Graduate School and Research Center in Digital Sciences
 

Mobility Modeling

[MobMod]
T Technical Teaching


Abstract

(Course for Post Master and International Master students only).

The module teaches the state-of-the art of the modeling techniques for vehicular mobility. The objectives are first to describe the challenges of close-to-reality random models for vehicular mobility, then to introduce the concepts of vehicular traffic flow models and Origin-Destination (O-D) Matrices for trip and path planning. Finally, it trains on best practices to apply these concepts for realistic vehicular traffic modeling on vehicular traffic simulators.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory.

Bibliography

  • Jérôme Härri, Vehicular Mobility Modeling for VANET, VANET Vehicular Applications and Inter-Networking Technologies, Hannes Hartenstein (Editor), Kenneth Laberteaux (Editor), ISBN: 978-0-470-74056-9, Chapter 5, pp. 107-156, January 2010.
  • Sandesh Uppoor, Marco Fiore, Jérôme Härri, Synthetic mobility traces for vehicular networking, in Book chapter N.6 in "Vehicular Networks: Models and Algorithms"; Beylot, André-Luc and Labiod, Houda (Eds), Wiley, ISBN: 978848214897, 2013.

Requirements

  • Basic Calculus Knowledge

Description

Random Mobility Modeling

  • Random Waypoint
  • Steady-State Distribution & Palm Theory

Vehicular Flow Modeling

  • Micro-, Meso-, Macro- Modeling
  • Fundamental Flow Diagrams

Vehicular Traffic Modeling

  • Trip & Path Planning
  • O-D matrices

Advanced Topics:

  • Analysis of Mobility Patterns & Impact on Communications
  • Behavioral Mobility Models
  • Pedestrian, Motorcycles, non-physical models…

Learning outcome:  

  • To be able to analyze the basic properties of random mobility
  • To be able to understand vehicular traffic flow modeling & vehicular trip planning
  • To be able to apply these concepts for realistic scenario design and analysis on traffic simulators

Nb hours : 21.00,  3 Lab sessions (9 hours)

Nb hours per week: 3.00

Grading Policy : Lab reports (50%), Final Exam (50%)

Nb hours: 21.00
Nb hours per week: 3.00