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Evaluating Two Semantics for Falsification using an Autonomous Driving Example

Ramezani, Zahra, 1988 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Smallbone, Nicholas, 1986 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Fabian, Martin, 1960 (author)
Chalmers tekniska högskola,Chalmers University of Technology
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Åkesson, Knut, 1972 (author)
Chalmers tekniska högskola,Chalmers University of Technology
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 (creator_code:org_t)
ISBN 9781728129273
2019
2019
English.
In: IEEE International Conference on Industrial Informatics (INDIN). - 1935-4576. - 9781728129273 ; 2019-July, s. 386-391
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • We consider the falsification of temporal logic properties as a method to test complex systems, such as autonomous systems. Since these systems are often safety-critical, it is important to assess whether they fulfill given specifications or not. An adaptive cruise controller for an autonomous car is considered where the closed-loop model has unknown parameters and an important problem is to find parameter combinations for which given specification are broken. We assume that the closed-loop system can be simulated with the known given parameters, no other information is available to the testing framework. The specification, such as, the ability to avoid collisions, is expressed using Signal Temporal Logic (STL). In general, systems consist of a large number of parameters, and it is not possible or feasible to explicitly enumerate all combinations of the parameters. Thus, an optimization-based approach is used to guide the search for parameters that might falsify the specification. However, a key challenge is how to select the objective function such that the falsification of the specification, if it can be falsified, can be falsified using as few simulations as possible. For falsification using optimization it is required to have a measure representing the distance to the falsification of the specification. The way the measure is defined results in different objective functions used during optimization. Different measures have been proposed in the literature and in this paper the properties of the Max Semantics (MAX) and the Mean Alternative Robustness Value (MARV) semantics are discussed. After evaluating these two semantics on an adaptive cruise control example, we discuss their strengths and weaknesses to better understand the properties of the two semantics.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Keyword

Max Semantics
Falsification
Mean Alternative Robustness Value
Testing
Autonomous Driving.

Publication and Content Type

kon (subject category)
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