Multi-Agent Safety / Juan R. Pimentel.

Format:

Book

Author/Creator:

Pimentel, Juan R., author.

Series:

Automated vehicle safety series.

Automated vehicle safety series

Language:

English

Subjects (All):

Automated vehicles.

Physical Description:

1 online resource (208 pages).

Edition:

1st ed.

Place of Publication:

Pennsylvania : SAE International, 2019.

Summary:

Safety has been ranked as the number one concern for the acceptance and adoption of automated vehicles since safety has driven some of the most complex requirements in the development of self-driving vehicles. Recent fatal accidents involving self-driving vehicles have uncovered issues in the way some automated vehicle companies approach the design, testing, verification, and validation of their products. Traditionally, automotive safety follows functional safety concepts as detailed in the standard ISO 26262. However, automated driving safety goes beyond this standard and includes other safety concepts such as safety of the intended functionality (SOTIF) and multi-agent safety. Multi-Agent Safety addresses the concept of safety for self-driving vehicles through the inclusion of 10 recent and highly relevent SAE technical papers. Topics that these papers feature include vehicle interaction with other vehicles, pedestrians, bicyclists, and other road objects. As the second title in a series on automated vehicle safety, each will contain introductory content by the Editor with 10 SAE technical papers specifically chosen to illuminate the specific safety topic of that book.

Contents:

Cover

Table of Contents

Introduction

CHAPTER 1 Lane-Keeping Behavior and Cognitive Load with Use of Lane Departure Warning

Methods

Participants

Materials

Procedure

Data Processing &amp

Analysis

Lane Keeping

Cognitive Load

Results

Cognitive Task Performance

Discussion

Contact Information

References

CHAPTER 2 Study on Test Scenarios of Environment Perception System under Rear-End Collision Risk

Materials and Processing

Extraction of Real Naturalistic Traffic Rear-End Risk Scenarios

Study of Dangerous Level of Risk Scenarios

Environment Perception Elements (EPEs) Considered in Analysis

Probability Distribution of EPEs

Weather and Light Conditions

Road Features and Road Markings

Traffic Signs

Traffic Lights

Other Vehicles, Pedal Cyclists and Pedestrians

Others

Study of the Correlation between EPEs and Dangerous Level of Risk Scenarios

Generation of Test Scenarios for EPS

Conclusions

Acknowledgments

CHAPTER 3 Motion Planning of Vehicle Obstacle Avoidance in Complex Traffic Scenarios

System Architecture

General Driving Risk Model

Collision Risk Model

Real-Time Collision Detection

Collision Risk

Non-Collision Risk Model

Violating Traffic Regulations Risk

Motion Planning and Control

Minimum Risk Search Algorithm

Experimental Results and Discussions

Experimental Scenarios

Results and Analysis

Abbreviations

CHAPTER 4 Driver Behavior While Operating Partially Automated Systems: Tesla Autopilot Case Study

Methodology

Study Design

Journaling

Observation

Interview.

Procedure

Qualitative Data

Autopilot Understanding and Usage Situations

System Expectations

Initial Exposure

Effect of Autopilot Accident on Driver Behavior

Behavior Analysis

Eye Glance Analysis

Hands-On/Off Steering Wheel

On-Highway/Off-Highway Autopilot Usage

Tasks Performed While Autopilot Is Active

Summary/Conclusions

Study Limitations

CHAPTER 5 Forward Collision Warning: Clues to Optimal Timing of Advisory Warnings

Sample

Procedure and Design

Measures and Statistical Analyses

Assessments of Functioning

Driving Performance Measures

Definitions/Abbreviations

CHAPTER 6 Situation Awareness, Scenarios, and Secondary Tasks: Measuring Driver Performance and Safety Margins in Highly Automated Vehicles

Types and Levels of Automation

Failure Modes of Driver-Automation Interaction

Driving Simulator Protocol

Latent Hazards to Assess Situation Awareness

Secondary Task Engagement

Measures of Driver Performance and Safety Margins

Conclusion

CHAPTER 7 Frontal Collisions-What Are the Limitations of Future Forward-Looking Safety Systems?

Limitations of Current and Future Pre-crash Systems

One Dimensional Example

Moving to Two Dimensions

Limiting Trajectories and Sampling in between

What Are the Problems?

What Can Be Done

CHAPTER 8 Hardware-in-the-Loop (HIL) Implementation and Validation of SAE Level 2 Autonomous Vehicle with Subsystem Fault Tolerant Fallback Performance for Takeover Scenarios

Introduction.

Hardware-in-the-Loop (HIL) Simulation

HIL Hardware

Engine Control Module (ECM)

Hybrid Control Module (HCU)

Gear Shift Module (GSM)

Transmission Range Control Module (TRCM)

Gateway Module (GWM)

Microautobox (MABX)

HIL Modeling

Automated Longitudinal Control

Automated Lateral Control

HIL SAE Level 2 Automation

Simulations and Test Results

Automated Longitudinal Control Simulations &amp

Test Results

Automated Lateral Control Simulations &amp

Subsystem Faults and Fallback Performance Simulation &amp

CHAPTER 9 Vehicle-GIS Assistant Driving System for Real-time Safety Speed Warning on Mountain Roads

1. Introduction

2. System Description

2.1 System Fundamentals

2.2 The Basic Structure of the System

2.3 Basic Process of the System

3. Modeling and Constraints

3.1 Designed Highway Speed Limit in Mountainous Area

3.1.1 Design Speed of Downhill Section in Mountainous Area

3.1.2 Highway Speed Limit

3.2 Vehicle Dynamics Modeling of Commercial Vehicles on Downhill

3.2.1 Ramp Brake Model

3.2.2 Weight Model

3.3 Brake Temperature Rise Model

3.3.1 Energy Analysis of Downhill Section

3.3.2 Analysis of Brake Temperature Rise

4. Case Studies and Simulations

4.1 The Main Parameters of the Target Vehicle Model

4.2 Safety Speed Simulation of Downhill Section

4.3 Influence of Vehicle Weight on Slope Top Safety Speed

4.4 Brake Temperature Rise Comparison

5. Conclusion

CHAPTER 10 Overtaking or Merging? Eco-Routing Decision and Speed Trajectory with Full Terrain Information

Vehicle Dynamic Model

Optimization Constraints

Internal Constraints

External Constraints

Platoons Initial State.

Overtaking Safety

Motion Planning Algorithm

Discrete Dynamic Programming (DP)

Introduction to DP

Forward Discrete DP

Cost Function

Model Predictive Control (MPC)and Linear Quadratic Regulator (LQR)

Linear Quadratic Regulator (LQR)

Model Predictive Control (MPC)

Simulation Results

Unconstrained Speed Trajectories vs. Uniform Motion

Constrained vs. MPC and LQR

One Preceding Platoon

Two Preceding Platoons

Three Preceding Platoons

Sensitivity Analysis

Influence of Initial Speed on Optimal Trajectories

Epilogue.

Notes:

Description based on online resource; title from PDF title page (SAE International, viewed March 15, 2023).

Description based on publisher supplied metadata and other sources.

ISBN:

9781523140374

1523140372

9780768002256

0768002257

9780768002232

0768002230

OCLC:

1302007365