scholarly journals Multiclock Constraint System Modelling and Verification for Ensuring Cooperative Autonomous Driving Safety

2020 ◽  
Vol 2020 ◽  
pp. 1-24
Author(s):  
Jinyong Wang ◽  
Zhiqiu Huang ◽  
Xiaowei Huang ◽  
Yi Zhu ◽  
Fei Wang
Keyword(s):  
Formal Model ◽  
System Modeling ◽  
Autonomous Driving ◽  
State Machine ◽  
System Level ◽  
Design Stage ◽  
Great Promise ◽  
System Modelling ◽  
Safety Critical ◽  
State Machine Diagram

CADS (cooperative autonomous driving systems) are software-intensive and safety-critical reactive systems and give great promise to our daily life, but system errors may not be identified in the design stage until the implement stage, and the cost to correct them will be more expensive later than the early stage. For designing trustworthy autonomous software systems, we have to deal with multiclock constraint models. SysML (System Modeling Language) meets increasing adoption in order to carry out system-level modelling and verification against abstract representations, but it suffers from semantic ambiguities in the design of safety-critical autonomous systems. The main objective is to investigate methods for coping with the design and analysis models simultaneously and to achieve semantic consistency based on mathematical foundations and formal model transformation. In this paper, we propose a method to combine the requirement modelling process with analysis process together for CADS safety and reliability guarantee. Firstly, we extend SysML metamodels and construct SysML profile for the CADS domain that could improve modelling correctness and enhance reusability. An instantiated CADS model has been designed by means of adopting a profile containing different key functional and nonfunctional attributes and behaviors. Secondly, we define formal syntax and semantic notations for modelling elements in the SysML state machine diagram and show transformation rules between the state machine diagram and the CCSL (Clock Constraint Specification Language) model. Semantic preservation is also proved using the bisimulation relation between them for rigorous mapping correctness. Thirdly, a cooperative autonomous overtaking driving case study on the highway scenario is used for illustration, and we use the tool TimeSquare to simulate CCSL specification execution traces at the system design stage.

Modeling the Propagation of Failures in Software Driven Hardware Systems to Enable Risk-Informed Design

2008 ◽  
Author(s):  
David C. Jensen ◽  
Irem Y. Tumer ◽  
Tolga Kurtoglu
Keyword(s):  
Complex System ◽  
Product Life Cycle ◽  
System Modeling ◽  
Software Component ◽  
Temperature Data ◽  
System Level ◽  
Design Stage ◽  
Redundancy Management ◽  
Hardware System ◽  
Failure Propagation

Software-driven hardware configurations account for the majority of modern complex systems. The often costly failures of such systems can be attributed to software specific, hardware specific, or software/hardware interaction failures. The understanding of the propagation of failures in a complex system is critical because, while a software component may not fail in terms of loss of function, a software operational state can cause an associated hardware failure. The least expensive phase of the product life cycle to address failures is during the design stage. This results in a need to evaluate how a combined software/hardware system behaves and how failures propagate from a design stage analysis framework. Historical approaches to modeling the reliability of these systems have analyzed the software and hardware components separately. As a result significant work has been done to model and analyze the reliability of either component individually. Research into interfacing failures between hardware and software has been largely on the software side in modeling the behavior of software operating on failed hardware. This paper proposes the use of high-level system modeling approaches to model failure propagation in combined software/hardware system. Specifically, this paper presents the use of the Function-Failure Identification and Propagation (FFIP) framework for system level analysis. This framework is applied to evaluate nonlinear failure propagation within the Reaction Control System Jet Selection of the NASA space shuttle, specifically, for the redundancy management system. The redundancy management software is a subset of the larger data processing software and is involved in jet selection, warning systems, and pilot control. The software component that monitors for leaks does so by evaluating temperature data from the fuel and oxidizer injectors and flags a jet as having a failure by leak if the temperature data is out of bounds for three or more cycles. The end goal is to identify the most likely and highest cost paths for fault propagation in a complex system as an effective way to enhance the reliability of a system. Through the defining of functional failure propagation modes and path evaluation, a complex system designer can evaluate the effectiveness of system monitors and comparing design configurations.

MODEL AND VERIFICATION OF WS-CDL BASED ON UML DIAGRAMS

2010 ◽  
Vol 20 (08) ◽  
pp. 1119-1149 ◽  
Author(s):  
PENGCHENG ZHANG ◽  
HENRY MUCCINI ◽  
YUELONG ZHU ◽  
BIXIN LI
Keyword(s):  
Unified Modeling Language ◽  
State Machine ◽  
Underlying Structure ◽  
Unified Modeling ◽  
Industry Standard ◽  
Modeling Analysis ◽  
Uml Class Diagram ◽  
Uml Diagrams ◽  
Uml Sequence Diagram ◽  
State Machine Diagram

The Web Services Choreography Description Language (WS-CDL) is a specification developed by the W3C and can be viewed as a blueprint for the development of end-point services. Consequently, it is worth providing a systematic approach for its modeling, analysis and verification. The Unified Modeling Language (UML) is an industry standard for modeling. Applying UML to model WS-CDL is obviously a promising solution to bring together academics and practitioners through a unique standard language. In this paper, we propose to use different UML diagrams to model WS-CDL. UML Component Diagram is used to model the underlying structure of WS-CDL. UML Sequence Diagram is utilized to model the activities in WS-CDL. UML State Machine Diagram is utilized to model the behaviors of each role participating in a WS-CDL specification. We then enrich the UML State Machine Diagram with data by the use of UML Class Diagram. Given the UML specification of WS-CDL, we then provide a systematic way of formally analyzing and verifying WS-CDL against desired properties. Some experiments show that our approach can verify structural, behavioral and data properties in a middle-scale data-enriched WS-CDL specification.

Identification of Human Errors During Early Design Stage Functional Failure Analysis

2018 ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stage ◽  
Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced FFIP (Functional Failure Identification and Propagation), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed towards the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. To explore the capabilities of the proposed method, it is applied to a hold-up tank example and the results are coupled with Digital Human Modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

scholarly journals SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications

2020 ◽  
Vol 34 (07) ◽  
pp. 10901-10908 ◽  
Author(s):  
Abdullah Hamdi ◽  
Matthias Mueller ◽  
Bernard Ghanem
Keyword(s):  
Neural Networks ◽  
Recent Work ◽  
Autonomous Navigation ◽  
General Framework ◽  
Deep Neural Networks ◽  
Autonomous Driving ◽  
Black Box ◽  
Semantic Meaning ◽  
Safety Critical ◽  
Adversarial Attack

One major factor impeding more widespread adoption of deep neural networks (DNNs) is their lack of robustness, which is essential for safety-critical applications such as autonomous driving. This has motivated much recent work on adversarial attacks for DNNs, which mostly focus on pixel-level perturbations void of semantic meaning. In contrast, we present a general framework for adversarial attacks on trained agents, which covers semantic perturbations to the environment of the agent performing the task as well as pixel-level attacks. To do this, we re-frame the adversarial attack problem as learning a distribution of parameters that always fools the agent. In the semantic case, our proposed adversary (denoted as BBGAN) is trained to sample parameters that describe the environment with which the black-box agent interacts, such that the agent performs its dedicated task poorly in this environment. We apply BBGAN on three different tasks, primarily targeting aspects of autonomous navigation: object detection, self-driving, and autonomous UAV racing. On these tasks, BBGAN can generate failure cases that consistently fool a trained agent.

Development of a sliding-leg tripod as an add-on device for manufacturing

Robotica ◽  
2001 ◽  
Vol 19 (3) ◽  
pp. 285-294 ◽  
Author(s):  
Fengfeng Xi ◽  
Wanzhi Han ◽  
Marcel Verner ◽  
Andrew Ross
Keyword(s):  
Laser Scanning ◽  
System Analysis ◽  
System Modeling ◽  
Kinematic Model ◽  
Joint Space ◽  
Cnc Machine Tools ◽  
System Control ◽  
System Modelling ◽  
Cnc Machine ◽  
Analysis System

This paper presents the work on developing a sliding-leg tripod as a programmable add-on device for manufacturing. The purpose is to enhance the capabilities of any machine by providing it with a more flexible range of motion. This device can be used as a toolhead for CNC machine tools and robots, or as a work stage for coordinate measuring machines and laser scanning systems. In this paper, system modelling, analysis and control of this device is presented. System modeling includes mobility study, kinematic model and inverse kinematics. System analysis includes workspace analysis, transmission ratio and stiffness analysis. System control includes path planning, joint space control and Cartesian space prediction. It is shown that the proposed device can provide flexibility and dexterity to machines.

Research on Behavior Modeling and Simulation of Complex UAV Based on SysML State Machine Diagram

2021 ◽  
pp. 401-409
Author(s):  
Yuanjie Lu ◽  
Zhimin Liu ◽  
Zhixiao Sun ◽  
Miao Wang ◽  
Wenqing Yi ◽  
...  
Keyword(s):  
Modeling And Simulation ◽  
State Machine ◽  
Behavior Modeling ◽  
State Machine Diagram

Computational Functional Failure Analysis to Identify Human Errors During Early Design Stages

2019 ◽  
Vol 19 (3) ◽  
Author(s):  
Lukman Irshad ◽  
Salman Ahmed ◽  
H. Onan Demirel ◽  
Irem Y. Tumer
Keyword(s):  
Failure Analysis ◽  
Human Error ◽  
Human Action ◽  
System Level ◽  
Design Stage ◽  
Human Factors Engineering ◽  
Human Errors ◽  
Functional Failure ◽  
Early Design ◽  
Early Design Stages

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced functional failure identification and propagation (FFIP), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed toward the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. The capabilities of the proposed method is presented via a hold-up tank example, and the results are coupled with digital human modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

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