NSF/USDOT Collaborative Proposal: Methodology for Calibration and Validation of Traffic Simulation Models

NSF/USDOT 合作提案：交通仿真模型校准和验证方法

• 批准号: 0339108
• 负责人: Haris Koutsopoulos
• 金额: $ 7.5万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2006-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0339108&HistoricalAwards=false
• 关键词: NSF; USDOT; Collaborative; Proposal; Methodology

Traffic simulation is a critical methodology for the analysis of complex transportation systems and evaluation of new technologies and concepts. Modern traffic simulation tools are a synthesis of a number of individual models, interacting in complex ways. These models capture traffic dynamics and network performance on one hand, and travel behavior on the other. Despite the importance of traffic simulation models, both in research and practice, systematic procedures for their calibration and validation are very limited. The objective of this research is to develop the basis for scientific and rigorous approaches to the calibration and validation of traffic simulation models using readily available data, e.g., loop detector counts, speeds, etc. The calibration and validation approaches to be developed recognize the aggregate nature of the available data (which makes the error associated with various components of the simulation model difficult to isolate); and the complex, large-scale nature of the applications. The research builds the required methodological foundations from diverse fields such as, stochastic optimization, statistics, traffic flow theory, and travel behavior and uses empirical analysis to provide support for theoretical developments. Important activities of the research include: Development of a rigorous modeling framework for calibration and validation.Exploration of algorithmic and computational aspects of the proposed solution approaches.Identification of appropriate statistical validation techniques, applicable to the type of data available for validation of traffic simulation models and consistent with the characteristics and properties of the measures of performance of interest.Identification of long-term research directions that will eventually lead to practical tools for calibration and validation.Empirical analysis to assess the validity of the proposed approaches. Successful completion of the research will have important broader impacts. Without appropriate validation and calibration, conclusions regarding new systems and designs can be erroneous with serious consequences in terms of deployment cost and time, and overall assessment of their value. Improvements in the accuracy of traffic simulators and the validity of the conclusions reached through simulation will result in the minimization of the risk involved in the deployment of new technologies and the development of appropriate risk mitigation strategies and better utilization of available resources. Case studies will be developed. The research results will be disseminated through scholarly journals, seminars and conferences as well as through a web page. The results will also be integrated into the curriculum at two universities.

交通模拟是分析复杂运输系统和新技术和概念的评估的关键方法。 现代交通模拟工具是许多单个模型的综合，以复杂的方式进行交互。 这些模型一方面捕获了流量动态和网络性能，另一方面捕获了旅行行为。 尽管交通模拟模型的重要性，无论是在研究和实践中，其校准和验证的系统程序还是非常有限的。 这项研究的目的是为使用易于可用的数据（例如，LOOP探测器计数，速度等）进行校准和验证流量模拟模型的校准和验证的基础。要开发的校准和验证方法识别可用数据的聚合性质（这使得与模拟模型的各种组成部分相关联的误差与隔离模型的各种组成部分相关联）；以及应用程序的复杂，大规模的性质。 该研究建立了所需的方法论基础，这些基础是不同领域的基础，例如随机优化，统计，交通流理论和旅行行为，并使用经验分析来为理论发展提供支持。 这项研究的重要活动包括：用于校准和验证的严格建模框架的开发。探索算法和计算方面所提出的解决方案方法的识别。确定适当的统计验证技术，适用于可用的数据类型，可用于验证交通模拟的验证和验证效率的效果。验证。评估拟议方法的有效性的经验分析。成功完成研究将产生重要的广泛影响。 没有适当的验证和校准，关于新系统和设计的结论可能是错误的，在部署成本和时间以及其价值的整体评估方面，会产生严重的后果。 交通模拟器准确性的提高以及通过模拟得出的结论的有效性将导致最小化新技术部署所涉及的风险，并开发适当的降低风险降低策略，并更好地利用可用资源。将开发案例研究。研究结果将通过学术期刊，研讨会和会议以及网页传播。结果还将集成到两所大学的课程中。