Mathematical Definitions of Scene and Scenario for Analysis of Automated Driving Systems in Mixed-Traffic Simulations

Abstract

This paper introduces a unified mathematical definition for describing commonly used terms encountered in systematical analysis of automated driving systems in mixedtraffic simulations. The most significant contribution of this work is in translating the terms that are clarified previously in literature into a mathematical set and function based format. Our work can be seen as an incremental step towards further formalisation of Domain-Specific-Language (DSL) for scenario representation. We also extended the previous work in the literature to allow more complex scenarios by expanding the model-incompliant information using set-theory to represent the perception capacity of the road-user agents. With this dynamic perception definition, we also support interactive scenarios and are not limited to reactive and pre-defined agent behavior. Our main focus is to give a framework to represent realistic roaduser behavior to be used in simulation or computational tool to examine interaction patterns in mixed-traffic conditions. We believe that, by formalising the verbose definitions and extending the previous work in DSL, we can support automatic scenario generation and dynamic/evolving agent behavior models for simulating mixed traffic situations and scenarios. In addition, we can obtain scenarios that are realistic but also can represent rare-conditions that are difficult to extract from field-tests and real driving data repositories.

Design of an automotive platform for computer vision research

“…Depending on the recorded situation and usage of sensor data, differently detailed scenario descriptions are required. In [13], the authors describe scenariobased safety assessment for simulation purposes in a formal framework. On a wider scope, in [14] the terms scene, situation and scenario for automotive testing are substantiated.…”

Criticality Assessment Method for Automated Driving Systems by Introducing Fictive Vehicles and Variable Criticality Thresholds

“…It is worth mentioning that a min,x stands for the maximum longitudinal deceleration, wherein we respect the positive and negative signs of acceleration in the longitudinal direction. Here, d s is calculated as equivalent to the evasion time t ev (5) needed to change a lane with maximum lateral acceleration, a max,y [17,21]. Unlike the longitudinal direction, in the lateral direction, we do not consider negative signs; therefore, a max,y denotes the maximum acceleration, regardless of direction.…”

“…A scenario in the context of this work represents a series of actions occurring over a period of time, as defined in [4]. Other similar definitions are introduced and can be found, for example, in [5,6]. After extracting scenarios from a synthesized or real dataset, the scenarios are analyzed and assessed on their criticality.…”

Heterogeneous Driver Modeling and Corner Scenarios Sampling for Automated Vehicles Testing

“…We refer to [33,34] for a mathematical description of the testing scenario. e semantic method is selected to define the scenario by splitting it into a sequence of scenes by time.…”