Mobility Modelling

Lecture 1 - Introduction

6 Feb 2023

Mozhgan Pourmoradnasseri, Ph.D.

Saame Tuttavaks!

BSc, MSc in Math (Iran)

PhD in Theoretical computer science (2013-2017 Tartu)

Postdoc (2017-18 France) 

Joined ITS Lab as a researcher (2019-2020)

Lecturer at ITS Lab  (2021- now)

Research interests include data-driven approaches for

  • Human Mobility
  • Urban Dynamics
  • Active Mobility

AND YOU?

 Course webpage:

 

 Schedule:

  • Lectures: Monday 14.15 - 16.00, Delta 1008

  • Lab assistant office hours: Thursday 14.15 - 16.00, Delta 3043

 

Communication:

  • Moodle, Teams, Slack?                                                                               

Helen Tera

other Courses @ITS Lab 

https://courses.cs.ut.ee/2023/DS4UM/spring
https://courses.cs.ut.ee/2022/ITS/fall
  • We focus on moving objects (often humans) that can change their position in space over time.
  • We use data to understand how, when, where, and why people move.
  • We study mathematical models that describe empirical data.
  • We talk about mobility's short-term and long-term impacts on the environment and society.
  • We focus on transitioning from the traditional vehicle-centric vision to a human-centric one.

In this course:

1. Human mobility is an indicator for analyzing various other phenomena.  

  • Transportation and traffic management

2. Opportunity: Data availability & Computational cabability

Why do we study human mobility?

  • Urban Planning
  • Economy
  • Environment
  • Sociology
  • Public health

non-trivial EXAMPLE: STUDY OF CULTURAL HISTORY

Reconstructed aggregate intellectual mobility over two millennia through the birth and death locations of more than 150,000 notable individuals. 

Schich, M., Song, C., Ahn, Y. Y., Mirsky, A., Martino, M., Barabási, A. L., & Helbing, D. (2014). A network framework of cultural history. science, 345(6196), 558-562.

Course Strucrure

Lectures

Tutorials

Projects

  • Homework Assignments: 50%

  • Project: 50%

  • To pass, you have to grade at least 60% in homework.

GRADING

Lectures

https://tarktartu.telia.ee/en-GB/
https://its.cs.ut.ee/modsplit/
Zhang, Xiaohui, et al. "Simultaneous modeling of car-following and lane-changing behaviors using deep learning." Transportation research part C: emerging technologies 104 (2019): 287-304.
Khoshkhah, K., Pourmoradnasseri, M., & Hadachi, A. (2022, October). A real-time model for pedestrian flow estimation in urban areas based on IoT sensors. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

Tutorials

Assignments

Projects

Questions?