Integrating activity-based and traffic assignment models: Methodology and case study application

S Agriesti; P Anashin; C Roncoli; BH Nahmias-Biran

doi:10.1109/MT-ITS56129.2023.10241611

Integrating activity-based and traffic assignment models: Methodology and case study application

S Agriesti, P Anashin^*, C Roncoli, BH Nahmias-Biran

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

1 Citation (Scopus)

Abstract

This paper presents a methodology to integrate two existing models: an activity-based model and a traffic assignment model, which are conceived as separately built and calibrated. Such a combination allows us to model the disaggregated interactions between supply and demand, which traditional modelling tools can frame only at the aggregate level (e.g. four-step models). An iterative method is proposed, combined with a novel formulation for a measure of error, which allows for achieving equilibrium in a limited number of iterations. The proposed method is tested using a real case study based on the City of Tallinn, Estonia, showing its effectiveness.

Original language	English
Title of host publication	2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
Publisher	IEEE
Number of pages	7
ISBN (Electronic)	978-1-6654-5530-5
DOIs	https://doi.org/10.1109/MT-ITS56129.2023.10241611
Publication status	Published - 2023
MoE publication type	A4 Conference publication
Event	IEEE International Conference on Models and Technologies for Intelligent Transportation Systems - Nice, France Duration: 14 Jun 2023 → 16 Jun 2023 Conference number: 8 https://mt-its2023.eurecom.fr/

Conference

Conference	IEEE International Conference on Models and Technologies for Intelligent Transportation Systems
Abbreviated title	MT-ITS
Country/Territory	France
City	Nice
Period	14/06/2023 → 16/06/2023
Internet address	https://mt-its2023.eurecom.fr/

Keywords

SimMobility
Activity-based modelling
Traffic assignment

Access to Document

10.1109/MT-ITS56129.2023.10241611

Cite this

@inproceedings{c628fa49297345ba8e1a9a05ca56a2fe,

title = "Integrating activity-based and traffic assignment models: Methodology and case study application",

abstract = "This paper presents a methodology to integrate two existing models: an activity-based model and a traffic assignment model, which are conceived as separately built and calibrated. Such a combination allows us to model the disaggregated interactions between supply and demand, which traditional modelling tools can frame only at the aggregate level (e.g. four-step models). An iterative method is proposed, combined with a novel formulation for a measure of error, which allows for achieving equilibrium in a limited number of iterations. The proposed method is tested using a real case study based on the City of Tallinn, Estonia, showing its effectiveness.",

keywords = "SimMobility, Activity-based modelling, Traffic assignment",

author = "S Agriesti and P Anashin and C Roncoli and BH Nahmias-Biran",

note = "| openaire: EC/H2020/856602/EU//FINEST TWINS; IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS ; Conference date: 14-06-2023 Through 16-06-2023",

year = "2023",

doi = "10.1109/MT-ITS56129.2023.10241611",

language = "English",

booktitle = "2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023",

publisher = "IEEE",

address = "United States",

url = "https://mt-its2023.eurecom.fr/",

}

Agriesti, S, Anashin, P, Roncoli, C & Nahmias-Biran, BH 2023, Integrating activity-based and traffic assignment models: Methodology and case study application. in 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023. IEEE, IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, Nice, France, 14/06/2023. https://doi.org/10.1109/MT-ITS56129.2023.10241611

Integrating activity-based and traffic assignment models: Methodology and case study application. / Agriesti, S; Anashin, P; Roncoli, C et al.
2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023. IEEE, 2023.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Integrating activity-based and traffic assignment models

T2 - IEEE International Conference on Models and Technologies for Intelligent Transportation Systems

AU - Agriesti, S

AU - Anashin, P

AU - Roncoli, C

AU - Nahmias-Biran, BH

N1 - Conference code: 8

PY - 2023

Y1 - 2023

N2 - This paper presents a methodology to integrate two existing models: an activity-based model and a traffic assignment model, which are conceived as separately built and calibrated. Such a combination allows us to model the disaggregated interactions between supply and demand, which traditional modelling tools can frame only at the aggregate level (e.g. four-step models). An iterative method is proposed, combined with a novel formulation for a measure of error, which allows for achieving equilibrium in a limited number of iterations. The proposed method is tested using a real case study based on the City of Tallinn, Estonia, showing its effectiveness.

AB - This paper presents a methodology to integrate two existing models: an activity-based model and a traffic assignment model, which are conceived as separately built and calibrated. Such a combination allows us to model the disaggregated interactions between supply and demand, which traditional modelling tools can frame only at the aggregate level (e.g. four-step models). An iterative method is proposed, combined with a novel formulation for a measure of error, which allows for achieving equilibrium in a limited number of iterations. The proposed method is tested using a real case study based on the City of Tallinn, Estonia, showing its effectiveness.

KW - SimMobility

KW - Activity-based modelling

KW - Traffic assignment

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U2 - 10.1109/MT-ITS56129.2023.10241611

DO - 10.1109/MT-ITS56129.2023.10241611

M3 - Conference article in proceedings

BT - 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023

PB - IEEE

Y2 - 14 June 2023 through 16 June 2023

ER -

Integrating activity-based and traffic assignment models: Methodology and case study application

Abstract

Conference

Keywords

Access to Document

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Fingerprint

FinEst Twins: FinEst Twins

ALCOSTO: Adaptive and Learning COntrol strategies for Sustainable future Traffic Operations

Cite this

Integrating activity-based and traffic assignment models: Methodology and case study application

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

FinEst Twins: FinEst Twins

ALCOSTO: Adaptive and Learning COntrol strategies for Sustainable future Traffic Operations

Cite this