Analysis,Modeling,and Simulation of Connected and Automated Trucks: State-of-the-Art and Identified Gaps

Abstract

Connected and automated trucks (CATs) have the potential to transform the transportation system and logistics industry. Their unique features, such as operational strategies and truck driving behaviors, can affect transportation system performance. For successful development, testing and deployment of CATs, analysis, modeling, and simulation (AMS) plays an important role, especially in evaluating the impacts of CAT technologies on existing transportation systems. This paper presents a comprehensive review and assessment of up-to-date studies related to CAT AMS, focusing on three correlated elements: CAT applications, data, and tools. The research delves into CAT applications from individual CAT and CAT fleet to CAT-involved traffic. It explores available data sources relevant to CAT system use cases, assessing their potential issues and opportunities. The study also reviews existing AMS tools used to analyze CAT applications at both operational performance and network integration levels, emphasizing research needs in CAT-specific tools development. The findings identify the data needs and point out that existing AMS tools may not capture the complexity of CAT operation, which involves driving behaviors, vehicle-to-everything communications, autonomous capabilities, and response to truck-specific scenarios. The study will lay a solid foundation for further development of the AMS framework for CATs and provide guidance to future research of CAT applications.