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Home / Journals / American Journal of Traffic and Transportation Engineering / Smartphone-Based Intelligent Transportation Systems
Smartphone-Based Intelligent Transportation Systems

Special Issue Flyer (PDF)

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Lead Guest Editor:
Mehdi Ghatee
Department of Computer Science, Tehran, Iran
Guest Editors
Johan Wahlström
Oxford University
Oxford, UK
Luis Carlos Gonzalez-Gurrola
School of Engineering, Universidad Autónoma de Chihuahua Circuito Universitario
Chihuahua, Mexico
Amir Golroo
Department of Computer Science, Faculty of Mathematics and Computer Science, Amirkabir University of Technology
Tehran, Iran
Hamid Reza Eftekhari
Department of computer science, Malayer University
Tehran, Iran
Sina Dabiri
Lime, Information Technology and Services
California, USA
Introduction
Intelligent Transportation Systems (ITS) have achieved an immense positive impact on transportation in modern cities. These systems can be designed to, for example, increase safety, improve traffic management operations, reduce shipping costs, enhance information services, and protect infrastructure. They process huge amounts of data that are collected by a versatile set of sensors, extracting a lot of different traffic-related information.
One way to collect traffic data is by using smartphones. Smartphones offer many options for collecting, saving, and processing data with a user-friendly interface. In particular, many established methods within data mining, artificial intelligence (AI), and the Internet of Things (IoT) have been proposed to solve sensing, networking, and signal processing problems that show up in transportation applications. Additionally, one may make use of knowledge from disciplines such as civil engineering, electrical engineering, communication, computer science, statistics, and psychology. The purpose of this special issue is to provide a link between academia and industry by focusing on modern AI algorithms applied to data collected from smartphone-embedded sensors to show how smartphones can improve safety and mobility in transportation. Papers that present reviews or experiment results on smartphone data by different AI technologies, or theoretical topics related to improving transportation issues, are welcome.
Topics of interest include but are not limited to:
  1. Statistical methods for collecting data from smartphone sensors
  2. Preprocessing on smartphones data for ITS
  3. Feature extraction methods on smartphone data
  4. Feature selection methods for removing irrelevant features of smartphone data
  5. Supervised, unsupervised and semi-supervised learning methods on smartphone data
  6. Frequent patterns detection in smartphone data
  7. Shallow networks and deep networks on smartphone data
  8. Probabilistic methods on smartphone data
  9. Fuzzy methods on smartphone data
  10. Big data analysis for smartphone-based ITS
  11. Cloud computing for smartphone data analysis
  12. Identification of road anomalies
  13. Driver fingerprinting
  14. Transportation mode classification
  15. Detecting smartphone status in vehicles
  16. Driver behavior classification
  17. Usage based insurance and smartphones
  18. Advanced driver assistance system based on smartphone data
  19. Warning system on smartphones
  20. Traffic monitoring and control based on smartphones
  21. V2I , V2V and V2P (Pedestrian) based systems on smartphones

Aims and Scope:

  1. Smartphone Applications in Transportation
  2. Intelligent Transportation Systems based on Smartphones
  3. Smartphone Data Mining
  4. Smartphone Sensors Fusion
  5. Traffic monitoring by smartphones
  6. Incident detection by smartphones
  7. Road Quality Assessment
  8. Maneuvers Recognition
  9. Driving Style Evaluation
  10. Driving Score Prediction
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