, to specify and verify its safety and bounded liveness properties in terms of its model. In addition, the paper also provides a short review on case-studies where Uppaal is applied, as well as references to its theoretical foundation. 1 Introduction Uppaal is a tool box for modeling, simulation

Abstract — We study the control of completely observed Markov chains with safety bounds as introduced in [3], but with more general safety constraints and the added requirement of optimality. In [3], the safety bounds were specified as unit-interval valued vector pairs (lower and upper bounds

of dependability, which is a kind of quality. Next, I discuss the structure of quality requirements and show how safety requirements can be engineered based on safety’s numerous quality subfactors. Then, I define and discuss safety constraints (i.e., mandated safeguards) and safety-critical requirements (i

Traffic lights have been existing for around 100 years. The first signals were installed for safety reasons for avoiding accident between opposed traffic flows at an intersection. Due to a continually increasing traffic, the traffic lights became a powerful tool for controlling the flows: the stake

the fault occurs in order to guarantee that the constraints are not violated. This is often achieved by using static safety constraints. However, it may be hard to nd such constraints, and they may be conservative. This article presents a method for implementing dynamic safety constraints based on fault

. By harnessing these desirable features, behaviour is bounded through incorporation of safety constraints – derived from safety requirements and hazard analysis. The constrained FSOM has been termed a ‘Safety Critical Artificial Neural Network’ (SCANN) and preserves valuable performance characteristics

This paper presents a Bayesian approach to learning flexible safety constraints in a coordinated, multi-planner ensemble, along with stochastic and active experimentation approaches for assigning degrees of blame when these constraints are violated. The blame is subsequently translated and conveyed

Hazard situations in safety-critical systems are typically complex, so there is a need for means to detect complex hazards and react in a timely and meaningful way. This paper addresses the problem of hazard detection through the development of an on-line analysis tool. The approach allows the user

Process optimization, Safety considerations. Maximizing the yield of a second-order reaction by manipulating the inlet flow rate is considered in both the isoperibolic and isothermal modes. For safety considerations, constraints on (i) the amount of heat produced, and (ii) the temperature under

This paper deals with the design of time-invariant memoryless control policies for robots that move in a finite two-dimensional lattice and are tasked with persistent surveillance of an area in which there are forbidden regions. We model each robot as a controlled Markov chain whose state comprises its position in the lattice and the direction of motion. The goal is to find the minimum number of robots and an associated time-invariant memoryless control policy that guarantees that the largest number of states are persistently surveilled without ever visiting a forbidden state. We propose a design method that relies on a finitely parametrized convex program inspired by entropy maximization principles. Numerical examples are provided.