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

被引：1
|
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
相关论文
共 50 条
  • [21] AI-based Detection of Pest Infected Crop and Leaf
    Ahmed, Mustafa
    Mahajan, Tushar
    Sharma, Bhupender Datt
    Kumar, Mahendra
    Singh, Sandeep Kumar
    ICSPC'21: 2021 3RD INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION (ICPSC), 2021, : 402 - 406
  • [22] AI-based anomaly detection in tunnel excavation data
    Macke, Sebastian
    Munsch, Stephan
    Stascheit, Janosch
    Maidl, Ulrich
    Hegemann, Felix
    Geomechanik und Tunnelbau, 2024, 17 (04): : 312 - 323
  • [23] AI-based novelty detection in crowdsourced idea spaces
    Just, Julian
    Stroehle, Thomas
    Fueller, Johann
    Hutter, Katja
    INNOVATION-ORGANIZATION & MANAGEMENT, 2024, 26 (03): : 359 - 386
  • [24] AI-based fruit identification and quality detection system
    Goyal, Kashish
    Kumar, Parteek
    Verma, Karun
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (16) : 24573 - 24604
  • [25] Explainable AI-based Intrusion Detection in the Internet of Things
    Siganos, Marios
    Radoglou-Grammatikis, Panagiotis
    Kotsiuba, Igor
    Markakis, Evangelos
    Moscholios, Ioannis
    Goudos, Sotirios
    Sarigiannidis, Panagiotis
    18TH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY & SECURITY, ARES 2023, 2023,
  • [26] AI-based detection for Remote Electrocardiogram Monitoring System
    Garcia, Max
    Kumar, Sanjeev
    2024 IEEE 5TH ANNUAL WORLD AI IOT CONGRESS, AIIOT 2024, 2024, : 0336 - 0341
  • [27] A BONE FRACTURE DETECTION USING AI-BASED TECHNIQUES
    Mehta, Rushabh
    Pareek, Preksha
    Jayaswal, Ruchi
    Patil, Shruti
    Vyas, Kishan
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2023, 24 (02): : 161 - 171
  • [28] DentalArch: AI-Based Arch Shape Detection in Orthodontics
    Tamayo-Quintero, J. D.
    Gomez-Mendoza, J. B.
    Guevara-Perez, S. V.
    APPLIED SCIENCES-BASEL, 2024, 14 (06):
  • [29] AI-Based Fall Detection Using Contactless Sensing
    Taha, Ahmad
    Taha, Mohammad M. A.
    Barakat, Basel
    Taylor, William
    Abbasi, Qammer H.
    Imran, Muhammad Ali
    2021 IEEE SENSORS, 2021,
  • [30] Fully automatic AI-based leak detection system
    Tylman, Wojciech
    Kolczynski, Jakub
    Anders, George J.
    ENERGY, 2010, 35 (09) : 3838 - 3848
12345