D4.4: Fail-safe Vehicle Control

This report includes the outcome of WP4/T4.3, that is the respective control commands for the subject vehicle based on the results of motion planning, taking especially into account the minimum risk manoeuvre in critical situations (e.g., fails of perception system, wrong decision of the CAV, no response within the due time of driver to a take-over request, and so on). In more detail, the outcomes of Task 4.1 and Task 4.2 are integrated with the concept of fail-safe control commands for the CAV. Based on the output of the perception self-assessment component (T3.5) and the estimated risk bounds for planned trajectories (T4.1), an automated emergency action can be performed (fall-back strategy). Fail-safe control in AD refers to mechanisms and strategies designed to ensure that a vehicle remains safe in the event of system failures, errors, or unexpected situations. Thus, these systems must prioritize safety above all, in order to prevent accidents or to reduce the impact of hazardous situations. It is worth to noting that it may be difficult to find a fail-safe plan that works in all cases. For example, braking can work in many cases, but can also lead to collisions or dangerous situations when performed at the wrong time. Therefore, the idea followed in this report is to decrease the complexity of the possible solution to assure the robustness and the efficacy (even if this can imply a minor number of covered scenarios).

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-18
DOI
https://doi.org/10.5281/zenodo.15291111
Primary Topic
Mitochondrial Function and Pathology
Type
article
Field-Weighted Citation Impact
0.00
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article

D4.4: Fail-safe Vehicle Control

Zenodo (CERN European Organization for Nuclear Research)
Mitochondrial Function and Pathology
article

D4.4: Fail-safe Vehicle Control

article en

Abstract

This report includes the outcome of WP4/T4.3, that is the respective control commands for the subject vehicle based on the results of motion planning, taking especially into account the minimum risk manoeuvre in critical situations (e.g., fails of perception system, wrong decision of the CAV, no response within the due time of driver to a take-over request, and so on). In more detail, the outcomes of Task 4.1 and Task 4.2 are integrated with the concept of fail-safe control commands for the CAV. Based on the output of the perception self-assessment component (T3.5) and the estimated risk bounds for planned trajectories (T4.1), an automated emergency action can be performed (fall-back strategy). Fail-safe control in AD refers to mechanisms and strategies designed to ensure that a vehicle remains safe in the event of system failures, errors, or unexpected situations. Thus, these systems must prioritize safety above all, in order to prevent accidents or to reduce the impact of hazardous situations. It is worth to noting that it may be difficult to find a fail-safe plan that works in all cases. For example, braking can work in many cases, but can also lead to collisions or dangerous situations when performed at the wrong time. Therefore, the idea followed in this report is to decrease the complexity of the possible solution to assure the robustness and the efficacy (even if this can imply a minor number of covered scenarios).

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 62%
Mitochondrial Function and Pathology
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D4.4: Fail-safe Vehicle Control · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS