Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
DOI https://doi.org/10.31876/er.v47i7.849
Crashworthiness analysis based on vehicle color and
driver perception
Análisis de accidentabilidad en función del color del vehículo y la
percepción de los conductores
Esteban Nicolás Pérez Chauca*
Luis Armando Lema Vaca*
Guillermo Gorky Reyes Campaña*
Received: July 03, 2023
Approved: September 20, 2023
Abstract
Road safety has been of increasing concern in recent years, and
vehicle crashworthiness has been highlighted as a significant
challenge. While known factors such as improper driving, road
conditions and driving under the influence of substances have
contributed to this problem, a new perspective has emerged
regarding the color of cars and its impact on crash rates. Recent
research has indicated that the color of a vehicle can play an
important role in road safety. The colors red, silver, white and black
have been identified as those that drivers perceive most clearly in
different scenarios, such as time of day, distance and traffic location.
Keywords:
perception, sinister, color.
.
Cite this:
Pérez, E., Lema, L., Reyes, G.
(2023). Análisis de accidentabilidad
en función del color del vehículo y la
percepción de los conductores.
Espirales Revista Multidisciplinaria
de investigación científica, 7 (47),
* Ingeniero Mecánico Automotriz, Universidad
Internacional del Ecuador, esperezch@uide.edu.ec
https://orcid.org/0009-0004-4328-1321
* Ingeniero Mecánico Automotriz, Universidad
Internacional del Ecuador, lulemava@uide.edu.ec
https://orcid.org/0009-0008-2524-8455
* Ingeniero Mecánico Automotriz, Magister En
Sistemas Automotrices, Doctorado En Educación
Superior, Universidad Internacional del Ecuador.
gureyesca@uide.edu.ec, https://orcid.org/0000-
0002-7133-9509
Crashworthiness analysis based on vehicle color and driver perception
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
36
Introduction
Some studies were aimed at investigating the cause of traffic crashes, how to deal with
them and how to prevent them. Very few studies have investigated whether vehicle
color influences crash risk. In this article, the incidence of vehicle color on traffic crashes
was tested, identifying a difference in crash risk with respect to color would make people
make a more informed decision. Most research determined that the majority of crashes
are due to inappropriate driving, poor road conditions, driving under the influence of
substances (CESVI, 2021). According to research data, there is no color with a lower
accident rate.
In this article, the visibility of color vehicles was analyzed through surveys to drivers and
mathematical models to determine if the color implies a risk factor at the time of an
accident and to inform citizens about the precautions that should be taken in this
scenario. It was determined that the vehicle color with more demand at national level
in the last decade; through information gathered from written sources, surveys to
buyers, and in this way the guidelines by which buyers are guided at the time of
choosing the color were identified. Likewise, the different perceptions that vehicle users
have regarding colors in different scenarios were studied through an analysis of distance
and time zone. The factors that influence buyers when choosing the color of a vehicle
were identified by means of surveys and by assessing the criteria of the citizens, in order
to have a direct relationship between the buyer's criteria and the color to be chosen.
A study by the University of Auckland in New Zealand indicates that vehicles with black
colors have a higher accident rate, since, in contrast to silver and red colors, they have
a lower percentage of vehicle collisions (Auckland, 2021). In some studies conducted in
more depth on dark colors have a higher probability of accidents, since the sunlight, no
matter how intense it is not able to reflect all its brightness in these colors. With this
type of visual limitations, many drivers and passers-by do not see these colors in time
(CESVI, 2021). Through studies conducted by the University of AUCKLAND it has been
determined that dark colored vehicles have a higher accident rate than light colored
Resumen
La seguridad vial ha sido motivo de creciente preocupación en los
últimos años, y la accidentabilidad de los vehículos se ha destacado
como un desafío significativo. Aunque factores conocidos como el
manejo incorrecto, las condiciones de las vías y la conducción bajo la
influencia de sustancias han contribuido a este problema, ha surgido
una nueva perspectiva relacionada con el color de los automóviles y
su impacto en la tasa de siniestros. Investigaciones recientes han
señalado que el color de un vehículo puede desempeñar un papel
importante en la seguridad vial. Los colores rojo, plateado, blanco y
negro han sido identificados como aquellos que los conductores
perciben con mayor claridad en diferentes escenarios, como horas
del día, distancia y ubicación de tránsito.
Palabras clave:
percepción, siniestro, color.
Esteban Nicolás Pérez Chauca, Luis Armando Lema Vaca, Guillermo Gorky Reyes Campaña
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
37
vehicles; due to factors such as: sunlight and perception of the human eye do not allow
a correct visualization of dark colors.
Based on results from Colombia, they determined that light colors are detected by
drivers and passers-by at a distance of 200 meters before a dark vehicle (El
espectador,2008).
With respect to the work published in the British medical Journal, a study published in
Epidemiology in 2002 commented that it was found that yellow and white vehicles are
less likely to be involved in an accident compared to vehicles of other colors (Lardelli
Claret, et al., 2002). Another study conducted on the basis of documentation from
public transit agencies in Australia in 2003 investigated that blue, green and gray colors
are more likely to be involved in an accident than white (Newstead & D'Elia, 2007). Thus,
it is known that, due to the perception of the human eye, it was investigated that
vehicles with lighter colors are less likely to be involved in a traffic accident.
They were guided by the statistics made by BASF Color Report in South America, since
the colors most purchased by people is white with 40%, silver with 17%, black with 10%
and red with 6%, through these statistics surveys will be conducted to different people
to verify the point of visual perspective of each of the drivers and pedestrians both in
urban areas. (BASF Color Report). In Ecuador the trend is in line with the region in the
white color as it is one of the most sold and popular at the moment, followed by the
red color (El Telegrafo, 2020).
The first automobiles were painted with varnishes of natural elements and painted with
brushes and brushes. These were composed of linseed oil or turpentine, in case of
people with more economic power amber was used. When production of the Ford T
began, the company that supplied Ford made a mixture of asphalt base, enamel and a
hydrocarbon resin that made it dry much faster, also included an oven at 200 ° C and
thus achieved that the paint dried in an hour.
In the mid 20's GM created and marketed nitrocellulose-based paints, from which all
the colored paints of this time were derived, the only problem was that they yellowed
easily. With this type of paint the spray gun began to be used.
The FIA, in order to differentiate the vehicles in the competitions, created a color code,
the purpose of which was to identify the teams. The French were given the color blue,
this color is distinctive of the Alpine and Bugatti teams, the French were given the color
silver, the English used dark green and the Italians such as Ferrari and Alfa Romeo
participated with the color red.
At the end of the 60's, alkyd resin was created in Europe, it was later mixed with melanin-
formaldehyde to reduce the yellowing of light colors, with this process factories began
to paint by immersion.
In the 70's premium brands developed the 2K Acryl-Polyurethane paint, this type of
paint dried faster and gave greater resistance to scratches. Following this, in the 80's a
Crashworthiness analysis based on vehicle color and driver perception
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
38
layer of transparent varnish began to be used to protect the paint, which revolutionized
the durability of the colors.
In the 80's the application of a coat of varnish was consolidated, this was something
that revolutionized the durability of the paint, over time solvents were replaced and
changed to water-based paints which is the technology currently used in the painting
of vehicles.
Studies conducted by University of Dayton eCommns mentions that there are groups
prone to collisions; due to the color of the vehicles, since this factor can influence the
driver's visibility and thus contribute to a collision (University of Dayton eCommns,
2019). The vehicle colors with the highest crash rates are red, black, white, and silver.
The vehicles representing the highest percentage of accidents are black colored
vehicles figuring 15.5% i.e. 147,272 vehicles, followed by red colored vehicles with
14.9% which is equivalent to 140,869 vehicles, white 150,477 accident vehicles figuring
15.9% and finally 130,364 accident vehicles belong to the silver color category; which
represents 13.7%. The aforementioned data are from accidents during the years 2011-
2015 (University of Dayton eCommns, 2019).
Color is a visual perception produced in the brain due to transmission of nerve signals
that are captured by photoreceptors located in the eye. In physics, color is specifically
associated with electromagnetic radiation of a certain range of wavelengths visible to
the human eye. Radiation of these wavelengths constitutes the part of the
electromagnetic spectrum known as the visible spectrum, i.e. light. To describe color
we must speak of three physical actions such as, the production of a stimulus in the form
of light, which then bounces or is absorbed on a surface of an object and finally, the
subjective results, such as the reception and interpretation of this stimulus in the eye,
together with the brain or visual system from the object. (Sainz Cacho, 2017) Color has
three attributes among these are hue, lightness and saturation. The most visible colors
to the human eye are red, yellow and orange.
When talking about visibility, this refers to the human visual system. The light detected
by the eyes that has been transmitted by light sources. The greatest progress in the
knowledge of our vision system became possible as soon as we were able to make
direct measurements on the eye receptors (Chrisment, 1998).
There are two reasons why humans have visual color deficiencies. These are innate, in
other words, permanent, and having acquired it, in the latter there is a possibility of
being able to remove this deficiency; this usually occurs due to disease or accidents.
Much of the processing of color vision takes place at an early stage, in the retinal and
NGL stages, then the signal is transmitted to the cortex where it undergoes
transformations related to the color appearance of the visual stimuli. This contrasts that
the shape of an object is processed first and then filled with color.
The 5 fundamental pillars of road safety are: road safety management, which aims to
encourage the creation of partnerships between different agencies to create national
road safety plans and strategies. Safer roads and mobility, this is more specialized in
pedestrians, cyclists and motorcyclists, safer vehicles, the purpose of this is to
Esteban Nicolás Pérez Chauca, Luis Armando Lema Vaca, Guillermo Gorky Reyes Campaña
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
39
encourage the creation and use of better technologies in the active and passive safety
of the vehicle driver by means of new technologies. Safer road users and post-accident
response.
Materials and methods
In this study, the inductive method was used to obtain the test values and fulfill the main
objective of the article. Through the detailed and systematic observation of particular
cases and the identification of recurring patterns, conclusions were drawn. This
approach made it possible to discover significant trends and establish relationships
between key variables. By applying the inductive method, it was possible to capture the
complexity of the data collected, which provided a deeper and more contextualized
understanding of the phenomenon under study. The results obtained from this
approach supported and enriched the central discussion of the article, thus
strengthening its contribution to the field of research.
Two complementary approaches were used, the bibliographic method and the
statistical method. By means of the bibliographic method, an exhaustive review of the
existing literature in the field of study was carried out. Various sources were collected
and analyzed, including scientific articles and relevant papers, which provided a solid
theoretical and conceptual knowledge base. This bibliographic approach provided a
thorough understanding of the background and research related to this topic, as well
as contextual information and previous perspectives that helped to ground and enrich
the conceptual framework of the article. In addition to the bibliographic method, the
statistical method was used to analyze the data collected. Statistical techniques, such
as descriptive analysis, were applied to examine the relationships and patterns present
in the data. Using specialized software, careful tabulation and coding of the data was
carried out, which allowed us to obtain results in line with those already obtained with
the bibliographic method. Rigorous statistical analysis provided solid evidence and
supported the interpretation of the results, allowing us to reach reliable conclusions
supported by empirical data.
Overall, the combination of the bibliographic method and the statistical method
strengthened the validity and robustness of the findings obtained, providing a solid
basis for the specific objectives of the article.
In this research, light SUV type vehicles were used; this type of vehicle is one of the
most commercialized at the national level, since they are used for daily, family or work
use inside and outside the city. In Ecuador, from January 2021 to April 2023, 44.97% of
vehicles sold were SUVs (AEADE, 2023).
Through studies already conducted by BASF Color Report 2019', the Telegraph states
that, in Ecuador, the trend is in line with the region: white is the most popular color
followed by red and silver (El Telégrafo ,2020). A report on what have been the most
popular car colors this year, and the result shows that consumers prefer cars on a
monochromatic scale. The favorite color was white (38%), followed by black (19%), gray
(15%) and silver (9%). Together they account for 81% of car sales worldwide. Among
Crashworthiness analysis based on vehicle color and driver perception
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
40
the remaining colors are blue (7%), red (5%), brown or beige (3%), yellow or gold (2%),
green (1%) and other colors (1%) (AXALTA,2021).
Table 1:
Field test in Autopista General Rumiñahui.
DATE
White
Silver
Black
Red
Orange
Win
e
Blue
Celest
e
Green
26/08/2022
483
459
427
438
81
68
97
16
82
27/08/2022
386
425
345
420
54
45
84
19
67
28/08/2022
429
394
356
373
64
59
79
24
76
Totals
1298
1278
1128
1231
199
172
260
59
225
The test area to determine the colors of the most predominant vehicles and those used
in this article was on the General Rumiñahui Highway, a very busy area where, according
to the provincial council, an estimated 70,000 vehicles pass daily.
The perception and observation test was conducted on an asphalt road in a rural area
of Cayambe. This location was intentionally chosen to reduce the likelihood that the
urban area and vehicular traffic could affect the results of these tests. The asphalt road
provided a suitable and standardized surface for testing, which ensured equal
conditions for all vehicles.
In this study, INEN 1155 was used as the main standard for this article. This standard
establishes the technical requirements and specifications for vehicle lights in Ecuador,
including aspects such as luminous intensity, color and proper location of the lights on
the vehicle. Following this regulation ensured that vehicles comply with the established
standards in terms of lighting and visibility.
This is due to the fact that there are currently no Ecuadorian standards that specifically
regulate the methodology or procedure for taking tests. However, all the necessary
precautions were taken to guarantee the validity and reliability of the data taken.
The ANSI Rp-1 standard was used for the data collection of the surveys, which explains
the amount of luminosity that should exist in a space for the best visualization, color
reproduction and contrast so that it is adequate for the specific tasks assigned.
Cronbach's Alpha method was used to evaluate the reliability of the measurement
scales used in the research. Cronbach's Alpha method is a statistical scale that allows
estimating the internal consistency of a set of items or questions in a scale. This was the
method used because it was essential to guarantee the reliability and consistency of the
measurements made in the study.
By using this method, it was possible to evaluate whether the survey items used in the
data collection were consistently measuring what they were intended to measure. The
calculation of Cronbach's alpha coefficient provides a numerical estimate from 0 to 1
where values closer to 1 indicate greater internal consistency in the survey.
Esteban Nicolás Pérez Chauca, Luis Armando Lema Vaca, Guillermo Gorky Reyes Campaña
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
41
The choice of using Cronbach's alpha method in this article was due to the need to
ensure the reliability of the measurements and guarantee the validity of the results
obtained.
Equation 1.
𝛼 =
𝑘
𝑘−1
&'1−
Σ𝑉
!
𝑉
"
*
Where
α = Cronbach's alpha
k= number of items
V
i
= Variance of each item
V
t
= Variance of total
It is used to obtain the average of the data obtained, it is the sum of all the data and
this is divided by the total of these.
Equation 2.
𝑥, =
∑
𝑥
!
𝑁
Where:
x
i
= Data
N = Total data
Results
In this test, four SUVs of black, white, red and lead colors were used. A static and
dynamic test was performed on a rural road near Cayambe. These shots were taken of
the vehicles at 50-100-150 meters, because these are distances that can be taken both
on city streets and on the highway for greater safety.
The data collection parameters are shown in Table 2 and were taken at the time of
testing.
Next, we have the survey of people between 18-25 years old in a 7x4 meter room,
where they were presented with the tests for 3 seconds, followed by a blank screen for
them to answer the survey questions.
Table 2.
Variables
TAKING OF PHOTOGRAPHS
PARAMETERS
VALUE EN
Temperature
22°C
Weather
Clear
Vehicle-to-
camera distance
50-100-150 m ts
Altitude
2830 masl
Location 1
C. Napo, Ayora
Time
Brightness
11 am
70000 lux
Crashworthiness analysis based on vehicle color and driver perception
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
42
SURVEY TAKING
PARAMETERS
VALUE EN
Number of
participants per
group
40
Image duration
time
3 seconds
Screen size
Brightness
2,1m x 1,2m
170 Lux
In this survey, 18-25 year olds were asked to observe vehicles. The objective of this was
to assess their ability to distinguish the colors and number of vehicles at different
distances, they were presented with vehicles at 50, 100 and 150m meters away and
asked to identify the colors of each one.
The graph presents the results of the respondents' responses to a static vehicle
visualization test, where they were asked to identify the number of vehicles they could
observe on the road. The graph reflects the responses collected in relation to the ability
to observe vehicles at such a distance.
The survey results indicate that, in general, people identify cars well at a distance of 150
meters. This is important for safety, as it allows people to be aware of their surroundings
and avoid potential hazards. However, there is a small percentage of people who had
difficulty identifying cars at this distance, which may be due to several factors, such as
poor eyesight, lack of experience or distractions.
Figure 1.
Observation table for black, red and white vehicles.
Esteban Nicolás Pérez Chauca, Luis Armando Lema Vaca, Guillermo Gorky Reyes Campaña
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
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43
This survey assessed participants' perception of flashing lights presented at 150 meters
distance. Participants were asked to identify whether the flashing lights were on in each
of the vehicles and to rate the perceived improvement in terms of visibility and safety
when in such a situation.
Figure 2.
Perception chart of lead, white, red, black vehicles.
The graph presents the results of the survey of vehicle perception in static and dynamic
tests of different vehicles and colors. The survey was conducted on 15-25 year olds, and
the results show that the most common score for visibility in static and dynamic tests is
1. This means that most students do not find an improvement in vehicle visibility at this
distance between vehicles using flashing lights and vehicles not using flashing lights at
the distance of 150 meters.
The vehicle with the highest improvement in visibility in the perception test is white,
followed by lead, red and black.
When comparing the results of the observation survey and the perception survey,
interesting conclusions can be drawn. While the observation survey focused on the
participants' ability to identify colors and number of vehicles at different distances, the
perception survey focused on the participants' ability to detect and evaluate the
improvement, in terms of visibility, perceived when using the flashing lights.
Crashworthiness analysis based on vehicle color and driver perception
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
44
Figure 3
. Comparative table of observation and perception of test vehicles.
It was found that in the observation tests the respondents have better visibility when
identifying distant red vehicles, followed by black and finally white, taking into account
that white can be confused with a lead or silver color, in this case in the response of the
white vehicle there was a majority of responses of lead color being a total of 18 or 47%
of responses.
In the perception tests, an improvement is noted in the dynamic tests with respect to
the white color, followed by the lead color, red and finally black, which has very little
improvement in its visibility.
This provided a more complete understanding of how visual perception and attention
relate to the identification of vehicles and their colors in different driving conditions,
thus informing road safety and the importance of visual aspects and their reactions.
Conclusions
Dark vehicles increase the probability of causing accidents, because drivers do not have
a good perception of these colors at different distances; it is important to mention that
the white and lead colors present in the study are those that have the lowest accident
rate, the mathematical method Cronbach's alpha helps define the test reliability for
perception studies, in this study this coefficient gives us a value of 0.83, this means that
this has a high level of reliability, the evaluation method is highly reliable and therefore
its results as well.
Based on the results obtained in the surveys conducted; it is determined that the color
with the highest perception is the white vehicle, followed by the lead color vehicle, a
lower visualization of the red and black color vehicle is observed, these results were
obtained through the field tests already mentioned, the observation in the red vehicle
is 95% this determines that this color is more visible to the driver, while the observation
of the black vehicle is 89%, and of the white vehicle 45% this refers to that this color has
a low visibility for the drivers. Within the studies conducted it was established that the
perception has an improvement of 13.75% of visualization when the driver uses the
flashing lights in the distances mentioned above, the flashing lights are a very important
tool that helps drivers to the perception and visualization of vehicles either by their color
or by certain distance.
Esteban Nicolás Pérez Chauca, Luis Armando Lema Vaca, Guillermo Gorky Reyes Campaña
Espirales. Revista multidisciplinaria de investigación científica, Vol. 7, No. 47
October - December 2023. e-ISSN 2550-6862. pp 35-47
45
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