From Simulation Data to Test Cases for Fully Automated Driving and ADAS

Sippl, Christoph; Bock, Florian; Wittmann, David; Altinger, Harald; German, Reinhard

doi:10.1007/978-3-319-47443-4_12

Cited by 22 publications

(14 citation statements)

References 12 publications

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“…This can be done either deterministically, e.g. by stepping (equidistantly) through V L or performing Boundary Value Analysis [36], or stochastically, e.g. using Monte Carlo methods [37].…”

Section: Test Derivationmentioning

confidence: 99%

Fundamental Considerations around Scenario-Based Testing for Automated Driving

Neurohr¹,

Westhofen²,

Henning³

et al. 2020

Preprint

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The homologation of automated vehicles, being safety-critical complex systems, requires sound evidence for their safe operability. Traditionally, verification and validation activities are guided by a combination of ISO 26262 and ISO/PAS 21448, together with distance-based testing. Starting at SAE Level 3, such approaches become infeasible, resulting in the need for novel methods. Scenario-based testing is regarded as a possible enabler for verification and validation of automated vehicles. Its effectiveness, however, rests on the consistency and substantiality of the arguments used in each step of the process. In this work, we sketch a generic framework around scenario-based testing and analyze contemporary approaches to the individual steps. For each step, we describe its function, discuss proposed approaches and solutions, and identify the underlying arguments, principles and assumptions. As a result, we present a list of fundamental considerations for which evidences need to be gathered in order for scenario-based testing to support the homologation of automated vehicles. * The research leading to these results is partly funded by the German Federal Ministry for Economic Affairs and Energy within the project "VVM -Verification & Validation Methods for Automated Vehicles Level 4 and 5" and by the German Federal Ministry of Education and Research within the project "TESTOMAT -The Next Level of Test Automation" under grant agreement No. 01IS17026H.

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“…This can be done either deterministically, e.g. by stepping (equidistantly) through V L or performing Boundary Value Analysis [36], or stochastically, e.g. using Monte Carlo methods [37].…”

Section: Test Derivationmentioning

confidence: 99%

Fundamental Considerations around Scenario-Based Testing for Automated Driving

Neurohr¹,

Westhofen²,

Henning³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…[9], [10], would have to be applied subsequently to find scenarios that conform with a desired specification. This process is proposed in [11], [12]. However, these data-driven approaches require large amounts of data to find scenarios that conform with a specification.…”

Section: A Related Workmentioning

confidence: 99%

“…1) The logical checking of the specifications T sc detects a contradiction in the specifications in each scene: We introduce the feasible set D pred ⊂ R l n pred,l × {0, 1} hnsc , denoting the mixed-integer set fulfilling predicate constraints (11) and binary constraints (12) of the longitudinal problem ( 9). An empty set D pred implies the contradiction of at least two specifications.…”

Section: F Feasibility Checkingmentioning

confidence: 99%

Synthesizing Traffic Scenarios from Formal Specifications for Testing Automated Vehicles

Klischat

Althoff

2020

2020 IEEE Intelligent Vehicles Symposium (IV)

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Virtual testing plays an important role in the validation and verification of automated vehicles. State-of-theart approaches first generate a huge amount of test scenarios through simulations or test drives, which are later filtered to obtain relevant scenarios for a given set of specifications. However, only few works exist on synthesizing scenarios directly from specifications. In this work, we present an optimizationbased approach to synthesize scenarios only from formal specifications and a given map. To concretize the specifications, we formulate predicates, which are subsequently converted to a mixed-integer quadratic optimization problem. We demonstrate how our method can generate scenarios for maps featuring merging lanes and intersections given a variety of specifications.

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“…The vehicle and tyre models have been characterized and validated for a reference GT vehicle, identifying the requisite complex tyre–road coupled phenomena concerning the temperature, wear, and road pavement dependencies [ 21 , 22 ]. Four different roads, i.e., dry, wet, snowy, and icy, two diverse tyre mileages, i.e., new and worn, and three thermal tyre conditions are combined and analyzed in the study to understand which could be the advantages of the employment of the model-based controllers, aware of the tyre instantaneous characteristics, boundary operating and weather conditions, and overall vehicle dynamic potential [ 23 ]. The model-based control logics, able to make use of the additional information concerning the dynamic limits of the system, is tested in co-simulation with a 14 degrees-of-freedom vehicle plant model, where the tyres are described by means of a Pacejka’s magic formula (MF) model.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the Model-Based Control Performance in Vehicle Safety Critical Scenarios with Varying Tyre Limits

Sakhnevych

Arricale

Bruschetta

et al. 2021

Sensors

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In recent years the increasing needs of reducing the costs of car development expressed by the automotive market have determined a rapid development of virtual driver prototyping tools that aims at reproducing vehicle behaviors. Nevertheless, these advanced tools are still not designed to exploit the entire vehicle dynamics potential, preferring to assure the minimum requirements in the worst possible operating conditions instead. Furthermore, their calibration is typically performed in a pre-defined strict range of operating conditions, established by specific regulations or OEM routines. For this reason, their performance can considerably decrease in particularly crucial safetycritical situations, where the environmental conditions (rain, snow, ice), the road singularities (oil stains, puddles, holes), and the tyre thermal and ageing phenomena can deeply affect the adherence potential. The objective of the work is to investigate the possibility of the physical model-based control to take into account the variations in terms of the dynamic behavior of the systems and of the boundary conditions. Different scenarios with specific tyre thermal and wear conditions have been tested on diverse road surfaces validating the designed model predictive control algorithm in a hardware-in-the-loop real-time environment and demonstrating the augmented reliability of an advanced virtual driver aware of available information concerning the tyre dynamic limits. The multidisciplinary proposal will provide a paradigm shift in the development of strategies and a solid breakthrough towards enhanced development of the driving automatization systems, unleashing the potential of physical modeling to the next level of vehicle control, able to exploit and to take into account the multi-physical tyre variations.

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From Simulation Data to Test Cases for Fully Automated Driving and ADAS

Cited by 22 publications

References 12 publications

Fundamental Considerations around Scenario-Based Testing for Automated Driving

Fundamental Considerations around Scenario-Based Testing for Automated Driving

Synthesizing Traffic Scenarios from Formal Specifications for Testing Automated Vehicles

Investigation on the Model-Based Control Performance in Vehicle Safety Critical Scenarios with Varying Tyre Limits

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