What makes driving difficult? Perceived effort and eye measures follow visible semantic complexity factors

Christopher Cabrall, Joost de Winter, Riender Happee

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

A majority (95%) of crashes can be attributed to humans, with the highest cause category (41%) involving errors of recognition (i.e., inattention, distraction, inadequate surveillance) [1]. Driving safety research often claims that as much as 90% of the information that drivers use is visual. However, these claims have been hampered by a lack of numerical measurement systems [2]. Presently, we develop an ordinal visual driving scene complexity measurement based on human judgments and eye behavior. Mimicking the rebuilding of situation awareness in take-over conditions we presented 60 randomly ordered video clips (3 s duration), varying complexity factors of traffic density, road curvature, and miscellaneous visual features. Eyes of 15 participants were recorded while viewing the clips, and participants rated “how much effort for you to take control and drive within that segment?” on a 100 point scale. Effort ratings showed a monotonic increase with the number of complexity factors present. A statistically significant increase was also found for saccade amplitude, whereas a statistically significant decrease was found for fixation duration. Pupil size also showed a significant increase but only between 2 complexity levels and at a relatively less convincing strength. In conclusion, the present complexity factor coding scheme apparently corresponds to subjective effort. Further consideration should be given to relating eye tracking measures to visual driving scene components and task demands. In real-time driving systems, both human occupant(s) and computerized processes may observe the same scene at the same time, and matching the machine quantification of the situation to intuitive human judgments is expected to aid in the adherence to advisories and acceptance of automated aids.
Original languageEnglish
Title of host publicationProceedings Road Safety & Simulation International Conference 2017 (RSS2017)
EditorsWael Alhajyaseen, Francisco Alonso, Jan Andersson
Number of pages10
Publication statusPublished - 2017
EventRSS2017: Road Safety and Simulation International Conference 2017 - Grand Hotel Amrâth Kurhaus, The Hague, Netherlands
Duration: 17 Oct 201719 Oct 2017
http://rss2017.org/

Conference

ConferenceRSS2017: Road Safety and Simulation International Conference 2017
Abbreviated titleRSS 2017
CountryNetherlands
CityThe Hague
Period17/10/1719/10/17
OtherThe Road Safety and Simulation conference series was established in Rome in 2007, and has since then provided a bi-annual platform for researchers and professionals from various disciplines to share their expertise and latest insights in the field of road safety and simulation. Delft University of Technology (TU Delft) is delighted to host the 2017 Road Safety and Simulation (RSS) international conference. RSS2017 will be organised in collaboration with the Dutch Institute for Road Safety Research (SWOV). The RSS2017 conference covers a wide area of topics. Furthermore we introduce a special theme focusing on advancing the safety of all road users with special attention for vulnerable road users. Especially, in the upcoming era of advanced technologies and vehicle automation new safety challenges have emerged. The road infrastructure design plays a critical role in accommodating these challenges.
Internet address

Keywords

  • Intelligent Vehicles
  • Transition of Control
  • Workload
  • Highly Automated Driving
  • Driver State Monitoring

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