Caricamento in corso...
Biological and vehicular traffic: stochastic models
01UHYKG
A.A. 2019/20
Course Language
Inglese
Degree programme(s)
Doctorate Research in Fisica - Torino
Course structure
| Teaching | Hours |
|---|---|
| Lezioni | 20 |
Lecturers
| Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
|---|---|---|---|---|---|---|---|
| Pelizzola Alessandro | Professore Ordinario | PHYS-02/A | 20 | 0 | 0 | 0 | 6 |
Co-lectures
Context
| SSD | CFU | Activities | Area context | *** N/A *** |
|---|
2019/20
PERIOD: SEPTEMBER
The course aims to introduce students to (i) the basics of traffic modeling, focusing on phenomena which are observed in vehicular traffic and in living systems, and (ii) the approaches to these problems which have been recently developed on the basis of the theory of stochastic processes and nonequilibrium statistical physics.
PERIOD: SEPTEMBER
The course aims to introduce students to (i) the basics of traffic modeling, focusing on phenomena which are observed in vehicular traffic and in living systems, and (ii) the approaches to these problems which have been recently developed on the basis of the theory of stochastic processes and nonequilibrium statistical physics.
1. Elements of statistical mechanics and stochastic processes.
2. Vehicular traffic, empirical findings: observables, fundamental diagram, jams, traffic phases and phase transitions.
3. Biological traffic: ribosomes, molecular motors, ants.
4. Stochastic modeling of traffic: random walks, simple exclusion processes, zero range process, Nagel-Schreckenberg model.
5. Methods for stochastic traffic models: mean field and cluster approximations, numerical methods, introduction to exact solutions.
Reading materials:
A. Schadschneider, D. Chowdhury and K. Nishinari, Stochastic transport in complex systems, Elsevier (2011).
T. Chou, K. Mallick and R. K. P. Zia, Rep. Prog. Phys. 74, 116601 (2011).
Lecture notes and slides will be provided.
1. Elements of statistical mechanics and stochastic processes.
2. Vehicular traffic, empirical findings: observables, fundamental diagram, jams, traffic phases and phase transitions.
3. Biological traffic: ribosomes, molecular motors, ants.
4. Stochastic modeling of traffic: random walks, simple exclusion processes, zero range process, Nagel-Schreckenberg model.
5. Methods for stochastic traffic models: mean field and cluster approximations, numerical methods, introduction to exact solutions.
Reading materials:
A. Schadschneider, D. Chowdhury and K. Nishinari, Stochastic transport in complex systems, Elsevier (2011).
T. Chou, K. Mallick and R. K. P. Zia, Rep. Prog. Phys. 74, 116601 (2011).
Lecture notes and slides will be provided.
Modalità di esame:
Exam:
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Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam:
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.