Modelling and simulation of (connected) autonomous vehicles longitudinal driving behavior: A state‐of‐the‐art

Abstract

Abstract Microscopic traffic models (MTMs) are widely used for assessing the impacts of (connected) autonomous vehicles ((C)AVs). These models utilize car‐following (CF) and lane‐changing models to replicate the (C)AVs driving behaviors. Numerous studies are being lately published regarding the approximation of the driving behaviors of (C)AVs (especially CF behavior) with many state‐of‐the‐art modelling methods. Still, there is no established CF model to mimic the accurate behavior of (C)AVs. Researchers often utilize existing mathematical CF models as well as limited data‐driven models for (C)AVs modelling. Meanwhile, several studies conduct simulation‐based impact assessments with various key performance indicators (KPIs). Identification of these KPIs is a crucial step for future studies. Hence, this paper presents a comprehensive outlook on different CF models with their adopted parameters for (C)AVs modelling and investigates how and in which aspects might the CF behaviors of (C)AVs are different from human‐driven vehicles. In addition, the recent publications in data‐driven CF models including their methodologies are explicitly discussed. This work also reviews simulation‐based studies with the reported impacts and used KPIs. Finally, in light of the findings of this paper, several future research needs are highlighted.

Keywords

• automated driving & intelligent vehicles
• autonomous driving
• transport modeling and microsimulation