SOCA: Domain Analysis for Highly Automated Driving Systems

被引：12

作者：

Butz, Martin ^{[1
]}

Heinzemann, Christian ^{[1
]}

Herrmann, Martin ^{[1
]}

Oehlerking, Jens ^{[1
]}

Rittel, Michael ^{[1
]}

Schalm, Nadja ^{[1
]}

Ziegenbein, Dirk ^{[1
]}

机构：

[1] Robert Bosch GmbH, Corp Sect Res & Adv Engn, Robert Bosch Campus 1, D-71272 Renningen, Germany

来源：

2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC) | 2020年

关键词：

VERIFICATION;

D O I：

10.1109/itsc45102.2020.9294438

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Highly automated driving systems need to master a highly complex environment and are required to show meaningful behavior in any situation occurring in mixed traffic with humans. Deriving a sufficiently complete and consistent set of system-level requirements capturing all possible traffic situations is a significant problem that has not been solved in existing literature. In this paper, we propose a new method called SOCA addressing this problem by introducing a novel abstraction of traffic situations, called zone graph, and using this abstraction in a morphological behavior analysis. The morphological behavior analysis enables us to derive a set of system-level requirements with guarantees on completeness and consistency. We illustrate our method on a slice-of-reality example from the automated driving domain.

引用

页数：6

共 26 条

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