Sustainable Transport Policy Impact Assessment Using Agent-based Modelling: A Case Study in Oxford, UK

The role of transportation in urban ecosystems is crucial, yet traditional approaches have historically favoured car-centric planning, overlooking broader environmental, economic, and social factors. As the impact of sustainable transport strategies has a profound effect on the entire urban network, policymakers and planners require more decision-support tools to navigate the growing complexity of modern transport systems. Traditional four-step transport models typically use aggregate data, missing the fine-grained details of how individuals make travel choices. Agent-based modelling allows for the modelling of individual agents with unique characteristics, providing a more nuanced understanding of travel behaviour. This paper develops a proof-of-concept agent-based model that focuses on the impact assessment of sustainable transportation policies, demonstrating potential insights based on a case study of Oxford. The presented modelling methodology captures high-level urban transport system dynamics based on the behaviour of individual agents, and can potentially be applied to other cases and settings to support assessment of sustainable transport policies.

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Published
2024-12-27
DOI
https://doi.org/10.1145/3731867.3731907
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Sustainable Transport Policy Impact Assessment Using Agent-based Modelling: A Case Study in Oxford, UK

Koen H. van Dam, Liu Yang, Maiia Sagdieva
Transportation Planning and Optimization
article

Sustainable Transport Policy Impact Assessment Using Agent-based Modelling: A Case Study in Oxford, UK

Koen H. van Dam, Liu Yang, Maiia Sagdieva
article en

Abstract

The role of transportation in urban ecosystems is crucial, yet traditional approaches have historically favoured car-centric planning, overlooking broader environmental, economic, and social factors. As the impact of sustainable transport strategies has a profound effect on the entire urban network, policymakers and planners require more decision-support tools to navigate the growing complexity of modern transport systems. Traditional four-step transport models typically use aggregate data, missing the fine-grained details of how individuals make travel choices. Agent-based modelling allows for the modelling of individual agents with unique characteristics, providing a more nuanced understanding of travel behaviour. This paper develops a proof-of-concept agent-based model that focuses on the impact assessment of sustainable transportation policies, demonstrating potential insights based on a case study of Oxford. The presented modelling methodology captures high-level urban transport system dynamics based on the behaviour of individual agents, and can potentially be applied to other cases and settings to support assessment of sustainable transport policies.

Beijing Jiaotong University (CN), Imperial College London (GB), Southeast University (CN)
Government of the United Kingdom, China Postdoctoral Science Foundation
Openalex Percentile: Top 74%
Transportation Planning and Optimization
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