Arash Kalatian

Transportation, Data, Urban Space




Machine Learning

Transport Modelling

Recent Publications

Due to their ubiquitous and pervasive nature, Wi-Fi networks have the potential to collect large-scale, low-cost, and disaggregate data …

To ensure pedestrian-friendly streets in the era of automated vehicles, reassessment of current policies, practices, design, rules and …

Pedestrian’s road crossing behaviour is one of the important aspects of urban dynamics that will be affected by the introduction …

We utilize Wi-Fi communications from smartphones to predict their mobility mode, i.e. walking, biking and driving. Wi-Fi sensors were …

This paper analyzes the distracted pedestrians’ waiting time before crossing the road in three conditions: 1) not distracted, 2) …

There has been growing interest in exploiting cellular network data for transportation planning purposes in recent years. In this …


I have worked as a teaching assistant for the following courses:

  • CVL316: Transportation Engineering, Winter 2018 and Winter 2019, Ryerson University
  • CVL910: Transportation planning, Fall 2017 and Fall 2020, Ryerson University
  • Python for Transportation (as the Python instructor for CVL910)
  • Simulation, Fall 2016, Sharif University of Technology