Relationship between Chauffeurs' Demographics, and Knowledge of Traffic Signs in the Kingdom of Saudi Arabia

Wael Alhajyaseen*, Nedal Ratrout, Deepti Muley

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


Authorities in the Kingdom of Saudi Arabia (KSA) are investing heavily on developing Intelligent Transport Systems, which includes installations of Variable Message Signs (VMS) for the road users. However, it is challenging to design the VMS messages since the population possess different cultural, linguistic, and social backgrounds. To aid in the process of VMS design, this paper presents results from a questionnaire survey, conducted on chauffeurs involved in crashes in the Kingdom to understand their knowledge of traffic signs. A sample of around 800 chauffeurs, who were involved in crashes, was collected by conducting personal interviews. The relationship between chauffeurs' demographic characteristics, such as nationality, age group, language skills, and knowledge of traffic signs were assessed. The chauffeurs' language skills were assessed for Arabic, English, and native language. Chauffeurs' knowledge of five traffic signs namely speed limit, no entry, no overtaking, stop sign, and roundabout were tested. The results from descriptive analysis indicated that more than 60% drivers were able to understand traffic signs written in Arabic and English language. The least understood sign was no entry and the most understood sign was stop sign. Nationality of chauffeur was related to the knowledge of traffic signs and language skills. These results suggest that more research should be undertaken before designing VMS especially in a heterogeneous driver population like that of the Kingdom of Saudi Arabia.

Original languageEnglish
Pages (from-to)34-41
Number of pages8
JournalProcedia Computer Science
StatePublished - 2018

Bibliographical note

Publisher Copyright:
© 2018 The Authors. Published by Elsevier B.V.


  • Chauffeurs
  • Demographic characteristics
  • Driver language skills
  • Traffic signs
  • Variable Message Signs

ASJC Scopus subject areas

  • General Computer Science


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