Modeling Language for Scenario Development of Autonomous Driving Systems
Autonomous driving systems are typically verified based on scenarios. To represent the positions and movements of cars in these scenarios, diagrams that utilize icons are typically employed. However, the interpretation of such diagrams is typically ambiguous, which can lead to misunderstandings among users, making them unsuitable for the development of high-reliability systems. To address this issue, this study introduces a notation called the car position diagram (CPD). The CPD allows for the concise representation of numerous scenarios and is particularly suitable for scenario analysis and design. In addition, we propose a method for converting CPD-based models into propositional logic formulas and enumerating all scenarios using a SAT solver. A tool for scenario enumeration is implemented, and experiments are conducted on both typical car behaviors and international standards. The results demonstrate that the CPD enables the concise description of numerous scenarios, thereby confirming the effectiveness of our scenario analysis method.
Sun 27 AprDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:30 | Session 1 - Formal Methods and Autonomous Systems Research Track at 203 Chair(s): Divya Gopinath NASA Ames (KBR Inc.) | ||
11:00 30mTalk | CPS Falsification using Autoencoded Input Models Research Track | ||
11:30 30mTalk | Modeling Language for Scenario Development of Autonomous Driving Systems Research Track Toshiaki Aoki JAIST, Takashi Tomita JAIST, Tatsuji Kawai Kochi University, Daisuke Kawakami Mitsubishi Electric Corporation, Nobuo Chida Mitsubishi Electric Corporation | ||
12:00 30mTalk | Robustness Verification of Video Classification Neural Networks Research Track Samuel Sasaki Vanderbilt University, Preston K. Robinette Vanderbilt University, Diego Manzanas Lopez Vanderbilt University, Taylor T Johnson Vanderbilt University |