L. Jácome, W. Jaramillo and S. Jaramillo

“Trac Congestion in Ecuador: A Comprehensive Review, Key Factors, Impact, and Solutions of Smart Cities”,

Latin-American Journal of Computing (LAJC), vol. 12, no. 1, 2025.

Trac Congestion

in Ecuador: A

Comprehensive Review,

Key Factors, Impact, and

Solutions of Smart Cities

ARTICLE HISTORY

Received 18 September 2024

Accepted 29 October 2024

Jácome-Galarza Luis-Roberto

Faculty of Technical Sciences

Universidad Internacional del Ecuador, UIDE

Loja, Ecuador

roberto.jacome@gmail.com

ORCID: 0000-0002-2886-3372

Jaramillo-Sangurima Wilson-Eduardo

Faculty of Architecture, Design and Art

Universidad Internacional del Ecuador, UIDE

Loja, Ecuador

wijaramillosa@uide.edu.ec

ORCID: 0000-0002-4058-5053

Jaramillo-Luzuriaga Silvia-Alexandra

Faculty of Business School

Universidad Internacional del Ecuador, UIDE

Loja, Ecuador

sijaramillolu@uide.edu.ec

ORCID: 0000-0003-0335-4325

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

Traffic Congestion in Ecuador: A Comprehensive

Review, Key Factors, Impact, and Solutions of

Smart Cities

Jácome-Galarza Luis-Roberto

Faculty of Technical Sciences

Universidad Internacional del Ecuador,

UIDE

Loja, Ecuador

roberto.jacome@gmail.com

ORCID: 0000-0002-2886-3372

Jaramillo-Sangurima Wilson-Eduardo

Faculty of Architecture, Design and Art

Universidad Internacional del Ecuador,

UIDE

Loja, Ecuador

wijaramillosa@uide.edu.ec

ORCID: 0000-0002-4058-5053

Jaramillo-Luzuriaga Silvia-Alexandra

Faculty of Business School

Universidad Internacional del Ecuador,

UIDE

Loja, Ecuador

sijaramillolu@uide.edu.ec

ORCID: 0000-0003-0335-4325

Abstract—This study explores the main sources of traffic

congestion in Ecuadorian cities and proposes solutions to address

this issue. The findings reveal that the main causes are natural

disasters which disrupt the transportation infrastructure and leading

to chaotic traffic flow, lack of infrastructure maintenance,

inadequate education, cultural issues, improper traffic signal timing,

or the absence of exclusive lanes for public transportation. Fast

transit projects have also faced obstacles, including absence of

political leadership, complications in the implementation, rushed

planning processes, resistance from stakeholders like bus operators,

and inaccurate cost estimations. Vehicle pollution is another

consequence of lower-quality fuel and the topography of highland

cities, which demand more engine power. The proposed solutions

are categorized into three types: smart city technologies,

implementing regulations, and enhancing public transportation

systems. To address traffic accidents, it is recommended to identify

high-risk areas, monitor fleet variables of buses, educate the

population on responsible driving practices, and implement

designated driver applications. By considering and implementing

these solutions, Ecuadorian cities can alleviate traffic congestion,

enhance transportation efficiency, reduce pollution, and improve

road safety.

Keywords—smart cities; urban planning; vehicular traffic; data

mining; optimization

I. INTRODUCTION

Traffic congestion in Ecuador has become a significant

problem, increasing travel times, fuel consumption, and

negative environmental impacts. However, analyzing traffic

congestion can provide invaluable insights that can lead to the

development of more efficient transportation systems.

Even though the use of smart solutions can improve traffic

congestion, they are not always applicable in developing

countries due to many factors. They include poor

infrastructure, such as roads and traffic signs in bad conditions

which are not useful for intelligent traffic lights, autonomous

vehicles, or automated transportation systems. Urban planning

is another challenge, as many Latin-American cities grow

disproportionately. Additionally, culture and lenient laws

contribute to this issue, with many drivers who do not follow

the traffic rules. High-costs of technology are also a problem,

as the implementation and operation of smart traffic solutions

can be unaffordable in many countries; or the characteristics

of territory: the topography of the land, the risks of natural

disasters. However, it is important to identify those

technological solutions that can be suitable for the

characteristics of countries like Ecuador.

Researchers have also focused on studying this problem.

Their valuable contributions have enriched our understanding

of traffic congestion and have led to innovative solutions. We

cite some of their effort to improve transportation systems in

the aforementioned country.

In [1], they remark that in cities like Babahoyo, the

inhabitants prioritize using private cars instead of the public

transportation system. In [2], they proposed an increase in

teleworking in Ecuador to tackle the traffic congestion

problem, and he analyzes the economic and environmental

costs of commuting from home to the workplace and its

possible benefits and savings. In [3], they reported that urban

planning is not considered on a practical basis in cities like

Cuenca where its uncontrolled growth makes the city look

disorganized and unsustainable. In [4], they used the Health

Economic Assessment Tool (HEAT) to calculate the

economic benefits of using the bicycle as a means of

transportation. The study was conducted in the city of Cuenca

and it obtained encouraging results even for small distances.

[5] builds a mobile application for collecting traffic

congestion data in the urban regeneration area in the city of

Loja. In [6], they characterized the causes of accidents in

Ecuador during the years 2015 to 2018, their findings suggest

that lack of attention, drunkenness, excess speed, or changing

lanes are the main causes of accidents in Ecuador. In contrast,

the report by the Transit National Agency (ANT) for the first

quarter of 2024 [58] indicates that the main causes of

accidents include the driver’s lack of skill and recklessness

(39.30%), speeding (18.57%), failure to obey traffic signs

(18.30%), and drunkenness (8.57%), among others. Solutions

for reducing traffic accidents include conducting driver exams

that assess both practical and theoretical knowledge, public

strategic, tactic, and operational policies, and implementing

technological solutions. These technologies may include

vehicle-to-vehicle communications, the internet of vehicles

model, smart lampposts with LED lights, wi-fi, and cameras,

roadside units for helping near vehicles.

Ecuadorian cities have their necessities, challenges, and

characteristics regarding traffic management. Our study

performs a comprehensive analysis of traffic congestion in

Ecuadorian cities, that identifies the specific causes of traffic

congestion and, on the other hand, the technological and

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

L. Jácome, W. Jaramillo and S. Jaramillo

“Traffic Congestion in Ecuador: A Comprehensive Review, Key Factors, Impact, and Solutions of Smart Cities”,

Latin-American Journal of Computing (LAJC), vol. 12, no. 1, 2025.

innovative solutions for traffic management that have been

implemented in the country highlighting their impact and

feasibility.

This paper continues with section 2 Materials and Methods

in which we describe the methodology used for conducting

this review and introduce the research questions. Section 3

Results describes the analyzed papers and provides answers to

the research questions. Finally, the conclusions of the paper

are presented.

II. M

ATERIALS AND METHODS

To conduct the present research, we use the methodology

proposed by [7], which suggests the following steps: a)

formulate the research questions, b) conduct the search

process, c) establish the inclusion and exclusion criteria, d)

carry out the data extraction, and complete the data analysis

and classification.

A. Research questions

RQ1: “What are the main sources of traffic congestion in

Ecuadorian cities?”

RQ2: “What solutions have been proposed to reduce the

traffic congestion in Ecuadorian cities?”

B. Conduct the research process

Next, we conducted a manual search in scientific

databases with the search string “traffic congestion Ecuador”

by means of the filter of retrieving papers from the year 2020,

obtaining the following number of papers: Google Scholar

3150, Springer Link 694, ScienceDirect 157, IEEE Xplore 24,

and Scopus 5.

C. Establish the inclusion and exclusion criteria

We consider the inclusion criteria: full papers written in

English or Spanish that focus on studying the impact of traffic

congestion or proposing solutions for traffic congestion in

Ecuadorian localities.

We excluded papers published more than four years ago

and those papers that fell below our quality evaluation criteria,

obtaining a final selection of 50 papers.

D. Carry out the data extraction, and complete the data

analysis and classification

For the data extraction part, we read the paper abstracts

and conclusions, if the content was pertinent we continued

reading the whole paper and retrieved the relevant information

for the research questions.

The Fig. 1 shows the number of papers found in each

scientific repository throughout the research process.

Fig. 1. Research process.

III. RESULTS

A. Categorization of the analyzed papers

In Table I, we list the analyzed papers and the purpose of

the study.

TABLE I. LIST OF ANALYZED PAPERS

Paper id

Purpose of the study

[8], [35], [36], [42], [55] Proposing electric vehicle solutions

[9], [10], [15], [16], [17],

[22], [25], [27], [28], [40],

[43], [44], [46], [47]

Modeling traffic congestion

[11] Traffic light timing, bus itinerary planning

[12], [19], [21], [23], [29],

[30], [48], [33]

Implementing traffic prediction models

[13], [14], [18], [20], [24],

[26], [31], [34], [39], [50],

[51], [56]

Pollution estimation due to traffic

[37], [45] Improving route infrastructure

[32], [37], [38], [41], [49],

[52], [53], [54], [57]

Implementing smart city solutions

B. Description of the contribution of each analyzed paper

Next, we extracted the contribution of each paper for the

present study.

In [8], they analyzed the cost of operation of electrical

buses compared with traditional diesel buses. The experiment

was conducted in the 3 best-performing bus lines in the city of

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

Cuenca. A major challenge is the installation of fast charging

stations for EVs in cities. The opportunity relates to the low

cost of electricity in Ecuador.

In [9], they conducted a study of traffic congestion in the

avenues America and Reales Tamarindos in Portoviejo city,

finding a C level of service where the HCM (High Capacity

Manual) standards indicate that A level of service corresponds

to <10 delays per vehicle (s/veh), B corresponds to >10-20

s/veh, C corresponds to >20-35 s/veh, and D means >35-55.

In [10], they proposed a traffic congestion model that uses

6 density-flow equations and 6 speed-density equations to

predict traffic conditions. The data is taken from Google

traffic information where a green line means no traffic delays,

an orange line represents medium traffic, a red line represents

traffic congestion, and a darker red line represents a slow

speed due to traffic congestion.

In [11], they conducted a study of traffic congestion on

“Pedro Menendez Gilbert” avenue in Guayaquil city. The

study suggests that instead of widening the avenue it should

improve the traffic light cycle times and build an exit of the

avenue which is less expensive and would give better results

in the long term.

In [12], they proposed a traffic congestion prediction

model that identifies interest origin and destination points in

the city of Quito. The data is collected with the Google

distance matrix tool. Interest points are grouped by clustering

models, the taxi cars should be electrical and the rapid

charging stations should be near interest points.

In [13], they introduced a visual recognition system that

notifies via SMS when a driver transits in an restricted lane of

the metrovia public transport network in Guayaquil city. The

system issues a fine when the vehicle uses this lane and

notifies the owner with an SMS message. The detection rate

is 78.04%. The challenges faced are the calibration of the

inclination angle of the camera, the resolution of the

Raspberry Pi camera, and the need for a better algorithm to

recognize the vehicle plates.

In [14], they presented an estimation of greenhouse gas

emissions in the cities of Ibarra and Guayaquil. They use

OpenStreetMap and the SUMO simulation software. The

simulations predict the amount of carbon monoxide and

dioxide, hydrocarbons, fine particles, and nitrogen oxides,

estimating the contribution of gases from cars, trucks,

motorcycles, and buses. The challenges include the

complexity of extending the study to a larger area, the

COVID-19 pandemic, and the use of manual counting of

vehicles. They recommend the use of smart parking systems,

and the use of simulation tools like SUMO before building

city infrastructures like new roads.

In [15], they reported a study of vehicle congestion in the

“Miguel Alcivar” and “Avenida del Ejercito”, “Avenida

Reales Tamarindos” and “P. E. Macías”, and “Avenida

Manabi” and “Tennis Club” in the city of Portoviejo. The

findings reveal the use of private cars with 64.83%,

motorcycles with 24.54%, bicycles with 6.40%, trucks with

3.76%, and buses with 0.47%. They recommend the use of

sharing cars, increasing the frequency of buses, implementing

new road spaces for bicycles, and educating the inhabitants of

the city about the transit rules and the right use of the roads.

In [16], they presented a diagnosis of the urban mobility in

the city of Bahía de Caráquez, it is found bad conditions on

many streets due to natural disasters and lack of maintenance,

lack of infrastructure for pedestrians and bicycles, the

presence of unregulated parking lots, and inefficient public

transportation. Private cars are preferred by 39% of the

population while public transportation (buses, taxis, tricycles)

are preferred by 32%. The solutions are the creation of

“pedestrian islands” that are safe, comfortable, and exclusive

areas for walking; encouraging the use of bicycles by

designated spaces and bicycle renting locations; implementing

the intermodal exchange of buses and bicycles, including

information on routes and frequencies, improving

accessibility for disabled people; and the regulation of

activities in the public spaces.

In [17], the author studied the kinematic variables of the

fleet of buses that travel from Ibarra city to Tulcán city and

vice versa. The study includes the identification of danger

zones where vehicles find curves in the route and also get high

speeds. The buses during this trajectory stay 17.25% in idle

state, 23.01% in cruise, 32.43% in accelerating mode, and

27.29% in deceleration. To compensate for the idle times, the

buses get speeds higher than 100km/h, giving an unsafe

driving of 61% on the route Ibarra - Tulcán, and 66% on the

route Tulcán - Ibarra. It is explained that the pollution on this

route is due to the lower quality of fuel, the topography of the

city, and the traffic congestion.

In [18], they carried out a study of emissions of greenhouse

gas in Guayaquil city. They use the International Vehicle

Emissions Model (IVE) which is a computer model for

estimating air pollutants. Small vehicles produce more carbon

monoxide and volatile organic compounds, while buses

produce more nitrogen oxide and particulate matter with a

diameter of less than 10 μm (PM10). It is recommended a

reduction of sulfur in the diesel fuel. Finally, higher pollution

is not found on the highways but in very populated areas with

an elevated number of roads.

In [19], they introduced a study of vehicle congestion

around the metrovia public transport system in Guayaquil city.

They get data through observation of vehicles and it is

processed in ArcGIS to characterize intersections with their

geometry, traffic flow, and traffic light cycles. The use of an

exclusive lane for the metrovia system produces vehicle

congestion and they suggest changing traffic light cycles

accordingly.

In [20], they proposed a methodology for estimating the

pollution made by vehicles. The data acquisition is obtained

from the OBD II port [14] of the vehicle from different sensors

such as intake manifold pressure (MAP), throttle position, or

engine temperature. They use Freematics ONE data logger to

obtain the engine and GPS information, the Portable Emission

Measurement System (PEMS), and the Brain Bee AGS-688

that works through the non-dispersive infrared absorption

method (NDIR) for the measurement of carbon dioxide,

carbon monoxide, and hydrocarbons; and electrochemical cell

for the measurement of nitrogen oxides. A neural network

estimates the pollution emitted by the vehicles using the

measured data. Finally, it suggests that the vehicles should

comply with the Euro 6 vehicle emission standard.

In [21], they presented a cross-platform architecture for

analyzing vehicle traffic. An Android application captures

data and the Google distance matrix API estimates the

distances and speed of vehicles. The area of study is in Quito,

at the intersections of Shyris - United Nations and Amazonas

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

L. Jácome, W. Jaramillo and S. Jaramillo

“Traffic Congestion in Ecuador: A Comprehensive Review, Key Factors, Impact, and Solutions of Smart Cities”,

Latin-American Journal of Computing (LAJC), vol. 12, no. 1, 2025.

- Gaspar de Villarroel avenues. They use the Sarimax model

for prediction and the BigML tool for implementing the

algorithms. The system is deployed with the Amazon web

services with web and digital TV interfaces.

In [22], they conducted a study of traffic congestion in the

cities of “La Troncal” and “El Triunfo”. Betweenness

centrality measures the importance of a node in a network as

an intermediary in the communication with other nodes

considering the shortest paths. Closeness centrality measures

the importance of a node in a network based on the speed with

which it can communicate with other nodes. These 2 metrics

were used to estimate the congestion points of the cities. Using

OpenStreetMap, Waze, and WazeRouteCalculator, the

number of dead-end nodes and mesh nodes (streets with 4

exits) was determined. The WazeRoute Calculator was used

to determine distances and traveling times from Ecuadorian

cities on different business days.

In [23], they used linear regression, neural networks, and

k-nearest neighbor algorithms to estimate traffic congestion

around the University of Guayaquil. The temperature,

distance, and times of the day predict the traffic flow around

the surroundings of the building of the university, enabling the

users to take alternative routes.

In [24], they presented a study of air quality based on the

traffic flow in the city of Quito, they used Google Traffic and

Waze to obtain data and the decision tree algorithm to estimate

the amount of particulate matter (PM)—PM2.5 (aerodynamic

diameter ≤2.5 µm). Monitoring stations in the central area of

the city collect the validation data on pollution levels. The

results suggest that before 9:00, the largest concentration of

particulate matter is found, while the prediction model

obtained an accuracy of 61% to 71%, which is acceptable for

predictions using a low-cost method.

In [25], they conducted a simulation of cargo

transportation in a mountainous city where difficult conditions

are met like earthquakes, floods, landslides, or mudslides. It

is also noted that many roads in Ecuador have presence of

steepness, curvature, limited visibility, and high accident

rates. The simulation took into account factors like speed flow

of traffic, reduction of number of lanes, distance between

points, and road conditions. On the other hand, they modified

the ant colony algorithm used for optimization purposes and it

is inspired by the behavior of real ants, which are known to

find the shortest path between their nest and the food sources.

In [26], they carried out a study for estimating the amount

of ozone pollution in the city of Cuenca using machine

learning techniques like random forests, gradient boosting

prediction, neural networks, and quantile regression methods.

The data was obtained by the Air Quality Monitoring Network

which has 20 stations across the city. The results show that the

historic center, industrial land, high labor-population areas,

and areas with high traffic light density have higher levels of

ozone. As counter-measures, they suggested an early alarm

system that identifies high levels of ozone, encourages

scientific proof of the levels of pollution, improves and strict

regulations of transport and industries, or alternatives in

transportation.

In [27], they conducted a traffic study in the city of

Portoviejo. The study zone is the intersection of the avenue

Pedro Gual and Córdova street, which is a connection point to

many places of interest. Among the mitigation solutions for

traffic congestion, they suggested using radars to monitor

traffic flow and to change the traffic light cycles according to

the demands of cars, especially during the rush hour and in the

zone of the bus station and the central market. Additionally, it

was recomended the implementation of cameras in the public

buses, and improving the information for the user of the public

transportation system; educating the population and

respecting the traffic regulations.

In [28], they reported a study of the sizing and routing of

internet access points around the stations of the metro system

in Quito. The study aimed to establish the areas where the

implementation of access points will give uninterrupted

internet access to the users of the metro system. It was also

necessary to implement GPS and GPRS devices in each car of

the metro system to update their location in real time. This

study highlights that such effort can improve this

transportation service and encourages the population to use it

instead of driving particular cars.

In [29], they introduced a methodology for estimating

traffic flow using clustering which is a technique that is used

for trajectory analysis. The data of 218 trajectories and 30577

records was collected in October 2022 by university students

using taxi cabs, motorcycles, and metrovia public system. The

prediction model uses an adaptation of the DyClee algorithm

obtaining different groups of instances with similar evolution

patterns like common speeds at different time instants.

Finally, an interactive map shows the grouping of traffic

congestion events.

In [30], they presented a mathematical model based on the

Sustainable Urban Mobility Plans (SUMPs), developed in

2014 in the city of Cuenca. The data consists of an origin-

destination matrix between outer areas of the city and its

central business district, cost functions, park-and-ride

locations, and public transport parameters. The main

contribution of the paper is that the public transport system

can be planned considering the location of the park-and-ride

locations. Finally, the model was able to identify the sources

of demand that go to the central business district.

In [31], they introduced a study on using a plant species as

a biomonitor. The Araucaria heterophylla needles have the

capacity to accumulate metals. The results concluded that the

concentration of Mn, Fe, Al, Ba, Zn, Cu, Cr, Pb, and Co

increases with traffic intensity, while there is no relationship

between the level of Ca, K, and Mg and the vehicular traffic

intensity. However, the presence of green areas reduces the

amount of pollution even in zones of high traffic density.

In [32], they presented a system for sending notifications

of traffic congestion events to drivers in the city of Quito. The

data included average vehicular speed, approximate delay

times, and average traffic density. The real-time platform uses

the message queue telemetry transport (MQTT) messaging

service, which allows subscribers to obtain the relevant traffic

information. The test results conclude that the application

needs less battery, CPU, or GPU demand than applications

like Google Maps or Waze.

In [33], they conducted a study on the causes of traffic

accidents in Ecuador. The data was obtained from the National

Transit Agency, which recorded 14410 accidents occurre

d in

the years 2016-2018. A decision tree algorithm extracted rules

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

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LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

like a) the lack of attention is a main cause of traffic accidents

that occur more frequently in the urban areas of the

Chimborazo province, especially on Sunday nights with

normal weather, and lateral collision is the most common

event; b) drunkenness is another important cause of accidents,

occurring in urban areas, on weekends, having normal

weather, and the lateral and frontal collisions are the most

common events. The use of the cell phone while driving is also

an important cause of traffic accidents.

In [34], they presented a study on air quality in the capital

of Ecuador, Quito. It is found that the period between

February and April has the highest levels of nitrogen dioxide

which coincides with the winter period. On the other hand, the

lowest levels were found from June to August which coincides

with student holidays when traffic flow decreases

considerably. Despite the air quality being acceptable in terms

of standards, vehicular traffic is identified as a main

contributor of tropospheric ozone precursors (nitrogen oxides

and volatile organic compounds). The metro system could be

a solution to reduce both the contamination and traffic

congestion levels.

In [35], they proposed a decarburization plan for Ecuador.

It highlighted the efforts to electrify massive transportation

systems like the metro in Quito, the tram in Cuenca, and the

airway in Guayaquil. The challenges include poor

infrastructure, high costs of electric vehicles, and high costs of

batteries. The benefits include reducing subsidies for gasoline

and diesel or decreasing greenhouse gas emissions.

In [36], they conducted a study on the optimal locations

for building charging stations for electrical taxis. Quito has an

altitude of 2800 meters and the internal combustion vehicles

are very inefficient, moreover, taxi cabs are very noisy and are

a major contributor to pollution. The study selected the BYD

e5 model for the experimental calculations and considered the

number of spots in each charging station based on the

electrical vehicle penetration of 30%, 40%, and 50%. The

results suggest that 393, 524, and 654 charging spots must be

installed in total respectively for ET penetration levels of 30%,

40%, and 50%.

In [37], they carried out a study on the challenges and

opportunities for the community of Montañita to become a

smart city. It remarks that mobility is important for

sustainability, efficiency of transportation infrastructure, as

well as local, national, and international accessibility which is

relevant since Montañita is a tourist community. Sustainable

transportation is relevant for local and national governments

to give the inhabitants quality access to study, work, or leisure.

Intelligent mobility is not just the use of technology, but,

giving the user access to relevant information such as

schedules or traffic flow which reduces accidents, and

enhances public transportation.

In [38], they conducted an experiment on position

correction systems for autonomous vehicles. They used a low-

cost Global Navigation Satellite System (GNSS) receiver with

the RTKLIB software and the NTRIP protocol. They

explained that autonomous vehicles can improve road safety,

and reduce emissions and traffic congestion. The research is

relevant because its goal is to use low-cost devices for

autonomous vehicles which can help developing countries to

adopt this technology. However, it will be difficult to

implement autonomous vehicles in countries like Ecuador due

to the road conditions. Finally, they reported that the use of

the low-cost RTK (Real Time Kinematic) position correction

system was affected by the coverage of the internet signal, the

correction latency, and the interruption of the satellite signal.

These barriers were compensated by the use of the inertial

measurement unit with the odometry system of the car.

In [39], they performed a study on air pollution during the

dry and rainy seasons in the city of Quito. Vehicle emissions

are a main contributor of CO and PM and precursors of

pollutants like NO2, and O3. For its part, NO is produced by

combustion of vehicles. The meteorological variables that

were used for detecting air pollutants are humidity,

temperature, wind speed, and solar radiation. It was found that

the presence of CO, NO2, and O3 has a negative correlation

with relative humidity in the dry and wet seasons, and a

negative correlation between PM2.5 and NO2 with wind

speed during the dry season, indicating that atmospheric

mixing contributes to the dilution of pollutants during the dry

season.

In [40], they conducted a research on pedestrian counting

in the city of Portoviejo to improve the mobility of citizens.

They explained that according to the HCM 2000, the

pedestrian service levels are A: >11.70 m2/pt, B: >3.6 m2/pt,

C: >2.6 m2/pt, D: >1.35 m2/pt, E: >0.54 m2/pt, F: <0.54

m2/pt. The results suggested that pedestrian congestion occurs

in América Avenue between Pedro Zambrano street and

Manabí avenue, especially in the morning, having a D level of

service. Mitigation measures include punishment for the

incorrect use of the sidewalks like parking or placement of

advertisement banners, building an exclusive path for

bicycles, and training the inhabitants and the local authorities

who make the policies of transportation.

In [41], they presented an analysis of the energy demand

of the public passenger buses in the city of Cuenca. Speed,

acceleration, slope of the road, and GPS location were

collected using the OBD II port with an open-source data

logger device. A machine learning algorithm obtained the

energy demand and it is explained by the characteristics of the

bus routes like average speeds from 16 to 19 km/h, road slopes

of minimum 8.82%, high demand of passengers during the

peak hours (the passenger per kilometer index (IPK) for the

bus line #16 is 4.5), and continuous acceleration and

decelerations due to traffic congestion (maximum

accelerations of 0.1014 m/s2 were found in the bus line #28).

Results showed that many bus routes have a consumption of

330.44 kW and slopes of 24.85%. Finally, they suggested new

designs for bus routes.

In [42], they introduced a study on the energy autonomy

of electrical vehicles in Cuenca which is a topologically

irregular city in the highlands. The city has a motorization

index higher than 200 vehicles per thousand inhabitants, the

bad service of the public transportation system makes 66% of

the population use particular vehicles in trajectories between

3km to 10km, the hybrid vehicle market represents 0.26%

while the electric vehicles represent 0.01%. While only 19%

of people in a survey are willing to buy an electric vehicle in

the next years, the rest of them reject the maintenance costs,

higher costs of electricity, and bad customer service for EVs.

The topology of the city produces a modification of the torque

curve of the electric engine which is considered a

disadvantage for its implementation because it allows an

autonomy of 124km which is 67% of the total capacity of the

batteries. Finally, authorities should plan the energy

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

L. Jácome, W. Jaramillo and S. Jaramillo

“Traffic Congestion in Ecuador: A Comprehensive Review, Key Factors, Impact, and Solutions of Smart Cities”,

Latin-American Journal of Computing (LAJC), vol. 12, no. 1, 2025.

consumption of industries and homes for the implementation

of EVs.

In [43], they developed an extension for the traffic

simulation tool called SUMO-based Traffic Mobility

Generation Tool. Building simulation scenarios in the SUMO

tool can be time-consuming for tasks like the road map, traffic

elements such as traffic lights, the types of vehicles, or vehicle

routes. The STGT extension allows an easy generation of the

simulation scenario and provides performance statistics. The

performance evaluation of the STGT extension was made

using a real map of the financial district of the city of Quito

obtained by the OpenStreetMap platform, while STGT

generates the road network and the traffic demand

configuration files.

In [44], he presented a study on a holistic decision-making

process to improve public transportation in the city of Cuenca.

Proposed measures include: increasing the population density

in areas where the road infrastructure is sub-used; improving

the routes of bus lines, redistributing the main interest points

(attractors of trips); giving priority to the public transportation

on the main corridors; implementing cameras, ticket

validators, and emergency buttons in the units; reduce parking

spots in the congested areas but increase them in the borders;

change the perception that car ownership increases social

status; and conduct training to bus drivers.

In [45], they conducted a study on the challenges in “rapid

transit projects”. They explained that in Ecuador 19 rapid

transit projects were planned but only 9 were implemented.

Among the barriers they found were a absence of political

leadership or confrontation; difficulty of implementation;

rushed planning process; resistance from stakeholders like bus

operators; and bad estimation of the costs. Among the

measures they have: connecting social, political, and technical

perspectives; increasing private participation; encouraging

community feedback and monitoring; and starting the

implementation of projects before the end of the political

cycle.

In [46], they tackled the unproportioned growth of cities,

identifying the urban areas where people build houses near big

cities forming integrated cities. They studied the patterns of

mobility between nearby locations resulting in the

identification of the Functional Urban Areas (FUA). Satellite

images identify the urban cores, then they connect

uncontiguous urban cores that belong to the same functional

area and finally, they identify the remote areas for those urban

cores. Results showed the presence of 34 urban cores in

Ecuador and 28 FUA obtained by a minimum travel time,

having Quito and Guayaquil cities as the largest attractors with

60% of the population. It is important to forecast future spots

of high traffic congestion.

In [47], they conducted a study on the impact of the

implementation of the metro system in the city of Quito. The

higher density of the population is located in the south,

northeast, and periphery. These areas are also the ones that

have the lowest living conditions. The population with higher

living conditions is located in the hypercenter, near the area of

concentration of services like jobs, shops, and public transport

stops. The areas of Cumbayá and Tumbaco, which are zones

of high living conditions, are not well served with public

transportation, so they use private cars to get to the hyper-

center producing heavy congestion. The metro system will

reduce the travel time of users but the impact will depend on

the location of residence, where some zones will require better

accessibility to the feeding units of the metro system.

In [48], they used a system to count passengers in public

buses, with the implementation of a long short-term memory

architecture of neural networks they could predict the future

flow of passengers. This kind of project helps to optimize

routes of the public transportation system, decreasing the

amount of fuel (Ecuadorian public transportation systems

utilize diesel) and the emission of CO2 gas. They also

highlighted more benefits like passengers planning their

routes, avoiding crowds, and getting to their destination on

time. Moreover, they proposed the use of the Internet of

Things and smart city technologies to implement smart nodes

where passengers can register themselves and record their

travels, those smart nodes would predict and improve their

travel experience.

In [49], they used images from drones and weather images

to detect vehicles and to classify the traffic conditions as

heavy, medium, low, and empty, with that information they

implemented a traffic prediction model for diverse areas and

times. It is underlined that this project is pertinent since there

is not much information on traffic congestion in large cities

like Quito and the information obtained from traffic prediction

models can improve the quality of life of their inhabitants.

Finally, they also remarked that the use of drones can decrease

the cost of traffic congestion studies, however, they are

constrained by other factors like battery time, permission for

flights, or experience with drones.

In [50], they conducted a study to determine the potential

of the city of Cuenca to use a big data approach to become a

smart and sustainable city driven by data. They emphasized

that Cuenca is the third largest city in Ecuador with over

450,000 inhabitants and its growth has to be planned

accordingly. In their research, they proposed using air quality

and noise sensors, traffic monitoring devices, and smart

lighting with a digital platform that can deliver information

about the services in the city in real-time. They recommended

the participation of public and private institutions to

implement those initiatives.

In [51], they conducted a study on the implementation of

a park-and-ride system in the city of Ibarra. Park-and-ride

systems allow private car drivers to park their vehicles near

public transportation stations, reducing the utilization of those

private vehicles and decreasing fuel consumption and air

pollution. In their study, they found that implementing park-

and-ride systems in the city of Ibarra could reduce gas

emissions per passenger by 13 times carbon dioxide, 8 times

carbon monoxide, and 1.7 times nitrogen oxide.

In [52], they proposed a VANET (vehicular ad-hoc

network) solution to optimize travel times in the city of

Esmeraldas which has recently experienced a substantial

growth in traffic congestion, especially in peak hours.

VANETs are a special type of MANETs (mobile ad-hoc

networks), in VANETs vehicles communicate with other

vehicles or nearby infrastructure. They implemented a

simulation with OMNET++ and SUMO simulators with

results that show an improvement in selecting routes reducing

travel time and distance.

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

In [53], they conducted a study where they developed a

classification model using a decision tree algorithm that

identifies different transportation methods like walking,

biking, taxi, tram, bus, and private vehicles utilizing data

gathered with a mobile application. The experiment was

carried out in the city of Cuenca and they used data related to

date, time, latitude, longitude, altitude, and speed. This project

is relevant as it can be used for detection of drivers that usually

exceed speed limits, hot spots of traffic congestion, and more

informed urban planning. For future work, they mentioned

including weather data, public transportation schedules, and

real-time traffic data to improve the precision of the algorithm.

In [54], they utilized artificial intelligence algorithms,

computer vision, and blockchain technologies to build a

simulated city model based on data gathered in the city of

Quito. The results showed that the AI algorithms reduced

traffic congestion by utilizing real-time traffic data from

security cameras and traffic lights. Moreover, blockchain

technology ensures the security and immutability of traffic

data which is an innovative solution. This study is relevant to

the results and could be implemented with traffic data from

other cities.

In [55], they proposed the implementation of a light

electric freight vehicle for the first/last mile in the historical

center of Quito which is a busy and popular area. They

explained that the high altitude of the city gives lower levels

of oxygen and air pressure which decreases the performance

of engines based on gasoline, this issue justifies the use of

electric vehicles. They presented a detailed proposal for the

execution which includes hardware and software designs,

logistics, and legal aspects to consider. However, this

initiative faces many challenges like the electrical supply

crisis that frequently affects Ecuador. This also remarks that

with the increasing adoption of electrical vehicles worldwide,

the country will have to plan how to cover the shortage of

electric power.

In [56], they studied the influence of travel times on carbon

dioxide emissions in the city of Quito. The data was obtained

by particular vehicles and the model utilized information like

model, year of manufacture, vehicle manufacturer, and

vehicle displacement. They estimated the amount of fuel that

is consumed during heavy traffic conditions and implemented

a regression model to forecast the CO2 gas emissions, finding

that the model obtains a high significance and correlation.

This study is pertinent as it presents an innovative approach

that can be replicated in other cities, and their findings would

tell the conditions of air pollution in those locations.

In [57], they developed a vehicle-to-vehicle

communication model utilizing the ZigBee wireless protocol

and the Arduino platform. The prototype triggers alerts when

there is a possibility of a collision between the 2 vehicles, it

also implements temperature and humidity sensors that report

on a display. The experiments were conducted at different

speeds and distances of the vehicles, obtaining good

connection tests at speeds up to 300 meters. This project is

significant because it uses low-cost technologies that offer

advantages over more expensive commercial solutions, so

further research should be considered.

C. Ansewring the research questions

To answer the research questions, we have the following

analysis:

RQ1: “What are the main sources of traffic congestion in

Ecuadorian cities?”

According to our findings, natural disasters like

earthquakes, floods, landslides, or mudslides are a major

challenge; lack of maintenance of infrastructure, lack of

education, or cultural issues bring out chaotic traffic flow; bad

public transportation service makes a high percentage of the

population to use private cars even for short distances;

Management of traffic like exclusive lanes for public

transportation, or bad traffic lights timing lead to traffic

congestion. Fast transit projects fail due to absence of political

leadership or confrontation, difficulty of implementation,

rushed planning process, resistance from stakeholders like bus

operators, or bad estimation of costs.

Table II relates the analyzed papers to the categories of

sources of traffic congestion and their outcome.

TABLE II. ANALYZED PAPERS RELATED TO THE CATEGORIES OF

SOURCES OF TRAFFIC AND THEIR OUTCOME

Paper

Category

Outcome

[16],

[25]

Natural disasters High cost of maintenance

[14],

[35],

[38]

Inadequate infrastructure

Cities with poor transit

infrastructure may not attract

businesses and residents,

slowing urban growth and

reducing investment

opportunities

[13],

[17],

[40],

[53]

Lack of education,

cultural issues

, not

complying with traffic

rules

Drivers may violate laws

creating unsafe conditions

[8],

[15],

[42],

[44],

[47],

[48],

[51]

Bad public transportation

service or planning

Poor service pushes more

people to drive

, leading to

higher congestion

[11],

[19],

[27]

Bad traffic light timing

When traffic lights are not

synchronized or have

improper timing, they can

cause bottlenecks leading to

long queues and significant

delays

[45],

[49],

[50],

[55]

Lack of political

leadership or

confrontation,

underestimation of

implementation

complexities

This can

cause many

infrastructure projects to fail

[10],

[13],

[16],

[19],

[22],

[23],

[27],

[28],

[32],

[37],

[54]

Lack of information on

public transportation or

traffic conditions

When schedules, routes, or

traffic delays are not available,

potential users ma

y find it

difficult to use public

transportation

[9],

[18],

[20],

[26],

[30],

[36],

[40]

Lack of adoption of

international

transportation standards

Not adopting international

transportation standards can

significantly impact the

efficiency, safety, and

sustainability of a

transportation system

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

L. Jácome, W. Jaramillo and S. Jaramillo

“Traffic Congestion in Ecuador: A Comprehensive Review, Key Factors, Impact, and Solutions of Smart Cities”,

Latin-American Journal of Computing (LAJC), vol. 12, no. 1, 2025.

For its part, the pollution produced by vehicles is also a

result of lower quality of fuel, and the topography of the

highland cities that require more power from engines.

RQ2: “What solutions have been proposed to reduce the

traffic congestion in Ecuadorian cities?”

Based on the results of our research, we can classify the

solutions for traffic congestion into 3 types:

Smart cities technologies: Implement smart parking

systems, visual recognition systems for pedestrians and

vehicles, shared car applications, real-time traffic maps, or

notification applications of traffic events. Big data and

machine learning can help spot trends of high vehicle

congestion in locations and periods. Use simulation and

optimization in the most congested places.

Regulations: punishment for incorrect sidewalk use, such

as parking or placement of advertisement banners;

implementation of pedestrian islands; increase in bicycle

spaces; improvement and strict regulations of transportation;

and making transportation units accomplish international

standards.

Improving public and private transportation systems:

offering information on routes and frequencies, implementing

GPS devices in buses to monitor travel speeds, or encouraging

the adoption of electric vehicles.

Table III relates the analyzed papers to the three types of

solutions of traffic congestion.

TABLE III. ANALYZED PAPERS RELATED TO THE TYPES OF SOLUTIONS

OF TRAFFIC CONGESTION

Paper

Technology / tool Regulations Improvements

[9]

---

HCM standard

---

[10]

Google traffic API

(real-time)

--- ---

[11],

[27]

--- ---

Traffic light

cycles

[12]

Google distance

matrix tool

(calculate

commute time

between origins

and destinations)

--- ---

[13]

Computer vision

---

[14]

OpenStreetMap,

SUMO simulation

software

--- ---

[15]

---

Shared cars

---

[16] ---

Pedestrian

islands

---

[17] ---

Identification of

danger zones

---

[18] ---

IVE model

(Computer model

designed to

estimate

emissions from

motor vehicles)

---

[19] ---

Exclusive lane

for public

transportation

Traffic light

cycles

[20]

Freematics ONE

data logger (Obtain

the engine and

GPS information

of cars and buses)

--- ---

[21]

Google distance

matrix tool,

BigML

--- ---

[22]

OpenStreetMap,

Waze, and

WazeRouteCalcul

ator

--- ---

[23],

[26],

[29],

[33],

[48],

[53]

Machine learning --- ---

[24]

Google traffic API,

Waze

--- ---

[25]

Artificial

intelligence

--- ---

[28] --- ---

GPS and GPRS

devices in each

car of the metro

system

[30],

[51]

---

Park-and-ride

system

---

[32]

Google Maps,

Waze

--- ---

[35] ---

Electrification of

massive

transportation

systems

---

[36] --- ---

Study of the

optimal

locations for

electric

charging

stations

[37] --- ---

Information on

bus schedules

and traffic flow

[38]

Global Navigation

Satellite System

--- ---

[39] ---

Vehicle exhaust

emissions

---

[40]

---

HCM standard

---

[41]

OBD II port

---

[42] --- ---

Electric public

transportation

[43]

OpenStreetMap,

SUMO simulation

software

--- ---

[44] ---

Priority to the

public

transportation

Conduct

training to bus

drivers

[45] ---

Connecting

social, political,

and technical

perspectives;

increasing private

participation

---

[46] Satellite images

Identification of

the Functional

Urban Areas

---

[47] ---

Extending public

transportation

system

---

[49]

Machine learning

with dron images

and weather

images

--- ---

[50]

Big data, noise

sensors, smart

lighting

--- ---

[52]

VANETs,

OMNET++ and

SUMO simulators

--- ---

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

[54]

Artificial

intelligence

algorithms,

computer vision,

and blockchain

(security and

immutability of

traffic data)

--- ---

[55] --- ---

Light electric

freight vehicle

[56]

Regression model

---

[57]

ZigBee wireless

protocol

--- ---

Moreover, to decrease pollution caused by vehicles, we

found the use of electric vehicles, or design the routes of

public transportation avoiding slopes.

Finally, having in mind the decrease in traffic accidents,

we found the identification of danger zones on roads,

monitoring kinematic variables of the fleet of buses, giving

education to the population especially for avoiding drinking

and driving, or implementing designated driver applications.

IV. C

ONCLUSIONS

Overall, this exhaustive study analyzes from an academic

point of view, the main causes of traffic congestion in

Ecuadorian cities, and the proposed solutions that have been

implemented. The findings reveal that natural disasters are not

only a threat for the lives of Ecuadorians but also represent a

challenge for the maintenance of roads. The topography of

cities, lack of education, or bad urban planning also explain

the causes of high levels of traffic congestion. By focusing on

infrastructure development, public transportation

improvements, urban planning, traffic management strategies,

data mining and big data technologies, and sustainable

alternatives, Ecuador and other Latin-American countries can

work towards reducing traffic congestion, enhancing mobility,

and improving the overall quality of life for its citizens.

However, the success of the implementation of those

technologies depends of factors such as collaboration between

the private and public organizations, good estimation of costs,

acceptance of the citizens, or adequate management of privacy

and security issues. We expect that this paper will be useful

for researches, authorities and students to understand the

current situation of traffic congestion in Ecuadorian cities and

it would be a reference for its improvement.

CKNOWLEDGMENT

The authors would like to thank to Universidad

Internacional de Ecuador for sponsoring the research project

entitled “Loxa Smart, prototype of a smart and sustainable

city” and for their assistance in the present study.

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Publishing, July 2024.

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

DOI:

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

10.5281/zenodo.14450073

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

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ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

AUTHORS

Luis Roberto Jácome Galarza ha obtenido los títulos de Ingeniero

en Sistemas Informáticos y Computación en la Universidad Técnica

Particular de Loja, Magíster en Telemática en la Universidad de Cuenca,

Magíster en Ingeniería Computacional y Sistemas Inteligentes de la

Universidad del País Vasco.

Se ha desempeñado como docente investigador de la Universidad

Nacional de Loja y la Universidad Internacional del Ecuador.

Sus líneas de investigación son aprendizaje de máquinas, aprendizaje

profundo y visión artiﬁcial.

Wilson Eduardo Jaramillo Sangurima ha obtenido los siguientes

títulos académicos: Ingeniero Civil en la Universidad Técnica Particular

de Loja, Magíster en construcción civil en desarrollo sustentable en

la Universidad Nacional de Loja, Magíster en Gestión del transporte

mención en tráﬁco, movilidad y seguridad vial en la Universidad

Internacional del Ecuador.

Se ha desenvuelto como director de la Unidad de Movilidad Tránsito y

Transporte Terrestre del GAD Municipal de Loja, director de la Empresa

de Vivienda VIVEM EP, docente de la Escuela de Arquitectura de la

Universidad Internacional del Ecuador, sede Loja.

Sus líneas de investigación son movilidad terrestre y tecnología e

innovación en educación.

Jácome-Galarza Luis-Roberto

Jaramillo-Sangurima Wilson E.

L. Jácome, W. Jaramillo and S. Jaramillo

“Trac Congestion in Ecuador: A Comprehensive Review, Key Factors, Impact, and Solutions of Smart Cities”,

Latin-American Journal of Computing (LAJC), vol. 12, no. 1, 2025.

ISSN:1390-9266 e-ISSN:1390-9134 LAJC 2025

LATIN-AMERICAN JOURNAL OF COMPUTING (LAJC), Vol XII, Issue 1, January 2025

AUTHORS

Silvia Alexandra Jaramillo Luzuriaga ha obtenido los siguientes

títulos académicos: Licenciada en Administración de Empresas en la

Universidad Nacional de Loja, Ingeniera Comercial en la Universidad

Nacional De Loja, Magister en Docencia Universitaria e Investigación

Educativa en la Universidad Nacional de Loja, Magister en Educación

a Distancia en la Universidad Nacional de Loja, y Magister en

Administración de Empresas en la Universidad Internacional del

Ecuador.

Se desempeña como docente de la Business School en la Universidad

Internacional del Ecuador - sede Loja y sus líneas de Investigación son

Administración, Marketing, Talento Humano

Jaramillo-Luzuriaga Silvia A.

L. Jácome, W. Jaramillo and S. Jaramillo

“Trac Congestion in Ecuador: A Comprehensive Review, Key Factors, Impact, and Solutions of Smart Cities”,

Latin-American Journal of Computing (LAJC), vol. 12, no. 1, 2025.