Landman et al 2017a - Revision history

Scipediacontent at 04:54, 2 February 2021

2021-02-02T04:54:12Z

Scipediacontent: Scipediacontent moved page Draft Content 754106450 to Landman et al 2017a

2021-01-25T09:40:50Z

Scipediacontent moved page Draft Content 754106450 to Landman et al 2017a

Scipediacontent: Created page with " == Abstract == Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However..."

2021-01-25T09:40:47Z

Created page with " == Abstract == Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However..."

New page

== Abstract ==

Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However, in-vehicle technologies and handheld electronic devices may also be a threat to driver safety due to information overload and distraction. Adaptive in-vehicle information systems may be a solution to this problem. Adaptive systems could aid the driver in obtaining information from the device (by reducing information density) or prevent distraction by not presenting or delaying information when the driverâs workload is high. In this paper, we describe an on-the-road evaluation of a real-time driver workload estimator that makes use of geo-specific information. The results demonstrate the relative validity of our experimental methods and show the potential for using location-based adaptive in-vehicle systems.

== Original document ==

The different versions of the original document can be found in:

* [http://resolver.tudelft.nl/uuid:1d3d8117-3ec6-4a65-a108-e6e6820ce335 http://resolver.tudelft.nl/uuid:1d3d8117-3ec6-4a65-a108-e6e6820ce335]

* [https://repository.tudelft.nl/islandora/object/uuid%3A98b509d4-da5e-45b2-8afe-7668ac624152/datastream/OBJ/download https://repository.tudelft.nl/islandora/object/uuid%3A98b509d4-da5e-45b2-8afe-7668ac624152/datastream/OBJ/download]

* [http://dx.doi.org/10.1007/978-3-319-41682-3_94 http://dx.doi.org/10.1007/978-3-319-41682-3_94],
: [http://resolver.tudelft.nl/uuid:98b509d4-da5e-45b2-8afe-7668ac624152 http://resolver.tudelft.nl/uuid:98b509d4-da5e-45b2-8afe-7668ac624152]

* [http://link.springer.com/content/pdf/10.1007/978-3-319-41682-3_94 http://link.springer.com/content/pdf/10.1007/978-3-319-41682-3_94],
: [http://dx.doi.org/10.1007/978-3-319-41682-3_94 http://dx.doi.org/10.1007/978-3-319-41682-3_94] under the license http://www.springer.com/tdm

* [https://link.springer.com/chapter/10.1007/978-3-319-41682-3_94 https://link.springer.com/chapter/10.1007/978-3-319-41682-3_94],
: [https://www.narcis.nl/publication/RecordID/oai%3Atudelft.nl%3Auuid%3A98b509d4-da5e-45b2-8afe-7668ac624152 https://www.narcis.nl/publication/RecordID/oai%3Atudelft.nl%3Auuid%3A98b509d4-da5e-45b2-8afe-7668ac624152],
: [https://repository.tudelft.nl/view/tno/uuid:1d3d8117-3ec6-4a65-a108-e6e6820ce335 https://repository.tudelft.nl/view/tno/uuid:1d3d8117-3ec6-4a65-a108-e6e6820ce335],
: [https://academic.microsoft.com/#/detail/2503523062 https://academic.microsoft.com/#/detail/2503523062]

← Older revision		Revision as of 04:54, 2 February 2021
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	== Abstract ==		== Abstract ==

−	Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However, in-vehicle technologies and handheld electronic devices may also be a threat to driver safety due to information overload and distraction. Adaptive in-vehicle information systems may be a solution to this problem. Adaptive systems could aid the driver in obtaining information from the device (by reducing information density) or prevent distraction by not presenting or delaying information when the ~~driverâs~~ workload is high. In this paper, we describe an on-the-road evaluation of a real-time driver workload estimator that makes use of geo-specific information. The results demonstrate the relative validity of our experimental methods and show the potential for using location-based adaptive in-vehicle systems.	+	Driver distraction is a leading cause of crashes. The introduction of in-vehicle technology in the last decades has added support to the driving task. However, in-vehicle technologies and handheld electronic devices may also be a threat to driver safety due to information overload and distraction. Adaptive in-vehicle information systems may be a solution to this problem. Adaptive systems could aid the driver in obtaining information from the device (by reducing information density) or prevent distraction by not presenting or delaying information when the driver’s workload is high. In this paper, we describe an on-the-road evaluation of a real-time driver workload estimator that makes use of geo-specific information. The results demonstrate the relative validity of our experimental methods and show the potential for using location-based adaptive in-vehicle systems.

← Older revision	Revision as of 09:40, 25 January 2021
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