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EAGER/Collaborative Research: An Autonomous Modular Vehicle Technology-based Multifaceted Mobility Service Paradigm – A Proof-of-Concept Study

EAGER/Collaborative Research: An Autonomous Modular Vehicle Technology-based Multifaceted Mobility Service Paradigm – A Proof-of-Concept Study
EAGER/协作研究:基于自主模块化车辆技术的多方面移动服务范式 — 概念验证研究
批准号:
2127677
负责人:
Jane Lin
金额:
$20.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-08-15 至 2024-05-31

项目摘要

项目成果

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中文摘要
翻译
这个早期概念探索性研究资助(EAGER)项目将支持一项概念验证研究,以(1)了解基于自主模块化车辆技术(AMVT)的双模态系统(AMVT-BM)的基本权衡,该系统提供集成的公共交通和最后一英里的物流服务与一队模块化自动驾驶车辆或吊舱,以及(2)评估潜在利益相关者对技术的兴趣和反应。在美国,公交车辆的平均载客率很低(10.1% ~ 12.4%),造成座位资源的过度浪费和单位载客里程的燃油经济性差。COVID-19大流行严重加剧了这一问题,在高峰期导致全国公交乘客量减少了近80%。另一方面,疫情加速了电子商务的快速发展,给最后一公里的交付带来了巨大压力。将过境服务与最后一英里物流相结合的多式联运系统,再加上模块化,为更好地利用/共享车辆能力和支持基础设施提供了一个有前途的解决方案。然而,这一理念的实现不仅需要技术突破,还需要一种超越运输行业两个高度孤立部门边界的系统方法。 在本研究中,我们将集中在两个最基本的问题:(1)什么是共模态和模块化的系统性能的影响? (2)从利益相关者的角度来看,如运输机构、城市规划者、物流公司、运输网络公司和汽车制造商,协同潜力和采用挑战是什么?研究议程包括两项任务,旨在寻求这些问题的答案。 任务1通过分析和模拟研究模块化和共模态的影响。 任务2招募并调查潜在利益攸关方对与采用AMVT-BM相关的广泛问题的看法。该项目将创建一套优化工具,用于分析模块化运输和最后一英里交付服务系统。 它还将开发第一个同类模拟试验台,以指导整合运输和最后一英里交付操作的AMVT-BM系统的设计和评估。通过三个阶段的利益相关者调查,该项目将记录和分析技术,机构和财务潜力以及AMVT-BM系统在现实世界中实施的障碍,这将有助于了解这些系统的设计和运营。该奖项反映了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。
英文摘要
This EArly-concept Grant for Exploratory Research (EAGER) project will support a proof-of-concept study to (1) understand the fundamental trade-offs in Autonomous Modular Vehicle Technology (AMVT) based bi-modality system, or AMVT-BM, that provides integrated public transit and last-mile logistics services with a fleet of modular autonomous vehicles, or pods, and (2) gauge potential stakeholders’ interest and reaction to the technology. In the U.S., public transit vehicles have a very low average load factor (10.1% ~ 12.4%), resulting in excessive waste of seat capacity and poor fuel economy per passenger mile served. This problem is gravely exacerbated by the COVID-19 pandemic, which at its peak had caused nearly 80% reduction in transit ridership nationwide. On the other hand, the rapid uptake of e-commerce, also accelerated by the pandemic, has put tremendous pressure on last-mile delivery. Coupled with modularity, a co-modality system that integrates transit services with last mile logistics offers a promising solution to better utilization/sharing of vehicle capacity and supporting infrastructure. Yet, the implementation of this idea requires not only technological breakthrough, but also a system approach that transcends the boundaries of the two highly siloed sectors in the transportation industry. In this study, we will focus on two most fundamental questions: (1) what are the impacts of co-modality and modularity on system performance? And (2) what are synergistic potential and adoption challenges from the perspective of stakeholders such as transit agencies, urban planners, logistics companies, transportation network companies, and auto makers? The research agenda consists of two tasks designed to seek answers to these questions. Task 1 investigates the impacts of modularity and co-modality via analysis and simulation. Task 2 recruits and surveys potential stakeholders for their views on a wide range of issues related to the adoption of AMVT-BM. The project will create a suite of optimization tools for analyzing modularized transit and last-mile delivery service systems. It will also develop the first of its kind simulation testbed to guide the design and evaluation of an AMVT-BM system that integrates transit and last-mile delivery operations. Through a three-phase stakeholder survey, the project will document and analyze technological, institutional, and financial potentials as well as barriers to the real-world implementation of AMVT-BM systems, which will shed light on the design and operation of these systems. The project findings will help identify critical future research agenda.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.
期刊论文(1)
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DOI: 10.1109/mits.2022.3159484
发表时间: 2023-01
期刊: IEEE Intelligent Transportation Systems Magazine
影响因子: 3.6
作者: [Jane Lin;Y. Nie;K. Kawamura]
通讯作者: Jane Lin;Y. Nie;K. Kawamura
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