Car Color Research Articles

Optimizing Correction Factors on Color Differences for Automotive Painting Services

Currently, the automotive sector is showing increased demands regarding the color of cars in general, but especially the quality and the time of painting, in particular. Companies working in this industry, especially in specialized painting services, must perform work of impeccable quality in the shortest possible time in order to be efficient. Color differences that appear in different areas of the car result from the use of different formulas for obtaining color. These differences can be reduced by using correction factors that are established for the colors in the partial or total painting process of cars. There are several factors that lead to settings that are not verified by the real color and, therefore, contribute to incorrect color results and also to high and unnecessary repair costs. In this study, the authors aimed to optimize the values of the correction factors applicable in the automotive industry, based on a set of 135 measurements performed with a BYK Gardner spectrophotometer, in order to minimize color differences. Through this study, authors have also aimed to find out how the color-identification process can be streamlined with the smallest possible tolerances by optimally adjusting the correction factors and by identifying the factors that influence the color-reading and identification process. A total of 85 pairs of samples were used for the DS1 (data set) and 53 pairs of samples for the DS2 (data set); these samples were used in the visual experiments for testing the performance of two color-differentiation formulas. The first part of the research aimed to investigate the visual perception of the painted cars in terms of differences in brightness, chroma and hue, data that were used to optimize the formulas used for color differences. Finally, authors have estimated the closest color variant to the objective color by optimizing the correction factors and thus achieving the efficiency of the color-identification process and the whole painting-identification process.

Accelerating Awareness: Hidden Equity, Diversity, and Inclusion Learning Outcomes within an Immersive Classroom Activity

This work addresses the challenge of meaningfully introducing engineering students to equity, diversity, and inclusion (EDI) principles. Traditionally, tertiary education introduces these concepts through online modules and/or workshops, often ‘down-selling’ them compared to technical courses. This paper proposes a more impactful experiential approach targeting the affective learning domain. In collaboration with the Centre for Student Wellness, instructors designed a lesson integrating EDI principles into an interactive car simulation game. Students form teams and customize their cars based on survey responses, with rewards and penalties reflecting real-world inequalities. For instance, certain car colors or gender characteristics may result in penalties, mirroring observed racism and gender biases in STEM fields. This innovative approach aims to foster critical thinking about the role of personal privilege in decision-making, offering a dynamic learning experience beyond conventional methods.

Perceived Quality in the Automotive Industry: Do Car Exterior and Interior Color Combinations Have an Impact?

Since in the automotive field colors play an important role, the present study tried to answer the following questions: is the perceived quality (PQ) of the vehicle interior color different after visually exploring the car body color? If so, how? Here, exploiting immersive virtual reality simulations and eye-tracking technology, participants were asked to visually explore an unbranded car in different exterior/interior color combinations and rate its PQ. Fixation duration (time eyes are fixed on a target) was considered as an implicit measure of visual attention allocation while PQ evaluations were considered as explicit measures of individual preferences for car colors. As for eye-tracking data, the results showed that white and red car exteriors affected the attention to interiors with the fixation duration being longer for gray than black interiors. Moreover, the subjective evaluations of car PQ predicted eye-tracking patterns: as the negative evaluation increased, the fixation duration on car interiors also increased. Overall, these preliminary results suggested the need to further explore the relationship between PQ and attentional/motivational processing as well as the role of subjective aesthetic preferences for color combinations in the automotive field.

Crashworthiness analysis based on vehicle color and driver perception

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.

Matte Finish vs Light Reflection: Effect of Car Exterior Finish on Product Attractiveness

Perceived quality in industrial design constitutes CMF (color, material, and finish). Previous studies have explored the impact of car color and materials used on consumer behavior; however, there are only few studies on the impact of the type of surface finish, which this study focuses on. In the automobile industry, matte finish is provided mainly for luxury products. It is also known that the exterior design of automobiles improves the perceived quality by reflecting light. In other words, matte finish and light reflection are positioned as opposite design features. In this study, the following hypothesis was derived based on the literature on glossy finish: a matte finish of a car’s exterior has a negative impact on product attractiveness. For verification, two designs with the same SUV styling but different surface finishes (matte finish and light reflection) were studied. This hypothesis was supported and assessed using paired comparisons in an online survey. The same result was obtained regardless of conditions, such as gender, age, and ownership. This study addresses the gaps in knowledge on the effects of finish on product attractiveness and suggests that practitioners should not blindly believe the conventional perceptions of the industry.

System for automatic detection and classification of cars in traffic

Objective: To develop a system for automatic detection and classification of cars in traffic in the form of a device for autonomic, real-time car detection, license plate recognition, and car color, model, and make identification from video.Methods: Cars were detected using the You Only Look Once (YOLO) v4 detector. The YOLO output was then used for classification in the next step. Colors were classified using the k-Nearest Neighbors (kNN) algorithm, whereas car models and makes were identified with a single-shot detector (SSD). Finally, license plates were detected using the OpenCV library and Tesseract-based optical character recognition. For the sake of simplicity and speed, the subsystems were run on an embedded Raspberry Pi computer.Results: A camera was mounted on the inside of the windshield to monitor cars in front of the camera. The system processed the camera’s video feed and provided information on the color, license plate, make, and model of the observed car. Knowing the license plate number provides access to details about the car owner, roadworthiness, car or license place reports missing, as well as whether the license plate matches the car. Car details were saved to file and displayed on the screen. The system was tested on real-time images and videos. The accuracies of car detection and car model classification (using 8 classes) in images were 88.5% and 78.5%, respectively. The accuracies of color detection and full license plate recognition were 71.5% and 51.5%, respectively. The system operated at 1 frame per second (1 fps).Conclusion: These results show that running standard machine learning algorithms on low-cost hardware may enable the automatic detection and classification of cars in traffic. However, there is significant room for improvement, primarily in license plate recognition. Accordingly, potential improvements in the future development of the system are proposed.

The Most Popular Car Colors in the World

The Most Popular Car Colors in the World

Multi-ColorGAN: Few-shot vehicle recoloring via memory-augmented networks

Despite the notable successes of Generative adversarial networks (GANs) achieved to date, applying them to real-world problems still poses significant challenges. In real traffic surveillance scenarios, for the task of generating images of multiple color of truck heads and cars without changing textures and license plates, conditional image generation hardly manipulate the generated images by the color attribute. Image style transfer methods inevitably produce color smearing. Even state-of-the-art methods of disentangled representation learning (e.g. MixNMatch) cannot disentangle colors individually, ensuring that irrelevant factors, such as texture remain the same. To solve this problem, we present an approach called Multi-ColorGAN based on memory-augmented networks for multi-color real vehicle coloring/generation with limited data. In particular, our model could filter out unwanted color changes in specific areas with a simple but effective method called Fusion Module, and generate more natural color images. Experiments on three vehicle image benchmarks and a new truck image dataset are conducted to evaluate the proposed Multi-ColorGAN compared to state-of-the-art.

The Most Popular Car Colors in the World

The Most Popular Car Colors in the World

Color Design: Stage Research of Rail Car Virtual Simulation Project

For a long time, the display mode of color design is mostly two-dimensional pictures, which is relatively single, and there is still a certain gap between the effect and the reality. Based on the technology of virtual reality, this paper aims to change the traditional way of color perception of picture, through the three-dimensional color display mode of virtual simulation, to realize the real feeling of car body color design, and to facilitate the revision and improvement of color design. Analyze the color proportion and various RGB values in the existing color pictures, design the color of the rail car according to the relevant values, and carry on the virtual simulation display.

PENGELOLAAN PERILAKU HEMAT ENERGI BERDASARKAN WARNA PINTAR PADA MOBIL

<p class="06IsiAbstrak">MANAGEMENT OF ENERGY SAVING BEHAVIOR BASED ON SMART COLORS ON THE CAR. Energy constraints in the world lie behind countries to save energy. Unwittingly, the cause of the high fuel usage in cars lies of uses AC (Air Conditioner). The temperature in the car is influenced by the color of the car. Based on the problems above, inspiring researchers to analyze the color car effect on temperature to save fuel usage.</p>In this study, the author uses the study method and the observation method that is observing car as the object. After conducting experiment, cars color from the lowest temperature to the color that has the highest temperature is obtained. So the car color affects the temperature of the car. If the temperature in the car is high, it will affect the use of AC which has an impact on the use of fuel. In this research, the car color sequences that are good in saving fuel are white, silver, beige, red, blue, gray, black.

Sales prediction of Four Wheelers Unit (4W) with seasonal algorithm Trend Decomposition with Loess (STL) in PT. Astra International, Tbk

Corporate Information System and Technology (CIS&T) division in PT Astra International Tbk is digitizing all business lines. Therefore, the company started to utilize machine learning to predict four wheelers (4W) sales in 2017. Data used were car sales data from 2014 to 2016. The data were obtained from company’s data warehouse (DW). Further, to develop application, firstly, Minitab was used to compare algorithm in modelling phase. Then, Azure Machine Learning Studio (Azure ML) was utilized to build prediction model based on algorithm chose in first phase. Finally, visualization was developed using Power Business Intelligence (Power BI). Time series algorithm used to solve the case is Seasonal Trend Decomposition with Loess (STL). While, machine learning model uses R library, and process flow module in Azure ML. The STL prediction model yield 9.38% error. Visualization of result is divided into two sections filtered by three parameters type, color and area. The first section in dashboard is sales data report showing percentage of type, color of cars and deployment of 4W units in Indonesia through ArcGIS Maps. The second section is forecast result containing chart of x axis to represent year and y axis to represent number of units. Further, the chart provide historical, current and forecast information. The research contributes to illustrate development of prediction using machine learning in industrial environment.

Fast Generalized Linear Models by Database Sampling and One-Step Polishing

In this article, I show how to fit a generalized linear model to N observations on p variables stored in a relational database, using one sampling query and one aggregation query, as long as observations can be stored in memory, for some . The resulting estimator is fully efficient and asymptotically equivalent to the maximum likelihood estimator, and so its variance can be estimated from the Fisher information in the usual way. A proof-of-concept implementation uses R with MonetDB and with SQLite, and could easily be adapted to other popular databases. I illustrate the approach with examples of taxi-trip data in New York City and factors related to car color in New Zealand. Supplementary materials for this article are available online.

Multi-Modal Compositional Analysis of Layered Paint Chips of Automobiles by the Combined Application of ATR-FTIR Imaging, Raman Microspectrometry, and SEM/EDX.

For the forensic analysis of multi-layered paint chips of hit-and-run cars, detailed compositional analysis, including minor/trace chemical components in the multi-layered paint chips, is crucial for the potential credentials of the run-away car as the number of layers, painting process, and used paints are quite specific to the types of cars, color of cars, and their surface protection depending on the car manufacturer and the year of manufacture, and yet overall characteristics of some paints used by car manufacturers might be quite similar. In the present study, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) imaging, Raman microspectrometry (RMS), and scanning electron microscopy/energy-dispersive X-ray spectrometric (SEM/EDX) techniques were performed in combination for the detailed characterization of three car paint chip samples, which provided complementary and comprehensive information on the multi-layered paint chips. That is, optical microscopy, SEM, and ATR-FTIR imaging techniques provided information on the number of layers, physical heterogeneity of the layers, and layer thicknesses; EDX on the elemental chemical profiles and compositions; ATR-FTIR imaging on the molecular species of polymer resins, such as alkyd, alkyd-melamine, acrylic, epoxy, and butadiene resins, and some inorganics; and RMS on the molecular species of inorganic pigments (TiO2, ZnO, Fe3O4), mineral fillers (kaolinite, talc, pyrophyllite), and inorganic fillers (BaSO4, Al2(SO4)3, Zn3(PO4)2, CaCO3). This study demonstrates that the new multi-modal approach has powerful potential to elucidate chemical and physical characteristics of multi-layered car paint chips, which could be useful for determining the potential credentials of run-away cars.

GENDER, PLACE OF ORIGIN, AND SUPERSTITIOUS BELIEFS OF THAIS

The purpose of this study was to examine associations between gender, place of origin and superstitious beliefs. Twenty-five graduate students in one public university in Bangkok were gathered for data collection through a self-administrated questionnaire. Superstitious beliefs were confined to car color and number superstitions. To test research hypothesis, Pearson’s Chi-Square test was used. Results indicated that there was no statistically significant association between gender and superstitious beliefs. Additionally, no statistically significant relationship between place of origin and superstitious beliefs was found. Sample size expansion was recommended for a further study.

Study on the Impact of Color Image and Safety Cognition on Consumers’ Car Purchasing Behavior

With the prevailing use of cars in daily life, more and more people start considering safety regarding the color of cars and accident rate. For the concern of safety, some people even attempt to treat the color of cars as a priority when buying cars. However, the color design of an automobile is more than just beauty and fashion, it is also an indicator of safe driving. This study aims to probe into the impact of the color image of cars, safety cognition, and consumers’ car purchasing behavior when purchasing a car in Taiwan. This study collects data through questionnaire survey and the SPSS statistical analysis program, and conducts t testing, one-way ANOVA, Pearson product-moment correlation analysis, and regression analysis to validate the hypotheses. According to analytical research results, car owners’ color image positively and significantly influences safety cognition; car owners’ color image positively and significantly influences consumers’ car purchasing behavior; car owners’ safety cognition positively and significantly influences consumers’ car purchasing behavior.

Be Like This. Norms, Examples, Documents and Indexicals from a Neo-Aristotelian Perspective

I propose an account of exemplarity based on the (neo-Aristotelian) ontological distinction between individuals and properties, and on the corresponding semantic distinction between singular terms, which single out individuals, and predicates, which designate properties. I shall focus on indexicals as paradigmatic singular terms. For instance, “this man” is an indexical, whereas “man” or “red” are predicates. I shall define an example as an individual used as a constituent of a predicate, as when one says “The color of my car is like this” pointing at a particular sample. An example, so understood, is a sort of virtual finger or wand, which turns an individual singled out by an indexical (“this”) into a predicate (“like this”). I shall develop this conception of exemplarity in order to account for the normative force of examples. First, I shall characterize a normative claim as a sentence that connects a subject to a predicate through a deontic verb (should, ought, must, can, may etc.). Then, I shall call “normative exemplarity” the case in which the predicate of a normative claim is an example, as when one says “You should behave like this man” pointing at Socrates. Finally, I shall argue that some norms can be enforced within a certain community through normative exemplarity, provided that the relevant features of the exemplar individual (that to whom the indexical refers in the expression “like this”) remain accessible to the members of the community. I shall show that if the exemplar individual does not exist anymore, the community can still keep such norms in force by relying on documents that allow the community's members to steadily preserve the relevant features of that individual. Ultimately, understanding such processes of generation and preservation of examples can contribute to explain how normative systems emerge from the historical content of the times.

A Computer Aided Color Appearance Design System for Metallic Car Paint

A computer aided design system for determining the color appearance of metallic automotive coatings has been developed. A sketch based bidirectional reflectance distribution function design interface allows simple concept art to be used to style new metallic car colors. The final design is specified using industrial measurement standards for metallic color appearance, and paint formulations are determined by employing an automotive refinish system. A virtual collection of existing automotive paints, specified using the measurement standard, is provided, and tools for searching this database, for both design and manufacturing purposes, are described. The system is assessed by using it in industrial and educational design studios.

A Computer Aided Color Appearance Design System for Metallic Car Paint

A computer aided design system for determining the color appearance of metallic automotive coatings has been developed. A sketch based bidirectional reflectance distribution function design interface allows simple concept art to be used to style new metallic car colors. The final design is specified using industrial measurement standards for metallic color appearance, and paint formulations are determined by employing an automotive refinish system. A virtual collection of existing automotive paints, specified using the measurement standard, is provided, and tools for searching this database, for both design and manufacturing purposes, are described. The system is assessed by using it in industrial and educational design studios.

Seeing red on the road.

Human and animal research has found that red perception is associated with specific behavioral reactions, generally characterized by intense responses. Here, we explored whether red cars are perceived as more dangerous than other colored cars. One hundred Spanish drivers examined several road scenarios which involved hazardous cars with different colors: red, green, yellow, black, gray, and white. Driver's behavior (response time and probability of braking) and the perceived level of risk for each scenario were analyzed. Although car color affected participants' response times, contrary to expectations, red cars did not elicit faster responses or higher perceived levels of risk.