Collaborative Research: CybeR-Enabled Demand-Interactive Transit for the Next-Generation Transportation Systems

合作研究：CybeR 支持的下一代交通系统的需求互动交通

• 批准号: 1402911
• 负责人: Yu Nie
• 金额: $ 17.5万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1402911&HistoricalAwards=false
• 关键词: Collaborative; Research; CybeR; Enabled; Demand

Being a mode of collective transport, transit tends to thrive in densely populated areas. In the US, unfortunately, suburb sprawl has made the condition progressively unfavorable for transit development since the 1950s. To reverse the trend of declining transit use in the US requires a concerted effort of planning, policy-making and engineering. Critical to this effort is to transform the way by which transit systems are designed and operated. In order to succeed in lower density areas where traditional transit systems fail, the next-generation transit systems must better interact with passengers, more closely cater to their demands, and operate efficiently to minimize costs. This award investigates a new kind of transit system called the CybeR-Enabled Demand-Interactive Transit system that takes into account these needs. The knowledge and insights gained from this project benefits the design and implementation of next-generation transit systems. The proposed evaluation framework, including a smartphone-based transit routing and data-collection tool, offers a platform to engage transit users, agencies and students. The passenger GPS traces collected in this project will form a large crowd-sourced database of high-fidelity transit demands that does not exist today. This wealth of the new data source will benefit researchers, policy-makers and practitioners.The objective of this project is to create theories and methods to characterize, analyze, operationalize, and evaluate the CybeR-Enabled Demand-Interactive Transit system. This system can be viewed as a hybrid system that integrates traditional fixed-route service and demand-responsive transit. The research activities are organized under three interwoven thrusts. The first thrust addresses the characterization and strategic design of the proposed system. The second thrust investigates mathematical problems arising from the need to operationalize the system which are: (1) the vehicle routing problem that determines the on-demand vehicle itineraries according to passenger requests; (2) the tactical design problem that coordinates schedules and adapts services to demands; and (3) the trip planning problem that generates optimal trip guidance for passengers using a data-driven and simulation-based framework that is based on a discrete-event simulation platform and a smartphone-based transit trip planning application known as TransitGenie. Different system designs and operational policies will be evaluated using case studies, which will be created from synthesized transit supply and demand data obtained from open sources and local transit agencies. TransitGenie will be instrumented with the ability to collect de-identified GPS traces from its users.

作为一种集体交通方式，公共交通往往在人口稠密的地区蓬勃发展。不幸的是，自 20 世纪 50 年代以来，美国郊区的扩张使得交通条件逐渐不利于交通发展。 要扭转美国公交使用量下降的趋势，需要规划、政策制定和工程的共同努力。这项努力的关键是改变交通系统的设计和运营方式。为了在传统交通系统无法胜任的低密度地区取得成功，下一代交通系统必须更好地与乘客互动，更密切地满足他们的需求，并高效运营以最大限度地降低成本。 该奖项研究了一种新型交通系统，称为“CybeR 支持的需求互动交通系统”，该系统考虑到了这些需求。 从该项目中获得的知识和见解有利于下一代交通系统的设计和实施。 拟议的评估框架包括基于智能手机的交通路线和数据收集工具，为交通用户、机构和学生提供了一个参与的平台。该项目中收集的乘客 GPS 轨迹将形成一个目前尚不存在的高保真交通需求的大型众包数据库。这些丰富的新数据源将使研究人员、政策制定者和从业者受益。该项目的目标是创建理论和方法来表征、分析、操作和评估 CybeR 支持的需求互动交通系统。该系统可以被视为集成了传统固定路线服务和需求响应型交通的混合系统。研究活动是在三个相互交织的主旨下组织的。第一个主旨涉及所提议系统的特征和战略设计。第二个重点研究因系统运行需要而产生的数学问题，这些问题是：（1）车辆路线问题，根据乘客的要求确定按需车辆行程； (2) 协调调度并使服务适应需求的战术设计问题； (3) 行程规划问题，使用数据驱动和基于模拟的框架为乘客生成最佳行程指导，该框架基于离散事件模拟平台和基于智能手机的交通行程规划应用程序（称为 TransitGenie）。将使用案例研究来评估不同的系统设计和运营政策，这些案例研究将根据从开源和当地交通机构获得的综合交通供需数据创建。 TransitGenie 将具备从用户那里收集去识别化 GPS 轨迹的能力。