Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, traditionally employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Commonly overlooked is the effect these maneuvers have on downward facing body fixed sensors, which as a result of bank, point away from the feature during turns. By adopting Skid-to-Turn maneuvers, the aircraft is able change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. Eliminating roll also helps to improve data quality, as sensors are no longer subjected to the swinging motion induced as they pivot about an axis perpendicular to their line of sight. Traditional tracking controllers that apply an indirect approach of capturing ground based data by flying directly overhead can also see the feature off center due to steady state pitch and roll required to stay on course. An Image Based Visual Servo controller is developed to address this issue, allowing features to be directly tracked within the image plane. Performance of the proposed controller is tested against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to simulate the field of view of a body fixed camera.

Using cooperative vehicle systems to collect near collision incidents events : a simulation study

On the road, near collision events (also close calls or near-miss incidents) largely outnumber actual crashes, yet most of them can never be recorded by current traffic data collection technologies or crashes analysis tools. The analysis of near collisions data is an important step in the process of reducing the crash rate. There have been several studies that have investigated near collisions; to our knowledge, this is the first study that uses the functionalities provided by cooperative vehicles to collect near misses information. We use the VISSIM traffic simulator and a custom C++ engine to simulate cooperative vehicles and their ability to detect near collision events. Our results showed that, within a simple simulated environment, adequate information on near collision events can be collected using the functionalities of cooperative perception systems. The relationship between the ratio of detected events and the ratio of equipped vehicle was shown to closely follow a squared law, and the largest source of nondetection was packet loss instead of packet delays and GPS imprecision.

Identifying differences in safe roads and crash prone roads using clustering data mining

Road asset managers are overwhelmed with a high volume of raw data which they need to process and utilise in supporting their decision making. This paper presents a method that processes road-crash data of a whole road network and exposes hidden value inherent in the data by deploying the clustering data mining method. The goal of the method is to partition the road network into a set of groups (classes) based on common data and characterise the class crash types to produce a crash profiles for each cluster. By comparing similar road classes with differing crash types and rates, insight can be gained into these differences that are caused by the particular characteristics of their roads. These differences can be used as evidence in knowledge development and decision support.

Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

An examination of the microscopic simulation models to identify traffic safety indicators

Evaluating the safety of different traffic facilities is a complex and crucial task. Microscopic simulation models have been widely used for traffic management but have been largely neglected in traffic safety studies. Micro simulation to study safety is more ethical and accessible than the traditional safety studies, which only assess historical crash data. However, current microscopic models are unable to mimic unsafe driver behavior, as they are based on presumptions of safe driver behavior. This highlights the need for a critical examination of the current microscopic models to determine which components and parameters have an effect on safety indicator reproduction. The question then arises whether these safety indicators are valid indicators of traffic safety. The safety indicators were therefore selected and tested for straight motorway segments in Brisbane, Australia. This test examined the capability of a micro-simulation model and presents a better understanding of micro-simulation models and how such models, in particular car following models can be enriched to present more accurate safety indicators.

Simulation of ankle joint forces to optimize total ankle replacement design

When compared with other arthoplasties, Total Ankle Joint Replacement (TAR) is much less successful. Attempts to remedy this situation by modifying the implant design, for example by making its form more akin to the original ankle anatomy, have largely met with failure. One of the major obstacles is a gap in current knowledge relating to ankle joint force. Specifically this is the lack of reliable data quantifying forces and moments acting on the ankle, in both the healthy and diseased joints. The limited data that does exist is thought to be inaccurate [1] and is based upon simplistic two dimensional discrete and outdated techniques.

Analysis of ten years historical weather data in Australia

Typical reference year (TRY) weather data is often used to represent the long term weather pattern for building simulation and design. Through the analysis of ten year historical hourly weather data for seven Australian major capital cities using the frequencies procedure of descriptive statistics analysis (by SPSS software), this paper investigates: • the closeness of the typical reference year (TRY) weather data in representing the long term weather pattern; • the variations and common features that may exist between relatively hot and cold years. It is found that for the given set of input data, in comparison with the other weather elements, the discrepancy between TRY and multiple years is much smaller for the dry bulb temperature, relative humidity and global solar irradiance. The overall distribution patterns of key weather elements are also generally similar between the hot and cold years, but with some shift and/or small distortion. There is little common tendency of change between the hot and the cold years for different weather variables at different study locations.

Considering weather in simulation traffic

The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.

Strategic renewal and competitive advantage in opportunity-driven and conservative new ventures

Strategic renewal has received relatively little attention in the context of new ventures. We examine the relationship among strategic renewal, competitive advantage and performance in opportunity-driven and conservative new ventures. Based on longitudinal data of a random sample of almost 373 new ventures, the link between strategic renewal and performance can be better understood by adding the mediating role of competitive advantage. Our results indicate that increased levels of strategic renewal positively relate to competitive advantage in conservative ventures, but not in opportunity-driven ventures. These findings place a different perspective on the dominant view that entrepreneurs should be opportunity maximizers. It suggests that both conservative and opportunity-driven new ventures can be successful if they follow different paths of strategic renewal in shaping competitive advantage.

Stakeholders' perceptions of data utility in the context of ERP outcomes

A substantial body of literature exists identifying factors contributing to under-performing Enterprise Resource Planning systems (ERPs), including poor communication, lack of executive support and user dissatisfaction (Calisir et al., 2009). Of particular interest is Momoh et al.’s (2010) recent review identifying poor data quality (DQ) as one of nine critical factors associated with ERP failure. DQ is central to ERP operating processes, ERP facilitated decision-making and inter-organizational cooperation (Batini et al., 2009). Crucial in ERP contexts is that the integrated, automated, process driven nature of ERP data flows can amplify DQ issues, compounding minor errors as they flow through the system (Haug et al., 2009; Xu et al., 2002). However, the growing appreciation of the importance of DQ in determining ERP success lacks research addressing the relationship between stakeholders’ requirements and perceptions of ERP DQ, perceived data utility and the impact of users’ treatment of data on ERP outcomes.

The ECOS green buildings project : data dramatization, visualization and manipulation

Buildings are key mediators between human activity and the environment around them, but details of energy usage and activity in buildings is often poorly communicated and understood. ECOS is an Eco-Visualization project that aims to contextualize the energy generation and consumption of a green building in a variety of different climates. The ECOS project is being developed for a large public interactive space installed in the new Science and Engineering Centre of the Queensland University of Technology that is dedicated to delivering interactive science education content to the public. This paper focuses on how design can develop ICT solutions from large data sets to create meaningful engagement with environmental data.

Communication and organizational social networks : a simulation model

Recent management research has evidenced the significance of organizational social networks, and communication is believed to impact the interpersonal relationships. However, we have little knowledge on how communication affects organizational social networks. This paper studies the dynamics between organizational communication patterns and the growth of organizational social networks. We propose an organizational social network growth model, and then collect empirical data to test model validity. The simulation results agree well with the empirical data. The results of simulation experiments enrich our knowledge on communication with the findings that organizational management practices that discourage employees from communicating within and across group boundaries have disparate and significant negative effect on the social network’s density, scalar assortativity and discrete assortativity, each of which correlates with the organization’s performance. These findings also suggest concrete measures for management to construct and develop the organizational social network.

Is simulation training effective in increasing podiatrists' confidence in foot ulcer management?

Background: Foot ulcers are a frequent reason for diabetes-related hospitalisation. Clinical training is known to have a beneficial impact on foot ulcer outcomes. Clinical training using simulation techniques has rarely been used in the management of diabetes-related foot complications or chronic wounds. Simulation can be defined as a device or environment that attempts to replicate the real world. The few non-web-based foot-related simulation courses have focused solely on training for a single skill or “part task” (for example, practicing ingrown toenail procedures on models). This pilot study aimed to primarily investigate the effect of a training program using multiple methods of simulation on participants’ clinical confidence in the management of foot ulcers. Methods: Sixteen podiatrists participated in a two-day Foot Ulcer Simulation Training (FUST) course. The course included pre-requisite web-based learning modules, practicing individual foot ulcer management part tasks (for example, debriding a model foot ulcer), and participating in replicated clinical consultation scenarios (for example, treating a standardised patient (actor) with a model foot ulcer). The primary outcome measure of the course was participants’ pre- and post completion of confidence surveys, using a five-point Likert scale (1 = Unacceptable-5 = Proficient). Participants’ knowledge, satisfaction and their perception of the relevance and fidelity (realism) of a range of course elements were also investigated. Parametric statistics were used to analyse the data. Pearson’s r was used for correlation, ANOVA for testing the differences between groups, and a paired-sample t-test to determine the significance between pre- and post-workshop scores. A minimum significance level of p < 0.05 was used. Results: An overall 42% improvement in clinical confidence was observed following completion of FUST (mean scores 3.10 compared to 4.40, p < 0.05). The lack of an overall significant change in knowledge scores reflected the participant populations’ high baseline knowledge and pre-requisite completion of web-based modules. Satisfaction, relevance and fidelity of all course elements were rated highly. Conclusions: This pilot study suggests simulation training programs can improve participants’ clinical confidence in the management of foot ulcers. The approach has the potential to enhance clinical training in diabetes-related foot complications and chronic wounds in general.

Comparison and modification of car following models toward a more accurate microscopic simulation parameters reproduction

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers of motor vehicles exhibit safe behaviours. Several car-following models are used in various micro-simulation models. This research compares the mainstream car following models’ capabilities of emulating precise driver behaviour parameters such as headways and Time to Collisions. The comparison firstly illustrates which model is more robust in the metric reproduction. Secondly, the study conducted a series of sensitivity tests to further explore the behaviour of each model. Based on the outcome of these two steps exploration of the models, a modified structure and parameters adjustment for each car-following model is proposed to simulate more realistic vehicle movements, particularly headways and Time to Collision, below a certain critical threshold. NGSIM vehicle trajectory data is used to evaluate the modified models performance to assess critical safety events within traffic flow. The simulation tests outcomes indicate that the proposed modified models produce better frequency of critical Time to Collision than the generic models, while the improvement on the headway is not significant. The outcome of this paper facilitates traffic safety assessment using microscopic simulation.

Microscopic cooperative traffic based on NGSIM data

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Vehicles are able to communicate on the local traffic state in real time, which could result in an automatic and therefore better reaction to the mechanism of traffic jam formation. An upstream single hop radio broadcast network can improve the perception of each cooperative driver within radio range and hence the traffic stability. The impact of a cooperative law on traffic congestion appearance is investigated, analytically and through simulation. Ngsim field data is used to calibrate the Optimal Velocity with Relative Velocity (OVRV) car following model and the MOBIL lane-changing model is implemented. Assuming that congestion can be triggered either by a perturbation in the instability domain or by a critical lane changing behavior, the calibrated car following behavior is used to assess the impact of a microscopic cooperative law on abnormal lane changing behavior. The cooperative law helps reduce and delay traffic congestion as it increases traffic flow stability.