Graduate School and Research Center in Digital Sciences
 

Transportation Planning

[PlanTP]
T Technical Teaching


Abstract

(Course for Post Master  et  international Master students only).This module addresses mechanisms and strategies to model multi-modal transportation. The objectives are first to introduce concepts of population modeling. Second, it extends graph theory concepts for modeling heterogeneous transportation networks, in particular public transport networks. Mechanisms for activity and demand modeling for multimodal transportation will also be discussed. Finally, this lecture trains on best practices to apply these concepts for efficient multimodal transportation planning on vehicular traffic simulator

 

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

Course Policies :  Attendance to Lab session is mandatory.

Requirements

  • Basic vehicular traffic modeling
  • Basic graph theory knowledge
  • Basic C++ and Bash / Python knowledge

Description

Graph Theory

  • Shortest Trip Planning
  • Nearest Neighbor Planning

Population Modeling and Analysis

Multi-modal transport theory 

  • Activity-based Modeling
  • Demand Modeling

Public Transportation Planning

  • Public network modeling
  • Multi-modal mapping

Advanced Topic in Transport Planning

Learning outcome:  

  • To be able to understand strategies and benefits of population modeling
  • To be able to analyze heterogeneous transportation networks
  • To be able to design activity-based modeling for multi-modal transportation
  • To be able to apply these concepts for multimodal transport planning 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