TraMPa: Transportation Modeling Using Publicly Available Data: An Evolution for Model Input Data
TraMPa:使用公开数据进行交通建模:模型输入数据的演变
基本信息
- 批准号:415208373
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:德国
- 项目类别:Research Grants
- 财政年份:2019
- 资助国家:德国
- 起止时间:2018-12-31 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
TraMPa investigates the use of openly available data for the development of transportation models. The proposed project builds upon the ever-growing amount of data that can be obtained by a diverse number of open data sources available. The analysis will be based on different levels of open source data availability to perform validation, sensitivity analyses and meta-model analyses for the investigation of the model performance based on real-world scenarios.This project aims at using openly available data as much as possible for model development, model calibration and model validation. A core finding will be how far openly available data may replace traditional data sources in transport modeling. Data sources to be tested in this project include all transport-related data that can be obtained openly online, legally and free of charge. This includes data that can be accessed through an Application Programming Interface (API), web-scraping or direct download (open data). Traditional data, in contrast, may be inaccessible to other researchers or cost money. By exploring the potential of open data, this proposal aims at establishing evidence how open data may support a more transparent and reproducible transport modeling approach. An Open Model will be compared with a Traditional Model that has been implemented for the Munich metropolitan area, the State of Maryland in the USA and Cape Town in South Africa. By comparing two traditional models with open models (and hybrids thereof) for the same study areas and the same scenarios, it will be possible to quantify the potential of openly available data to replace traditional data sources. It is perceivable that the Open Model will even perform better than the Traditional Model, as it is hypothesized that the data used for the Open Model is less biased and less error-filled than conventional data used for the Traditional Model. In order to allow for a better understanding of the effect that open data could have in the definition of the Open Transportation Model, different mixes of traditional data and open data will be tested by validation, sensitivity analyses and meta analyses to examine the performance of the models estimated based on Key Performance Indicators (KPIs). This comparison of the Open Model with the Traditional Model (and hybrids thereof) will help explore the impact that levels of data availability and penetration have on transportation models. Should this research show that the Open Model outperforms the Traditional Model, the implications on data collection, model design and required funding could be substantial.
TraMPa研究使用公开可用的数据来开发运输模型。拟议的项目建立在不断增长的数据量的基础上,这些数据可以通过各种开放数据源获得。该分析将基于不同程度的开放源数据的可用性,以进行验证、敏感性分析和元模型分析,以便根据真实世界的情景调查模型性能。该项目旨在尽可能使用开放源数据进行模型开发、模型校准和模型验证。一个核心发现将是在多大程度上公开可用的数据可以取代传统的数据源在交通建模。本项目将测试的数据来源包括可在网上公开、合法和免费获得的所有与运输有关的数据。这包括可以通过应用程序编程接口(API)、网络抓取或直接下载(开放数据)访问的数据。相比之下,传统数据可能无法被其他研究人员访问或需要花费资金。通过探索开放数据的潜力,该提案旨在确立开放数据如何支持更透明和可重复的运输建模方法的证据。开放模式将与在慕尼黑大都市区、美国马里兰州和南非开普敦实施的传统模式进行比较。通过对相同研究领域和相同情景的两个传统模型与开放模型(及其混合模型)进行比较,将有可能量化公开可用数据取代传统数据来源的潜力。可以看出,开放式模型甚至比传统模型表现得更好,因为假设用于开放式模型的数据比用于传统模型的常规数据更少偏差和更少错误填充。为了更好地理解开放数据在定义开放运输模型时可能产生的影响,将通过验证、敏感性分析和Meta分析对传统数据和开放数据的不同组合进行测试,以检查基于关键绩效指标(KPI)估计的模型性能。开放模式与传统模式(及其混合模式)的比较将有助于探索数据可用性和渗透水平对运输模式的影响。如果这项研究表明,开放模式优于传统模式,对数据收集,模型设计和所需资金的影响可能是巨大的。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Professor Dr. Constantinos Antoniou其他文献
Professor Dr. Constantinos Antoniou的其他文献
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{{ truncateString('Professor Dr. Constantinos Antoniou', 18)}}的其他基金
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