Self-Driving Car Safety Quantification via Component-Level Analysis

Vaicenavicius, Juozas; Wiklund, Tilo; Grigaitė, Austė; Kalkauskas, Antanas; Vysniauskas, Ignas; Keen, Steve

doi:10.4271/12-04-01-0004

Cited by 11 publications

(4 citation statements)

References 6 publications

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“…With the demands of SOTIF for autonomous vehicles, some SOTIF-related studies on automated driving functions have emerged. Different SOTIF analysis methods, which combined with system analysis theories such as Systems Theory Process Analysis (STPA) and Model-Based Systems Engineering (MBSE), were presented in [37][38][39][40], and these methods were applied to autonomousemergency braking (AEB) systems. Both [41] and [42] studied the SOTIF-related problems of lane-keeping assist (LKA) systems and proposed solutions.…”

Section: Sotif Of the Automated Driving Functionmentioning

confidence: 99%

Layered SOTIF Analysis and 3σ-Criterion-Based Adaptive EKF for Lidar-Based Multi-Sensor Fusion Localization System on Foggy Days

Cao

Luo

et al. 2023

Remote Sensing

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The detection range and accuracy of light detection and ranging (LiDAR) systems are sensitive to variations in fog concentration, leading to the safety of the intended functionality-related (SOTIF-related) problems in the LiDAR-based fusion localization system (LMSFLS). However, due to the uncontrollable weather, it is almost impossible to quantitatively analyze the effects of fog on LMSFLS in a realistic environment. Therefore, in this study, we conduct a layered quantitative SOTIF analysis of the LMSFLS on foggy days using fog simulation. Based on the analysis results, we identify the component-level, system-level, and vehicle-level functional insufficiencies of the LMSFLS, the corresponding quantitative triggering conditions, and the potential SOTIF-related risks. To address the SOTIF-related risks, we propose a functional modification strategy that incorporates visibility recognition and a 3σ-criterion-based variance mismatch degree grading adaptive extended Kalman filter. The visibility of a scenario is recognized to judge whether the measurement information of the LiDAR odometry is disturbed by fog. Moreover, the proposed filter is adopted to fuse the abnormal measurement information of the LiDAR odometry with IMU and GNSS. Simulation results demonstrate that the proposed strategy can inhibit the divergence of the LMSFLS, improve the SOTIF of self-driving cars on foggy days, and accurately recognize the visibility of the scenarios.

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Section: Sotif Of the Automated Driving Functionmentioning

confidence: 99%

Layered SOTIF Analysis and 3σ-Criterion-Based Adaptive EKF for Lidar-Based Multi-Sensor Fusion Localization System on Foggy Days

Cao

Luo

et al. 2023

Remote Sensing

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show abstract

“…The main performance metric used in the test is the Mean Average Precision (MAP) which is said to be the most popular performance measure since 2012. Vaicenavicius et al (2021) highlighted one important functional requirement, i.e., the ability of an AV to stop in a bid to avoid harm or danger. This requirement sums up a couple of requirements.…”

Section: Introductionmentioning

confidence: 99%

“…The identification of functional capabilities for AVs was discussed by Matthaei and Maurer (2015), Vaicenavicius et al (2021) and Badue et al (2021). The functional requirements are needed to make sure that the capabilities are met.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of the Functional Capabilities of an Autonomous Vehicle

Ndlovu,

Ayomoh

2023

Int. j. math. eng. manag. sci.

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The reliability of autonomous vehicles (AVs) is a research domain of high interest, covering a diverse pool of researchers, captains of smart auto industries, government agencies, and technology enthusiasts. The reliability of AVs is not extensively explored in the literature, despite the apprehension due to fatal accidents recorded in the past. Despite being in existence for over a decade, AVs have yet to reach a certified commercial-level deployment. Due to the complexity that comes with the self-operation of an AV, the issue of trustworthiness, which signifies reliability, becomes inevitable. The identification, analysis, and categorization of functional elements using systems engineering conceptual design principles and the linkage of these to the road traffic rules were conducted to address this. Also, the evaluation of the reliability of AVs using various developed vehicles from selected industries was addressed by integrating the traﬀic rules. The analysis of reliability was carried out using life-to-failure data premised on the probability plotting approach. It was found that there is a 99.94% chance that an autonomous vehicle will fail at least one of the traﬀic rules within 20 minutes of driving. Furthermore, the hazard rate of AVs was found to be on the rise, meaning a high indication of accidents.

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“…Autonomous driving has been a hot topic. In terms of traffic safety, Juozas et al [6] proposed a strict modular statistical method to demonstrate the safety or deficiency of autonomous driving. Li and Ban [7] proposed an automated driving algorithm in a 5G network environment.…”

Section: Introductionmentioning

confidence: 99%

Development Status and Hotspot Visualized Analysis of Autonomous Vehicles Based on CiteSpace

Yan

Zeng

Deng

et al. 2022

Journal of Advanced Transportation

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The safety of autonomous driving has been a constant concern, with autonomous driving becoming a research focus in the world today. This study collects the literature in the field of autonomous driving in the Web of Science core data collection from 2005 to 2020. The research status, hot research topics, and the development trend of autonomous driving are reviewed based on CiteSpace from the aspects of number of articles, national collaboration, institutions, scholars, research areas, literature co-citation, keywords, and trends. The results show that the quantitative development of autonomous driving literature has experienced three stages. The research of the United States, China, and Germany is leading in this field. The development of autonomous driving will be in the stage of man-machine driving for a long time. In this study, the progress and trend of visualization in the field of autonomous driving are given, and the future research direction is forecasted, which provides a theoretical basis for the development of autonomous driving. Furthermore, it has reference significance for relevant researchers to understand the research hotspots and future trends in this field.

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Self-Driving Car Safety Quantification via Component-Level Analysis

Cited by 11 publications

References 6 publications

Layered SOTIF Analysis and 3σ-Criterion-Based Adaptive EKF for Lidar-Based Multi-Sensor Fusion Localization System on Foggy Days

Layered SOTIF Analysis and 3σ-Criterion-Based Adaptive EKF for Lidar-Based Multi-Sensor Fusion Localization System on Foggy Days

Reliability Analysis of the Functional Capabilities of an Autonomous Vehicle

Development Status and Hotspot Visualized Analysis of Autonomous Vehicles Based on CiteSpace

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