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

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.