Airborne systems laboratory for automation research

This paper presents an Airborne Systems Laboratory for Automation Research. The Airborne Systems Laboratory (ASL) is a Cessna 172 aircraft that has been specially modified and equipped by ARCAA specifically for research in future aircraft automation technologies, including Unmanned Airborne Systems (UAS). This capability has been developed over a long period of time, initially through the hire of aircraft, and finally through the purchase and modification of a dedicated flight-testing capability. The ASL has been equipped with a payload system that includes the provision of secure mounting, power, aircraft state data, flight management system and real-time subsystem. Finally, this system has been deployed in a cost effective platform allowing real-world flight-testing on a range of projects.

Partitioning composite web services for decentralized execution using a genetic algorithm

Composite web services comprise several component web services. When a composite web service is executed centrally, a single web service engine is responsible for coordinating the execution of the components, which may create a bottleneck and degrade the overall throughput of the composite service when there are a large number of service requests. Potentially this problem can be handled by decentralizing execution of the composite web service, but this raises the issue of how to partition a composite service into groups of component services such that each group can be orchestrated by its own execution engine while ensuring acceptable overall throughput of the composite service. Here we present a novel penalty-based genetic algorithm to solve the composite web service partitioning problem. Empirical results show that our new algorithm outperforms existing heuristic-based solutions.

Validation of the Algase Wandering Scale (Version 2) in a cross cultural sample

This study examined the psychometric properties of an expanded version of the Algase Wandering Scale (Version 2) (AWS-V2) in a cross-cultural sample. A cross-sectional survey design was used. Study subjects were 172 English-speaking persons with dementia (PWD) from long-term care facilities in the USA, Canada, and Australia. Two or more facility staff rated each subject on the AWS-V2. Demographic and cognitive data (MMSE) were also obtained. Staff provided information on their own knowledge of the subject and of dementia. Separate factor analyses on data from two samples of raters each explained greater than 66% of the variance in AWS-V2 scores and validated four (persistent walking, navigational deficit, eloping behavior, and shadowing) of five factors in the original scale. Items added to create the AWS-V2 strengthened the shadowing subscale, failed to improve the routinized walking subscale, and added a factor, attention shifting as compared to the original AWS. Evidence for validity was found in significant correlations and ANOVAs between the AWS-V2 and most subscales with a single item indicator of wandering and with the MMSE. Evidence of reliability was shown by internal consistency of the AWS-V2 (0.87, 0.88) and its subscales (range 0.88 to 0.66), with Kappa for individual items (17 of 27 greater than 0.4), and ANOVAs comparing ratings across rater groups (nurses, nurse aids, and other staff). Analyses support validity and reliability of the AWS-V2 overall and for persistent walking, spatial disorientation, and eloping behavior subscales. The AWS-V2 and its subscales are an appropriate way to measure wandering as conceptualized within the Need-driven Dementia-compromised Behavior Model in studies of English-speaking subjects. Suggestions for further strengthening the scale and for extending its use to clinical applications are described.

Design of a static thruster for microair vehicle rotorcraft

This paper presents a case study of a design for a complete microair vehicle thruster. Fixed-pitch small-scale rotors, brushless motors, lithium-polymer cells, and embedded control are combined to produce a mechanically simple, high-performance thruster with potentially high reliability. The custom rotor design requires a balance between manufacturing simplicity and rigidity of a blade versus its aerodynamic performance. An iterative steady-state aeroelastic simulator is used for holistic blade design. The aerodynamic load disturbances of the rotor-motor system in normal conditions are experimentally characterized. The motors require fast dynamic response for authoritative vehicle flight control. We detail a dynamic compensator that achieves satisfactory closed-loop response time. The experimental rotor-motor plant displayed satisfactory thrust performance and dynamic response.

Life-cycle management of construction projects based on virtual prototyping technology

Life-cycle management (LCM) has been employed in the management of construction projects for many years in order to reduce whole life cost, time, risk and improve the service to owners. However, owing to lack of an effective information sharing platform, the current LCM of construction projects is not effectively used in the construction industry. Based upon the analysis of the information flow of LCM, a virutal prototyping (VP)-based communication and collaboration information platform is proposed. Following this, the platform is customized using DASSAULT sofware. The whole process of implementing the VP-based LCM are also discussed and, from a simple case study, it is demonstrated that the VP-based communication and collaboration information platform is an effective tool to support the LCM of construction projects.

Evaluation of risk factors leading to cost overrun in delivery of highway construction projects

Accurate owner budget estimates are critical to the initial decision-to-build process for highway construction projects. However, transportation projects have historically experienced significant construction cost overruns from the time the decision to build has been taken by the owner. This paper addresses the problem of why highway projects overrun their predicted costs. It identifies the owner risk variables that contribute to significant cost overrun and then uses factor analysis, expert elicitation, and the nominal group technique to establish groups of importance ranked owner risks. Stepwise multivariate regression analysis is also used to investigate any correlation of the percentage of cost overrun with risks, together with attributes such as highway project type, indexed cost, geographics location, and project delivery method. The research results indicate a correlation between the reciprocal of project budgets size and percentage cost overrun. This can be useful for owners in determining more realistic decision-to-build highway budget estimates by taking into account the economies of scale associated with larger projects.

Benchmarking framework to measure extent of ICT adoption for building project management

This project discusses a component of the research study conducted to provide construction organizations with a generic benchmarking framework to assess their extent of information communication technology (ICT) adoption for building project management processes. It defines benchmarking and discusses objectives of the required benchmarking framework and development of the framework. The study focuses on ICT adoption by small and medium enterprises (SMEs) in the construction industry and with respect to SMEs it is important to understand processes, their indicators, and measures in the local context. Structure of the suggested benchmarking framework has been derived after extensive literature survey and a questionnaire survey conducted in the Indian construction industry. The suggested benchmarking process is an iterative process divided into four stages. It can be implemented at organization and industry levels for rating the construction organizations for ICT adoption and performance measurement. The framework has a generic structure and can be generalized and applied for other countries with due considerations.

Iteratively specified tree-based regression : theory and trip generation example

Focuses on a study which introduced an iterative modeling method that combines properties of ordinary least squares (OLS) with hierarchical tree-based regression (HTBR) in transportation engineering. Information on OLS and HTBR; Comparison and contrasts of OLS and HTBR; Conclusions.

Identifying large truck hot spots using crash counts and PDOEs

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

Framework for measuring corporate safety culture and its impact on construction safety performance

This paper presents the results of a structural equation model (SEM) that describes and quantifies the relationships between corporate culture and safety performance. The SEM is estimated using 196 individual questionnaire responses from three companies with better than average safety records. A multiattribute analysis of corporate safety culture characteristics resulted in a hierarchical description of corporate safety culture comprised of three major categories — people, process, and value. These three major categories were decomposed into 54 measurable questions and used to develop a questionnaire to quantify corporate safety culture. The SEM identified five latent variables that describe corporate safety culture: (1) a company’s safety commitment; (2) the safety incentives that are offered to field personal for safe performance; (3) the subcontractor involvement in the company culture; (4) the field safety accountability and dedication; and (5) the disincentives for unsafe behaviors. These characteristics of company safety culture serve as indicators for a company’s safety performance. Based on the findings from this limited sample of three companies, this paper proposes a list of practices that companies may consider to improve corporate safety culture and safety performance. A more comprehensive study based on a larger sample is recommended to corroborate the findings of this study.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

Petri net modeling of spatial and temporal constraints in track allocation problem at railway stations

The track allocation problem (TAP) at a multi-track, multi-platform mainline railway station is defined by the station track layout and service timetable, which implies combinations of spatial and temporal conflicts. Feasible solutions are available from either traditional planning or advanced intelligent searching methods and their evaluations with respect to operational requirements are essential for the operators. To facilitate thorough analysis, a timed Coloured Petri Nets (CPN) model is presented here to encapsulate the inter-relationships of the spatial and temporal constraints in the TAP.

Optimisation of a class of transportation problems using genetic algorithms

This paper presents a Genetic Algorithms (GA) approach to search the optimized path for a class of transportation problems. The formulation of the problems for suitable application of GA will be discussed. Exchanging genetic information in the sense of neighborhoods will be introduced for generation reproduction. The performance of the GA will be evaluated by computer simulation. The proposed algorithm use simple coding with population size 1 converged in reasonable optimality within several minutes.

Evaluation on service quality of railway timetable

From the business viewpoint, the railway timetable is a list of the products presented by the railway transportation operators to the customers, specifying the schedules of all the train services on a railway line or network. In order to evaluate the quality of the train service schedules, a number of indices are proposed in this paper. These indices primarily take the passengers’ needs, such as waiting time, transfer time and transport capacity into consideration. Delay rate is usually used in post-evaluation. In this study, we propose to give an evaluation on the probability that the scheduled train services are likely to be delayed and the recovery ability of the timetable after delay has occurred. The evaluation identifies the possible problems in the services, such as excessive waiting time, non-seamless transfer, and high possibility of delay. This paper also discusses the improvement of these problems through certain adjustments on the timetable. The indices for evaluation and the adjustment method on timetable are then applied to a case study on the Hu-Ning-Hang railway in China, followed by the discussions of the merits of the proposed indices for timetable evaluation and possible improvement.