Comparison of the HAZOP, FMEA, FRAM and STPA Methods for the Hazard Analysis of Automatic Emergency Brake Systems

2021 ◽  
Author(s):  
Liangliang Sun ◽  
Yan-Fu Li ◽  
Enrico Zio
Keyword(s):  
Process Analysis ◽  
Hazard Analysis ◽  
Autonomous Vehicle ◽  
Risk Identification ◽  
The Road ◽  
Emergency Braking ◽  
Analysis Methods ◽  
Potential System ◽  
Comprehensive Comparison ◽  
On The Road

Abstract As autonomous vehicle (AV) intelligence for controllability continues to develop, involving increasingly complex and interconnected systems, the maturity level of AV technology increasingly depends on the systems reliability level, also considering the interactions among them. Hazard analysis is typically used to identify potential system risks and avoid loss of AV system functionality. Conventional hazard analysis methods are commonly used for traditional standalone systems. New hazard analysis methods have been developed that may be more suitable for AV system-of-systems complexity. However, a comprehensive comparison of hazard analysis methods for AV systems is lacking. In this study, the traditional hazard analysis methods, hazard and operability (HAZOP) and failure mode and effects analysis (FMEA), as well as the most recent methods, like functional resonance analysis method (FRAM; Hollnagel, 2004, 2012) and system-theoretic process analysis (STPA; Leveson, 2011), are considered for implementation in the automatic emergency braking system. This system is designed to avoid collisions by utilizing the surrounding sensors to detect objects on the road, warning drivers with alerts about any collision risk, and actuating automatic partial/full braking through calculated adaptive braking deceleration. The objective of this work is to evaluate the methods in terms of their applicability to AV technologies. The advantages of HAZOP, FMEA, FRAM, and STPA, as well as the possibility of combining them to achieve systematic risk identification in practice, are discussed.

scholarly journals An Indoor Vehicle-in-the-Loop Simulation Platform Testing Method for Autonomous Emergency Braking

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ying Gao ◽  
Xiangmo Zhao ◽  
Zhigang Xu ◽  
Jingjun Cheng ◽  
Wenwei Wang
Keyword(s):  
Traffic Safety ◽  
Autonomous Vehicle ◽  
Testing Time ◽  
Simulation Platform ◽  
The Road ◽  
Emergency Braking ◽  
Safety Function ◽  
Fast Solution ◽  
On The Road ◽  
And Performance

Autonomous vehicle (AV) is expected to be the ultimate solution for traffic safety, while autonomous emergency braking (AEB), as a crucial and fundamental active safety function of AV, has excellent potential for reducing fatalities and improving road safety. Although AV has the ability to cope with harsh conditions, it is supposed to be tested fully, systematically, and rigorously before it is officially commercialized. This study developed a novel indoor AV-in-the-loop (AVIL) simulation platform based on Client-Server (C/S) architecture for real full-scale AV testing. The proposed AVIL simulation platform consists of three parts: physical hardware components, software components, and various electrical interfaces that ensure the bidirectional virtual reality (VR) interaction. To validate the functionality and performance of the platform, this paper then adopted the Udwadia–Kalaba (U-K) approach to build the AEB system based on a typical driving situation due to the explicitness and simplicity of the U-K approach. Further, a group of real road-based experiments and AVIL-based experiments were conducted. The experimental results showed that the testing data obtained from the proposed AVIL platform have a high similarity to those of the real road tests, which means that the proposed AVIL platform is capable of simulating the AV running condition when it performs linear emergency braking on the road, thus confirming the feasibility and effectiveness of the AVIL platform for AV AEB testing. Simultaneously, the testing time and repeatability of the latter performed better. The findings of this study provide a new safe, effective, and fast solution to AV testing, and the practicability of this method has been verified.

scholarly journals New Operating Strategies for an On-the-Road Modular, Electric and Autonomous Vehicle Concept in Urban Transportation

2019 ◽  
Vol 10 (4) ◽  
pp. 91
Author(s):  
Christian Ulrich ◽  
Horst E. Friedrich ◽  
Jürgen Weimer ◽  
Stephan A. Schmid
Keyword(s):  
Business Model ◽  
Urban Areas ◽  
Business Models ◽  
Autonomous Vehicle ◽  
Vehicle Concept ◽  
Drive Unit ◽  
The Road ◽  
Business Model Canvas ◽  
Operating Strategies ◽  
On The Road

Today commercial transport in urban areas faces major challenges. These include making optimal use of limited space, avoiding empty trips, meeting driver shortages as well as reducing costs and emissions such as CO2, particulate matter and noise. The mutual acceleration and reinforcement of technological trends such as electrification, digitization and automation may enable new vehicle and mobility concepts that can meet these challenges. One possible vehicle concept is presented in this article. It is based on on-the-road modularization, i.e., a vehicle that can change different transport capsules during operation. The vehicle is divided into an electrically propelled autonomous drive unit and a transport unit. Standardized interfaces between these units enable the easy design of capsules for different uses, while the drive unit can be used universally. Business models and operating strategies that allow optimal use of this vehicle concept are discussed in depth in the article. First, the current situation is analyzed followed by a detailed description of an exemplary business model using a business model canvas. The operating strategies and logistics concepts are illustrated and compared with conventional concepts.

scholarly journals Obstacle Detection and Safely Navigate the Autonomous Vehicle from Unexpected Obstacles on the Driving Lane

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4719
Author(s):  
Malik Haris ◽  
Jin Hou
Keyword(s):  
Deep Learning ◽  
Autonomous Vehicle ◽  
Research Area ◽  
Visual Navigation ◽  
Obstacle Detection ◽  
The Road ◽  
Markov Random ◽  
Active Research ◽  
On The Road ◽  
Active Research Area

Nowadays, autonomous vehicle is an active research area, especially after the emergence of machine vision tasks with deep learning. In such a visual navigation system for autonomous vehicle, the controller captures images and predicts information so that the autonomous vehicle can safely navigate. In this paper, we first introduced small and medium-sized obstacles that were intentionally or unintentionally left on the road, which can pose hazards for both autonomous and human driving situations. Then, we discuss Markov random field (MRF) model by fusing three potentials (gradient potential, curvature prior potential, and depth variance potential) to segment the obstacles and non-obstacles into the hazardous environment. Since the segment of obstacles is done by MRF model, we can predict the information to safely navigate the autonomous vehicle form hazardous environment on the roadway by DNN model. We found that our proposed method can segment the obstacles accuracy from the blended background road and improve the navigation skills of the autonomous vehicle.

scholarly journals On the Road: Route Proposal from Radar Self-Supervised by Fuzzy LiDAR Traversability

AI ◽  
2020 ◽  
Vol 1 (4) ◽  
pp. 558-585
Author(s):  
Michael Broome ◽  
Matthew Gadd ◽  
Daniele De Martini ◽  
Paul Newman
Keyword(s):  
Autonomous Vehicle ◽  
Optimal Path ◽  
Extreme Environments ◽  
Point Clouds ◽  
Learning Approaches ◽  
Weak Supervision ◽  
The Road ◽  
Optimal Path Planning ◽  
Rule Set ◽  
On The Road

This is motivated by a requirement for robust, autonomy-enabling scene understanding in unknown environments. In the method proposed in this paper, discriminative machine-learning approaches are applied to infer traversability and predict routes from Frequency-Modulated Contunuous-Wave (FMCV) radar frames. Firstly, using geometric features extracted from LiDAR point clouds as inputs to a fuzzy-logic rule set, traversability pseudo-labels are assigned to radar frames from which weak supervision is applied to learn traversability from radar. Secondly, routes through the scanned environment can be predicted after they are learned from the odometry traces arising from traversals demonstrated by the autonomous vehicle (AV). In conjunction, therefore, a model pretrained for traversability prediction is used to enhance the performance of the route proposal architecture. Experiments are conducted on the most extensive radar-focused urban autonomy dataset available to the community. Our key finding is that joint learning of traversability and demonstrated routes lends itself best to a model which understands where the vehicle should feasibly drive. We show that the traversability characteristics can be recovered satisfactorily, so that this recovered representation can be used in optimal path planning, and that an end-to-end formulation including both traversability feature extraction and routes learned by expert demonstration recovers smooth, drivable paths that are comprehensive in their coverage of the underlying road network. We conclude that the proposed system will find use in enabling mapless vehicle autonomy in extreme environments.

scholarly journals STABILITY AND VIBRATIONS OF THE ELECTRONIC CLOSED SYSTEM STABILIZING THE COURSE OF A CAR WITH A TANK

2021 ◽  
pp. 44-63
Author(s):  
Yevgen Aleksandrov ◽  
Tetyana Aleksandrova ◽  
Alexander Grigoriev ◽  
Yaroslav Morhun
Keyword(s):  
Free Surface ◽  
Low Frequency ◽  
Control Valve ◽  
Maximum Speed ◽  
Liquid Lead ◽  
The Road ◽  
Emergency Braking ◽  
Directional Stability ◽  
On The Road ◽  
Discrete Mathematical Model

To describe the disturbed movement of a car with a tank, a discrete mathematical model has been compiled, which allows one to take into account the oscillations of the free surface of the liquid and determine their effect on the directional stability of the car during uniform movement and during emergency braking. Linearization is carried out and an equation is obtained for the natural frequencies of oscillations of the electrohydromechanical system, which combines dynamic changes in the parameters of the movement of a car with a tank, partial layers of liquid in a tank and the operation of an electromagnetic drive of the control valve and an electronic PID controller for a two-circuit scheme to ensure directional stability. It is shown that low-frequency oscillations of the free surface of liquid lead to a significant reduction in the stability region, which indicates the need to take such oscillations into account when solving problems of analysis and synthesis of this system. It has been established that for a car with a tank, where low-frequency transverse oscillations of the liquid occur, which are accompanied by redistribution of mass and disturb the movement, an increase in the speed unambiguously leads to a deterioration in road-holding ability. This made it possible to exclude the speed from the variable parameters and significantly simplify the task. It was found that the liquid level in the tank, taking into account its connection with the maximum speed, has an ambiguous effect on the road-holding ability of the vehicle, and it is unacceptable to limit the research to calculations for 50 % of the load. Instead of this traditional simplification, it is necessary to find a line that bends from above those stability boundaries that correspond to many liquid levels from the entire range of their variation. It is shown that the dynamics of emergency braking weakly depends on the viscosity of the liquid in the tank, but with long-term continuous operation of the brake control system, self-oscillations appear in it. A method for tuning the parameters of an electronic regulator for low-amplitude self-oscillations is proposed.

scholarly journals Research on Virtual Test of Automobile Automatic Emergency Braking System on Ice-Snow Road

2021 ◽  
Vol 261 ◽  
pp. 02065
Author(s):  
Xianchao Zhu ◽  
Sheng Chang ◽  
Bingtao Li ◽  
Hualei Lu
Keyword(s):  
Weather Conditions ◽  
Simulation Method ◽  
Time To Collision ◽  
The Road ◽  
Injury Reduction ◽  
Emergency Braking ◽  
Virtual Test ◽  
Braking Distance ◽  
On The Road ◽  
Basic Characteristics

In view of the severe weather conditions in cold regions, the basic characteristics and braking distance of ice snow covered pavement are analyzed. This paper uses the PreScan/CarSim/Simulink software co-simulation method to test the automatic emergency braking (AEB) system on ice-snow roads. Through the appropriate adjustment of the time to collision (TTC) threshold, the car makes automatic emergency braking on the road with low friction coefficient system can achieve the effect of collision avoidance and injury reduction.

Self-Driving Cars

2020 ◽  
pp. 490-507
Author(s):  
Pooja Jha ◽  
K. Sridhar Patnaik
Keyword(s):  
Traffic Safety ◽  
Autonomous Vehicle ◽  
Technological Advancement ◽  
Social Environments ◽  
Highway Traffic ◽  
National Highway Traffic Safety ◽  
Human Errors ◽  
The Road ◽  
On The Road ◽  
Self Driving Cars

Human errors are the main cause of vehicle crashes. Self-driving cars bear the promise to significantly reduce accidents by taking the human factor out of the equation, while in parallel monitor the surroundings, detect and react immediately to potentially dangerous situations and driving behaviors. Artificial intelligence tool trains the computers to do things like detect lane lines and identify cyclists by showing them millions of examples of the subject at hand. The chapter in this book discusses the technological advancement in transportation. It also covers the autonomy used according to The National Highway Traffic Safety Administration (NHTSA). The functional architecture of self-driving cars is further discussed. The chapter also talks about two algorithms for detection of lanes as well as detection of vehicles on the road for self-driving cars. Next, the ethical discussions surrounding the autonomous vehicle involving stakeholders, technologies, social environments, and costs vs. quality have been discussed.

Self-Driving Robotic Cars

2021 ◽  
pp. 599-631
Author(s):  
Jelena L. Pisarov ◽  
Gyula Mester
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicle ◽  
Closed Circuit ◽  
Small Scale ◽  
Traffic Patterns ◽  
Complex Environments ◽  
The Road ◽  
Traffic Jams ◽  
Simulation Techniques ◽  
On The Road

Even the behavior of a single driver can have a dramatic impact on hundreds of cars, making it more difficult to manage traffic. While the attempts to analyze and correct the traffic patterns that lead to congestion began as early in the 1930s, it wasn't until recently that scientists developed simulation techniques and advanced algorithms to create more realistic visualizations of traffic flow. In experiments conducted by Alexandre Bayen and the Liao-Cho, which included several dozen cars in a small-scale closed circuit, a single autonomous vehicle could eliminate traffic jams by moderating the speed of every car on the road. In larger simulations, the research showed that once their number rises to 5-10% of all cars in the traffic, they can manage localized traffic even in complex environments, such as merging multiple lanes of traffic into two or navigating extremely busy sections.

Self-Driving Robotic Cars

2022 ◽  
pp. 969-1001
Author(s):  
Jelena L. Pisarov ◽  
Gyula Mester
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicle ◽  
Closed Circuit ◽  
Small Scale ◽  
Traffic Patterns ◽  
Complex Environments ◽  
The Road ◽  
Traffic Jams ◽  
Simulation Techniques ◽  
On The Road

Even the behavior of a single driver can have a dramatic impact on hundreds of cars, making it more difficult to manage traffic. While the attempts to analyze and correct the traffic patterns that lead to congestion began as early in the 1930s, it wasn't until recently that scientists developed simulation techniques and advanced algorithms to create more realistic visualizations of traffic flow. In experiments conducted by Alexandre Bayen and the Liao-Cho, which included several dozen cars in a small-scale closed circuit, a single autonomous vehicle could eliminate traffic jams by moderating the speed of every car on the road. In larger simulations, the research showed that once their number rises to 5-10% of all cars in the traffic, they can manage localized traffic even in complex environments, such as merging multiple lanes of traffic into two or navigating extremely busy sections.

Construction of Control Algorithm for an Autonomous Vehicle

2001 ◽  
Vol 13 (4) ◽  
pp. 387-394
Author(s):  
Hyung-Eun Im ◽  
◽  
Ichiro Kageyama ◽  
Yoshiyuki Nozaki
Keyword(s):  
Control Algorithm ◽  
Prediction Models ◽  
Autonomous Vehicle ◽  
Risk Level ◽  
Minimum Risk ◽  
Control Motion ◽  
Risk Elements ◽  
The Road ◽  
On The Road ◽  
Risk Potential

In this study, a control algorithm of an autonomous vehicle is proposed on the basis of risk level to simulate control motion of a real driver. The normal traffic situation can be expressed by risk level. The risk level is affected by several risk elements: roadside edges, curves, the other vehicles, obstacles, and so on. Each risk element is represented by an exponential function. The risk elements make risk potential field on the road. It is assumed that the desirable course to follow is determined as the point of minimum risk potential in the cross section of the road. Tree prediction models are examined to predict the future position of vehicle. The change of preview time is considered on the curved road. A lateral and longitudinal control algorithm with the prediction model proposed in this study shows similar control motion to that of a real driver.

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