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Playlist: Software Safety for Vehicle Automation Table of Contents

Software Safety for Vehicle Automation
01 Intro: Software Safety for Vehicle Automation
02 Overview of ADS Safe Software needs
03 ADS Technology is Sold Based on Safety
04 Sensing to Model of External World to Vehicle Control
05 Machine Learning and Deep Neural Networks
06 The Race To Autonomy Is Going Slowly
07 Integration and Validation Issues are Urgent
08 The True Winner Must Be Safe
09 Automation Changes the Needs for Safety

Software Safety for Vehicle Automation (Part 2 – Validating Machine Learning-Based Systems)
10 Validating Machine Learning Based Systems Title
11 Why Not Use a Traditional Driver Test?
12 Machine Learning Challenges
13 Traditional Validation vs Machine Learning
14 Early Testing Public Road Testing
15 Validation via Brute Force Road Testing
16 Closed Course Testing
17 Simulation
18 Scenario Based Simulation
19 Simulation Components
20 Simulation Validity
21 What Does It Mean for a Test to Pass
22 Changing Validation Approache

Software Safety for Vehicle Automation (Part 3 Edge Cases)
23 SOTIF and Edge Cases Title
24 Identifying and Mitigating Hazards
25 Six Sigma Is Not Enough For Safety
26 It Is All About the Edge Cases
27 Why Edge Cases Matter
28 The Real World and Heavy Tail Distributions
29 From Driver Assist to Automation
30 ADS Must Handle Unusual Situations
31 Stop Sign for Burgers
32 Human Intuition Is Not Enough
33 Changing Relevance of Perception Defects

Software Safety for Vehicle Automation (Part 4 – Removing the Driver)
34 Implications of Removing the Human Driver
35 Toyota Uncommanded Acceleration
36 Tesla Crashes Blamed On Human Drivers
37 US Government Blames Drivers for Unintended Acceleration
38 Can Humans Safely Supervise Autonomy?
39 The 94 Percent Human Error False Narrative
40 Humans Are Amazing Fault Mitigators
41 Automotive Software Quality Issues
42 Automotive Software Recall Defects
43 Example Required ADS Fault Handling
44 Controllability Without a Human Driver
45 No Human Driver To Blame
46 Vehicle Automation Modes Overview
47 Operations and Human Interactions
48 Lifecycle Issues
49 Summary of Changing Role of Human Driver

Software Safety for Vehicle Automation (Part 5 – Safety Architectures)
50 Safety Architectures Title
51 Safety Envelope Approach to ML Deployment
52 Architecting A Safety Envelope System
53 Shuttle Emergency Stop Safety
54 Physics-Based Checker Rules
55 Uncertainty In The World Model
56 Validating An Autonomous Vehicle Pipeline
57 Importance of Behavior Prediction
58 From Fail Silent ADAS to Fail Operational ADS
59 BMW ADS Redundancy Concept
60 Redundancy and ASIL B(D) Decomposition
61 Move To Centralized Architecture
62 Changing Computing Architecture

Software Safety for Vehicle Automation (Part 6 – Safe Enough)
63 How Safe Is Safe Enough Title
64 Public Lack of Trust in Vehicle Automation technology
65 Is Supervised Autopilot Actually Safer
66 People Want Automated Vehicles To Be Much Safer
67 Current Regulatory Strategy for Automated Vehicles
68 How Safe Is Safe Enough
69 Which Driver Are We Better Than for Automated Driving?
70 ODD Affects Safe Enough Value
71 Approaches To Measuring Safe
72 Standards Based Automated Vehicle Engineering Approach
73 Changing Safety Expectations Standards and Regulation

Software Safety for Vehicle Automation (Part 7 – Building Trust)
74 Building Trust Title
75 Stakeholder Trust
76 Hypothetical Validation Campaign Pyramid
77 How Much Do You Trust Validation?
78 Engineering Rigor
79 Field Engineering Feedback
80 Safety Culture
81 UATG and Safety Culture
82 Positive Trust Balance Overview
83 Building Trust with Stakeholders

Software Safety for Vehicle Automation (Part 8 — Getting To Deployed+Safe)
84 System and Safety Engineering Title
85 System Engineering
86 Computer Based System Safety Engineering
87 Staffing Profile for Automotive Software
88 Technical Safety Challenges
89 Organizational Safety Challenges
90 Getting To Deployed and Safe
91 End Title