Traffic Scenarios for Automated Vehicle Testing: A Review of Description Languages and Systems

Testing and validation of the functionalities and safety of automated vehicles shifted from a distance-based to a scenario-based method in the past decade. A number of domain-specific languages and systems were developed to support scenario-based testing. The aim of this paper is to review and compare the features and characteristics of the major scenario description languages and systems (SDLS). Each of them is designed for different purposes and with different goals; therefore, they have their strengths and weaknesses. Their characteristics are highlighted with an example nontrivial traffic scenario that we designed. We also discuss some directions for further development and research of these SDLS.

Representing Qualitative Action Models for Learning in Complex Virtual Worlds

<p>This thesis addresses the problem of representing and learning qualitative models of behaviour in complex virtual worlds. It presents a novel representation, ‘Q-Systems’, that integrates two existing representation frameworks: qualitative process models and action description languages. QSystems combines the expressive power of both frameworks to allow actions and world dynamics to be modelled in a common way using a representation based on non-deterministic and probabilistic finite state machines. The representation supports learning and planning by using a modular approach that partitions world behaviour into ‘systems’ of objects with specific contexts and a related behaviour. Q-Systems was developed and tested using an agent in a rich simulated world that was created as part of the thesis. The simulation uses a rigid body physics engine to produce complex realistic interactions between objects. An action system and a qualitative vision system were also developed to allow the agent to observe and act in the simulated world. The thesis includes a proposed two stage learning process comprising an initial stage in which ‘histories’ (contextually and temporally restricted sequences of observations) are extracted from interactions with the simulation, and a second stage in which the histories are generalised to create a knowledge base of system models. An algorithm for generating histories is presented and a number of heuristics are implemented and compared. A system for learning generalised models is presented and it is used to assess the suitability of Q-Systems with respect to learning in complex environments. Planning with Q-Systems is demonstrated in an agent which reasons with generalised models to work out how to achieve goals in the simulated world. A simple planning algorithm is described and a variety of issues are explored. Planning with a single system is shown to be relatively straightforward due to the modular nature of Q-Systems. This thesis demonstrates that Q-Systems successfully integrate two different representation frameworks and that they can be used in learning and planning in complex environments. The initial results are promising, but further investigation is required to fully understand the advantages and disadvantages of the Q-System approach compared with existing learning systems. This would involve the development of benchmark problems (currently there are none for this particular domain).</p>

Representing Qualitative Action Models for Learning in Complex Virtual Worlds

<p>This thesis addresses the problem of representing and learning qualitative models of behaviour in complex virtual worlds. It presents a novel representation, ‘Q-Systems’, that integrates two existing representation frameworks: qualitative process models and action description languages. QSystems combines the expressive power of both frameworks to allow actions and world dynamics to be modelled in a common way using a representation based on non-deterministic and probabilistic finite state machines. The representation supports learning and planning by using a modular approach that partitions world behaviour into ‘systems’ of objects with specific contexts and a related behaviour. Q-Systems was developed and tested using an agent in a rich simulated world that was created as part of the thesis. The simulation uses a rigid body physics engine to produce complex realistic interactions between objects. An action system and a qualitative vision system were also developed to allow the agent to observe and act in the simulated world. The thesis includes a proposed two stage learning process comprising an initial stage in which ‘histories’ (contextually and temporally restricted sequences of observations) are extracted from interactions with the simulation, and a second stage in which the histories are generalised to create a knowledge base of system models. An algorithm for generating histories is presented and a number of heuristics are implemented and compared. A system for learning generalised models is presented and it is used to assess the suitability of Q-Systems with respect to learning in complex environments. Planning with Q-Systems is demonstrated in an agent which reasons with generalised models to work out how to achieve goals in the simulated world. A simple planning algorithm is described and a variety of issues are explored. Planning with a single system is shown to be relatively straightforward due to the modular nature of Q-Systems. This thesis demonstrates that Q-Systems successfully integrate two different representation frameworks and that they can be used in learning and planning in complex environments. The initial results are promising, but further investigation is required to fully understand the advantages and disadvantages of the Q-System approach compared with existing learning systems. This would involve the development of benchmark problems (currently there are none for this particular domain).</p>

Invariant-Based Safety Assessment of FPGA Projects: Conception and Technique

This paper describes a proposed method and technology of safety assessment of projects based on field programmable gate arrays (FPGA). Safety assessment is based on special invariants, e.g., properties which remain unchanged when a specified transformation is applied. A classification and examples of FPGA project invariants are provided. In the paper, two types of invariants are described. The first type of invariants used for such assessment are those which are versatile since they reflect the unchanged properties of FPGA projects, hardware description languages, etc. These invariants can be replenished as experience gained in project implementation accumulates. The second type of invariants is formed based on an analysis of the specifics of a particular FPGA project and reflects the features of the tasks to be solved, the algorithms that are implemented, the hardware FPGA chips used, and the computer-aided design tools, etc. The paper contains a description of the overall conception and particular stages of FPGA projects invariant-based safety assessment. As examples for solving some tasks (using of invariants and defect injections), the paper contains several algorithms written in the VHSIC hardware description language (VHDL). The paper summarizes the results obtained during several years of practical and theoretical research. It can be of practical use for engineers and researchers in the field of quality, reliability, and security of embedded systems, software and information management systems for critical and business applications.

CoCEC: An Automatic Combinational Circuit Equivalence Checker Based on the Interactive Theorem Prover

Checking the equivalence of two Boolean functions, or combinational circuits modeled as Boolean functions, is often desired when reliable and correct hardware components are required. The most common approaches to equivalence checking are based on simulation and model checking, which are constrained due to the popular memory and state explosion problems. Furthermore, such tools are often not user-friendly, thereby making it tedious to check the equivalence of large formulas or circuits. An alternative is to use mathematical tools, called interactive theorem provers, to prove the equivalence of two circuits; however, this requires human effort and expertise to write multiple output functions and carry out interactive proof of their equivalence. In this paper, we (1) define two simple, one formal and the other informal, gate-level hardware description languages, (2) design and develop a formal automatic combinational circuit equivalence checker (CoCEC) tool, and (3) test and evaluate our tool. The tool CoCEC is based on human-assisted theorem prover Coq, yet it checks the equivalence of circuit descriptions purely automatically through a human-friendly user interface. It either returns a machine-readable proof (term) of circuits’ equivalence or a counterexample of their inequality. The interface enables users to enter or load two circuit descriptions written in an easy and natural style. It automatically proves, in few seconds, the equivalence of circuits with as many as 45 variables (3.5 × 10 13 states). CoCEC has a mathematical foundation, and it is reliable, quick, and easy to use. The tool is intended to be used by digital logic circuit designers, logicians, students, and faculty during the digital logic design course.

A User-Centric QoS-Based Web Service Selection Framework

With the proliferation of web services, the selection process, especially the one based on the non-functional properties (e.g. Quality of Service – QoS attributes) has become a more and more important step to help requestors locate a desired service. There have been many research works proposing various QoS description languages and selection models. However, the end user is not generally the focal point of their designs and the user support is either missing or lacking in these systems. The QoS language sometimes is not flexible enough to accommodate users’ various requirements and is too complex so that it puts extra burden on users. In order to solve this problem, in this thesis we design a more expressive and flexible QoS query language (QQL) targeted for non-expert users, together with the user support on formulating queries and understanding services in the registry. An enhanced selection model based on Mixed Integer Programming (MIP) is also proposed to handle the QQL queries. We performed experiments with a real QoS dataset to show the effectiveness of our framework.

A User-Centric QoS-Based Web Service Selection Framework

With the proliferation of web services, the selection process, especially the one based on the non-functional properties (e.g. Quality of Service – QoS attributes) has become a more and more important step to help requestors locate a desired service. There have been many research works proposing various QoS description languages and selection models. However, the end user is not generally the focal point of their designs and the user support is either missing or lacking in these systems. The QoS language sometimes is not flexible enough to accommodate users’ various requirements and is too complex so that it puts extra burden on users. In order to solve this problem, in this thesis we design a more expressive and flexible QoS query language (QQL) targeted for non-expert users, together with the user support on formulating queries and understanding services in the registry. An enhanced selection model based on Mixed Integer Programming (MIP) is also proposed to handle the QQL queries. We performed experiments with a real QoS dataset to show the effectiveness of our framework.