A study of cultural models in automotive HMI : framework for accommodating cultural influence.

This doctoral innovation report presents a research study examining the importance of understanding automotive users’ cultural values and their individual preferences for HMI features and functionalities. The goal of this research was to explore how a cultural model can be applied in the development of automotive HMI solutions and future design localisation. To meet this goal, it was necessary to (1) identify the characteristics of the Hofstede cultural model; (2) identify the differences in cultural values using the model; (3) identify differences in HMI design preferences, usability and task performances across automotive user groups; (4) identify the potential success of a culturally adapted automotive HMI solution in automotive user acceptance and satisfaction. To explore the differences between users from two cultural regions, India and the UK, a series of user-centered HMI evaluation studies are conducted in which participants from each cultural region evaluate representative HMI samples. The outcomes of the user studies generate good quality data about automotive users’ cultural values and its relationship with vehicle user interface usability, task performances, and their feature preferences. The results are used in the development of a conceptual culturally adapted HMI design solution. This conceptual design is evaluated during the application phase of the research in order to explore whether such a design solution has a greater level of learnability and usability compared to the conventional solution when evaluated by Indian drivers. The results are also analysed to identify specific cultural traits that may influence the intention to use such solution in emerging markets like India. The outcome of the study shows different cultural groups have different behavioural tendencies and performances while using vehicle HMI solutions and have differences in expectations in design, suggesting an influence of culture on the perception of vehicle user interface technology. The analysis also highlights a preference for the culturally adapted automotive HMI solution when Indian drivers are provided with a choice between this and a non-adapted conventional solution. This leads to the conclusion that an understanding of cultural biases can influence design localisation and, as such, culturally-generated theories and recommendations can be applied as a basis for future automotive HMI design and development

Cross-cultural differences in automotive HMI design : a comparative study between UK and Indian users’ design preferences

This paper presents a research study examining the importance of understanding automotive users’ cultural values and their individual preferences for human machine interface (HMI) design features and functionalities. The goal of this research was to explore how a cultural model can be applied in the development of automotive HMI solutions and future design localization. To meet this goal, it was necessary to (a) identify the characteristics of the Hofstede cultural model, (b) identify the differences in cultural values using the model, and (c) identify regional differences in HMI design needs and preferences across drivers from India and the UK. The results highlighted differences in expectations for HMI systems between the groups, suggesting an influence of culture on the perception of vehicle user interface technology. This led to the conclusion that an understanding of cultural biases can influence design localization and support development strategies. In addition, two main categories of further research have arisen as a result of this project. The first category focuses on identifying methodologies to establish relationships between culture and regional drivers’ HMI design preferences. The second category comprises new research questions on tools and processes to deal with cultural influences

3D Simulation of a Yogurt Filling Machine Using Grafcet Studio and Factory IO: Realization of Industry 4.0

Manufacturing systems, enterprises and academic institutions worldwide are implementing Industry 4.0 (IR4.0). By integrating the services and equipment, IR4.0 develops autonomous systems that manage industrial operations and exchange real-time data in real time. This study includes a simulation of an existing production system using the GRAFCET Studio software. To realize the concept of a 3D smart factory, the GRAFCET programming language was used and connected to the Factory IO software. The simulation can accurately replicate the filling, scanning and removing processes in an actual yogurt filling system. A virtual factory was designed and developed using the IO Factory software to clarify the workflow and simplify the modification of the production line. This virtual factory better enables the identification of areas for optimization, improving also efficiency and productivity. A comparison between the simulated and the actual system results shows that the simulated results are approximately 90% accurate. In addition, some improvements are proposed to enhance the existing system\u27s efficiency. The improvements involved the testing of the system under different conditions to identify shortcomings and modify the design accordingly

What If Your Car Would Care? Exploring Use Cases For Affective Automotive User Interfaces

In this paper we present use cases for affective user interfaces (UIs) in cars and how they are perceived by potential users in China and Germany. Emotion-aware interaction is enabled by the improvement of ubiquitous sensing methods and provides potential benefits for both traffic safety and personal well-being. To promote the adoption of affective interaction at an international scale, we developed 20 mobile in-car use cases through an inter-cultural design approach and evaluated them with 65 drivers in Germany and China. Our data shows perceived benefits in specific areas of pragmatic quality as well as cultural differences, especially for socially interactive use cases. We also discuss general implications for future affective automotive UI. Our results provide a perspective on cultural peculiarities and a concrete starting point for practitioners and researchers working on emotion-aware interfaces

Designing the Human Machine Interface to Address Range Anxiety

It is essential that the interfaces of low carbon vehicles particularly fully Electric Vehicle (EV) support new users while they adjust to a different type of driving experience. Use of EV is not yet widespread and little is known about the user requirements for Human Machine Interfaces. One of the common concerns is driver anxiety about his/her vehicle’s ability to cover the distance required. However the problem is one of perception and driver experience in the context of new technologies, EV’s limited range and an immature charging infrastructure. Nevertheless eliminating range anxiety for the EV owner is one of a major design challenges for future Low Carbon Vehicle manufacturers. The current study found that drivers who had some experience of driving an EV have less anxiety than those who had never driven an EV. Experienced drivers develop strategies to ensure that they only undertake those journeys that they are confident about having enough range to complete and aware of the factors that could potentially impact on the range. It is clear from users’ feedback that estimated range of the vehicle is one of the most critical pieces of information for a driver. Combining this with battery state of charge information can provide the driver with a better understanding of the current range of their EV. However accuracy is a key factor to gain trust in range information. EV drivers need dynamic information on factors that influence available range. There is also a requirement for information that will enable drivers to drive economically. While designing the EV driver information system, designers must overcome the information complexity issue. Concerns were raised that complex information in current EVs could potentially lead to driver distraction and may increase anxiety further. In conclusion providing reliable, relevant and prioritise information can help to minimise range anxiety

A study of cultural influence in automotive HMI : measuring correlation between culture and HMI usability

This paper describes a comparative study aimed at identifying cultural differences in automotive-HMI usability. This was part of a larger research to investigate in depth the problems users experience with vehicle-HMI in emerging-regions and help in the development of HMI design guidelines to include cultural consideration. Culture is recognised as a significant influence on user behaviour, as it correlates with certain preferences and abilities. A system may be fully usable for one group of users and environmental conditions but totally unsuitable for another. Even if a conscientious engineer designs a proper human-machine-interface for use in a given environment, the designer is often unable to foresee effects of a different culture on vehicle's HMI usability. Culture has different patterns of social behaviour and interaction which have led many researchers to develop cultural-models to describe these differences. With these in mind, current focus of this study seeks to address three interrelated questions, 1) Are there elements within automotive-HMI that can be identified as culturally specific? 2) Does culture influences user usability performances and how or if cultural-model can be applied to explain the findings? 3) How cultural-model can assist in understanding cross-cultural differences in automotive-HMI usability. This study is based on Hofstede cultural-model. The research assessed their application in cross-cultural differences and applicability in automotive-HMI. To identify cultural sensitive design elements for usability and universal access, systematic usability experimentation was performed in a vehicle-HMI-system. The result showed different cultural groups have different behavioural tendencies and performances while using HMI in a vehicle

Designing the human machine interface to address range anxiety

It is essential that the interfaces of low carbon vehicles particularly fully Electric Vehicle (EV) support new users while they adjust to a different type of driving experience. Use of EV is not yet widespread and little is known about the user requirements for Human Machine Interfaces. One of the common concerns is driver anxiety about his/her vehicle's ability to cover the distance required. However the problem is one of perception and driver experience in the context of new technologies, EVs limited range and an immature charging infrastructure. Nevertheless eliminating range anxiety for the EV owner is one of a major design challenges for future Low Carbon Vehicle manufacturers. The current study found that drivers who had some experience of driving an EV have less anxiety than those who had never driven an EV. Experienced drivers develop strategies to ensure that they only undertake those journeys that they are confident about having enough range to complete and aware of the factors that could potentially impact on the range. It is clear from users' feedback that estimated range of the vehicle is one of the most critical pieces of information for a driver. Combining this with battery state of charge information can provide the driver with a better understanding of the current range of their EV. However accuracy is a key factor to gain trust in range information. EV drivers need dynamic information on factors that influence available range. There is also a requirement for information that will enable drivers to drive economically. While designing the EV driver information system, designers must overcome the information complexity issue. Concerns were raised that complex information in current EVs could potentially lead to driver distraction and may increase anxiety further. In conclusion providing reliable, relevant and prioritise information can help to minimise range anxiety

Identifying HMI requirements from field trials and the accounts of early adopters of low carbon vehicles

Low carbon vehicles offer a means of reducing carbon emissions and helping sustainability. However, their rapid introduction has meant that there has been little opportunity to fully consider the nature of the eco-driving task, the added demands it places on drivers, the HMI requirements and the development of a road infrastructure that can support low carbon driving. In the transition to more sustainable forms of transport it is worth considering what lessons Original Equipment Manufacturers (OEMs) and interface designers can learn from the experiences of early adopters and how these can inform future development of HMI

Offline Handwritten Character Recognition Including Compound Character from Scanned Document

Recognizing the handwritten characters and converting them into machine-editable text is very tedious due to the diversity of writing styles and character patterns. Extracting data from images and identifying the characters becomes more complicated when a language consists of compound structures and characters, such as Bengali. There has been a lack of programs for recognizing Bengali scripted basic and com-plex numeric signs and letters with high accuracy. This paper develops a novel approach to extracting and identifying Bengali handwritten primary characters, digits, and primarily used compound characters. In this proposed model, an image containing Bengali handwritten text takes as input and processed. Then processed images are segmented into lines and characters. The features are extracted from segmented characters and recognized using a Convolutional Neural Network (CNN). The CNN obtains 98.23% accuracy in the training dataset and 96.02% in the validation dataset. Apart from that, the proposed model has gained 89.6% precision and 92.6% recall scores on scanned image data