Literature Review on Maneuver-Based Scenario Description for Automated Driving Simulations

Abstract

The increasing complexity of automated driving functions and their growing operational design domains imply more demanding requirements on their validation. Classical methods such as field tests or formal analyses are not sufficient anymore and need to be complemented by simulations. For simulations, the standard approach is scenario-based testing, as opposed to distance-based testing primarily performed in field tests. Currently, the time evolution of specific scenarios is mainly described using trajectories, which limit or at least hamper generalizations towards variations. As an alternative, maneuver-based approaches have been proposed. We shed light on the state of the art and available foundations for this new method through a literature review of early and recent works related to maneuver-based scenario description. It includes related modeling approaches originally developed for other applications. Current limitations and research gaps are identified.

arXiv comment8 pages, 1 figure, 1 table

References in corpus (4)

• How would surround vehicles move? A Unified Framework for Maneuver Classification and Motion Prediction
• Predicting Future Lane Changes of Other Highway Vehicles using RNN-based Deep Models
• Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review
• Automatic lane change scenario extraction and generation of scenarios in OpenX format from real-world data

Cited by in corpus (2)

• An Approach to Systematic Data Acquisition and Data-Driven Simulation for the Safety Testing of Automated Driving Functions
• A Two-Level Stochastic Model for the Lateral Movement of Vehicles Within Their Lane Under Homogeneous Traffic Conditions