journal of Applied Sciences, Vol - 12(6). 847-859.
Services for Science and Education – United Kingdom
Using the ELECTRE Tri Method to Categorize Roads: The Case of
the Ngaoundéré Town in Cameroun
Guidana, Gazawa Frédéric
Department of Mathematics and Computer Science,
Ngaoundéré of University, Cameroun
Abdelaziz Kali
Ngaounderé University,
Department of Mathematics and Computer Science
Tanone, Demas
Ngaounderé University,
Department of Mathematics and Computer Science
ABSTRACT
A road network is the set of roads that enable people and goods to move from one
point to another. It provides access to important infrastructures such as health and
education services. In Cameroon, the road network inherited from the colonial era
poses major challenges. The case of Ngaoundéré, capital of the Adamaoua region, a
transit city between the regions of the far south of Cameroon and the far north, sees
its road networks frequently used. Given the increase in traffic, poor user behavior
and deterioration, the problem of road safety (assaults, frequent accidents) and the
deterioration of the means of locomotion, which contributes most to greenhouse
gas emissions (GHG), has arisen. This work involves assigning the various roads to
distinct categories in order to highlight potentially dangerous roads requiring
special attention. To do this, we'll be building a more or less exhaustive, coherent
and non-redundant set of criteria enabling a multi-criteria evaluation of these
different roads. Seven relevant and coherent criteria (distance, type, condition,
season, infrastructure, behavior and aggression) were selected. We used the
ELECTRE Tri method, derived from the AMCD assignment problem, to categorize
these roads. After a robustness analysis, this method enabled us to identify at-risk
roads in the city of Ngaoundéré from among 42 essential ones. Some 95.24% of
Ngaoundéré's roads are poor and 4.76% are hazardous. According to these criteria,
the city does not have any roads in the Good or Very Good categories.
Keywords: Road safety, Assignment, ELECTRE Tri, Road, AMCD.
INTRODUCTION
A road network is the set of roads used to move people and goods from one point to another. It
provides access to important infrastructures such as health and education services. In
Cameroon, the primary objective of road infrastructure was to facilitate the export of natural
resources to Germany (1884-1916) and France (1916-1960). After independence, they remain
a major development problem, particularly in urban areas [1]. Cameroon records an alarming
number of people who lose their lives or are seriously injured in road accidents [2]. Plus de
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European Journal of Applied Sciences (EJAS) Vol. 12, Issue 6, December-2024
3000 cas d’accident de la route sont enregistrés au cours de l’année de 2024 [3]. Infrastructure
deterioration, traffic jams, traffic accidents and many other problems related to human life are
topical issues in cities [4].
THE EXISTING RANKING METHOD
Thus, it is important and very urgent to categorize the road networks of certain cities in order
to help the State and the population in the intervention as well as its use. Several studies have
been carried out on road networks, highlighting their importance in the connectivity and
construction of public space in Cameroon [5], [6]. Similarly, the ELECTRE Tri method was used
to prioritize drainage sections and identify the most deteriorated sections in Alsace [7]. The
detection of hazardous roads in Khorasan province was carried out using hybrid AMCD
methods [8]. In addition, AMCD has been used to assess multimodal accessibility and the
contribution of roads to sustainable development [9]. A hybrid multicriteria approach
combining three methods and artificial intelligence as well as the notion of fuzzy logic was used
to categorize roads in 27, wilaya of Oran, Alsace and Iran [10] [9], [11], [12]. There was also a
question of prioritizing road maintenance, in which roads are evaluated and ranked according
to various criteria [13]. The evaluation of public road policies in Cameroon was carried out
using the matching method in order to reach the most disadvantaged strata [14]. For our study,
we chose to use the ELECTRE Tri multicriteria method, recognized for its ability to handle
complex problems involving varied and often contradictory evaluation criteria [15], [16] in
order to assign the various roads in the city of Ngaoundéré to predefined categories.
MATERIALS AND METHODS
The city of Ngaoundéré, located in the Adamaoua region of Cameroon, with a surface area of
17,196 km2, is a strategic city linking the various regions of Cameroon from north to south. It is
also a commercial crossroads, attracting populations of diverse origins. Despite the importance
of its progressive development, its roads have serious infrastructure problems such as a high
state of deterioration, frequent traffic jams, insufficient signposting, lack of maintenance and
many other problems such as insecurity [17]. We used the urban map of Ngaoundéré, various
geographical tools and data collected on the various roads, based on the criteria selected, to
draw up a database of Ngaoundéré's essential roads in order to assign them to predefined
categories [18].
Evaluation Criteria Used
Multicriteria evaluation consists in assessing or enabling decision-makers to make better, more
consistent decisions [19] Thus, the coherent, non-redundant and exhaustive evaluation criteria
used in our study are:
• distance: research has shown that the longer and more isolated the journey, the higher
the number of high-speed accidents [20];
• type of road (National, Regional, Urban and Departmental: a criterion for distinguishing
roads according to their physical characteristics and the traffic they carry. It also enables
the implementation of safety measures adapted to each type of road [21], [22];
• Road condition (tarmac, earth, cobblestone): this is a factor contributing to accidents
when it is poorly maintained or contains potholes or cracks;
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Guidana, G. F., Kali, A., & Tanone, D. (2024). Using the ELECTRE Tri Method to Categorize Roads: The Case of the Ngaoundéré Town in Cameroun.
European Journal of Applied Sciences, Vol - 12(6). 847-859.
URL: http://dx.doi.org/10.14738/aivp.126.18149
• Season: this criterion is important in categorizing roads, as weather conditions vary
throughout the year and can have a significant impact on the risk of road accidents [23],
[24];
• Infrastructures : the lack of road signs, darkness, can progressively increase the risk of
accidents [25] and the proximity of a school, market, road signs on each road also
explores the importance and relevance in the categorization of roads [26], [27], [28];
• User behavior (Prudent, educated, reckless, ...) are the major cause of road accidents [29];
• Aggression per week: is an essential element as a criterion when categorizing roads.
Physical aggression, harassment and vandalism are all behaviors that can lead to road
[30];
• Accidents case: It is also important to know whether there have been any accidents on
the section in the past. When this is affirmed, it is also essential to know the frequency
per week, month or year.
It's important to note that these criteria are not exhaustive, and that there are many other
factors that can affect road safety. However, these criteria are a good starting point for
understanding the causes of road accidents [31].
Data Standardization
In this section, we model categorical or qualitative data as numerical data, thus scaling from 1
to 5 to facilitate calculations and visualization (Table 1).
Tableau 1 : Characterization of evaluation criteria
Criteria Type Standardized values Direction
Distance Numeric value En Km Assending
Type Enumerated value National = 1, Regional = 2, Departmental = 3, Urban
= 4
Descending
Condition Enumerated value Earth = 1, Tared = 2,
Paved = 3, Iron = 4
Descending
Season Enumerated value Rainy = 1, Dry = 2 Assending
Infrastructures Boolean Nil, fair, good, Excellent Assending
Behavior Enumerated value Prudent = 1, Imprudent = 2 Descending
Aggression Enumerated value Frequent = 1, Less frequent = 2, never mentioned =
3
Descending
Accident Enumerated value Not yet = 6, Rarely = 4,
Frequently = 2, very frequently = 0
Assending
Pr4 = very good, Pr3 = Good, Pr2 = Bad, Pr1 = Dangerous
We present the routes implemented and the evaluation criteria used, along with a detailed
description of each route in Table 2.
Table 2: Performance table
Roads g1 g2 g3 g4 g5 g6 g7 g8 Roads description
R1 0.830 4 2 1 3 2 1 Carrefour Trois-Mala at the Grand marché
R2 0.800 4 2 1 2 2 1 Marhaba in social housing
R3 0.616 4 2 1 2 1 1 The road to Garwa Boullaye