TRINITY: Tradable Mobility Credits for Efficient Transportation

TRINITY：可交易的移动积分以实现高效运输

• 批准号: 1917891
• 负责人: Moshe Ben-Akiva
• 金额: $ 40万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1917891&HistoricalAwards=false
• 关键词: TRINITY; Tradable; Mobility; Credits; Efficient

Tradable mobility credit (TMC) schemes as a way to manage travel demand have received significant attention in the transportation domain in recent years. In a TMC scheme, a regulator initially provides an initial endowment of mobility credits or tokens to all potential travelers. In order to use the transportation system, users need to spend a certain amount of tokens that could vary with the choice of travel mode, route, departure time etc. The tokens can be bought and sold in a market at a price that is determined by token demand and supply. This project will design, model and evaluate a system of TMCs--named Trinity--that operate in real-time. Trinity is personalized for each user and is designed to improve system-level objectives such as social welfare using future predictions of the transportation system. This study has the potential to accelerate the understanding and real-world deployment of TMCs and aid transportation agencies and operators in achieving long-term societal goals of sustainability by mitigating congestion and reducing energy and emissions. Algorithms and software developed under the project will be open-source and publically shared. They will be integrated with a transportation system prediction and control platform, DynaMIT, which will provide a useful tool for researchers to further extend the scientific knowledge. Educational benefits from the project include the training of graduate students and the involvement of postdoctoral researchers in undergraduate and graduate teaching activities and advising. Specifically, the project pursues the following goals: (1) Design and implement a novel bi-level optimization framework tailored for 'online' applications that includes two components: a system-level optimization that periodically (in real-time) determines 'optimal' token (mobility credit) rates for different mobility options by utilizing short term predictions of the transportation network, and a user-level optimization that will determine a personalized 'optimal' menu of mobility options to display to each individual user subject to the optimal system-level token charging policy; (2) Model the operation/dynamics of the token market by considering actions of the user (individual buying and selling decisions and plausible behavioral models incorporating heterogeneity) and regulator; and (3) Perform extensive simulation?based experiments on real-world networks to gain insights into how the design of the TMC schemes, user behavior, and network conditions can impact performance and market dynamics (for example: how should the allocation/acquisition/expiration of tokens be designed; how and when does the regulator intervene in the market, how should the token policies be designed to allow for scalability/effectiveness of optimization and network control?). The Trinity system, in employing complex simulation-based disaggregate transportation and market models, will allow a community of researchers to gain insights into system behavior when the token charges, traffic flow patterns and market price evolve together?a topic of immense interest which has received limited attention thus far.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.

近年来，可交易流动信贷（TMC）计划作为一种管理出行需求的方式在交通领域受到了极大的关注。在TMC计划中，监管机构最初向所有潜在的旅行者提供移动信用或令牌的初始捐赠。为了使用交通系统，用户需要花费一定数量的代币，这些代币可能会随着出行方式、路线、出发时间等的选择而变化。代币可以在市场上以由代币需求决定的价格买卖。和供应。该项目将设计、模拟和评估一个实时运行的TMC系统-名为Trinity。Trinity为每个用户提供个性化服务，旨在通过对交通系统的未来预测来改善系统级目标，例如社会福利。这项研究有可能加快对TMC的理解和实际部署，并帮助交通机构和运营商通过缓解拥堵、减少能源和排放来实现可持续发展的长期社会目标。在该项目下开发的算法和软件将是开源的，并以数字方式共享。它们将与交通系统预测和控制平台DynaMIT集成，这将为研究人员进一步扩展科学知识提供有用的工具。该项目的教育效益包括培训研究生和博士后研究人员参与本科和研究生教学活动和咨询。 具体而言，该项目追求以下目标：（1）设计和实现一个新的双层优化框架，为“在线”应用程序量身定制，包括两个组件：系统级优化，（实时）确定“最佳”令牌通过利用运输网络的短期预测，以及用户级优化，其将确定移动性选项的个性化“最佳”菜单以显示给服从最佳系统级令牌计费策略的每个单独用户;（2）通过考虑用户的行为来模拟代币市场的运行/动态（个人买卖决策和合理的行为模型，包括异质性）和监管机构;（3）进行广泛的模拟？基于真实网络的实验，深入了解TMC方案的设计、用户行为和网络条件如何影响性能和市场动态（例如：应该如何设计令牌的分配/获取/到期;监管机构如何以及何时干预市场，应该如何设计令牌策略以实现优化和网络控制的可扩展性/有效性？）。Trinity系统采用复杂的基于模拟的非聚合运输和市场模型，将允许研究人员社区深入了解系统行为时，令牌收费，交通流量模式和市场价格一起演变？这个奖项反映了NSF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。

项目成果

Congestion tolling — Dollars versus tokens: Within-day dynamics

• DOI: 10.1016/j.trc.2022.103836
• 发表时间: 2022-10
• 期刊: Transportation Research Part C: Emerging Technologies
• 作者: Ravi Seshadri;A. de Palma;M. Ben-Akiva

Market design for tradable mobility credits

• DOI: 10.1016/j.trc.2023.104121
• 发表时间: 2021-01
• 期刊: Transportation Research Part C: Emerging Technologies
• 作者: Siyu Chen;Ravi Seshadri;C. L. Azevedo;A. Akkinepally;Renming Liu;Andrea Araldo;Yu Jiang;M. Ben-Aki

Contextual Bayesian optimization of congestion pricing with day-to-day dynamics

• DOI: 10.1016/j.tra.2023.103927
• 发表时间: 2024-01
• 期刊: Transportation Research Part A: Policy and Practice
• 作者: Renming Liu;Yu Jiang;Ravi Seshadri;M. Ben-Akiva;C. L. Azevedo