Visual crowding in driving

Ye Xia (Corresponding Author), Mauro Manassi, Ken Nakayama, Karl Zipser, David Whitney

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
7 Downloads (Pure)


Visual crowding—the deleterious influence of nearby objects on object recognition—is considered to be a major bottleneck for object recognition in cluttered environments. Although crowding has been studied for decades with static and artificial stimuli, it is still unclear how crowding operates when viewing natural dynamic scenes in real-life situations. For example, driving is a frequent and potentially fatal real-life situation where crowding may play a critical role. In order to investigate the role of crowding in this kind of situation, we presented observers with naturalistic driving videos and recorded their eye movements while they performed a simulated driving task. We found that the saccade localization on pedestrians was impacted by visual clutter, in a manner consistent with the diagnostic criteria of crowding (Bouma's rule of thumb, flanker similarity tuning, and the radial-tangential anisotropy). In order to further confirm that altered saccadic localization is a behavioral consequence of crowding, we also showed that crowding occurs in the recognition of cluttered pedestrians in a more conventional crowding paradigm. We asked participants to discriminate the gender of pedestrians in static video frames and found that the altered saccadic localization correlated with the degree of crowding of the saccade targets. Taken together, our results provide strong evidence that crowding impacts both recognition and goal-directed actions in natural driving situations.
Original languageEnglish
Article number6
Pages (from-to)1-17
Number of pages17
JournalJournal of Vision
Issue number6
Publication statusPublished - 3 Jun 2020

Bibliographical note

This work was funded in part by NIH Grant 1R01CA236793-01.


  • crowding
  • driving
  • contextual modulation
  • eye movements
  • saccade localization
  • spatial vision


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