Improving Displacement Measurement for Evaluating Longitudinal Road Profiles

2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper introduces a half-wavelength peak matching (HWPM) model, which improves the accuracy of vehicle based longitudinal road profilers used in evaluating road unevenness and mega-textures. In this application, the HWPM model is designed for profilers which utilize a laser displacement sensor with an accelerometer for detecting surface irregularities. The process of converting acceleration to displacement by double integration (which is used in most rofilers) is error-prone, and although there are techniques to minimize the effect of this error, this paper proposes a novel approach for improving the generated road profile results. The technique amends the vertical displacement derived from the accelerometer samples, by using data from the laser displacement sensor as a reference. The vehicle based profiler developed for this experiment (which uses the HWPM model) shows a huge improvement in detected longitudinal irregularities when compared with pre-processed results, and uses a 3-m rolling straight edge as a benchmark.Peer reviewe

Safety Verification for Autonomous Ships

Autonomous and unmanned ships are approaching reality. One of several unsolved challenges related to these systems is how to perform safety verification. Although this challenge represents a many-faceted problem, which must be addressed at several levels, it seems likely that simulatorbased testing of high-level computer control systems will be an important technique. In the field of reliability verification and testing, design verification refers to the process of verifying that specified functions are satisfied over the life of a system. A basic requirement for any autonomous ship is that it has to be safe. In this paper, we propose to use the Systems-Theoretic Process Analysis (STPA) to (i) derive potential loss scenarios for autonomous ships and safety requirements to prevent them from occurring, and (ii) to develop a safety verification program, including test cases, intended to verify safety. Loss scenarios and associated safety requirements are derived using STPA. To derive a safety verification program, these unsafe scenarios and safety requirements are used to identify key variables, verification objectives, acceptance criteria and a set of suitable verification activities related to each scenario. The paper describes the proposed methodology and demonstrates it in a case study. Test cases for simulator-based testing and practical sea-trials are derived for autonomous ships. The case study shows that the proposed method is feasible as a way of generating a holistic safety verification program for autonomous ships

Human factors and ergonomics systems-based tools for understanding and addressing global problems of the twenty-first century

Sustainability is a systems problem with humans as integral elements of the system. However, sustainability problems usually have a broader scope than socio-technical systems and therefore, require additional considerations. This requires a fuller integration of complex systems understanding into the systems analysis toolset currently available to human factors and ergonomics. In this paper, we outline these complex systems requirements necessary to tackle global problems such as sustainability and then assess how three common systems analysis tools (i.e. Accimap, System Theoretic Accident Mapping and Processes, and Cognitive Work Analysis) stand up against these revised criteria. This assessment is then further explored through applying two of these tools (i.e. Accimap and System Theoretic Accident Mapping and Processes) to a transnational food integrity system problem. This case study shows that no single systems analysis method can be used in isolation to help identify key insights for intervention and that new methods may need to be developed or existing methods need to be adapted to understand these dynamic, adaptive systems. The implications for the further development of systems analysis tools are discussed

Forward-Looking Strategies for Safely Adopting Digital Transformation in Aviation

Aviation leaders in the U.S. federal government face challenges in adopting technical evolution and advancing modernization while adhering to the rigor of a deeply entrenched safety culture. The purpose of this qualitative modified Delphi study was to determine how a panel of 21 aerospace experts based in Washington, DC viewed strategies for adopting to new technologies while ensuring safety. The management concepts that framed the study were safety culture and digital transformation. The study addressed the research question of how a panel of aviation experts viewed the desirability, feasibility, and importance of forward-looking strategies for adopting digital transformation while adhering to the rigor of a deeply entrenched safety culture in aviation. Data analysis included content analysis of narrative responses to the digital transformation statements, statistical analysis of desirability and feasibility ratings to determine consensus, weighted average calculations to determine the importance ranking, and statistical analysis to determine confidence in the final results. The purposively selected panelists completed four rounds of data collection and reached consensus on the 10 most desirable, feasible, and important strategies in four categories derived from the Federal Aviation Administration Strategic Plan for 2019–2022. Aviation leaders may use the results to positively impact the safe adoption of Industry 4.0 technologies and impact social change by fostering stronger economic conditions for aviation customers and improving quality of life for travelers

A PhD research project on safety risk assessment of complex changes to railway infrastructure and vehicles

This study investigates the risk assessment of railway changes in an interconnected environment. Systems are a collection of subsystems and parts, and this thesis develops a new method, the Combined Assessment Method (CAM), to analyse them. CAM potentially applies to many industries, including aviation, defence and nuclear, where there is a requirement to assess system safety objectively. The railway is a specific case of a closely coupled socio-technical system of critical physical interfaces between systems and a stringent example of systems in other industries. The Author has carried out: an assessment of current techniques, a review of relevant literature, a survey of risk assessment practitioners, an appraisal of current methods, and a review of accident data to identify current accident characteristics. CAM incorporates established assessment techniques to perform subsystem analysis. Subsystem results are combined using systems engineering methods in a novel way producing an overall risk assessment for a system, which incorporates emergent behaviours. The assurance of CAM is through a case study and two test cases. It uses safety performance, ease of use, and economic saving criteria to judge success. Illustrative studies include a metro system, indicating that CAM is potentially a process and is application-independent. Furthermore, test cases illustrate that CAM combines the risks from multiple parts of a whole system into overall risks. Finally, test cases measure the verification through a match between the findings of official incident reports and the CAM output. This thesis is the first step to creating CAM as a fully-fledged system safety risk analysis method. Further work is proposed to take CAM forward and address identified weaknesses. Finally, suggestions have been made for further work to “productionize” CAM to increase the likelihood that practitioners in the field will use CAM

Early Concept Development and Safety Analysis of Future Transportation Systems

As transportation systems become increasingly complex and the roles of human operators and autonomous software continue to evolve, traditional safety-related analytical methods are becoming inadequate. Traditional hazard analysis tools are based on an accident causality model that does not capture many of the complex behaviors found in modern engineered systems. Additionally, these traditional approaches are most effective during the late stages of system development, when detailed design information is available. However, system safety cannot be cost-effectively assured by discovering problems at these late stages and adding expensive updates to the design. Rather, safety should be designed into complex intelligent transportation systems from their very conception, which can be achieved by integrating powerful hazard analysis techniques into the general systems engineering process. The primary barrier to achieving this objective is the lack of effectiveness of the existing analytical tools during early concept development. This paper introduces a new technique, which is based on a systems- and control-theoretic model of accident causality that can capture behaviors that are prevalent in these complex software-intensive systems. The goals are to (1) develop rigorous systematic tools for the analysis of future concepts to identify potentially hazardous scenarios and undocumented assumptions and to (2) extend these tools to assist stakeholders in the development of concepts using a safety-driven approach. Current work focuses on air transportation, but future goals of this research are to extend to and generalize all modes of transportation

Early Concept Development and Safety Analysis of Future Transportation Systems

As transportation systems become increasingly complex and the roles of human operators and autonomous software continue to evolve, traditional safety-related analytical methods are becoming inadequate. Traditional hazard analysis tools are based on an accident causality model that does not capture many of the complex behaviors found in modern engineered systems. Additionally, these traditional approaches are most effective during the late stages of system development, when detailed design information is available. However, system safety cannot be cost-effectively assured by discovering problems at these late stages and adding expensive updates to the design. Rather, safety should be designed into complex intelligent transportation systems from their very conception, which can be achieved by integrating powerful hazard analysis techniques into the general systems engineering process. The primary barrier to achieving this objective is the lack of effectiveness of the existing analytical tools during early concept development. This paper introduces a new technique, which is based on a systems- and control-theoretic model of accident causality that can capture behaviors that are prevalent in these complex software-intensive systems. The goals are to (1) develop rigorous systematic tools for the analysis of future concepts to identify potentially hazardous scenarios and undocumented assumptions and to (2) extend these tools to assist stakeholders in the development of concepts using a safety-driven approach. Current work focuses on air transportation, but future goals of this research are to extend to and generalize all modes of transportation