Philipp Wintersberger, A. Riener, Anna-Katharina Frison
It is expected that automated vehicles (AVs) will only be used when customers believe them to be safe, trustworthy, and match their personal driving style. As AVs are not very common today, most previous studies on trust, user experience, or acceptance measures in automated driving are based on qualitative measures. The approach followed in this work is different, as we compared the direct effect of human drivers versus automated driving systems (ADSs) on the front seat passenger. In a driving simulator study (N=48), subjects had either to ride with an ADS, a male, or a female driver. Driving scenarios were the same for all subjects. Findings from quantitative measurements (HRV, face tracking) and qualitative pre-/post study surveys and interviews suggest that there are no significant differences between the passenger groups. Our conclusion is, that passengers are already inclined to accept ADS and that the market is ready for AVs.
{"title":"Automated Driving System, Male, or Female Driver: Who'd You Prefer? Comparative Analysis of Passengers' Mental Conditions, Emotional States & Qualitative Feedback","authors":"Philipp Wintersberger, A. Riener, Anna-Katharina Frison","doi":"10.1145/3003715.3005410","DOIUrl":"https://doi.org/10.1145/3003715.3005410","url":null,"abstract":"It is expected that automated vehicles (AVs) will only be used when customers believe them to be safe, trustworthy, and match their personal driving style. As AVs are not very common today, most previous studies on trust, user experience, or acceptance measures in automated driving are based on qualitative measures. The approach followed in this work is different, as we compared the direct effect of human drivers versus automated driving systems (ADSs) on the front seat passenger. In a driving simulator study (N=48), subjects had either to ride with an ADS, a male, or a female driver. Driving scenarios were the same for all subjects. Findings from quantitative measurements (HRV, face tracking) and qualitative pre-/post study surveys and interviews suggest that there are no significant differences between the passenger groups. Our conclusion is, that passengers are already inclined to accept ADS and that the market is ready for AVs.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133706054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Large, G. Burnett, Bennett Anyasodo, L. Skrypchuk
Given the proliferation of digital assistants in everyday mobile technology, it appears inevitable that next generation vehicles will be embodied by similar agents, offering engaging, natural language interactions. However, speech can be cognitively captivating. It is therefore important to understand the demand that such interfaces may place on drivers. Twenty-five participants undertook four drives (counterbalanced), in a medium-fidelity driving simulator: 1. Interacting with a state-of-the-art digital driving assistant ('DDA') (presented using Wizard-of-Oz); 2. Engaged in a hands-free mobile phone conversation; 3. Undertaking the delayed-digit recall ('2-back') task and 4. With no secondary task (baseline). Physiological arousal, subjective workload assessment, tactile detection task (TDT) and driving performance measures consistently revealed the '2-back' drive as the most cognitively demanding (highest workload, poorest TDT performance). Mobile phone and DDA conditions were largely equivalent, attracting low/medium cognitive workload. Findings are discussed in the context of designing in-vehicle natural language interfaces to mitigate cognitive demand.
{"title":"Assessing Cognitive Demand during Natural Language Interactions with a Digital Driving Assistant","authors":"D. Large, G. Burnett, Bennett Anyasodo, L. Skrypchuk","doi":"10.1145/3003715.3005408","DOIUrl":"https://doi.org/10.1145/3003715.3005408","url":null,"abstract":"Given the proliferation of digital assistants in everyday mobile technology, it appears inevitable that next generation vehicles will be embodied by similar agents, offering engaging, natural language interactions. However, speech can be cognitively captivating. It is therefore important to understand the demand that such interfaces may place on drivers. Twenty-five participants undertook four drives (counterbalanced), in a medium-fidelity driving simulator: 1. Interacting with a state-of-the-art digital driving assistant ('DDA') (presented using Wizard-of-Oz); 2. Engaged in a hands-free mobile phone conversation; 3. Undertaking the delayed-digit recall ('2-back') task and 4. With no secondary task (baseline). Physiological arousal, subjective workload assessment, tactile detection task (TDT) and driving performance measures consistently revealed the '2-back' drive as the most cognitively demanding (highest workload, poorest TDT performance). Mobile phone and DDA conditions were largely equivalent, attracting low/medium cognitive workload. Findings are discussed in the context of designing in-vehicle natural language interfaces to mitigate cognitive demand.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126609903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sandra Trösterer, Magdalena Gärtner, Alexander G. Mirnig, Alexander Meschtscherjakov, Rod McCall, N. Louveton, M. Tscheligi, T. Engel
In the scope of autonomous driving, the question arises if the increased use of automated systems will have an impact on driver's skills in handling the car in the long term. In order to gain more insights on the issue of driver deskilling and how it relates to driving experience and time intervals of non-driving, we conducted an online survey (n=703) considering three driver groups. We found that initial skilling is more of an issue than deskilling after long periods of driving inactivity, i.e., while once learned driving skills seem to remain stable after longer periods of non-driving, they are much more influenced by driving experience in terms of annual mileage and frequency of use. Applied to the autonomous context, this means that drivers must be trained to a high enough skill level or require sufficient manual driving experience, in order to be able to react properly when driving themselves.
{"title":"You Never Forget How to Drive: Driver Skilling and Deskilling in the Advent of Autonomous Vehicles","authors":"Sandra Trösterer, Magdalena Gärtner, Alexander G. Mirnig, Alexander Meschtscherjakov, Rod McCall, N. Louveton, M. Tscheligi, T. Engel","doi":"10.1145/3003715.3005462","DOIUrl":"https://doi.org/10.1145/3003715.3005462","url":null,"abstract":"In the scope of autonomous driving, the question arises if the increased use of automated systems will have an impact on driver's skills in handling the car in the long term. In order to gain more insights on the issue of driver deskilling and how it relates to driving experience and time intervals of non-driving, we conducted an online survey (n=703) considering three driver groups. We found that initial skilling is more of an issue than deskilling after long periods of driving inactivity, i.e., while once learned driving skills seem to remain stable after longer periods of non-driving, they are much more influenced by driving experience in terms of annual mileage and frequency of use. Applied to the autonomous context, this means that drivers must be trained to a high enough skill level or require sufficient manual driving experience, in order to be able to react properly when driving themselves.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122111531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper explores how navigational guidance which references the world around the driver influences their experience of workload and environmental engagement on multiple journeys. In an on-road study thirty participants drove following three intersecting routes in the city of Nottingham, UK on two separate occasions, one week apart. In a between subjects design, participants followed navigational guidance from either: an existing navigation system (SatNav); or the semi-structured wayfinding prompts of an informed passenger. Results indicated that drivers following the navigational guidance of the informed passenger benefitted from lower workload overall which also reduced significantly on their second drive. Additionally, these drivers made significantly fewer errors on route and demonstrated superior survey knowledge compared to their SatNav counterparts. This evidence supports the case for enhanced route directions in future navigation devices, referencing the driver's environment in a manner that can reduce workload and navigation errors, whilst assisting in spatial knowledge development.
{"title":"\"Turn Left At The Fairham Pub\" Using Navigational Guidance to Reconnect Drivers With Their Environment","authors":"Vicki Antrobus, G. Burnett, L. Skrypchuk","doi":"10.1145/3003715.3005392","DOIUrl":"https://doi.org/10.1145/3003715.3005392","url":null,"abstract":"This paper explores how navigational guidance which references the world around the driver influences their experience of workload and environmental engagement on multiple journeys. In an on-road study thirty participants drove following three intersecting routes in the city of Nottingham, UK on two separate occasions, one week apart. In a between subjects design, participants followed navigational guidance from either: an existing navigation system (SatNav); or the semi-structured wayfinding prompts of an informed passenger. Results indicated that drivers following the navigational guidance of the informed passenger benefitted from lower workload overall which also reduced significantly on their second drive. Additionally, these drivers made significantly fewer errors on route and demonstrated superior survey knowledge compared to their SatNav counterparts. This evidence supports the case for enhanced route directions in future navigation devices, referencing the driver's environment in a manner that can reduce workload and navigation errors, whilst assisting in spatial knowledge development.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114924939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Philipp Hock, J. Kraus, Marcel Walch, Nina Lang, M. Baumann
Human errors are a major reason for traffic accidents. One of the aims of the introduction of automated driving functions in vehicles is to prevent such accidents as such systems are supposed to be more reliable, react faster with higher precision. Therefore, we assume that an increase of automation features will also increase safety. However, when drivers are not willing to relinquish control to the vehicle, safety benefits of automated vehicles do not take effect. Therefore, convincing drivers to actively make use of the automation when appropriate can increase traffic safety. In this paper we investigate the influence of system feedback in proactive, safety critical takeover situations in automated driving. In contrast to handover, which is initiated by the system, proactive takeover is initiated by the driver, who's intention for steering the car is the reason for driving manually. We compare auditory feedback with audio-visual feedback realized as a virtual co-driver in a user study. We conducted a virtual reality simulator study (n=38) to investigate how system feedback influences the willingness of drivers to relinquish control to the vehicle. There were three conditions of system feedback: in condition none no feedback was given, in condition audio spoken feedback was given, and in condition co-driver additionally to audio feedback, a virtual co-driver on the front passenger seat was displayed. Our research provides evidence that system feedback can lead to an increase of willingness to maintain automation and to follow its safety related advices.
{"title":"Elaborating Feedback Strategies for Maintaining Automation in Highly Automated Driving","authors":"Philipp Hock, J. Kraus, Marcel Walch, Nina Lang, M. Baumann","doi":"10.1145/3003715.3005414","DOIUrl":"https://doi.org/10.1145/3003715.3005414","url":null,"abstract":"Human errors are a major reason for traffic accidents. One of the aims of the introduction of automated driving functions in vehicles is to prevent such accidents as such systems are supposed to be more reliable, react faster with higher precision. Therefore, we assume that an increase of automation features will also increase safety. However, when drivers are not willing to relinquish control to the vehicle, safety benefits of automated vehicles do not take effect. Therefore, convincing drivers to actively make use of the automation when appropriate can increase traffic safety. In this paper we investigate the influence of system feedback in proactive, safety critical takeover situations in automated driving. In contrast to handover, which is initiated by the system, proactive takeover is initiated by the driver, who's intention for steering the car is the reason for driving manually. We compare auditory feedback with audio-visual feedback realized as a virtual co-driver in a user study. We conducted a virtual reality simulator study (n=38) to investigate how system feedback influences the willingness of drivers to relinquish control to the vehicle. There were three conditions of system feedback: in condition none no feedback was given, in condition audio spoken feedback was given, and in condition co-driver additionally to audio feedback, a virtual co-driver on the front passenger seat was displayed. Our research provides evidence that system feedback can lead to an increase of willingness to maintain automation and to follow its safety related advices.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127742616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Feuerstack, Bertram Wortelen, C. Kettwich, Anna Schieben
Automotive HMI design evaluation methods, such as usability assessments, attention and reaction time measurements require full working HMI prototypes to assess the usability and the subjects' performances in realistic situations. The theater-system technique and model-based prediction methods do not depend on functional HMI implementations and therefore promise HMI evaluation already in an early design phase. We applied both methods to evaluate three HMI designs for an Urban Adaptive Cruise Control (ACC) System. In a qualitative study with twelve participants, we used a theater-system-based technique to let them experience the HMIs in realistic situations. Subjects clearly preferred the HMI variant, which offers the best understanding of the vehicle's automation. By following a model-based approach, we evaluated the impacts to the driver's visual attention distribution of the three HMI variants with six human factor experts and found significant attention changes for the front window and for the Urban ACC HMI.
{"title":"Theater-system Technique and Model-based Attention Prediction for the Early Automotive HMI Design Evaluation","authors":"S. Feuerstack, Bertram Wortelen, C. Kettwich, Anna Schieben","doi":"10.1145/3003715.3005466","DOIUrl":"https://doi.org/10.1145/3003715.3005466","url":null,"abstract":"Automotive HMI design evaluation methods, such as usability assessments, attention and reaction time measurements require full working HMI prototypes to assess the usability and the subjects' performances in realistic situations. The theater-system technique and model-based prediction methods do not depend on functional HMI implementations and therefore promise HMI evaluation already in an early design phase. We applied both methods to evaluate three HMI designs for an Urban Adaptive Cruise Control (ACC) System. In a qualitative study with twelve participants, we used a theater-system-based technique to let them experience the HMIs in realistic situations. Subjects clearly preferred the HMI variant, which offers the best understanding of the vehicle's automation. By following a model-based approach, we evaluated the impacts to the driver's visual attention distribution of the three HMI variants with six human factor experts and found significant attention changes for the front window and for the Urban ACC HMI.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130453750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thomas Friedrichs, Marie-Christin Ostendorp, A. Lüdtke
Truck platooning has advantages for fuel consumption, road safety, and use of the existing infrastructure. However, it does not simplify the job of the drivers who fear driving in close distance and mistrust the automation. To support drivers in overcoming these issues we present two novel Human-Machine Interfaces (HMI) for truck platooning which we designed using two different methods, User-centered design (UCD) and Konect (a novel design method), to explore creative visualization strategies. We further present the results of our experimental evaluation of both HMIs in terms of trust, hazard avoidance, and visual effort with an eye-tracker. Trust ratings decrease upon a simulated ACC failure for the UCD HMI in 12 categories, while trust with the Konect HMI was only decreased in three categories. Visual effort differed significantly between both HMIs, depending on continuous or static information visualization. A discussion and guidelines for future development are provided.
{"title":"Supporting Drivers in Truck Platooning: Development and Evaluation of Two Novel Human-Machine Interfaces","authors":"Thomas Friedrichs, Marie-Christin Ostendorp, A. Lüdtke","doi":"10.1145/3003715.3005451","DOIUrl":"https://doi.org/10.1145/3003715.3005451","url":null,"abstract":"Truck platooning has advantages for fuel consumption, road safety, and use of the existing infrastructure. However, it does not simplify the job of the drivers who fear driving in close distance and mistrust the automation. To support drivers in overcoming these issues we present two novel Human-Machine Interfaces (HMI) for truck platooning which we designed using two different methods, User-centered design (UCD) and Konect (a novel design method), to explore creative visualization strategies. We further present the results of our experimental evaluation of both HMIs in terms of trust, hazard avoidance, and visual effort with an eye-tracker. Trust ratings decrease upon a simulated ACC failure for the UCD HMI in 12 categories, while trust with the Konect HMI was only decreased in three categories. Visual effort differed significantly between both HMIs, depending on continuous or static information visualization. A discussion and guidelines for future development are provided.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114330739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Olivia Wiles, M. Mahmoud, P. Robinson, Eduardo Dias, L. Skrypchuk
Current navigational systems rarely consider generic road landmarks in their navigation instructions, which can lead to mistakes, frustration, and distraction. However, automatic detection of road landmarks is difficult, as current approaches to object detection focus either on out-of-context objects which have special characteristics or on very specific domains. This work presents a future direction for a user-friendly navigational system based on state-of-the-art computer vision techniques that use deep learning for object detection. We propose an automatic hierarchical approach for detecting and classifying a set of static and dynamic road landmarks that would be useful in automatic navigational systems. We further demonstrate a set of optimisations that improve performance and accuracy of the basic system. We evaluate our approach on a natural, 'in-the-wild' dataset to determine how well it handles natural automotive input. Finally, we demonstrate a use-case for our system that extracts information about a vehicle's location and intention.
{"title":"Towards a User-Centric In-Vehicle Navigational System","authors":"Olivia Wiles, M. Mahmoud, P. Robinson, Eduardo Dias, L. Skrypchuk","doi":"10.1145/3003715.3005457","DOIUrl":"https://doi.org/10.1145/3003715.3005457","url":null,"abstract":"Current navigational systems rarely consider generic road landmarks in their navigation instructions, which can lead to mistakes, frustration, and distraction. However, automatic detection of road landmarks is difficult, as current approaches to object detection focus either on out-of-context objects which have special characteristics or on very specific domains. This work presents a future direction for a user-friendly navigational system based on state-of-the-art computer vision techniques that use deep learning for object detection. We propose an automatic hierarchical approach for detecting and classifying a set of static and dynamic road landmarks that would be useful in automatic navigational systems. We further demonstrate a set of optimisations that improve performance and accuracy of the basic system. We evaluate our approach on a natural, 'in-the-wild' dataset to determine how well it handles natural automotive input. Finally, we demonstrate a use-case for our system that extracts information about a vehicle's location and intention.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115869644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thomas Friedrichs, Shadan Sadeghian Borojeni, Wilko Heuten, A. Lüdtke, Susanne CJ Boll
Truck platooning has advantages for fuel consumption, road safety, and use of the existing road infrastructure. However, it does not simplify the job of truck drivers who reportedly fear driving in close distance and mistrust the automation. Prior work indicates that a platooning assistant system can help overcoming these issues. However, there are no practical experiences with on-the-road platooning that shed light on how drivers perceive and evaluate such a system. In this work, we close this gap and present PlatoonPal, a platooning assistance system which we rigorously developed in a user centered way. We further present the results of a field test with three platooning trucks where drivers used PlatoonPal under real conditions. The results show that drivers are positive using the system and preferred information related closely to the current situation. We conclude the paper with guidelines for the future development of assistance systems for platooning.
{"title":"PlatoonPal: User-Centered Development and Evaluation of an Assistance System for Heavy-Duty Truck Platooning","authors":"Thomas Friedrichs, Shadan Sadeghian Borojeni, Wilko Heuten, A. Lüdtke, Susanne CJ Boll","doi":"10.1145/3003715.3005449","DOIUrl":"https://doi.org/10.1145/3003715.3005449","url":null,"abstract":"Truck platooning has advantages for fuel consumption, road safety, and use of the existing road infrastructure. However, it does not simplify the job of truck drivers who reportedly fear driving in close distance and mistrust the automation. Prior work indicates that a platooning assistant system can help overcoming these issues. However, there are no practical experiences with on-the-road platooning that shed light on how drivers perceive and evaluate such a system. In this work, we close this gap and present PlatoonPal, a platooning assistance system which we rigorously developed in a user centered way. We further present the results of a field test with three platooning trucks where drivers used PlatoonPal under real conditions. The results show that drivers are positive using the system and preferred information related closely to the current situation. We conclude the paper with guidelines for the future development of assistance systems for platooning.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121870481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Large, G. Burnett, E. Crundall, Glyn Lawson, L. Skrypchuk
Touchscreen Human-Machine Interfaces (HMIs) inherently demand some visual attention. By employing a secondary device, to work in unison with a touchscreen, some of this demand may be alleviated. In a medium-fidelity driving simulator, twenty-four drivers completed four typical in-vehicle tasks, utilising each of four devices -- touchscreen, rotary controller, steering wheel controls and touchpad (counterbalanced). Participants were then able to combine devices during a final 'free-choice' drive. Visual behaviour, driving/task performance and subjective ratings (workload, emotional response, preferences), indicated that in isolation the touchscreen was the most preferred/least demanding to use. In contrast, the touchpad was least preferred/most demanding, whereas the rotary controller and steering wheel controls were largely comparable across most measures. When provided with 'free-choice', the rotary controller and steering wheel controls presented as the most popular candidates, although this was task-dependent. Further work is required to explore these devices in greater depth and during extended periods of testing.
{"title":"Twist It, Touch It, Push It, Swipe It: Evaluating Secondary Input Devices for Use with an Automotive Touchscreen HMI","authors":"D. Large, G. Burnett, E. Crundall, Glyn Lawson, L. Skrypchuk","doi":"10.1145/3003715.3005459","DOIUrl":"https://doi.org/10.1145/3003715.3005459","url":null,"abstract":"Touchscreen Human-Machine Interfaces (HMIs) inherently demand some visual attention. By employing a secondary device, to work in unison with a touchscreen, some of this demand may be alleviated. In a medium-fidelity driving simulator, twenty-four drivers completed four typical in-vehicle tasks, utilising each of four devices -- touchscreen, rotary controller, steering wheel controls and touchpad (counterbalanced). Participants were then able to combine devices during a final 'free-choice' drive. Visual behaviour, driving/task performance and subjective ratings (workload, emotional response, preferences), indicated that in isolation the touchscreen was the most preferred/least demanding to use. In contrast, the touchpad was least preferred/most demanding, whereas the rotary controller and steering wheel controls were largely comparable across most measures. When provided with 'free-choice', the rotary controller and steering wheel controls presented as the most popular candidates, although this was task-dependent. Further work is required to explore these devices in greater depth and during extended periods of testing.","PeriodicalId":448266,"journal":{"name":"Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"65 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128598403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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