Servizi per la didattica
PORTALE DELLA DIDATTICA

Big Data application in transport (didattica di eccellenza)

01GTBRS

A.A. 2022/23

Course Language

Inglese

Degree programme(s)

Doctorate Research in Urban And Regional Development - Torino

Course structure
Teaching Hours
Lezioni 20
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Pronello Cristina Professore Ordinario ICAR/05 2 0 0 0 1
Co-lectuers
Espandi

Context
SSD CFU Activities Area context
*** N/A ***    
This course presents different methods to analyse big data from different sources (e. g. cellular phones and GPS), which are becoming essential in transport planning and management.
This course presents different methods to analyse big data from different sources (e. g. cellular phones and GPS), which are becoming essential in transport planning and management.
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Course Description Big data provides new ways of gathering novel information from passenger and vehicle movements and allows for a shift from passive approaches to active crowd-sourcing with innovative transport solutions. This course presents different methods to analyse big data from different sources (e. g. cellular phones and GPS), which are becoming essential in transport planning and management. The course will be articulated in six sessions. The introductory session will introduce to the students the topic of the course, the objective and the structure. Then, the diverse data collection methods will be presented, distinguishing between passive and active travel data collection. After having given the sufficient background on the topic, two applications, related to the route choice model and origin-destination matrix construction, will be presented. Finally, the household surveys will be explained to compare their potential with that of the passive and active data collection. The description of the above sessions follows. Introduction – what is big data (2 hours) • Motivation • 3 V’’s definition • Course purpose • Course structure Passive travel data collection (4 hours) • Conventional data sources • Cellular phones • GPS / GNSS Active travel data collection (4 hours) • Conventional methods • Smart phones • Serious games Route choice model application (4 hours) • Route choice modeling • Choice set generation methods • Data collection • Model estimation Origin – destination matrix application (2 hours) • Trip distribution models • Data collection • Data filtering Household surveys (4 hours) • Conventional surveys • GPS assisted surveys • Active surveys • Data analysis
Course Description Big data provides new ways of gathering novel information from passenger and vehicle movements and allows for a shift from passive approaches to active crowd-sourcing with innovative transport solutions. This course presents different methods to analyse big data from different sources (e. g. cellular phones and GPS), which are becoming essential in transport planning and management. The course will be articulated in six sessions. The introductory session will introduce to the students the topic of the course, the objective and the structure. Then, the diverse data collection methods will be presented, distinguishing between passive and active travel data collection. After having given the sufficient background on the topic, two applications, related to the route choice model and origin-destination matrix construction, will be presented. Finally, the household surveys will be explained to compare their potential with that of the passive and active data collection. The description of the above sessions follows. Introduction – what is big data (2 hours) • Motivation • 3 V’’s definition • Course purpose • Course structure Passive travel data collection (4 hours) • Conventional data sources • Cellular phones • GPS / GNSS Active travel data collection (4 hours) • Conventional methods • Smart phones • Serious games Route choice model application (4 hours) • Route choice modeling • Choice set generation methods • Data collection • Model estimation Origin – destination matrix application (2 hours) • Trip distribution models • Data collection • Data filtering Household surveys (4 hours) • Conventional surveys • GPS assisted surveys • Active surveys • Data analysis
In presenza
On site
Presentazione report scritto - Presentazione orale
Written report presentation - Oral presentation
P.D.1-1 - Dicembre
P.D.1-1 - December


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