Excellence in Research/Collaborative Research: Modeling Transportation Choices Under the Presence of Real-time Information Using Simulated-based Virtual Experiments

这个卓越研究（EiR）项目将调查实时信息对使用智能城市中交通基础设施和服务的旅行者的顺序选择行为的影响。未来的智慧城市被设想为一个日常服务数字化、传感技术互联和城市管理智能算法带来创新社会经济和社会技术增长的地方。在这些“未来城市”中使用交通服务的旅行者在动态演变的系统中做出各种选择，诸如目的地、出发时间、旅行模式、旅行路线和/或停车位置的选择。本研究采用数据驱动的建模方法，研究选择之间的相互关系以及实时信息对选择的影响。作为该项目的一部分开发的工具和模型将实现数据驱动的选择建模和未来交通系统的管理，并将有助于NSF的使命，促进科学的进步和国家的繁荣和福利。除了其智力价值，该项目将（a）使历史上黑人学院和大学的学生能够参与未来交通系统的研究，（B）开发教育工具，用于响应实时信息的旅行者准确选择建模，以及（c）制定激励措施，指导未来智慧城市的设计和开发。最终，该项目将使各机构能够更好地执行短期和长期交通规划，这将产生重大的社会影响。作为其主要目标，该项目将使用先进的计量经济学框架来解释旅行者在实时信息存在下的选择，该框架确定了影响这些选择的因素，包括新兴技术的时变特征，服务水平，和社会人口统计变量。该项目将通过以下方式为选择建模理论和实验做出贡献：（1）明确地将实时信息纳入旅行者的顺序动态选择中，（2）通过D-有效实验设计对易出错或聚合信息对旅行选择的影响进行建模，以及（3）开发能够评估广泛的智能城市相关交通政策的政策敏感工具。该项目将采用创新技术，例如创建基于模拟的虚拟环境，用于在动态演化系统中对旅行者的选择进行实验，以及开发和校准用于准确预测旅行行为的强大数学模型。该项目的重点应用还将为民用基础设施系统的优化和运营提供指导，并将对可能长期影响出行行为的智能城市交通政策进行方法评估。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。

This Excellence in Research (EiR) project will investigate the impacts of real-time information on the sequential choice-making behavior of travelers using transportation infrastructure and services in smart cities. Smart cities of the future are envisioned as a place where digitalization of day-to-day services, interconnectedness of sensing technologies, and intelligent algorithms for city management lead to innovative socioeconomic and socio-technical growth. Travelers using transportation services in these “cities of the future” make various choices in a dynamically evolving system such as the choice of destination, departure time, mode of travel, travel route, and/or parking location. This project studies the interrelation of choices and the impact of real-time information on choices by adopting a data-driven modeling approach. The tools and models developed as part of this project will enable data-driven choice modeling and management of future transportation systems and will contribute toward NSF’s mission of promoting the progress of science and advancing the nation’s prosperity and welfare. Beyond its intellectual merit, this project will (a) enable underrepresented students at Historically Black Colleges and Universities to participate in research on future transportation systems, (b) develop educational tools for accurate choice modeling of travelers in response to real-time information, and (c) develop incentives that guide the design and development of smart cities of the future. Eventually, the project will enable agencies to perform better short-term and long-term transportation planning, which will have a substantial societal impact.As its primary goal, the project will explain travelers’ choices under the presence of real-time information using an advanced econometric framework that identifies the factors affecting these choices, including time-varying characteristics of emerging technologies, level-of-service, and socio-demographic variables. This project will contribute to the choice modeling theory and experiments by (1) explicitly incorporating real-time information in sequential dynamic choices of travelers, (2) modeling the impact of the error-prone or aggregated information on travel choices through D-efficient experimental design, and (3) developing a policy-sensitive tool that will be able to evaluate a wide range of smart-city-related transportation policies. This project will adopt innovative techniques such as creating a simulation-based virtual environment for experiments on choices made by travelers in a dynamically evolving system, and developing and calibrating robust mathematical models useful for accurate forecasting of travel behavior. The focus applications in this project will also provide guidance on optimization and operations of civil infrastructure systems and will enable methodological evaluation of transportation policies in Smart Cities that may impact travel behavior over the long term.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.