Automotive Human Machine Interface Research Articles

Navigating from data-driven design to designing with ML: a case study of truck HMI system design

AbstractData-driven design is believed to be empowered by machine learning (ML) with advanced pattern classification and prediction. However, research on how ML can be used to support automotive human-machine interface (HMI) design is lacking. We presented a case study of truck HMI design to understand the current data use and expectations of ML in the design process. Findings show decentralized data practices, the role of expertise in decision-making, and the envisioned reactive use of ML, where we underscore the implications for advancing human-ML collaboration in designing future truck HMI systems.

The Impact of Transparency on Driver Trust and Reliance in Highly Automated Driving: Presenting Appropriate Transparency in Automotive HMI

Automation transparency offers a promising way for users to understand the uncertainty of automated driving systems (ADS) and to calibrate their trust in them. However, not all levels of information may be necessary to achieve transparency. In this study, we conceptualized the transparency of the automotive human–machine interfaces (HMIs) in three levels, using driving scenarios comprised of two degrees of urgency to evaluate drivers’ trust and reliance on a highly automated driving system. The dependent measures included non-driving related task (NDRT) performance and visual attention, before and after viewing the interface, along with the drivers’ takeover performance, subjective trust, and workload. The results of the simulated experiment indicated that participants interacting with an SAT level 1 + 3 (system’s action and projection) and level 1 + 2 + 3 (system’s action, reasoning, and projection) HMI trusted and relied on the ADS more than did those using the baseline SAT level 1 (system’s action) HMI. The low-urgency scenario was associated with higher trust and reliance, and the drivers’ visual attention and NDRT performance improved after viewing the HMI, but not statistically significantly. The findings verified the positive role of the SAT model regarding human trust in the ADS, especially in regards to projection information in time-sensitive situations, and these results have implications for the design of automotive HMIs based on the SAT model to facilitate the human–ADS relationship.

A Study of Bibliometric Trends in Automotive Human–Machine Interfaces

With the development of autonomous driving technology and the internet, automotive human–machine interface (HMI) technology has become an important part of contemporary automotive design. Currently, global automakers are designing a variety of innovative in-car HMIs that illustrate the direction of automotive design in the new era from the perspective of technological aesthetics and experience design. However, sleek designs and innovative experience methods must be built on the basis of safety. Therefore, it is necessary to summarize existing research in the field of automotive HMI and construct a literature review of automotive design research. In this paper, literature on automotive HMI from the Scopus database was analyzed using bibliometric methods such as descriptive analysis, keyword co-occurrence, and literature co-citation network analysis. The final mapping analysis revealed that the current automotive HMI research literature primarily focuses on user research, interface research, external environment research, and technology implementation research related to automotive HMI. The three main stages of automotive HMI research include conceptual construction, system and technology refinement, and user perception research from the perspective of driver assistance and information recognition. Additionally, burst detection suggests that future research should focus on driver assistance, trust levels, and e-HMI information communication.

Translating non-experts’ perception for expert engineers: A first step in co-designing automotive human–machine interfaces

This paper focuses on the study of a product experience’s perception. It is then discussed how automotive Human-Machine Interfaces, as interactive products, are singular in their design process, perception, and evaluation. As essential products for a satisfactory user onboard experience, it is necessary for experts to have access to a translation of the non-expert perception, in a research and development perspective. Arguments about the benefits of using a sensory evaluation method, adapted to this kind of complex product, are provided. In this study, a sorting task evaluation is performed on naive people, to quantify and qualify the perception of a large number of stimuli. The paper proposes a statistical analysis methodology for processing data from a complex product evaluation. The analysis offers several levels of perception interpretation in order to provide a translation at different levels as well. An application example is given for three attributes that are different in nature and interpretation.

Challenges and Opportunities in Developing Next Generation In-Vehicle HMI Systems

The next generation of automotive human machine interface (HMI) systems is expected to be heavily dependent upon artificial intelligence; from autonomous driving to speech assistance, from gesture & touch-enabled interfaces to web & mobile integration. Smooth, safe, and user-friendly interaction between the driver and the vehicle is a key to winning market share. This panel aims to discuss challenges and opportunities for the next generation of automotive HMI from the perspective of human factors and user behavior. Panelists from industry and academia will offer their unique perspectives on the concerns and opportunities in developing future in-vehicle HMIs.

An engineering perspective on the quality of the automotive push-buttons’ haptic feedback in optimal and suboptimal interactions

Designing automotive Human–Machine Interfaces falls into a resource-intensive and iterative prototyping process. Design inputs, including those resulting from an automaker’s brand sense, frequently emerge from subjectively evaluating the products. This research aims at characterising the haptic feedback afforded by push-buttons’ prototypes. It introduces quality criteria, by assessing feedback degradation when actuations depart from optimal conditions and fall into suboptimal interactions. From reviewing published literature in HMIs’, metrics for characterising haptic profiles are insufficient and the taxonomy is unclear, redundant and conflicting. Experiments were built, providing prototypes with distinguishable feedbacks. Their haptic profile was measured and translated into unique engineering parameters, including new metrics to address feedback resilience in suboptimal actuations. Perceptual processes are involved, with the interpretation of data extended by using human Just-Noticeable-Differences (JNDs) thresholds and a psychophysical model of finger compliance. The outcome of this research is twofold: a contribution to a better understanding of push-buttons haptic feedback, enabling the definition of desired interactions and meeting brand sense expectations in early design stages of HMIs; and a proposed taxonomy for characterising push-button haptic feedback. The results achieved and the research methodology are extendable for similar design activities that require Human–Machine interactions, development of HMIs in general, and virtualisation of haptics.

Evaluating secondary input devices to support an automotive touchscreen HMI: A cross-cultural simulator study conducted in the UK and China

Touchscreen Human-Machine Interfaces (HMIs) are a well-established and popular choice to provide the primary control interface between driver and vehicle, yet inherently demand some visual attention. Employing a secondary device with the touchscreen may reduce the demand but there is some debate about which device is most suitable, with current manufacturers favouring different solutions and applying these internationally. We present an empirical driving simulator study, conducted in the UK and China, in which 48 participants undertook typical in-vehicle tasks utilising either a touchscreen, rotary-controller, steering-wheel-controls or touchpad. In both the UK and China, the touchscreen was the most preferred/least demanding to use, and the touchpad least preferred/most demanding, whereas the rotary-controller was generally favoured by UK drivers and steering-wheel-controls were more popular in China. Chinese drivers were more excited by the novelty of the technology, and spent more time attending to the devices while driving, leading to an increase in off-road glance time and a corresponding detriment to vehicle control. Even so, Chinese drivers rated devices as easier-to-use while driving, and felt that they interfered less with their driving performance, compared to their UK counterparts. Results suggest that the most effective solution (to maximise performance/acceptance, while minimising visual demand) is to maintain the touchscreen as the primary control interface (e.g. for top-level tasks), and supplement this with a secondary device that is only enabled for certain actions; moreover, different devices may be employed in different cultural markets. Further work is required to explore these recommendations in greater depth (e.g. during extended or real-world testing), and to validate the findings and approach in other cultural contexts.

Psychoacoustic metrics for assessing the quality of automotive HMIs’ impulsive sounds

Designing an automotive HumanMachine Interface (HMI) falls into a resource intensive and iterative prototyping process, where design inputs also emerge from subjectively evaluating the products. These inputs are defined from the outcome of the automaker’s brand sense appraisal process: achieving a desired and holistic perception of product experience. This work aims at characterizing the acoustic feedback of mechanical push–buttons’ prototypes, parametrizing their sound by an array of acoustic and psychoacoustic parameters. A review of literature published in automotive sound quality was performed, specially addressing impulsive sounds. From this review, a list of metrics for both temporal and spectral content stands as a contribution to methodologies addressing impulsive sounds.This research made use of a Design of Experiment (DOE), producing 18 minor variations of an automotive push–button, designed for affording different haptic feedback. Yet, the DOE impact on acoustic emissions remained unclear. An experimental procedure allowed the prototypes’ sound characterization with acoustic and psychoacoustic metrics. Parametric data was analysed to assess feedback consistence within each design and sound differences among design variations. The work includes an interpretation of results with perceptual thresholds, including Just–Noticeable Differences (JNDs) for the hearing sense. This work also found discrepancies and reports different interpretations of results when comparing SPL with loudness models, and standardized loudness models with a psychoacoustic model specific for impulsive sounds. It was concluded that both sound duration and the nature of fast-decaying impulsive sounds explains the different results among loudness models. Despite numerical differences, the introduction of JNDs in the interpretation of results showed that the design variations of the prototypes almost do not introduce noticeable differences in the psychoacoustic feedback. Exceptions were found in some designs for a single metric, sound duration.

Plastic Displays Will Play a Major Role in Automotive HMIs

Automotive trends, including increasing reliance on the human‐machine interface (HMI) for the vehicle, indicate that future displays will need to be curved and shaped to fit any surface in the car. To speed adoption and reduce costs, it is desirable that this new generation of displays is manufactured using the existing automotive supply chain and building as much as possible on proven technologies.

26‐4: Invited Paper: Automotive HMI: Present Uses and Future Needs

Nowadays, Human‐Machine Interfaces (HMI) are used everywhere and according to the forecasts, automotive HMI market will reach several billions by 2022. In automotive industry, HMI are more and more present with, for example, displays with new properties (curved, flexible, contact‐less, transparent...) or immersive systems (Head‐Up Display and augmented reality systems). Our challenge is to propose best‐in‐class user‐experience, up‐to‐date and affordable HMI systems to pave the way of attractive and autonomous vehicles. The aim of this talk is to give an overview of this field in automotive. After a brief introduction on automotive’s challenges for next decade and automotive’ qualification constraints, present uses and futures needs for Human Machine Interface systems from displays to Head‐Up Display and Augmented Reality including controls with and without contact will be exposed.

Toward best practice in Human Machine Interface design for older drivers: A review of current design guidelines

Older adults are the fastest growing segment of the driving population. While there is a strong emphasis for older people to maintain their mobility, the safety of older drivers is a serious community concern. Frailty and declines in a range of age-related sensory, cognitive, and physical impairments can place older drivers at an increased risk of crash-related injuries and death. A number of studies have indicated that in-vehicle technologies such as Advanced Driver Assistance Systems (ADAS) and In-Vehicle Information Systems (IVIS) may provide assistance to older drivers. However, these technologies will only benefit older drivers if their design is congruent with the complex needs and diverse abilities of this driving cohort. The design of ADAS and IVIS is largely informed by automotive Human Machine Interface (HMI) guidelines. However, it is unclear to what extent the declining sensory, cognitive and physical capabilities of older drivers are addressed in the current guidelines. This paper provides a review of key current design guidelines for IVIS and ADAS with respect to the extent they address age-related changes in functional capacities. The review revealed that most of the HMI guidelines do not address design issues related to older driver impairments. In fact, in many guidelines driver age and sensory cognitive and physical impairments are not mentioned at all and where reference is made, it is typically very broad. Prescriptive advice on how to actually design a system so that it addresses the needs and limitations of older drivers is not provided. In order for older drivers to reap the full benefits that in-vehicle technology can afford, it is critical that further work establish how older driver limitations and capabilities can be supported by the system design process, including their inclusion into HMI design guidelines.

Service based Mobile Test Automation Framework for Automotive HMI

Objectives: To implement a Service based Test Automation framework for testing web services in automotive Human Machine Interface (HMI) application. In this paper, we propose a service based test automation framework for web service testing in automotive HMI (Human Machine Interface). Methods: There are number of testing frameworks available for testing mobile application; In this proposal, an automated testing framework has been designed to test services which communicate between mobile application and real vehicles (cars) using differenttechnologies web services and mobility testing tools. Findings: In our findings, a customized mobile test automation framework has been developed which can eliminate most of the errors that may exist in manual testing by human and reduce a lot of time. Moreover, the framework can easily be extended to find a broader range of testing in automotive mobile applications. The techniques and mechanisms used in creating a test automation framework leads to analyze how they can do regression testing on mobile services in an efficient manner.

Developing Visual Complexity Metrics for Automotive Human-Machine Interfaces

Objective: The purpose of this study is to develop visual complexity metrics based on theoretical bases.BR Background: With the development of IT technologies, drivers process a large amount of information caused by automotive human-machine interface (HMI), such as a cluster, a head-up display, and a center-fascia. In other words, these systems are becoming more complex and dynamic than traditional driving systems. Especially, these changes can lead to the increase of visual demands. Thus, a concept and tool is required to evaluate the complicated systems.BR Method: We reviewed prior studies in order to analyze the visual complexity. Based on complexity studies and human perceptual characteristics, the dimensions characterizing the visual complexity were determined and defined. BR Results: Based on a framework and complexity dimensions, a set of metrics for quantifying the visual complexity was developed.BR Conclusion: We suggest metrics in terms of perceived visual complexity that can evaluate the in-vehicle displays.BR Application: This study can provide the theoretical bases in order to evaluate complicated systems. In addition, it can quantitatively measure the visual complexity of In-vehicle information system and be helpful to design in terms of preventing risks, such as human error and distraction.

Use of electromagnetic simulation for signal integrity analysis of TFT interfaces in automotive human machine interface systems

This article discusses about the use of electromagnetic (EM) simulation for signal integrity (SI) design on the interface to a thin film transistor (TFT) display used in automotive human-machine- interface (HMI) cluster. As the display size increases, so does the operating frequency of the display. With that, signal integrity (SI) simulation has become an integral part of automotive design. In order to perform an SI analysis of such interface, information of the printed circuit board (PCB) and flexible printed circuit (FPC) cable are required. Hence, a brute force approach of simulation and analysing such interface is time-consuming. Given the iterative nature of such design work, this has significant impact on the time to market. In this paper, several key methods to reduce computational effort is discussed and evaluated. This includes the use of equivalent circuit models, different modelling methods for the PCB and FPC, and models conversion. A practical example is demonstrated using the various co-simulation approaches to achieve fast SI analysis without compromising on its accuracy.

Optimizing and evaluating new automotive HMI image enhancement algorithms under bright light conditions using display reflectance characteristics

AbstractWe have developed and investigated new image enhancement (tone mapping) algorithms for automotive Human Machine Interfaces (HMIs) so that displays can be better read in bright light. Our ‘ΔL/L’ approach with adaptive color rendering (CR) is based on Weber's fraction and is easy to use with various displays and illumination variables. In tests with automotive HMIs under different lighting conditions—including driver glare—the ‘ΔL/L + CR’ image enhancement method proved to be a good choice. First, reflective, transflective, and transmissive displays were tested and their image quality compared with and without new tone mapping. It was found that enhancing improved the gray scale perception, even on reflective (e‐paper by dithering) displays. A transmissive LCD, which only reflects monochrome, is highly suitable for mostly monochrome content as it maintains a high contrast ratio under bright light; however, its gamut is degraded at large extent. Transmissive matte LCDs perform best with image enhancement for automotive color HMIs.

Ford’s Approach to Managing Driver Attention: SYNC and MyFord Touch

SYNC and MyFord Touch represent the new direction in automotive human-machine interface (HMI) for Ford Motor Company. Improving driver focus was one of the most critical aspects in the development of the new HMI. This article describes the approach used in development to ensure that driver attention would be improved with this new system. This approach includes research, technology, requirements, and education. The research that was conducted and used, the technology and associated benefits, and the requirements that were followed during the development of the new system are summarized.

Towards the Automotive HMI of the Future: Overview of the AIDE-Integrated Project Results

The Adaptive Integrated Driver-vehicle interfacE (AIDE) is an integrated project funded by the European Commission in the Sixth Framework Programme. The project, which involves 31 partners from the European automotive industry and academia, deals with behavioral and technical issues related to automotive human-machine interface (HMI) design, with a particular focus on integration and adaptation. The project involves tightly integrated empirical research, driver-behavior modeling, and methodological and technological development. This paper provides an overview of the AIDE Sub-Project 3 results dealing with the design, development, and integration of the AIDE system in three prototype vehicles, together with the evaluation results of the trials.