Evaluation of perception performance modeling in microscopic traffic simulation

Microscopic traffic simulation models rely on simplifications of many aspects of driving behavior to describe traffic phenomena. Some aspects omitted by these simplifications become essential to distinguish the driving behavior of automated driving systems (ADSs) and humans. We consider the perception processes as one of such omitted aspects. The aim of this study is to evaluate the effects of an imperfect perception on the traffic flow dynamics using microscopic traffic simulation. A modeling approach is used which explicitly describes the perception performance in terms of accuracy, precision, delay, and range. Simulation experiments are presented which demonstrate possible effects on car-following and lane-changing situations. Results show that traffic phenomena such as instabilities, oscillations, and moving traffic jams can be simulated, providing a broader perspective about potential risks to the traffic flow performance. The explicit modeling of the perception has direct application on the study of mixed traffic of human and automated driving in microscopic traffic simulation.