| 1. |
- Johansson, Mikael, 1987, et al.
(author)
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The decline of user experience in transition from automated driving to manual driving
- 2021
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In: Information (Switzerland). - Basel : MDPI AG. - 2078-2489. ; 12:3
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Journal article (peer-reviewed)abstract
- Automated driving technologies are rapidly being developed. However, until vehicles are fully automated, the control of the dynamic driving task will be shifted between the driver and automated driving system. This paper aims to explore how transitions from automated driving to manual driving affect user experience and how that experience correlates to take-over performance. In the study 20 participants experienced using an automated driving system during rush-hour traffic in the San Francisco Bay Area, CA, USA. The automated driving system was available in congested traffic situations and when active, the participants could engage in non-driving related activities. The participants were interviewed afterwards regarding their experience of the transitions. The findings show that most of the participants experienced the transition from automated driving to manual driving as negative. Their user experience seems to be shaped by several reasons that differ in temporality and are derived from different phases during the transition process. The results regarding correlation between participants’ experience and take-over performance are inconclusive, but some trends were identified. The study highlights the need for new design solutions that do not only improve drivers’ take-over performance, but also enhance user experience during take-over requests from automated to manual driving.
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| 2. |
- Nilsson, H., et al.
(author)
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The effects of information relevancy on driving behavior A simulator study on professional bus drivers
- 2021
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In: Cognition Technology & Work. - : Springer Science and Business Media LLC. - 1435-5558 .- 1435-5566. ; 23, s. 429-437
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Journal article (peer-reviewed)abstract
- Bus driving is a complex and cognitively challenging task that places high demands on bus drivers' working memory. Increasing use of "In-Vehicle Information Systems" leads to driver distraction and is a contributing factor to many road accidents globally, and with systems for tickets, navigation, and timetables, bus drivers are more exposed to this additional workload than other actors in the traffic. This study provides insights into how bus drivers' driving behavior is affected by auditory traffic information through a driving simulator study at the Swedish National Road and Transport Research Institute. A pre-study showed that many bus drivers in Gothenburg experience that a majority of the messages they receive are irrelevant to them. Difference in driving behavior was identified for conditions in which the drivers received messages irrelevant to their route, which might indicate that irrelevancy is an important factor for the workload imposed to the drivers. We hypothesize that irrelevant messages require processing in the visuospatial sketchpad, which might increase workload more than just auditory information processing. The results of this study implies that the routines for traffic communication between traffic controllers and bus drivers should be considerate, as to reduce the number of irrelevant messages that are cognitively loading the bus drivers.
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| 3. |
- Rydström, Annie, et al.
(author)
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Drivers’ Performance in Non-critical Take-Overs From an Automated Driving System—An On-Road Study
- 2023
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In: Human Factors. - Thousand Oaks, CA : SAGE Publications. - 1547-8181 .- 0018-7208. ; 65:8, s. 1841-1857
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Journal article (peer-reviewed)abstract
- Objective: The objective of this semi-controlled study was to investigate drivers’ performance when resuming control from an Automated Driving System (ADS), simulated through the Wizard of Oz method, in real traffic. Background: Research on take-overs has primarily focused on urgent scenarios. This article aims to shift the focus to non-critical take-overs from a system operating in congested traffic situations. Method: Twenty drivers drove a selected route in rush-hour traffic in the San Francisco Bay Area, CA, USA. During the drive, the ADS became available when predetermined availability conditions were fulfilled. When the system was active, the drivers were free to engage in non-driving related activities. Results: The results show that drivers’ transition time goes down with exposure, making it reasonable to assume that some experience is required to regain control with comfort and ease. The novel analysis of after-effects of automated driving on manual driving performance implies that the after-effects were close to negligible. Observational data indicate that, with exposure, a majority of the participants started to engage in non-driving related activities to some extent, but it is unclear how the activities influenced the take-over performance. Conclusion: The results indicate that drivers need repeated exposure to take-overs to be able to fully resume manual control with ease. Application: Take-over signals (e.g., visuals, sounds, and haptics) should be carefully designed to avoid startle effects and the human-machine interface should provide clear guidance on the required take-over actions.
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