An Evaluation of Input Controls for In-Car Interactions

The way drivers operate in-car systems is rapidly changing as traditional physical controls, such as buttons and dials, are being replaced by touchscreens and touch-sensing surfaces. This has the potential to increase driver distraction and error as controls may be harder to find and use. This paper presents an in-car, on the road driving study which examined three key types of input controls to investigate their effects: a physical dial, pressure-based input on a touch surface and touch input on a touchscreen. The physical dial and pressure-based input were also evaluated with and without haptic feedback. The study was conducted with users performing a list-based targeting task using the different controls while driving on public roads. Eye-gaze was recorded to measure distraction from the primary task of driving. The results showed that target accuracy was high across all input methods (greater than 94%). Pressure-based targeting was the slowest while directly tapping on the targets was the faster selection method. Pressure-based input also caused the largest number of glances towards to the touchscreen but the duration of each glance was shorter than directly touching the screen. Our study will enable designers to make more appropriate design choices for future in-car interactions

User expectations of partial driving automation capabilities and their effect on information design preferences in the vehicle

Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system's status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers' expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone. [Abstract copyright: Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Rich media mobile advertising: comparison of gestures used for navigation through a photo gallery

Cilj ovoga članka je ustanoviti preferencije korisnika u različitim interakcijama s obavijestima na prenosivom telefonu. Posebno nas je zanimalo da li korisnici više vole potezanje prstom (swiping) ili kuckanje (tapping) dok pregledavaju foto galeriju. Analizirala se korelacija između korisnikovog sučelja i angažmana (broja pregledanih fotografija). Dijelu korisnika je također pokazana obavijest s uputstvom kako postupati da bi se ustanovilo je li smanjenje mogućnosti izbora poboljšava korisnikovu funkcionalnost. Kako bismo odgovorili na ova pitanja razvili smo sustav praćenja u svrhu analize ponašanja 663 korisnika i anketirali 46 korisnika. Rezultati pokazuju da kod pregledavanja galerije potezanje prstom ima prednost pred kuckanjem i da način navigacije uistinu utječe na broj pregledanih fotografija. Također smo mogli pokazati da je postojanje upute smanjilo broj pogrešnih pokreta, ali smo predložili daljnje istraživanje kako bi se potpuno iskoristio njen potencijal.The aim of this paper was to get an insight into user’s preferences over different interactions with mobile ads. In particular, we were interested whether the users prefer swiping or tapping while navigating through a photo gallery. A correlation between the user interface and user engagement (the number of photos viewed) was analysed. A subset of users were also shown a coach notice with an information about how to navigate to examine whether coach notices can improve user experience by reducing usability issues. To answer these questions we developed a tracking system to analyse behaviour of 633 users and performed a survey on 46 people. The results show that swiping is preferable to tapping when navigating through the gallery and that the navigation mode does have an impact on the number of photos viewed. We were also able to show that the presence of a coach notice decreased the number of faulty gestures, but suggested a further work to maximize its potential

User expectations of partial driving automation capabilities and their effect on information design preferences in the vehicle

Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system’s status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers’ expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone

Physiologically attentive user interface for improved robot teleoperation

User interfaces (UI) are shifting from being attention-hungry to being attentive to users’ needs upon interaction. Interfaces developed for robot teleoperation can be particularly complex, often displaying large amounts of information, which can increase the cognitive overload that prejudices the performance of the operator. This paper presents the development of a Physiologically Attentive User Interface (PAUI) prototype preliminary evaluated with six participants. A case study on Urban Search and Rescue (USAR) operations that teleoperate a robot was used although the proposed approach aims to be generic. The robot considered provides an overly complex Graphical User Interface (GUI) which does not allow access to its source code. This represents a recurring and challenging scenario when robots are still in use, but technical updates are no longer offered that usually mean their abandon. A major contribution of the approach is the possibility of recycling old systems while improving the UI made available to end users and considering as input their physiological data. The proposed PAUI analyses physiological data, facial expressions, and eye movements to classify three mental states (rest, workload, and stress). An Attentive User Interface (AUI) is then assembled by recycling a pre-existing GUI, which is dynamically modified according to the predicted mental state to improve the user's focus during mentally demanding situations. In addition to the novelty of the proposed PAUIs that take advantage of pre-existing GUIs, this work also contributes with the design of a user experiment comprising mental state induction tasks that successfully trigger high and low cognitive overload states. Results from the preliminary user evaluation revealed a tendency for improvement in the usefulness and ease of usage of the PAUI, although without statistical significance, due to the reduced number of subjects.info:eu-repo/semantics/acceptedVersio

Designing Automated Vehicle and Traffic Systems towards Meaningful Human Control

Ensuring operational control over automated vehicles is not trivial and failing to do so severely endangers the lives of road users. An integrated approach is necessary to ensure that all agents play their part including drivers, occupants, vehicle designers and governments. While progress is being made, a comprehensive approach to the problem is being ignored, which can be solved in the main through considering Meaningful Human Control (MHC). In this research, an Integrated System Proximity framework and Operational Process Design approach to assist the development of Connected Automated Vehicles (CAV) under the consideration of MHC are introduced. These offer a greater understanding and basis for vehicle and traffic system design by vehicle designers and governments as two important influencing stakeholders. The framework includes an extension to a system approach, which also considers ways that MHC can be improved through updating: either implicit proximal updating or explicit distal updating. The process and importance are demonstrated in three recent cases from practice. Finally, a call for action is made to government and regulatory authorities, as well as the automotive industry, to ensure that MHC processes are explicitly included in policy, regulations, and design processes to ensure future ad-vancement of CAVs in a responsible, safe and humanly agreeable fashion.Comment: In: Research Handbook on Meaningful Human Control of Artificial Intelligence Systems. Edward Elgar Publishin

A framework for evaluating in-vehicle applications regarding safety

Driver distraction is a serious and growing hazard to road safety. With the rapid introduction of the new information, communication, and entertainment technologies, this problem is becoming more threatening in the coming years. For instance, drivers who use mobile phones while driving are more likely to be involved in the car crash than those who do not. However, using technologies such as mobile phones and navigation systems in a vehicle can have different personal, social, practical, and psychological advantages which outweigh the risk. Therefore, there are number of metrics and methods for evaluating in-vehicle technologies, their services, applications, and functionalities to improve and make them safer. The purpose of this thesis was to investigate and develop a new framework which consists of a safety evaluation library and server for evaluating in-vehicle applications with safety consideration. By the use of the framework, Original Equipment Manufacturers (OEMs) and third-party developers can get safety feedback from their in-vehicle applications in the real driving situation. For the safety analysis, different metrics were investigated. Due to the time restriction and based on the possible information that could be collected from an application and a vehicle, four metrics were used in the safety analysis including, total task time, number of interactions, speed, and completed task rate. In addition, the framework was deployed and tested by two case-study applications and some interesting results were discovered. Moreover, it was found out using the safety library by third-party developers is quite easy, which is one of the most important factors in the usability area

A framework for evaluating in-vehicle applications regarding safety

Driver distraction is a serious and growing hazard to road safety. With the rapid introduction of the new information, communication, and entertainment technologies, this problem is becoming more threatening in the coming years. For instance, drivers who use mobile phones while driving are more likely to be involved in the car crash than those who do not. However, using technologies such as mobile phones and navigation systems in a vehicle can have different personal, social, practical, and psychological advantages which outweigh the risk. Therefore, there are number of metrics and methods for evaluating in-vehicle technologies, their services, applications, and functionalities to improve and make them safer. The purpose of this thesis was to investigate and develop a new framework which consists of a safety evaluation library and server for evaluating in-vehicle applications with safety consideration. By the use of the framework, Original Equipment Manufacturers (OEMs) and third-party developers can get safety feedback from their in-vehicle applications in the real driving situation. For the safety analysis, different metrics were investigated. Due to the time restriction and based on the possible information that could be collected from an application and a vehicle, four metrics were used in the safety analysis including, total task time, number of interactions, speed, and completed task rate. In addition, the framework was deployed and tested by two case-study applications and some interesting results were discovered. Moreover, it was found out using the safety library by third-party developers is quite easy, which is one of the most important factors in the usability area