详情

Toward Artificial Intelligence-Enabled Decision Support Systems for TSMO Applications

项目名称：	Toward Artificial Intelligence-Enabled Decision Support Systems for TSMO Applications
摘要：	As contemporary transportation systems get more complex, it becomes more challenging for decision makers to consider the large number of intertwined factors needed to optimize systemwide processes and performance. For example, when an on-roadway vehicle crash occurs, operational systems such as dynamic vehicle routing and variable speed limits may need to be activated and used to provide timely and effective improvement in traffic incident management performance. These systems are examples of transportation systems management and operations (TSMO) strategies. According to the Federal Highway Administration (FHWA), “TSMO is defined as an integrated set of strategies to optimize the performance of existing infrastructure through the implementation of multimodal and intermodal, cross-jurisdictional systems, services, and projects designed to preserve capacity and improve security, safety, and reliability of the transportation system.” Decision support systems (DSSs), which are primarily computer-based information systems used to sort, rank, or choose alternatives, have been developed to improve TSMO. However, conventional DSSs are usually built on a set of expert rules that might not be able to provide customized and optimal solutions. Meanwhile, artificial intelligence (AI) offers potential to revolutionize many facets of our daily lives, including transportation. AI has the capacity to process multiple-sourced, large-scale, real-time data to model system behaviors, predict traffic conditions and evaluate system performance, which aligns with the key functions of DSSs. Research is needed to support state departments of transportation (DOTs) in selecting and deploying the right AI technologies in DSSs for TSMO applications. The objective of this research is to develop a guide, including implementation roadmaps, to help state DOTs and other transportation agencies in developing and deploying next-generation, data-driven, and AI-enabled DSSs for TSMO applications. A key emphasis should be on identifying areas where AI technologies can improve DSSs for TSMO applications and providing detailed implementation steps, resource needs, and assessing reliability and scalability of AI-based solutions.
状态：	Proposed
资金：	450000
资助组织：	National Cooperative Highway Research Program；American Association of State Highway and Transportation Officials (AASHTO)；Federal Highway Administration
项目负责人：	Deng, Zuxuan
开始时间：	20221108
主题领域：	Data and Information Technology；Highways；Operations and Traffic Management；Planning and Forecasting