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Sökning: WFRF:(Jansson Herman) > (2021)

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  • Ahlström, Christer, et al. (författare)
  • Effects of partially automated driving on the development of driver sleepiness
  • 2021
  • Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575 .- 1879-2057. ; 153
  • Tidskriftsartikel (refereegranskat)abstract
    • The objective of this study was to compare the development of sleepiness during manual driving versus level 2 partially automated driving, when driving on a motorway in Sweden. The hypothesis was that partially auto-mated driving will lead to higher levels of fatigue due to underload. Eighty-nine drivers were included in the study using a 2 ? 2 design with the conditions manual versus partially automated driving and daytime (full sleep) versus night-time (sleep deprived). The results showed that night-time driving led to markedly increased levels of sleepiness in terms of subjective sleepiness ratings, blink durations, PERCLOS, pupil diameter and heart rate. Partially automated driving led to slightly higher subjective sleepiness ratings, longer blink durations, decreased pupil diameter, slower heart rate, and higher EEG alpha and theta activity. However, elevated levels of sleepiness mainly arose from the night-time drives when the sleep pressure was high. During daytime, when the drivers were alert, partially automated driving had little or no detrimental effects on driver fatigue. Whether the negative effects of increased sleepiness during partially automated driving can be compensated by the positive effects of lateral and longitudinal driving support needs to be investigated in further studies.
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  • Martinson, Johan, et al. (författare)
  • HAnS: IDE-based editing support for embedded feature annotations
  • 2021
  • Ingår i: ACM International Conference Proceeding Series. - New York, NY, USA : ACM. ; Part F171625-B, s. 28-31
  • Konferensbidrag (refereegranskat)abstract
    • When developers maintain or evolve software, they often need to know the locations of features. This proves challenging when the feature locations are not documented, when the code was written by different developers who may have left the organization, or when the developer's memory of the implementation has faded. Automated feature location techniques are hard to adopt in practice, especially since they boast too many false positives. To address these challenges, embedded feature annotations have been proposed to allow developers to trace features in code during development with minimal effort. However, tool support is needed for developers to effectively record and use these annotations. We propose HAnS as a tool to meet this need; it is implemented as an IntelliJ IDE plugin to support developers seamlessly record feature locations while they write their code. HAnS supports developers when mapping features to software assets, such as files and code fragments, with code completion and syntax highlighting. It also provides functionality to browse feature definitions and locations, as well as refactor features. A demo video is available at https://youtu.be/cx_-ZshHLgA.
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