Centimeter-Accurate GNSS Corrections and Integrity Information via ISO 26262 Certified Modules for Autonomous Driving Applications

2019 ◽  
Author(s):  
Philip Kreikenbohm ◽  
Adrian Kipka ◽  
Markus Brandl ◽  
Herbert Landau ◽  
Fabian Pastor ◽  
...  
Keyword(s):  
Autonomous Driving ◽  
Iso 26262

scholarly journals Analysis of Hazards for Autonomous Driving

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Edward Schwalb
Keyword(s):  
Hazard Analysis ◽  
Autonomous Driving ◽  
Hazard Identification ◽  
Safety Engineering ◽  
Functional Safety ◽  
Safety Standard ◽  
Iso 26262 ◽  
The Core ◽  
Probabilistic Hazard Analysis ◽  
Definition Of

Abstract Hazard analysis is the core of numerous approaches to safety engineering, including the functional safety standard ISO-26262 (FuSa) and Safety of the Intended Function (SOTIF) ISO/PAS 21448. We focus on addressing the immense challenge associated with the scope of training and testing for rare hazard for autonomous drivers, leading to the need to train and test on the equivalent of >108 naturalistic miles. We show how risk can be estimated and bounded using the probabilistic hazard analysis. We illustrate the definition of hazards using well-established tests for hazard identification. We introduce a dynamic hazard approach, whereby autonomous drivers continuously monitor for potential and developing hazard, and estimate their time to materialization (TTM). We describe systematic TTM modeling of the various hazard types, including environment-specific perception limitations. Finally, we show how to enable accelerated development and testing by training a neural network sampler to generate scenarios in which the frequency of rare hazards is increased by orders of magnitude.

scholarly journals Safety Design Strategies in Highly Autonomous Drive Level 2 – Lateral Control Decomposition Concept

2021 ◽  
Vol 27 (8) ◽  
pp. 811-829
Author(s):  
Svatopluk Stolfa ◽  
Jakub Stolfa ◽  
Petr Simonik ◽  
Tomas Mrovec ◽  
Tomas Harach
Keyword(s):  
Experimental Study ◽  
Autonomous Driving ◽  
Design Strategies ◽  
Lateral Control ◽  
Safe Driving ◽  
Iso 26262 ◽  
Driving Mode ◽  
Safe State ◽  
Hazard And Risk ◽  
Fusion Concept

The paper is based on an experimental study at VSB TUO Ostrava with a DEMOCAR vehicle that simulates a real car with sensor fusion concept and a vehicle gateway to send and coordinate commands to ECUs to realize and manage autonomous driving. In this experimental study of autonomous driving vehicles control, a HARA (Hazard and Risk Analysis, ISO 26262:2018) has been done on vehicle level and strategies have been defined and implemented to manage safety situations where the car lateral control shall be hand over to a driver when in HAD 2 mode. The issue is that the switching to safe state shall not be done immediately but the vehicle has to stay in safe driving mode – fail-operational up to 4 seconds until a driver can take over. The UECE and other relevant studies show that it can take up to 6 seconds if driver/operator is not in the flow (HAD 3) and up to the 2 seconds when driver is in the flow (HAD 1). The paper makes assumptions and proposals about vehicle lateral control strategy to ensure the smooth take- over of the car by driver and its impact on control software development architectures.

A Lightweight and Multi-OS Compatible Middleware Designed for Autonomous Driving

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Kun Jiang ◽  
Yunlong Wang ◽  
Shengjie Kou ◽  
Diange Yang
Keyword(s):  
Autonomous Driving

Trend of an Autonomous Driving Control Vehicle

2013 ◽  
Vol 133 (9) ◽  
pp. 595-598
Author(s):  
Kenji SUZUKI ◽  
Hisaaki ISHIDA ◽  
Hirofumi INOSE ◽  
Rui KOBAYASHI
Keyword(s):  
Autonomous Driving

Imaging through Scattering Media with a Learning Based Prior

2020 ◽  
Vol 2020 (14) ◽  
pp. 306-1-306-6
Author(s):  
Florian Schiffers ◽  
Lionel Fiske ◽  
Pablo Ruiz ◽  
Aggelos K. Katsaggelos ◽  
Oliver Cossairt
Keyword(s):  
Optimization Problem ◽  
Autonomous Driving ◽  
Scattering Media ◽  
Photon Scattering ◽  
Point Spread ◽  
Spread Function ◽  
Radiative Transport Equation ◽  
Spatio Temporal ◽  
Transient Imaging

Imaging through scattering media finds applications in diverse fields from biomedicine to autonomous driving. However, interpreting the resulting images is difficult due to blur caused by the scattering of photons within the medium. Transient information, captured with fast temporal sensors, can be used to significantly improve the quality of images acquired in scattering conditions. Photon scattering, within a highly scattering media, is well modeled by the diffusion approximation of the Radiative Transport Equation (RTE). Its solution is easily derived which can be interpreted as a Spatio-Temporal Point Spread Function (STPSF). In this paper, we first discuss the properties of the ST-PSF and subsequently use this knowledge to simulate transient imaging through highly scattering media. We then propose a framework to invert the forward model, which assumes Poisson noise, to recover a noise-free, unblurred image by solving an optimization problem.

F1_Tenth_Course_Report_Group_C

2018 ◽  
Author(s):  
Yi Chen ◽  
Sagar Manglani ◽  
Roberto Merco ◽  
Drew Bolduc
Keyword(s):  
Operating System ◽  
Autonomous Driving ◽  
Software Tools ◽  
Simulation Environment ◽  
Robot Operating System ◽  
Available Information

In this paper, we discuss several of major robot/vehicle platforms available and demonstrate the implementation of autonomous techniques on one such platform, the F1/10. Robot Operating System was chosen for its existing collection of software tools, libraries, and simulation environment. We build on the available information for the F1/10 vehicle and illustrate key tools that will help achieve properly functioning hardware. We provide methods to build algorithms and give examples of deploying these algorithms to complete autonomous driving tasks and build 2D maps using SLAM. Finally, we discuss the results of our findings and how they can be improved.

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