A Formal Model of Train Control with AI-Based Obstacle Detection

被引：2
|
作者：
Gruteser, Jan [1 ]
Gelessus, David [1 ]
Leuschel, Michael [1 ]
Rossbach, Jan [1 ]
Vu, Fabian [1 ]
机构：
[1] Univ Dusseldorf, Inst Informat, Univ Str 1, D-40225 Dusseldorf, Germany
来源：
RELIABILITY, SAFETY, AND SECURITY OF RAILWAY SYSTEMS, RSSRAIL 2023 | 2023年 / 14198卷
关键词：
Railway System; AI; B method; Validation; Verification;
D O I：
10.1007/978-3-031-43366-5_8
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The research project KI-LOK aims to develop a certification methodology for incorporating AI components into rail vehicles. In this work, we study how to safely incorporate an AI for obstacle detection into an ATO (automatic train operation) system for shunting movements. To analyse the safety of our system we present a formal B model comprising the steering and AI perceptions subsystems as well as the shunting yard environment. Classical model checking is applied to ensure that the complete system is safe under certain assumptions. We use SIMB to simulate various scenarios and estimate the likelihood of certain errors when the AI makes mistakes.
引用
收藏
页码：128 / 145
页数：18
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