Cost-Effective Redundancy Approach for Fail-Operational Autonomous Driving System

Ishigooka, Tasuku; Honda, Shinya; Takada, Hiroaki

doi:10.1109/isorc.2018.00023

Cited by 15 publications

(5 citation statements)

References 9 publications

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“…To verify the results and to relate computation speeds, the proposed implementation described here was compared to a direct solution of (7): To achieve comparable result quality, t fail was discretized into Tfail such that, during a transition, any intermediate arc length ŝ ∈ Ŝ is evaluated at least once, as is the case with the proposed algorithm. For each a next ∈ Â, the direct solver computes and minimizes ⟨P⟩ by (8), and therein computes P(..., t fail , ...) by ( 5); the proposed solver precomputes I B , I C ▶ , I C ■ , and then for each a next ∈ Â, computes and minimizes P B + P C ▶ + P C ■ , accumulated over t, via (54), ( 58), (59).…”

Section: Practical Resultsmentioning

confidence: 99%

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Realtime Global optimization of a Fail-Safe Emergency Stop Maneuver for Arbitrary Electrical/ Electronical Failures in Automated Driving

Duerr

Ziehn

Kohlhaas

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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In the event of a critical system failures in automated vehicles, fail-operational or fail-safe measures provide minimum guarantees for the vehicle's performance, depending on which of its subsystems remain operational. Various such methods have been proposed which, upon failure, use different remaining sets of operational subsystems to execute maneuvers that bring the vehicle into a safe state under different environmental conditions. One particular such method proposes a fail-safe emergency stop system that requires no particular electric or electronic subsystem to be available after failure, and still provides a basic situation-dependent emergency stop maneuver. This is achieved by preemptively setting parameters to a hydraulic / mechanical system prior to failure, which after failure executes the preset maneuver "blindly". The focus of this paper is the particular challenge of implementing a lightweight planning algorithm that can cope with the complex uncertainties of the given task while still providing a globallyoptimal solution at regular intervals, based on the perceived and predicted environment of the automated vehicle.

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Section: Practical Resultsmentioning

confidence: 99%

“…Degraded capabilities of the ego vehicle include single-or multiple-point faults, which can be addressed by redundant systems to provide a fail-operational behavior (cf. [8]), possibly including graceful degradation (cf. [9]) by reducing active vehicle functions depending on the occurring failure Fig.…”

Section: Introductionmentioning

confidence: 99%

Realtime Global optimization of a Fail-Safe Emergency Stop Maneuver for Arbitrary Electrical/ Electronical Failures in Automated Driving

Duerr

Ziehn

Kohlhaas

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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“…The 1-out-of-2 with diagnostics (1oo2D) approach is investigated in [20]. In this paper, the recovery process is accelerated by using state backup and partial hot-standby approaches.…”

Section: Fail-operational Architecturesmentioning

confidence: 99%

Development and Experimental Validation of High Performance Embedded Intelligence and Fail-Operational Urban Surround Perception Solutions of the PRYSTINE Project

et al. 2021

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Automated Driving Systems (ADSs) commend a substantial reduction of human-caused road accidents while simultaneously lowering emissions, mitigating congestion, decreasing energy consumption and increasing overall productivity. However, achieving higher SAE levels of driving automation and complying with ISO26262 C and D Automotive Safety Integrity Levels (ASILs) is a multi-disciplinary challenge that requires insights into safety-critical architectures, multi-modal perception and real-time control. This paper presents an assorted effort carried out in the European H2020 ECSEL project—PRYSTINE. In this paper, we (1) investigate Simplex, 1oo2d and hybrid fail-operational computing architectures, (2) devise a multi-modal perception system with fail-safety mechanisms, (3) present a passenger vehicle-based demonstrator for low-speed autonomy and (4) suggest a trust-based fusion approach validated on a heavy-duty truck.

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“…Most related work is our previous work. We adopted the adaptation modeling approaches from Chameleon [16] and its successor Mars [1]. Chameleon introduced modular adaptation behavior modeling using preconditions, postconditions, and priorities.…”

Section: Related Workmentioning

confidence: 99%

Engineering and Hardening of Functional Fail-Operational Architectures for Highly Automated Driving

Adler

Akram

Feth

et al. 2019

2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)

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Rising automation levels in the automotive domain demand a shift from the fail-safe to the fail-operational paradigm. Fail-operational architectures and behaviors are inherently more complex and thus require special diligence from a safety engineering point of view. In this work, we present how we tailored and applied a methodology that facilitates the design of fail-operational architectures from early design stages on by enabling informed judgment regarding the gradually evolved architecture's fitness for purpose. The method specifically considers resilience regarding dynamic changes in environmental conditions, including V2X aspects and internal capabilities. In this paper, we summarize our experiences in applying the methodology in a highway pilot case study. Furthermore, we present essential extensions of the methodology for modeling and evaluating the operational design domain.

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Cost-Effective Redundancy Approach for Fail-Operational Autonomous Driving System

Cited by 15 publications

References 9 publications

Realtime Global optimization of a Fail-Safe Emergency Stop Maneuver for Arbitrary Electrical/ Electronical Failures in Automated Driving

Realtime Global optimization of a Fail-Safe Emergency Stop Maneuver for Arbitrary Electrical/ Electronical Failures in Automated Driving

Development and Experimental Validation of High Performance Embedded Intelligence and Fail-Operational Urban Surround Perception Solutions of the PRYSTINE Project

Engineering and Hardening of Functional Fail-Operational Architectures for Highly Automated Driving

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