# Non-Compliant Behaviour of Automated Vehicles in a Mixed Traffic Environment
###### Abstract
Furthermore, the role of authorities, which includes the regulation of automated vehicles, has rarely been investigated on the basis of TFS. Most studies utilizing traffic flow simulation address the functionalities of future vehicle systems. However, many of these studies primarily focus on implementing the longitudinal behavior of AVs, especially on Adaptive Cruise Control (ACC). Lateral motion control is mostly achieved by means of models which are also used for human-driven vehicles. A similar conclusion was reached by [PERSON] et al. [6]. In their study, parameter values of existing human driver behavior models were adjusted to capture AV driving behavior. Beyond this approach, they also outlined further methods for testing AV-related effects in a TFS environment: For instance, in most simulators, it is possible to replace the existing models by specific behavior models for AVs, with the aim of increasing the realism of the AV driving behavior. Another option is to extend existing driver models with 'nanoscopic' components, to incorporate elements such as sensor systems, vehicle dynamics, or vehicle communication. In course of this study, we present newly developed automated driving functions for longitudinal and lateral control on multi-lane highway segments, including strategies for on- and off-ramps. The models are intended to increase the realism of AV driving behavior. In addition, they allow the consideration and evaluation of varying driving regulations for AVs. In this context, we introduce the concept of non-compliant behavior as a clearly defined and controlled mechanism that enables AVs to operate effectively in complex, high-density traffic situations without negatively impacting traffic flow. Unlike previous studies, which often adjusted model parameters to allow for headway relaxation, our approach explicitly specifies both the extent and duration of non-compliance, making it possible to systematically study its impact on traffic performance, while guaranteeing clear legal specifications. To evaluate the necessity for such a concept, we analyzed the effects of the developed automated driving functionalities by performing a simulation study. For this purpose, we simulated 13 different scenarios considering varying driving regulations and AV penetration rates on an on-ramp highway segment. The simulation results are analyzed in terms of car-following and lane-changing behavior. In addition, the macroscopic effects on traffic flow (travel time, spatiotemporal speed profiles) are presented. The paper is organized in the following way. Section 2 describes related work regarding different AV-modeling approaches in TFS and their results. On that basis, we then explain the functions of automated driving, including a detailed model description of the non-compliant module in Section 3. The results, how the automated driving functions behave and their impact on traffic, are presented in Section 4. The main findings are discussed in Section 5 and we close with the conclusion of our analyses and give an outlook for further research in Section 6.