The Longitudinal Driving Behavior of a Vehicle Assisted with Lv2 Driving Automation: An Empirical Study

Table 6

Methods for estimating the Wiedemann 99 model parameters for AVs with Lv1 and Lv2 autonomy.

Source	Data	Parameter estimation
Goodall and Lan [14]	Field experiments were conducted under real traffic situations using a 2017 Audi Q7 assisted by the ACC functionality.	Parameters of the Wiedemann 99 model were measured directly from the field observations of the test vehicle.
Zeidler et al. [25]	Based on the data collected in the CoExist project [27].	The Wiedemann 99 parameters in PTV Vissim were adjusted to match the derived characteristics of both automated cars tested.
Sukennik et al. [16]	Field experiments were conducted on a test track using 2 Toyota Prius cars. One had equipped the CACC functionality, while the other had the dCACC functionality.	The Wiedemann 99 parameters in PTV Vissim were adjusted to reproduce three driving logics for AVs based on the derived characteristics of the cars tested.
Rossen [26]	No trajectory data were collected in this study.	The driving behavior of AVs was simulated in PTV Vissim based on the assumptions and parameter values found in earlier literature.
Atkins [24]	No trajectory data were collected in this study.	The authors modified the existing Wiedemann 99 model parameters within PTV Vissim to reproduce several forms of AVs based on their knowledge of early ACC and CACC systems.
Bierstedt et al. [23]	No trajectory data were collected in this study.	The authors modified the existing Wiedemann 99 model parameters within PTV Vissim to develop conservative, intermediate, and aggressive ACC characteristics.