Carsharing System for Urban Transport in Lima using Internet of

Things

Jean Pierre V

asquez-Garaya, Elizabeth Munayco-Apolaya and Willy Ugarte

Universidad Peruana de Ciencias Aplicadas (UPC), Lima, Peru

Keywords:

Car-sharing, Internet of Things, Urban Transport, Shared Economy, Lima.

Abstract:

Carsharing has become a trend in the transport industry that has been growing exponentially in recent years

and gaining popularity in large cities in Europe and Asia such as Madrid, Berlin, Amsterdam, among others.

This work presents an implementation of a carsharing system that activates all the car’s functionalities through

an application without the need for additional elements such as cards, physical keys, etc. Likewise, being able

to connect the car and mobile application through an IoT device and backed by a cloud infrastructure, it offers

a new mobility modality that unites technology, in the city of Lima that is ﬂexible, safe and affordable for most

of the people; in addition to bringing to Peru the concepts of shared economy and uberization of things. We

present that in Lima there is a very deplorable, disorderly and low-quality urban transport system generating

many problems for users. The ﬁrst alternative solution would be to acquire a private car, but for many people

it is not accessible, especially for people between 20 and 45 years old, since it entails having a large budget

that includes the cost of the car, maintenance, security permits, among others, that many people do not have

in their entirety. We report such as Internet of Things, Cloud Computing and Applications Mobile, with an

innovative technological architecture with new advances in the automotive ﬁeld, such as electric cars.

1 INTRODUCTION

Nowadays, the trafﬁc management systems in the

world have struggled to keep pace with the relentless

onslaught of vehicles that they have to deal with now

and the disorganization of different types of public

transportation, generating a big waste of time for citi-

zens, especially in Latin-American cities like Lima.

According to a study by Universidad del Pac

ıﬁco

(Peru) and the Marketing Consulting ﬁrm for the pe-

ruvian newspaper “Gestion”, the Lima citizens lose

about 4 hours a day in transport and most of the

trips in the capital are for work reasons

. Further-

more, according to a report by INRIX, published in

the newspaper Gesti

on, 51% of Lima residents use

public transport as a basic necessity. This is based on

the fact that there is no ﬂexible private transport alter-

native available in terms of usability, accessibility and

price. In addition, in the same report it is mentioned

that the taxi is a means of transport that is not very ac-

cessible for the majority of the population, being used

by only 25% of the Lima population

https://orcid.org/0000-0002-7510-618X

Gestion - https://bit.ly/3ssOhNv

Gesti

on - https://bit.ly/2UlU0YM

A solution to these problems could be the imple-

mentation of a new form of mobility such as car-

sharing, which is present in European cities such as

Madrid, Paris, Rome, etc., but unfortunately these

systems are not adapted to the reality and culture of

a Latin American city like Lima. The implementa-

tion of a carsharing system in Lima takes on greater

importance in the current context, since currently, ac-

cording to the newspaper La Vanguardia, it is a ﬂex-

ible mobility tool. This is reﬂected in large cities,

ﬁtting in much better with new drivers who seek in-

dependence, autonomy and immediacy, but also sav-

ings, sustainability and comfort. In addition, having

the smartphone as a connection through mobile appli-

cations and with an agile procedure, makes this type

of mobility much more ﬂexible for these drivers

. Im-

plementing this in Lima means bringing new tech-

nologies and disruptive business models generating

greater economic, social and technological develop-

ment not only to the city but also to the country,

futhermore managing to be a complement to the most

modern transport systems such as the electric train,

the Metropolitan or scattered road corridors in the

city.

La Vanguardia - https://bit.ly/3iK5MVY

324

Vásquez-Garaya, J., Munayco-Apolaya, E. and Ugarte, W.

Carsharing System for Urban Transport in Lima using Internet of Things.

DOI: 10.5220/0010674400003058

In Proceedings of the 17th International Conference on Web Information Systems and Technologies (WEBIST 2021), pages 324-331

ISBN: 978-989-758-536-4; ISSN: 2184-3252

Carsharing has a complex process for its imple-

mentation within a city due to two main factors: so-

cial and technological (Wang, 2018). On one hand,

the social factor is fundamental since the place where

it is implemented is required to be a developed or de-

veloping city. This is necessary due to the series of

important accessories within the city such as parking

lots, electric charging centers or gas stations, among

others. Likewise, the reality of the city, its security

level and the means of transport with which it would

coexist must be taken into account. On the other

hand, the technological factor is fundamental, since

an advanced infrastructure and next-generation con-

nections are necessary for this to work 100%.

This can include from wireless connection de-

vices, mobile applications, 4G or 5G networks,

among others, and above all, they provide highly reli-

able security to avoid risks.

Speciﬁcally, Lima is a complex city, but it is not

impossible to implement a carsharing system, since

there are more Internet of Things (IoT) developments

in different aspects of the city. Nevertheless, the main

problem is the current urban transport system due

to its disorganization, informality, its non-integration

among them and, above all, the little use of tech-

nology. Given this, a carsharing system would be

a disruptor within Lima society, paving the way for

the modernization of the city. However, this must be

adapted to the reality of the city, which is totally dif-

ferent from large European cities, especially in terms

of safety, operating processes, prices, and type of

technology.

As mentioned above, implementing a carsharing

system depends on different components. Taking Eu-

ropean countries as a reference, this was implemented

but with devices such as a key or a pin code. What

is proposed now is the use of the cell phone, which

through an application will be able to activate or block

the selected car. For the implementation, a cell phone

is required which is connected by Bluetooth to the IoT

device in the car and a fast and stable connection to

the internet.

Focusing on the application, it will be developed

for the Android operating system. In addition, the

language to use is Java with the Flutter programming

framework. Regarding the connection with the car, an

IoT device will be installed in the vehicle so that its

mechanical and electrical system can be controlled in

its entirety from the mobile device without the need

for keys, cards, etc. The application is supported

by the Amazon Web Services (AWS) cloud platform.

For this paper, an Minimum Value Proposition (MVP)

will be carried out to be able to test together with key

users if this system becomes a viable alternative in

Lima. Our contributions are as follows:

• We develop an Android carsharing application,

which allows the user to reserve a car, show the

user the fastest route to their destination and con-

trol the car wirelessly.

• We implement the technological infrastructure of

the mobile application in the cloud using the ser-

vices provided by AWS, applying the DevOps

methodology and through an IoT device installed

in the cars.

• We make experiments with the system through a

series of tests with key users to be able to deﬁne

through their experiences that this system could

be an alternative in the urban transport system of

Lima.

This paper is organized as follows. Section 2 dis-

cusses related work. Section 3 introduces the rele-

vant concepts and deﬁnes the problem formally while

Section 4 presents our approach and our development.

This is evaluated in Section 5 after which we show the

results of our experiments in Section 6, and we con-

clude in Section 7.

2 RELATED WORKS

In the ﬁrst place, in (Boukhechba et al., 2017) the

authors propose the development of a ﬂeet electric

vehicle system that works optimally and meets peo-

ple’s expectations, where according to different stud-

ies, different missing aspects were covered, such as

the simulation of the cargo establishments and return

policies, based on existing systems and in cities where

this form of mobility is already established. In our

case, we develop a carsharing system that meets dif-

ferent expectations, which differs from research, in a

city where a similar or equal system has not been de-

veloped, taking into account the reality of a develop-

ing city such as Lima and the different deﬁciencies,

all this through direct and focused investigations in

the city in question.

Also, in (Lim et al., 2020), the authors presented a

green logistics delivery framework with shared cars,

based on IoT (Internet of Things) and using algo-

rithms that allow travel optimization. The architec-

ture included in the framework consists of a cus-

tomer data layer, an information collection layer, a

cloud optimization layer, and a delivery task execu-

tion layer. This shared delivery framework can pro-

vide customers with a more ﬂexible delivery service.

For our part, compared to what is proposed in this pa-

per, we have implemented different algorithms that al-

low travel routes to be deﬁned according to the current

Carsharing System for Urban Transport in Lima using Internet of Things

325

trafﬁc collected by the API that we have integrated,

seeking that the user can avoid wasting a lot of time

in some unnecessary route; In addition, using a cloud

architecture that ensures data consistency, high avail-

ability and where it gives us the possibility of mon-

itoring cars in real time through Internet of Vehicles

technology.

In (Min and Xing-Fu, 2020), the authors through a

study of the theory in English ”Theory of Planed Be-

havior” or TPB (for its acronym in English) and in this

the key factors required by a shared vehicle system

were identiﬁed. The authors’ study concluded with

the series of steps to follow for the implementation

of this system, because people do not usually opt for

the carsharing system because they do not consider

it a safe or convenient service. For this reason, the

authors seek to change this idea by presenting a car-

sharing model that can be adapted to different needs.

From this, we achieve this through the different social

studies carried out in third-party works and generat-

ing a design at the user experience level very similar

to the most used taxi applications in the country, gen-

erating greater users in tests conﬁdence of use, also

generating a simpler ﬂow so that people who use it

feel that it is a convenient mobility alternative to the

traditional public transport system.

Finally, in (Wei et al., 2017), the authors presented

a key exchange system for car rental or car sharing

services based on the hierarchical signature, called

HIBS-KSharing. This proposal is useful for com-

pany car rental services and also presents versatility

to be adapted to the shared use of private owners ve-

hicles. The proposal allows the electronic keys of in-

vited users to be remotely issued, revoked and del-

egated by companies or owners. The end user will

use their smartphones to access the vehicle using the

NFC communication protocol. Compared to our re-

search project, we use different keys that each device

type and is unique, which are stored in our database

and that allow that at the time of connection of our

IoT device it can make a validation closer to the mo-

ment of access Likewise, the device that we use in

cars makes use of the BLE communication protocol,

which, compared to what was proposed by previous

authors, usually takes a fraction of a second or more to

identify and secure a connection, but it is considerably

more versatile than NFC, thanks to its longer range;

Furthermore, the data transmission speed is very dif-

ferent, as NFC barely reaches 424 kbit/s, while Blue-

tooth can exceed 20 MB/s. Finally, BLE is a tech-

nology that already exists in millions of smartphones,

tablets and computers, so in that sense, BLE has al-

ready won a battle over NFC in the mobile market.

3 CONTEXT

Now we present a few concepts about our approach.

3.1 Internet of Things (IoT)

Internet of Things (IoT) (van Moergestel et al., 2016)

refers to communication between the digital and

physical world. It provides a wide infrastructure to

provide services, such as the sending and receiving

of information and interconnections through virtual

elements. It consists of a set of sensors and radio

frequency identiﬁcation (RFID) technology that com-

municate over a network with various devices (Noori

et al., 2020).

3.1.1 Bluetooth Low Energy (BLE)

Bluetooth Low Energy (BLE) also called Bluetooth

4.0 or Smart Bluetooth. BLE advertising beacons

are particularly attractive because of the promise of

long battery lives of many years, and so low main-

tenance requirements. Moreover, the low price of

Bluetooth beacons (around 20$) represents an attrac-

tive solution for transmitting Smart Points of Interest

data (SPOI) metadata. Beacons transmit a low-power

signal that can be picked up by nearby Bluetooth-

enabled mobile devices, including smartphones. They

broadcast short-range signals that can be detected by

apps on mobile devices in close proximity to a beacon

(20–200 m) (Boukhechba et al., 2017).

3.1.2 Internet of Vehicles (IoV)

Internet of Vehicles (IoV) is a promising technol-

ogy that can aid communication between vehicles on

the road. IoV belongs to a special Mobile ad hoc

Networks that enables communication between vehi-

cles. Ad hoc network connectivity can be achieved

through wireless communication devices installed in

vehicles (Wang et al., 2020).

3.1.3 IoT World Forum Reference Model

This model can be considered as a multi-level system,

which are detailed in Fig. 1 (Milenkovic, 2020).

This model is made up of 7 layers, each one with

a different purpose:

• Physical Devices and Controllers: This layer

refers to the sensors and devices that are managed

by the IoT architecture

• Connectivity: This layer is the connection be-

tween the device and the Edge computing layer,

this involves various communication alternatives

and data transformation.

WEBIST 2021 - 17th International Conference on Web Information Systems and Technologies

326

(a) IoT World Forum Reference Model (Milenkovic, 2020). (b) Our adaptation of IoT World Forum Reference Model.

Figure 1: Adapting the IoT World Forum Reference Model.

• Edge Computing: This is the computing layer

where the conversion protocols will be imple-

mented, the route for making latency decisions,

among others.

• Data Accumulation: This layer where the in-

coming data is stored to be processed later.

• Data Abstraction: This layer where the informa-

tion from the sensors or devices will be collected.

• Application Layer: This layer the application

logic is executed.

• Collaboration and Processes: The last layer and

where the processed data of the previous layers is

presented to the end users.

As detailed, this layer-by-layer model achieves

that both the IoT devices and the infrastructure with

the services can take full advantage of it to achieve

optimization together (Cocca et al., 2019).

3.2 Carsharing

To understand the carsharing, which you want to im-

plement, you need to ﬁrst understand two important

terms:

3.2.1 Shared Economy

The collaborative economy called shared economy is

a different way of acquiring goods and services. This

alternative differs from the traditional business model

of different corporations. In this, people rent goods

such as homes or cars for a period of time. Once com-

pleted, someone else can use the same asset (Ruslan

et al., 2020).

3.2.2 Uberization of Things

“Uberization” is known as the “killer” of interme-

diaries, since Internet technology platforms connect

consumers with providers of goods and services. It

allows you to perform several operations at the same

time such as searching, ordering and paying. To-

day, “uberization” is spreading to various markets,

such as ﬁnancial and banking, medical, educational

and commercial. It should be taken into account that

the term appeared by the company Uber Technolo-

gies (Uber), known for developing a mobile applica-

tion to call taxis faster and cheaper than the traditional

one (Giniyatullin et al., 2019).

With both terms deﬁned, you can better under-

stand what Carsharing would be, is a form of shared

mobility. Its system consists of a large number of ve-

hicles distributed in a certain area that a person can

access when making a payment. The cost depends on

the duration of the trip and the distance traveled. Its

main objective is to provide a service similar to that

of a private transport (Sai et al., 2020).

4 CAR SHARING SYSTEM FOR

URBAN TRANSPORT

In this section, we will take a total view of the entire

development of the carsharing system, from the archi-

tecture to the development and commissioning of the

application in connection with the IoT device.

In the ﬁrst place, a research was made for the most

appropriate technologies for the development of the

systems such as Cloud Platforms to host the back-

end and front-end of the application, as well as other

resources such as databases, images, among others.

Also, as the IoT device that will help us to carry out

total control of the car. On one hand, a benchmark-

ing (see Table 1) was generated with those that best

suited the project requirements and, as mentioned in

Section 1, the services of AWS will be used. On the

other hand, for the IoT device, the Mobokey device

Carsharing System for Urban Transport in Lima using Internet of Things

327

from RoboArt, Inc. was used, which will allow us to

have control of the mechanical and electrical system

of the car.

For the creation of the benchmarkings, shown in

Table 1, a search of 10 papers was carried out to ob-

tain the alternatives and some characteristics of these

platforms and two papers to carry out both the def-

inition of the dimensions and the weighting of each

of these. The 10 dimensions were deﬁned, including:

Scope, Storage, Mobile Applications, Certiﬁcations,

Cost, Integration, Internet of Things (IoT), Migration

and transfer, Networks and content delivery, Security,

Usability. On the side of IoT Devices, in the same

way, a search was carried out for 10 papers to ob-

tain the alternatives and some characteristics of the

devices and two papers to carry out both the deﬁni-

tion of the dimensions and the weighting of each of

these. The 8 dimensions were deﬁned among them:

Standards and protocols, Consumption, Compatibil-

ity, Connectivity, Usability, Cost, Security, Support.

As mentioned above, the winning cloud platform was

AWS and the case of the IoT Device is Mobokey.

Likewise, the Android application will be devel-

oped under the Google framework, Flutter, which

will allow us to make the approval to iOS in the fu-

ture. Based on this, the application architecture was

designed under AWS services, which will help us,

as mentioned in Section 1, to make the application

serverless. In Fig. 2, the different AWS services that

will be used in the development of the project are

shown.

Figure 2: Application Architecture.

In the Fig. 2 we have Amazon RDS which will be

where we will store our relational database and can be

consulted by our back end. In the case of the Amazon

ElasticBeanstalk service, it will be the one who exe-

cutes our back end in a server-less manner with the

API’s necessary to obtain the information requested

by our application. Likewise, Amazon S3 will be

our storage for multimedia resources such as refer-

ence images of our cars, as well as images of driver’s

licenses. In addition to this, for our front-end deploy-

ments we will use the CodeCommit, CodeBuild and

Device Farm services, to be able to bring from our

repository, deploy, generate our APK and perform the

tests. Finally, AWS IoT and Amazon DynamoDB will

help us connect our IoT device to AWS and the col-

lected data can be stored in a non-relational database

in Amazon DynamoDB.

Followed by this, for the architecture to be con-

sidered as a mobile application architecture with IoT,

it must comply with the layers stipulated in the IoT

World Forum Reference Model, which is shown in

more detail in Section 2. According to this, the ar-

chitecture was modeled under the 7 layers of the ref-

erence model, complying with all the requirements.

The adaptation of this model according to our pro-

posed architecture is found in Fig. 1b.

As shown in Fig. 1b, in the Physical Devices and

Controller layer is our IoT Device, in our Connectiv-

ity layer, there is the connectivity protocol of our de-

vice that as mentioned in Section 2 will be BLE, in the

layer from Edge Computing and Data Accumulation

is the AWS IoT service, in the Data Abstraction layer

our two AWS services are positioned for each type

of database, AWS DynamoDB and AWS RDS. In the

Application layer, there are all the services that help

our application run such as AWS Elastic Beanstalk,

AWS S3, AWS CodeCommit, AWS CodeBuild, AWS

DeviceFarm and AWS Cognito. Finally, in Collabo-

ration and Processes you will ﬁnd both the car and the

Android smartphone. From this, we can conﬁrm that

the previously built architecture complies with the IoT

World Forum reference model.

As previously mentioned, the mobile application

was developed entirely under Flutter, where the user

registration logic was generated, which allows that

when the user registers, the specialized personnel of

the application can verify that the income data is true

and that it does not have serious or very serious traf-

ﬁc offenses, according to Peruvian legislation. In this

way, an additional layer of security is generated so

that trafﬁc rules are not violated or there is a bad

driver using our service.

In the case of the logic of the cost and the es-

timated time of the trip, the Google Maps Platform

APIs were used where different variables trafﬁc, time,

route and places were obtained from the Maps, Routes

and Places APIs, generating an algorithm that can

give the shortest route to the destination, estimated

WEBIST 2021 - 17th International Conference on Web Information Systems and Technologies

328

Table 1: Benchmarking (Cloud Platforms and IoT devices).

Dimension Weighting AWS Azure Alibaba GCP SCP

Scope 3% 0.09 0.15 0.09 0.09 0.00

Storage 10% 1.50 1.50 1.00 1.50 1.00

Mobile apps 4% 0.60 0.60 0.60 0.60 0.60

Certiﬁcations 3% 0.60 1.05 1.20 0.45 0.75

Cost 5% 0.65 0.55 0.50 0.65 0.25

Integration 10% 0.50 0.50 0.50 0.50 0.00

IoT 20% 12.00 11.00 8.00 12.00 8.00

Migration and transfer 15% 2.25 2.25 1.50 2.25 1.50

Networking and content delivery 15% 1.50 1.50 1.20 1.50 1.50

Safety 10% 1.00 1.00 1.00 1.00 1.00

Usability 5% 0.25 0.25 0.25 0.25 0.25

Total 20.94 20.35 15.84 20.79 14.85

time and cost of the service.

In the case of our IoT device, the Support team

gave us access to their SDK and the respective doc-

umentation, where they mentioned that the SDK and

API’s were in Native Android, being more speciﬁc in

Java, so the development team performed a Method

channel in both Android and Flutter to link the An-

droid activities and they can be executed through the

app in Flutter, linking each of the activities or func-

tions in Android with an asynchronous activity or

function in Flutter, that is, the Flutter function waits

for the response of the function on Android. In Fig. 3

the ﬁnal version of the application is shown.

Figure 3: Application Interface.

As can be seen in Fig. 3, there is the ﬁnal front-end

of the application where the client can register in the

application with a simple form to ﬁll out with infor-

mation such as name, surname, cell phone, identity

document, driver’s license, date of birth, email and

password. After that, they register and go to an eval-

uation stage that should not take more than 3 hours,

at that time the application administrator is alerted

through an email, evaluates that the user meets the

requirements described above, After evaluation, the

user is accepted or rejected. If the user is accepted,

they can log in to the application, where they can

make a reservation to any part of Metropolitan Lima

and choose the car closest to their location, show-

ing the route, the cost and the estimated time of the

trip and making the reservation. After that, the user

must approach the car and be able to connect with the

car, unlock the car or unlock the latches, start the trip

where the vehicle will turn on and when the destina-

tion is reached the car will turn off and after a few

seconds the carriage will lock completely. Followed

by this, users will be able to view the details of their

trip. Finally, users can also modify their proﬁle, reset

their password and view their travel history, as well

as the administrator can register, activate and block

users, and add new cars to the ﬂeet.

5 EXPERIMENTS

In this section, the experiments carried out in this pa-

per will be explained, starting from the experimental

protocol and the results, as well as its discussion.

5.1 Experimental Protocol

For the development of the application, we used a

laptop with a 64-bit Windows operating system, a

seventh-generation core Intel i5 processor, with 8 GB

ram (expanded to 24GB) and 2 TB storage was used.

Also, on the side of the programs we use Android Stu-

dio with version 4.2.1, Flutter 2.0.1 as an SDK, Java

8 and Spring Boot 4.12.

The APK for our app is available at https://bit.ly/

3iKLjRa

Carsharing System for Urban Transport in Lima using Internet of Things

329

Table 2: EasyDrive VS. Current situation.

Variables Now EasyDrive Reduction (%)

Public Transport







Average Waiting Time (min) 12.00 1.30 -89.17%

Travel Time per single trip (min) 59.00 37.00 -37.29%

Travel Time round trip (min) 171.00 97.00 -43.27%

Taxi







Average price per trip by taxi ($) 5.05 4.00 -20.83%

Average price weekly taxi rides ($) 50.51 40.10 -20.77%

Average price monthly taxi rides ($) 204.29 151.14 -26.02%

*A trip is aroung 8.3km

5.2 Results

In this section, we will show the results of the two

experiments developed in this investigation. In the

ﬁrst place, we will take into account the time and

cost savings with respect to the two most used means

of transport in Lima Metropolitana, which are buses

or popularly called ”micros o combis” and taxis. On

the one hand, in the case of buses, only the saving in

time will be taken into account, because in Lima bus

transport is considerably cheaper than other means of

transport, but the time that is invested is much greater

in comparison to other means of transport. On the

other hand, in the case of taxis, the economic savings

will be taken into account, since the time is equal to

or slightly greater than it would be in carsharing.

In principle, the annual report of the consulting

ﬁrm Moovit Insights in the city of Lima

will be taken

as base information for the case of buses, taking dif-

ferent variables such as: average waiting time in min-

utes, travel time per 8.3 km in minutes. Likewise, an

own study was carried out to obtain travel time per

16.2 km in minutes. On the side of the experiment

with taxis, the real prices obtained from the Cabify

app were taken into account, one of the most used

taxi applications in Lima, and the one generated by

our application with the aforementioned algorithms,

having a destination point same. As can be seen in

Table 2, in the case of buses there is an 89.17% or

10.7 minute reduction in waiting time for the vehi-

cle or at a bus stop. Likewise, the travel time for a

single trip (8.3 km) has been reduced by 37.29% or

22 minutes using EasyDrive carsharing compared to

buses. It has also been reduced by 43.27% or 74 min-

utes in travel time by 16.2 km. A dditionally, in the

case of the comparison between carsharing and taxis,

a reduction of 20.83% about 1.5$ was obtained in the

average price of a trip of approximately 8.3 km using

carsharing compared to taxi. There is also a reduc-

tion of 20.77% or 10.41 dollars in the weekly cost

Moovit Insights - https://moovitapp.com/insights/en/

Moovit Insights Public Transit Index Peru Lima-1102

that is currently had by using taxi versus what would

be spent weekly using carsharing. Finally, it was ob-

tained with simulated data, based on the information

previously extracted, that monthly there would be a

reduction of 26.02% or 53.14 dollars in the cost of

using a taxi twice a day versus the cost of using car-

sharing.

Second, functional tests were carried out with

Lima citizens within 20 and 55 years of different

districts of Lima, who tested the application and re-

sponded to a survey taking into account the user ex-

perience they had in this test, taking into account dif-

ferent variables such as:

• For the question “Do you think that carsharing

could help you to move to your workplace, your

study center or some other private place?”. 8 peo-

ple responded that carsharing can help them to

move in their daily activities. Therefore, it is con-

cluded that the service would be consumed by the

vast majority of inhabitants of Metropolitan Lima

belonging to our target audience.

• For the question “If the service were available to-

day, would the carsharing system be a primary or

complementary transportation alternative to other

modes of transportation?”. 6 people responded

that if the service were available today it would

be the main one they would use compared to other

means of transport and 2 that it would be comple-

mentary to these. Therefore, it is concluded that

the use of the service would be mostly used as the

main means of transportation.

• For the question “Based on your experience and

the Peruvian reality, do you consider that carshar-

ing could be a viable alternative for the Urban

Transport System of Metropolitan Lima?”. 8 peo-

ple responded that according to the current real-

ity, carsharing would be a viable alternative to

the urban transport system of Metropolitan Lima.

Therefore, it is concluded that the proposed ser-

vice would have great viability in the Lima popu-

lation of the proposed age range.

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5.3 Discussion

As could be seen in the previous section, the results

presented in the ﬁrst experiment (See Table II) show

that with the use of the application, a person can save

up to 43.37% of the time in trips through public trans-

port in Metropolitan Lima, this being a great contri-

bution to users since it is the transport where people

waste more time. Additionally, compared to one of

the most used alternatives to the well-known buses in

Lima, taxis, users would save an average of 20.77%

on the monthly cost that they currently use taxis for

trips of approximately 8km.

On the side of the experiment with end users (See

Fig. 5-9), the results show that the application has as

its main attribute functionality and development inno-

vation, obtaining 75% approval by the respondents.

Likewise, end users agree that the carsharing applica-

tion could become the main means of transport, suc-

ceeding in completely replacing it, and to a lesser ex-

tent complementing it with some means of transport.

Finally, the results obtained show that users consider

that the carsharing application has a clear viability in

the city of Lima Metropolitana.

6 CONCLUSIONS

Based on the research, it is concluded that a carshar-

ing system is feasible to be implemented in the city of

Lima Metropolitana, becoming an alternative to the

city’s Urban Transport System, based on the experi-

ments both with Lima citizens and through the com-

parative with studies carried out in the city. Likewise,

one of the main attractions for the use of the applica-

tion by the users who participated in the experiment is

the cost, since with the algorithm developed the sav-

ing in time and money is considerable compared to

other transport alternatives.

Finally, it is proposed that in future research, an

integration of the project is carried out in conjunc-

tion with artiﬁcial intelligence, helping to further en-

rich the different algorithms that provide more op-

timal routes and suggestions to the needs of users.

In addition, the implementation of a security model

aimed at carsharing applications is proposed where

the components of this will be analyzed both at the

application, data and technology level involved (Ban-

gui et al., 2018) and similarly to health applica-

tions (Jorge-L

evano et al., 2021). Finally, this type of

service could be expanded to other means of transport

and not focus only on cars. For example, join motor-

cycles, bicycles in conjunction with cars to meet the

needs of a larger group of users.

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