Visible to the public CPS: Synergy: Collaborative Research: Semantics of Optimization for Real Time Intelligent Embedded Systems (SORTIES)Conflict Detection Enabled

Project Details
Lead PI:Behcet Acikmese
Performance Period:01/01/15 - 12/31/15
Institution(s):University of Texas at Austin
Sponsor(s):National Science Foundation
Award Number:1446520
1076 Reads. Placed 226 out of 804 NSF CPS Projects based on total reads on all related artifacts.
Abstract: Advances in technology mean that computer-controlled physical devices that currently still require human operators, such as automobiles, trains, airplanes, and medical treatment systems, could operate entirely autonomously and make rational decisions on their own. Autonomous cars and drones are a concrete and highly publicized face of this dream. Before this dream can be realized we must address the need for safety - the guaranteed absence of undesirable behaviors emerging from autonomy. Highly publicized technology accidents such as rocket launch failures, uncontrolled exposure to radiation during treatment, aircraft automation failures and unintended automotive accelerations serve as warnings of what can happen if safety is not adequately addressed in the design of such cyber-physical systems. One approach for safety analysis is the use of software tools that apply formal logic to prove the absence of undesired behavior in the control software of a system. In prior work, this approach this been proven to work for simple controller software that is generated automatically by tools from abstract models like Simulink diagrams. However, autonomous decision making requires more complex software that is able to solve optimization problems in real time. Formal verification of control software that includes such optimization algorithms remains an unmet challenge. The project SORTIES (Semantics of Optimization for Real Time Intelligent Embedded Systems) draws upon expertise in optimization theory, control theory, and computer science to address this challenge. Beginning with the convergence properties of convex optimization algorithms, SORTIES examines how these properties can be automatically expressed as inductive invariants for the software implementation of the algorithms, and then incorporates these properties inside the source code itself as formal annotations which convey the underlying reasoning to the software engineer and to existing computer-aided verification tools. The SORTIES goal is an open-source-semantics-carrying autocoder, which takes an optimization algorithm and its convergence properties as input, and produces annotated, verifiable code as output. The demonstration of the tool on several examples, such as a Mars lander, an aircraft avionics system, and a jet engine controller, shows that the evidence of quality produced by annotations is fully compatible with its application to truly functional products. Project research is integrated with education through training of "tri-lingual" professionals, who are equally conversant in system operation, program analysis, and the theory of control and optimization.