Sign location, sign recognition, and driver expectancies

Research output: Contribution to journalArticlepeer-review

48 Scopus citations


Background: According to police reports, failure to heed signs is one of the most frequent causes of accidents. We examined situations in which experience might paradoxically impair detection and timely identification of traffic signs: when they are located in unexpected places. Hypothesis: Experienced drivers have a well-learned schema for scanning the roadway, and will have difficulty detecting traffic signs when their location violates the expectations. Method: Twenty experienced drivers were exposed briefly to pictures of real street and road scenes; some included "no right-turn" (NRT) signs in the expected location (on the right curb) and some contained the same sign in an unexpected location (on the left curb). Participants' eye movements were recorded during the experiment. Results: Drivers were less likely to identify the NRT sign when it was located at the unexpected location. Females were less sensitive to sign location and their performance was much better than that of males. Conclusions: To increase their timely probability of identification, traffic signs should be posted in expected locations. Schema that drivers bring to the road enables them to handle large amounts of information, but the same schema can endanger drivers if traffic signs placement does not conform to the schema. Implications: When signs are misplaced, crash causes can be due to inappropriate design, rather than inappropriate driving. Highway designers should ensure that their design conforms to standards that shape drivers' expectations.

Original languageEnglish
Pages (from-to)459-465
Number of pages7
JournalTransportation Research Part F: Traffic Psychology and Behaviour
Issue number6
StatePublished - 1 Jan 2008


  • Driver's behavior
  • Driving experience
  • Expectations
  • Schemata
  • Skill
  • Traffic sign recognition

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Applied Psychology


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