Toward Risk-Informed Operation of Autonomous Vehicles to Increase Resilience in Unknown and Dangerous Environments

2016 ◽  
Author(s):  
Zachary Mimlitz ◽  
Adam Short ◽  
Douglas L. Van Bossuyt
Keyword(s):  
Autonomous Vehicles ◽  
Health Management ◽  
Space Exploration ◽  
Autonomous Systems ◽  
Risk Attitude ◽  
Local Area ◽  
Behavioral Risk ◽  
Risk Averse ◽  
Critical System ◽  
Scientific Mission

Operation of autonomous and semi-autonomous systems in hostile and expensive-to-access environments requires great care and a risk-informed operating mentality to protect critical system assets. Space exploration missions, such as the Mars Exploration Rover systems Opportunity and Curiosity, are very costly and difficult to replace. These systems are operated in a very risk-averse manner to preserve the functionality of the systems. By constraining system operations to risk-averse activities, scientific mission goals cannot be achieved if they are deemed too risky. We present a quantifiable method that increases the lifetime efficiency of obtaining scientific goals via the implementation of the Goal-Oriented, Risk Attitude-Driven Reward Optimization (GORADRO) method and a case study conducted with simulated testing of the method. GORADRO relies upon local area information obtained by the system during operations and internal Prognostics and Health Management (PHM) information to determine system health and potential localized risks such as areas where a system may become trapped (e.g.: sand pits, overhangs, overly steep slopes, etc.) while attempting to access scientific mission objectives through using an adaptable operating risk attitude. The results of our simulations and hardware validation using GORADRO show a large increase in the lifetime performance of autonomous rovers in a variety of environments, terrains, and situations given a sufficiently tuned set of risk attitude parameters. Through designing a GORADRO behavioral risk attitude set of parameters, it is possible to increase system resilience in unknown and dangerous environments encountered in space exploration and other similarly hazardous environments.

scholarly journals R2U2: Tool Overview

10.29007/5pch ◽  
2018 ◽  
Author(s):  
Kristin Yvonne Rozier ◽  
Johann Schumann
Keyword(s):  
Health Management ◽  
Autonomous Systems ◽  
Building Blocks ◽  
Unmanned Aerial Systems ◽  
Critical System ◽  
Safety Critical System ◽  
Target Architecture ◽  
Wide Range ◽  
Aerial Systems ◽  
Temporal Formula

R2U2 (Realizable, Responsive, Unobtrusive Unit) is an extensible framework for runtime System Health Management (SHM) of cyber-physical systems. R2U2 can be run in hardware (e.g., FPGAs), or software; can monitor hardware, software, or a combination of the two; and can analyze a range of different types of system requirements during runtime. An R2U2 requirement is specified utilizing a hierarchical combination of building blocks: temporal formula runtime observers (in LTL or MTL), Bayesian networks, sensor filters, and Boolean testers. Importantly, the framework is extensible; it is designed to enable definitions of new building blocks in combination with the core structure. Originally deployed on Unmanned Aerial Systems (UAS), R2U2 is designed to run on a wide range of embedded platforms, from autonomous systems like rovers, satellites, and robots, to human-assistive ground systems and cockpits.R2U2 is named after the requirements it satisfies; while the exact requirements vary by platform and mission, the ability to formally reason about Realizability, Responsiveness, and Unobtrusiveness is necessary for flight certifiability, safety-critical system assurance, and achievement of technology readiness levels for target systems. Realizability ensures that R2U2 is sufficiently expressive to encapsulate meaningful runtime requirements while maintaining adaptability to run on different platforms, transition be- tween different mission stages, and update quickly between missions. Responsiveness entails continuously monitoring the system under test, real-time reasoning, reporting intermediate status, and as-early-as-possible requirements evaluations. Unobtrusiveness ensures compliance with the crucial properties of the target architecture: functionality, certifiability, timing, tolerances, cost, or other constraints.

Risk Attitude and Corporate Investment under Output Market Uncertainty: Evidence from The Mekong River Delta, Vietnam

2016 ◽  
pp. 59-70
Author(s):  
Ninh Le Khuong ◽  
Nghiem Le Tan ◽  
Tho Huynh Huu
Keyword(s):  
Negative Relationship ◽  
Risk Attitude ◽  
Business Strategies ◽  
Risk Averse ◽  
Market Uncertainty ◽  
Firm Investment ◽  
Output Market ◽  
The Impact ◽  
The Relationship

This paper aims to detect the impact of firm managers’ risk attitude on the relationship between the degree of output market uncertainty and firm investment. The findings show that there is a negative relationship between these two aspects for risk-averse managers while there is a positive relationship for risk-loving ones, since they have different utility functions. Based on the findings, this paper proposes recommendations for firm managers to take into account when making investment decisions and long-term business strategies as well.

scholarly journals OPTIMAL OUTCOME SHARING WITH A CONSORTIUM OF CONTRACTORS

2015 ◽  
Vol 22 (5) ◽  
pp. 655-665 ◽  
Author(s):  
S. Mahdi HOSSEINIAN ◽  
David G. CARMICHAEL
Keyword(s):  
Risk Aversion ◽  
Risk Attitude ◽  
Risk Averse ◽  
Optimal Outcome ◽  
Original Solution ◽  
Project Outcome ◽  
Risk Neutral ◽  
Current Practices

Where a consortium of contractors is involved, there exist no guidelines in the literature on what the outcome sharing arrangement should be. The paper addresses this shortfall. It derives the optimal outcome sharing arrangement for risk-neutral and risk-averse contractors within the consortium, and between the consortium and a risk-neutral owner. Practitioners were engaged in a designed exercise in order to validate the paper’s propositions. The paper demonstrates that, at the optimum: the proportion of outcome sharing among contractors with the same risk-attitude should reflect the levels of their contributions; the proportion of outcome sharing among contractors with the same level of contribu­tion should be lower for contractors with higher levels of risk aversion; a consortium of risk-neutral contractors should receive or bear any favourable or adverse project outcome respectively; and the proportion of outcome sharing to a con­sortium of risk-averse contractors should reduce, and the fixed component of the consortium fee should increase, when the contractors become more risk-averse or the level of the project outcome uncertainty increases. The paper proposes an original solution to the optimal sharing problem in contracts with a consortium of contractors, thereby contributing to current practices in contracts management.

Cutoff Threshold Decisions for Classification Algorithms with Risk Aversion

2021 ◽  
Author(s):  
Andrea C. Hupman
Keyword(s):  
Risk Aversion ◽  
Risk Attitude ◽  
Classification Algorithm ◽  
Classification Algorithms ◽  
Risk Averse ◽  
Optimal Cutoff ◽  
Data Set ◽  
Risk Neutral ◽  
Bayes Algorithm ◽  
Cutoff Threshold

Classification algorithms predict the class membership of an unknown record. Methods such as logistic regression or the naïve Bayes algorithm produce a score related to the likelihood that a record belongs to a particular class. A cutoff threshold is then defined to delineate the prediction of one class over another. This paper derives analytic results for the selection of an optimal cutoff threshold for a classification algorithm that is used to inform a two-action decision in the cases of risk aversion and risk neutrality. The results provide insight to how the optimal cutoff thresholds relate to the associated costs and the sensitivity and specificity of the algorithm for both the risk neutral and risk averse decision makers. The optimal risk averse threshold is not reliably above or below the optimal risk neutral threshold, but the relation depends on the parameters of a particular application. The results further show the risk averse optimal threshold is insensitive to the size of the data set or the magnitude of the costs, but instead is sensitive to the proportion of positive records in the data and the ratio of costs. Numeric examples and sensitivity analysis derive further insight. Results show the percent value gap from a misspecified risk attitude increases as the specificity of the classification algorithm decreases.

Pedestrians, Autonomous Vehicles, and Cities

2016 ◽  
Vol 38 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Adam Millard-Ball
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Neighborhoods ◽  
Urban Traffic ◽  
Risk Averse ◽  
Strategic Interactions ◽  
Road Users ◽  
Self Driving Cars ◽  
Time Autonomous

Autonomous vehicles, popularly known as self-driving cars, have the potential to transform travel behavior. However, existing analyses have ignored strategic interactions with other road users. In this article, I use game theory to analyze the interactions between pedestrians and autonomous vehicles, with a focus on yielding at crosswalks. Because autonomous vehicles will be risk-averse, the model suggests that pedestrians will be able to behave with impunity, and autonomous vehicles may facilitate a shift toward pedestrian-oriented urban neighborhoods. At the same time, autonomous vehicle adoption may be hampered by their strategic disadvantage that slows them down in urban traffic.

scholarly journals Search-Based Planning and Reinforcement Learning for Autonomous Systems and Robotics

2020 ◽  
Author(s):  
Than Le
Keyword(s):  
Reinforcement Learning ◽  
Autonomous Vehicles ◽  
Optimal Trajectory ◽  
Autonomous Systems ◽  
Autonomous Mobile Robots ◽  
Artificial Intelligent ◽  
Unstructured Environment ◽  
And Robotics ◽  
Over Time ◽  
Basic Prerequisite

<p>In this chapter, we address the competent Autonomous Vehicles should have the ability to analyze the structure and unstructured environments and then to localize itself relative to surrounding things, where GPS, RFID or other similar means cannot give enough information about the location. Reliable SLAM is the most basic prerequisite for any further artificial intelligent tasks of an autonomous mobile robots. The goal of this paper is to simulate a SLAM process on the advanced software development. The model represents the system itself, whereas the simulation represents the operation of the system over time. And the software architecture will help us to focus our work to realize our wish with least trivial work. It is an open-source meta-operating system, which provides us tremendous tools for robotics related problems.</p> <p>Specifically, we address the advanced vehicles should have the ability to analyze the structured and unstructured environment based on solving the search-based planning and then we move to discuss interested in reinforcement learning-based model to optimal trajectory in order to apply to autonomous systems.</p>

Information Fake in Supply Chains

2011 ◽  
Vol 267 ◽  
pp. 958-962
Author(s):  
Jiang Hong
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chains ◽  
Information Management ◽  
Stable Distribution ◽  
Risk Attitude ◽  
Risk Averse ◽  
Stable States ◽  
Stochastically Stable

In this paper, we set risk attitude into decision making research for the supply chain manage. We focus on the information management. We discuss the stable states and the stochastically stable distribution for the fake game in the supply chain. We find there always exist information fake behaviors of low-yield suppliers. And, the less risk averse suppliers are, the more information fake they use.

Loyalty Discounts

2013 ◽  
Vol 13 (2) ◽  
pp. 655-685 ◽  
Author(s):  
Uğur Akgün ◽  
Ioana Chioveanu
Keyword(s):  
Private Information ◽  
Risk Attitude ◽  
Differentiated Products ◽  
Quantity Discounts ◽  
Risk Averse ◽  
Product Substitution ◽  
Market Outcomes ◽  
Wide Range ◽  
Parameter Values ◽  
Pricing Schemes

Abstract This article analyses the use of loyalty inducing discounts in vertical supply chains. An upstream supplier and a competitive fringe sell differentiated products to a retailer who has private information about the stochastic demand. We compare the market outcomes, when the supplier uses two-part tariffs (2PT), all-unit quantity discounts (AU), and market-share discounts (MS). We show that the retailer’s risk attitude affects supplier’s preferences over these pricing schemes. When the retailer is risk neutral, it bears all the risk and the three schemes lead to the same outcome. When the retailer is risk averse, a 2PT performs the worst from the supplier’s perspective, but it leads to the highest welfare. For a wide range of parameter values (but not for all), the supplier prefers MS to AU. By limiting the retailer’s product substitution possibilities, MS makes the demand for the manufacturer’s product more inelastic. This reduces the amount (share of total profits) the supplier needs to leave to the retailer for the latter to participate in the scheme.

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