2 RELATED WORK
The technological advances of smartphones, in terms
of processing capacity, sensor integration and data
communication, has motivated a massive use by users
around the world. In particular, the fact that
smartphones integrate different types of sensors, e.g.,
location, environmental variables, user activity,
facilitate the acquisition of information about what
surround us. Based on these data, it is possible to
develop applications and provide services geared to
user needs (Rafael, et al., 2016).
Conventional, low-cost GPS devices that are
integrated in various devices, e.g. smartphones, have
an error that, depending on the purpose of their use,
may or may not meet the necessary requirements. In
the case of the monitoring of the geographical
position of vehicles, this error can be an obstacle to
the safety of users. In order to increase location
accuracy, even using non-professional GPS sensors,
there are algorithm-based solutions that allow you to
present more accurate data.
Han Kim propose an algorithm to increase the
accuracy in positioning the data collected by a low-
cost GPS sensor. This method uses the information
collected by the GPS sensor associated with the
vehicle in progress, places that data in a buffer and,
after the buffer is complete, matches the vehicle's
trajectory with a predefined map (Kim, et al., 2016).
Based on the determined error, rotations and
translations are applied to correct the trajectory of the
vehicle.
Based on the location of the vehicles through the
GPS coordinates and later calculation of their travel
path, it is possible to monitor the traffic at a certain
location. For this, it is only necessary to count
vehicles and contextualize the route on a map. By
knowing the number of vehicles that circulate in a
certain street and adding the vehicles that follow the
same route, it is possible to anticipate a forecast of the
traffic.
What D’Andrea e Marcelloni presents is a system
to detect congestion and traffic incidents, from GPS
data collected in real time. This system aims to be an
useful tool for countries and cities in the management
of traffic density. Therefore, it uses the GPS sensors
present in vehicles and mobile devices to acquire the
necessary data for the system, e.g., smartphones or
tablets (D'Ándrea and Marcelloni, 2017).
Adaptative Cruise Control (ACC) is a system that
keeps the speed of a vehicle constant and safe for the
user, taking into account the distance of the vehicle in
front of you. This system uses "LiDAR" (Light
Detection And Ranging) sensors to measure distance
and cause accelerations and decelerations as needed
(Noei, et al., 2016). However, the response of the
sensors to the changes has a large delay. In addition,
they are also susceptible to interference from the
environment, e.g., in the case of vegetation, their
physiognomy may induce the result of the reflection
in error. A solution to increase the response speed of
the ACC system is to use wireless communication
between vehicles-to-vehicles (V2V) and vehicles-to-
infrastructures (V2I) (Noei, et al., 2016). This
paradigm is called the Cooperative Adaptive Cruise
Control (CACC). Considering, then, the scheme in
Figure 1 composed of three vehicles, a leader and two
precedents: each vehicle sends via V2V
communications its current state that includes its
position, speed and acceleration or deceleration. This
same data is received by other vehicles traveling in
the same range (Noei, et al., 2016).
Wireless comm. Wireless comm.
Follower l=1Follower l=2Follower l=3
LIDAR LIDARLIDAR
Figure 1: Representation of CACC system based in (Noei,
et al., 2016).
However, as it happens with the GPS signal, both
are susceptible to electronic interference. These
interferences may arise from natural causes, e.g.,
electromagnetic noise or, hence, structured attacks by
hackers (Carson, et al., 2016). To keep the system
robust, both systems should be used together, i.e.
"Drive" sensors for distance control and V2V or V2I
communication to increase the speed response.
3 METHODOLOGY
The parade of Sr. ª D’Agonia is organized by sections,
in which each section is composed of participants
and/or floats (Carros Alegóricos). During the parade
the distance between the sections should be
considered uniform, for example, between the
participants and the float of section 1 and section 2
there should be a range of 10 meters. An empty space
happens when this distance is not respected and does
not allow the spectacle to be able to see two
consecutive sections in a row, as Figure 2 shows.
Thus, a break in the flow of the parade is generated.
During the parade there are people, called
collaborators and organizers, who are responsible for
keeping the parade together and organized, avoiding
the existence of empty spaces. These people are