Big Data Perspective for Driver/Driving Behavior

Terzi R., SAĞIROĞLU Ş., Demirezen M. U.

IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, cilt.12, sa.2, ss.20-35, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 2
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1109/mits.2018.2879220
  • Dergi Adı: IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Compendex, INSPEC
  • Sayfa Sayıları: ss.20-35
  • Anahtar Kelimeler: Intelligent vehicles, Biological system modeling, Big Data, Acceleration, Sensors, Road traffic, Event detection, DRIVING BEHAVIOR, DRIVER-BEHAVIOR, SAFETY, RECOGNITION
  • Gazi Üniversitesi Adresli: Evet

Özet

There are many articles published in driving/driver behavior (DDB) but few of them have focused on DDB with big data in the literature. The reasons for this might be the lack of media coverage, data, expertise or big data perspectives. This paper presents a big data perspective for investigating the DDB based on models, data features, and experiences. For this purpose, DDB studies were reviewed and grouped into six perspectives. 6V's of big data (volume, velocity, variety, veracity, vulnerability and value) were also revised and discussed how these V's were compatible with DDB data. Finally, the use of big data in DDB analysis was discussed and some suggestions were presented. The lack of big data perception on DDB research was also overviewed and a new perspective was presented for researchers, applicants or business managers to do more effective and suitable studies in the field of big data DDB.