Eye movements of cyclists when interacting with automated vehicles: What can static images tell us?

Sander van der Kint, Luuk Vissers, Ingrid van Schagen, Marjan Hagenzieker

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientific

45 Downloads (Pure)

Abstract

The transition period towards large-scale or full automated driving will pose specific challenges. One of the challenges concerns the interaction of automated vehicles with vulnerable road users. So far, most studies into this type of interactions took the perspective of the car. The current study, however, takes the perspective of the vulnerable road user. More specifically, it explores how cyclists perceive and expect automated vehicles to ‘behave’ and how cyclists would react. Expectations are important determinants of traffic behaviour. Incorrect expectations could lead to overly trustful or hesitant behaviour and subsequent unsafe interactions. Recently, Hagenzieker and colleagues (2017) conducted a photo experiment in which regular cyclists had to judge photos
of traffic situations where they encountered manually-driven cars and automated cars (recognisable by either a sticker on the side of the car or a roof name plate on top of the car). Participants judged 30 photos twice, in random order. In that study a subset of nine participants were equipped with an eye tracker in order to study their eye movements while judging the photos. This study further examined these eye tracking data, comparing timeto- first-fixation, dwell time from the start of the first fixation, and total number of revisits in interactions with automated and with manually-driven cars. Results indicate no differences in time-to-first-fixation nor in the number of revisits between situations with automated cars and traditional cars. Dwell times revealed an effect of familiarity, showing that cyclists spent more time looking at cars during the first round of photos compared to the second round. In particular, they spent more time looking at automated cars which were identifiable by a ticker on the side. The results are discussed and suggestions for future research are given.
Original languageEnglish
Title of host publicationProceedings of the Road Safety and Simulation Conference
Subtitle of host publication17-19 October 2017, The Hague, the Netherlands
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

Fingerprint Dive into the research topics of 'Eye movements of cyclists when interacting with automated vehicles: What can static images tell us?'. Together they form a unique fingerprint.

Cite this