Rethinking traffic modelling for next generation city-scale networks

重新思考下一代城市规模网络的流量建模

• 批准号: DE220101320
• 负责人: Dr Mehmet Yildirimoglu
• 金额: $ 30.66万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2022
• 资助国家: 澳大利亚
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE220101320
• 关键词: Rethinking; traffic; modelling; next; generation

This project aims to develop an efficient traffic simulation model that enables data-informed traffic monitoring and automated model development, streamlining the fundamental transformation that next-generation cities will undergo in the coming decades. The project expects to generate new knowledge in traffic modelling by developing an innovative approach to inferring traffic conditions and traveller behaviour from diverse data feeds, and automating model calibration through an optimisation formulation. Expected outcomes address the eventual transition to smart cities and connected and autonomous vehicle technologies, providing significant social, economic and environmental benefits through optimal planning and effective operation schemes.

该项目旨在开发一个高效的交通模拟模型，实现数据化交通监控和自动化模型开发，简化下一代城市在未来几十年将经历的根本性转变。该项目预计将通过开发一种创新方法来从不同的数据源中推断交通状况和旅行者行为，并通过优化公式自动进行模型校准，从而在交通建模方面产生新的知识。预期成果涉及最终向智慧城市以及互联和自动驾驶汽车技术的过渡，通过最佳规划和有效的运营方案提供重大的社会、经济和环境效益。