SBIR Phase I: Simulating Demand and Competition for Emerging Transportation Modes

SBIR 第一阶段：模拟新兴交通模式的需求和竞争

• 批准号: 2233320
• 负责人: Alan Walker
• 金额: $ 26.86万
• 依托单位: ATLANTA ANALYTICS LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2233320&HistoricalAwards=false
• 关键词: SBIR; Phase; Simulating; Demand; Competition

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to advance the state-of-the-art for demand modeling for electric aircraft by developing a decision support tool that assesses the broad economic, environmental, and equity impacts that these new modes of transportation will have on society. The project is motivated by recent advancements in battery technologies, autonomy, and distributed propulsion that are transforming air transportation through the development of a new class of electric vertical takeoff and landing (eVTOL) aircraft. The development of electric aircraft for longer distances is also in progress and could revitalize and support new service out of regional airports. The decision support tool can be used by government agencies, aircraft manufacturers, and other stakeholders to guide policy and multi-million dollar public and private infrastructure investments in a way that achieves a balance between economic, environmental, and equity impacts. This SBIR Phase I project will push the frontiers in modeling demand for new transportation modes, simultaneously addressing competition with ground modes, competitive pricing, and stimulated demand. The project focuses on examining how to model competition between air and ground transportation for distances between 50 and 350 miles where air travel has not been economically feasible in the past. This project focuses on three unproven, high-impact innovations. The first is the design of a scalable, demand simulation platform for air travel that includes distances in which the new aircraft are expected to operate. The second is the development of algorithms that use location-based data to identify the movement of current passengers between airport pairs and to predict demand stimulation. The third is the use of machine learning to calibrate air transportation networks for competitive marketplaces that have hundreds of inputs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小企业创新研究（SBIR）第一阶段项目的广泛影响是，通过开发一种决策支持工具，评估这些新的交通方式对社会产生的广泛的经济、环境和公平影响，从而推进电动飞机需求模型的最先进水平。该项目的动力来自于电池技术、自主性和分布式推进技术的最新进展，通过开发新型电动垂直起降（eVTOL）飞机，这些技术正在改变航空运输。长途电动飞机的发展也在进行中，可以振兴和支持区域机场的新服务。政府机构、飞机制造商和其他利益相关者可以使用决策支持工具来指导政策和数百万美元的公共和私人基础设施投资，以实现经济、环境和公平影响之间的平衡。SBIR一期项目将推动新交通模式需求建模的前沿，同时解决与地面模式的竞争、竞争性定价和刺激需求。该项目的重点是研究如何在50至350英里的距离内建立空中和地面交通竞争的模型，在过去，航空旅行在经济上是不可行的。该项目侧重于三个未经证实的高影响力创新。首先是设计一个可扩展的航空旅行需求模拟平台，包括新飞机预计运行的距离。第二是算法的发展，利用基于位置的数据来识别当前乘客在机场对之间的移动，并预测需求刺激。第三个是使用机器学习来校准航空运输网络，以适应有数百个输入的竞争市场。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。