Work

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

Year: 2024

Type: conference-paper

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.

Source: International Conference on Computer, Internet of Things and Smart City (CIoTSC)

DOI: 10.1145/3731867.3731907

Authors: Maiia Sagdieva, Koen H. van Dam, Liu Yang

Institutions: Imperial College London, Beijing Jiaotong University, Southeast University

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: hybrid

Funders: Government of the United Kingdom, China Postdoctoral Science Foundation