EAGER/Collaborative Research: Enable Elastic Capacity for Transportation Infrastructure through a Transmodal Modular Autonomous Vehicle System

EAGER/协作研究：通过跨模式模块化自动驾驶车辆系统实现交通基础设施的弹性能力

• 批准号: 2023408
• 负责人: Xiaopeng Li
• 金额: $ 18.81万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2023408&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Enable; Elastic

While roadway infrastructure provides limited capacity, vehicles operating on roads dominated by passenger cars may easily exceed road capacity over peak hours, causing traffic congestion, excessive energy consumption and increased safety risks. In observing that a passenger car takes much space on a roadway due to the relatively long gap following a preceding vehicle, this EArly-concept Grant for Exploratory Research (EAGER) project explores emerging modular autonomous vehicle (MAV) technology that can dynamically adjust gaps between vehicles. With the MAV technology, vehicles composed of multiple modular pods can be dynamically docked and separated during operations. For example, during peak hours, modular pods will be docked into longer MAVs, resulting in zero gaps between the modular pods docked together, which obviously improves highway throughput and reduces congestion. Whereas during off-peak hours, a long MAV may separate into shorter MAVs to ensure flexible system accessibility and reduce vehicle operation costs. This way, the MAV service equivalently creates “elastic” capacity for fixed transportation infrastructure to adapt spatiotemporally-varying travel demand. This project is for a new transmodal MAV system paradigm to realize such elastic capacity of a road transportation system. To realize this vision, we will adapt multidisciplinary theoretical methods (e.g., time-geography, queuing theory, traffic flow theory, and homogeneous analysis) to understand and formulate operations of an MAV system. Then we will build mathematical models for the optimal design and operations of an MAV system at various scales by synchronizing demands and modular pods over time and space. The major challenge is to deal with continuous time and space as opposed to traditional fleet management problems with discrete time-space states. This challenge will be overcome by integrating microscopic trajectory control into macroscopic fleet management. If successful, this project will provide transmodal concepts to improve transportation and other related systems that are currently segregated into different modes. It will help boost the MAV service from a startup stage to a sustainable industry. The results will help transportation stakeholders understand feasibility and benefits of the MAV service and devise measures to incorporate it in their future planning, which may result in profound positive impacts on surface transportation including transit and freight operations.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.

虽然道路基础设施可提供有限的容量，但在由乘用车主导的道路上运行的车辆在高峰时段很容易超过道路容量，从而导致交通拥堵，过量的能源消耗和增加的安全风险。在观察者汽车上，由于前一辆车辆之后的相对长差距，在巷道上占用了很多空间，这项早期概念探索性研究（急切）项目探索了新兴的模块化自动驾驶汽车（MAV）技术，可以动态调节车辆之间的间隙。使用MAV技术，可以在操作过程中动态停靠和分离由多个模块化吊舱组成的车辆。例如，在高峰时段，模块化豆荚将停靠在更长的MAV中，从而导致模块化吊舱之间的零间隙为零，这显然改善了高速公路吞吐量并减少了拥塞。而在非高峰时段，长长的MAV可能会分离为较短的MAV，以确保灵活的系统可访问性并降低车辆运行成本。这样，MAV服务也同样创造了固定运输基础设施以适应空间变化的旅行需求的“弹性”能力。该项目是为了实现新的跨模型MAV系统范式，以实现公路运输系统的这种弹性能力。为了实现这一愿景，我们将适应多学科理论方法（例如时间地理位置，排队理论，交通流理论和同质分析），以理解和制定MAV系统的操作。然后，我们将通过在时间和空间上同步需求和模块化荚来构建MAV系统最佳设计和操作的数学模型。主要的挑战是处理连续的时间和空间，而不是离散时间空间状态的传统车队管理问题。通过将微观轨迹控制整合到宏观的车队管理中，将克服这一挑战。如果成功，该项目将提供跨模式概念，以改善当前隔离为不同模式的运输和其他相关系统。这将有助于将MAV服务从创业阶段转变为可持续行业。结果将有助于运输利益相关者了解MAV服务的可行性和利益，并制定措施将其纳入未来的计划中，这可能会对表面运输（包括过境和货运操作）产生深远的积极影响。该奖项反映了NSF的法定任务，并通过使用该基金会的智力功能和广泛的影响来评估Criteria criiteria criteria criperia criiteria被视为珍贵。

项目成果

Designing corridor systems with modular autonomous vehicles enabling station-wise docking: Discrete modeling method

• DOI: 10.1016/j.tre.2021.102388
• 发表时间: 2021-06-25
• 期刊: TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
• 影响因子: 10.6
• 作者: Chen, Zhiwei;Li, Xiaopeng
• 通讯作者: Li, Xiaopeng