Integrating real time positioning systems to improve blind lifting and loading crane operations

Mobile/tower cranes are the most essential forms of construction plant in use in the construction industry but are also the subject of several safety issues. Of these, blind lifting has been found to be one of the most hazardous of crane operations. To improve the situation, a real-time monitoring system that integrates the use of a Global Positioning System (GPS) and Radio Frequency Identification (RFID) is developed. This system aims to identify unauthorized work or entrance of personnel within a pre-defined risk zone by obtaining positioning data of both site workers and the crane. The system alerts to the presence of unauthorized workers within a risk zone——currently defined as 3m from the crane. When this happens, the system suspends the power of the crane and a warning signal is generated to the safety management team. In this way the system assists the safety management team to manage the safety of hundreds of workers simultaneously. An onsite trial with debriefing interviews is presented to illustrate and validate the system in use.

Urban transit quality of service : user perception and behaviour

Despite its potential multiple contributions to sustainable policy objectives, urban transit is generally not widely used by the public in terms of its market share compared to that of automobiles, particularly in affluent societies with low-density urban forms like Australia. Transit service providers need to attract more people to transit by improving transit quality of service. The key to cost-effective transit service improvements lies in accurate evaluation of policy proposals by taking into account their impacts on transit users. If transit providers knew what is more or less important to their customers, they could focus their efforts on optimising customer-oriented service. Policy interventions could also be specified to influence transit users’ travel decisions, with targets of customer satisfaction and broader community welfare. This significance motivates the research into the relationship between urban transit quality of service and its user perception as well as behaviour. This research focused on two dimensions of transit user’s travel behaviour: route choice and access arrival time choice. The study area chosen was a busy urban transit corridor linking Brisbane central business district (CBD) and the St. Lucia campus of The University of Queensland (UQ). This multi-system corridor provided a ‘natural experiment’ for transit users between the CBD and UQ, as they can choose between busway 109 (with grade-separate exclusive right-of-way), ordinary on-street bus 412, and linear fast ferry CityCat on the Brisbane River. The population of interest was set as the attendees to UQ, who travelled from the CBD or from a suburb via the CBD. Two waves of internet-based self-completion questionnaire surveys were conducted to collect data on sampled passengers’ perception of transit service quality and behaviour of using public transit in the study area. The first wave survey is to collect behaviour and attitude data on respondents’ daily transit usage and their direct rating of importance on factors of route-level transit quality of service. A series of statistical analyses is conducted to examine the relationships between transit users’ travel and personal characteristics and their transit usage characteristics. A factor-cluster segmentation procedure is applied to respodents’ importance ratings on service quality variables regarding transit route preference to explore users’ various perspectives to transit quality of service. Based on the perceptions of service quality collected from the second wave survey, a series of quality criteria of the transit routes under study was quantitatively measured, particularly, the travel time reliability in terms of schedule adherence. It was proved that mixed traffic conditions and peak-period effects can affect transit service reliability. Multinomial logit models of transit user’s route choice were estimated using route-level service quality perceptions collected in the second wave survey. Relative importance of service quality factors were derived from choice model’s significant parameter estimates, such as access and egress times, seat availability, and busway system. Interpretations of the parameter estimates were conducted, particularly the equivalent in-vehicle time of access and egress times, and busway in-vehicle time. Market segmentation by trip origin was applied to investigate the difference in magnitude between the parameter estimates of access and egress times. The significant costs of transfer in transit trips were highlighted. These importance ratios were applied back to quality perceptions collected as RP data to compare the satisfaction levels between the service attributes and to generate an action relevance matrix to prioritise attributes for quality improvement. An empirical study on the relationship between average passenger waiting time and transit service characteristics was performed using the service quality perceived. Passenger arrivals for services with long headways (over 15 minutes) were found to be obviously coordinated with scheduled departure times of transit vehicles in order to reduce waiting time. This drove further investigations and modelling innovations in passenger’ access arrival time choice and its relationships with transit service characteristics and average passenger waiting time. Specifically, original contributions were made in formulation of expected waiting time, analysis of the risk-aversion attitude to missing desired service run in the passengers’ access time arrivals’ choice, and extensions of the utility function specification for modelling passenger access arrival distribution, by using complicated expected utility forms and non-linear probability weighting to explicitly accommodate the risk of missing an intended service and passenger’s risk-aversion attitude. Discussions on this research’s contributions to knowledge, its limitations, and recommendations for future research are provided at the concluding section of this thesis.

Determining operations affected by delay in predictive train timetables

Constructing train schedules is vital in railways. This complex and time consuming task is however made more difficult by additional requirements to make train schedules robust to delays and other disruptions. For a timetable to be regarded as robust, it should be insensitive to delays of a specified level and its performance with respect to a given metric, should be within given tolerances. In other words the effect of delays should be identifiable and should be shown to be minimal. To this end, a sensitivity analysis is proposed that identifies affected operations. More specifically a sensitivity analysis for determining what operation delays cause each operation to be affected is proposed. The information provided by this analysis gives another measure of timetable robustness and also provides control information that can be used when delays occur in practice. Several algorithms are proposed to identify this information and they utilise a disjunctive graph model of train operations. Upon completion the sets of affected operations can also be used to define the impact of all delays without further disjunctive graph evaluations.

Displacement motion prediction of a landing deck for recovery operations of rotary UAVs

This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer.

A nonlinear position controller for maritime operations of Rotary-wing UAVs

This paper presents a disturbance attenuation controller for horizontal position stabilization for hover and automatic landings of a Rotary-wing Unmanned Aerial Vehicle (RUAV) operating in rough seas. Based on a helicopter model representing aerodynamics during the landing phase, a nonlinear state feedback H-infinity controller is designed to achieve rapid horizontal position tracking in a gusty environment. The resultant control variables are further treated in consideration of practical constraints (flapping dynamics, servo dynamics and time lag effect) for implementation purpose. The high-fidelity closed-loop simulation using parameters of the Vario helicopter verifies performance of the proposed position controller. It not only increases the disturbance attenuation capability of the RUAV, but also enables rapid position response when gusts occur. Comparative studies show that the H-infinity controller exhibits great performance improvement and can be applied to ship/RUAV landing systems.

Mining temporal and spatial travel regularities for transit planning

Smart Card data from Automated Fare Collection system has been considered as a promising source of information for transit planning. However, literature has been limited to mining travel patterns from transit users and suggesting the potential of using this information. This paper proposes a method for mining spatial regular origins-destinations and temporal habitual travelling time from transit users. These travel regularity are discussed as being useful for transit planning. After reconstructing the travel itineraries, three levels of Density-Based Spatial Clustering of Application with Noise (DBSCAN) have been utilised to retrieve travel regularity of each of each frequent transit users. Analyses of passenger classifications and personal travel time variability estimation are performed as the examples of using travel regularity in transit planning. The methodology introduced in this paper is of interest for transit authorities in planning and managements

A microscopic simulation model to estimate bus rapid transit station bus capacity

The Bus Rapid Transit (BRT) station is the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on BRT line capacity. This study uses microscopic traffic simulation modeling to treat the BRT station operation and to analyze the relationship between station bus capacity and BRT line bus capacity. First, the simulation model is developed for the limit state scenario and then a statistical model is defined and calibrated for a specified range of controlled scenarios of dwell time characteristics. A field survey was conducted to verify the parameters such as dwell time, clearance time and coefficient of variation of dwell time to obtain relevant station bus capacity. The proposed model for BRT bus capacity provides a better understanding of BRT line capacity and is useful to transit authorities in BRT planning, design and operation.

Design of a gust-attenuation controller for landing operations of Unmanned Autonomous Helicopters

This paper presents an innovative and practical approach to controlling heave motion in the presence of acute stochastic atmospheric disturbances during landing operations of an Unmanned Autonomous Helicopter (UAH). A heave motion model of an UAH is constructed for the purpose of capturing dynamic variations of thrust due to horizontal wind gusts. Additionally, through construction of an effective observer to estimate magnitudes of random gusts, a promising and feasible feedback-feedforward PD controller is developed, based on available measurements from onboard equipment. The controller dynamically and synchronously compensates for aerodynamic variations of heave motion resulting from gust influence, to increase the disturbance-attenuation ability of the UAH in a windy environment. Simulation results justify the reliability and efficiency of the suggested gust observer to estimate gust levels when applied to the heave motion model of a small unmanned helicopter, and verify suitability of the recommended control strategy to realistic environmental conditions.

Impacts of vehicle-to-grid (V2G) technologies on electricity market operations

The Vehicle-to-Grid (V2G) concept is based on the newly developed and marketed technologies of hybrid petrol-electric vehicles, most notably represented by the Toyota Prius, in combination with significant structural changes to the world's energy economy, and the growing strain on electricity networks. The work described in this presentation focuses on the market and economic impacts of grid connected vehicles. We investigate price reduction effects and transmission system expansion cost reduction. We modelled a large numbers of plug-in-hybrid vehicle batteries by aggregating them into a virtual pumped-storage power station at the Australian national electricity market's (NEM) region level. The virtual power station concept models a centralised control for dispatching (operating) the aggregated electricity supply/demand capabilities of a large number of vehicles and their batteries. The actual level of output could be controlled by human or automated agents to either charge or discharge from/into the power grid. As previously mentioned the impacts of widespread deployments of this technology are likely to be economic, environmental and physical.

Advance transit oriented development typology : case study in Brisbane, Australia

Internationally, transit oriented development (TOD) is characterised by moderate to high density development with diverse land use patterns and well connected street networks centred around high frequency transit stops (bus and rail). Although different TOD typologies have been developed in different contexts, they are based on subjective evaluation criteria derived from the context in which they are built and typically lack a validation measure. Arguably there exist sets of TOD characteristics that perform better in certain contexts, and being able to optimise TOD effectiveness would facilitate planning and supporting policy development. This research utilises data from census collection districts (CCDs) in Brisbane with different sets of TOD attributes measured across six objectively quantified built environmental indicators: net employment density, net residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility. Using these measures, a Two Step Cluster Analysis was conducted to identify natural groupings of the CCDs with similar profiles, resulting in four unique TOD clusters: (a) residential TODs, (b) activity centre TODs, (c) potential TODs, and; (d) TOD non-suitability. The typologies are validated by estimating a multinomial logistic regression model in order to understand the mode choice behaviour of 10,013 individuals living in these areas. Results indicate that in comparison to people living in areas classified as residential TODs, people who reside in non-TOD clusters were significantly less likely to use public transport (PT) (1.4 times), and active transport (4 times) compared to the car. People living in areas classified as potential TODs were 1.3 times less likely to use PT, and 2.5 times less likely to use active transport compared to using the car. Only a little difference in mode choice behaviour was evident between people living in areas classified as residential TODs and activity centre TODs. The results suggest that: (a) two types of TODs may be suitable for classification and effect mode choice in Brisbane; (b) TOD typology should be developed based on their TOD profile and performance matrices; (c) both bus stop and train station based TODs are suitable for development in Brisbane.

Spreading peak demand for urban rail transit through differential fare policy : a review of empirical evidence

More evenly spread demand for public transport throughout a day can reduce transit service provider‟s total asset and labour costs. A plausible peak spreading strategy is to increase peak fare and/or to reduce off-peak fare. This paper reviews relevant empirical studies for urban rail systems, as rail transit plays a key role in Australian urban passenger transport and experiences severe peak loading variability. The literature is categorised into four groups: a) passenger opinions on willingness to change time for travel, b) valuations of displacement time using stated preference technique, c) simulations of peak spreading based on trip scheduling models, and: d) real-world cases of peak spreading using differential fare. Policy prescription is advised to take into account impacts of traveller‟s time flexibility and joint effects of mode shifting and peak spreading. Although focusing on urban rail, arguments in this paper are relevant to public transport in general with values to researchers and practitioners.

Transit Capacity and Quality of Service Manual (TCQSM) applications for education

Relevant Education Contexts, Examples of TCQSM Applicability to Undergraduate Disciplines, Why Teach with the TCQSM?, TCQS Teaching Tools, Theory Curriculum Example: Examination Question, Problem Based Learning Example: Senior Year Semester Team Project, Honors Dissertation Example Topics, Where to From Here?

How transit route passenger load and distance can together influence quality of service

This paper investigates: - correlation between transit route passenger loading and travel distance - its implications on quality of service (QoS) and resource productivity. It uses Automatic Fare Collection (AFC) data across a weekday on a premium bus line in Brisbane, Australia. A composite load-distance factor is proposed as a new measure for profiling transit route on-board passenger comfort QoS. Understanding these measures and their correlation is important for planning, design, and operational activities.

How transit route passenger load and distance can together influence quality of service

This paper investigates quality of service and resource productivity implications of transit route passenger loading and travel distance. Weekday Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate correlation between load factor and distance factor. Relationships between boardings and transit work indicate that distance factor generally increases with load factor. Time series analysis is then presented by examining each direction on an hour by hour basis. Inbound correlation is medium to strong across the entire span of service and strong for daytime services up to 19:30, while outbound correlation is strong across the entire span. Passengers tend to be making longer distance, peak direction commuter trips under the least comfortable conditions under stretched peak schedules than off-peak. Therefore productivity gains may be possible by adjusting fleet utilization during off-peak times. Weekday profiles by direction are established for a composite load-distance factor. A threshold corresponding to standing passengers on the Maximum Load Segment reveals that on-board loading and travel distance combined are more severe during the morning inbound peak than evening outbound peak, although the sharpness of the former suggests that encouraging shoulder peak travel during the morning would be more effective than evening peak. Further research suggested includes: consideration of travel duration factor, relating noise within hour to Peak Hour Factor, profiling load-distance factor across a range of case studies, and relating load-distance factor threshold to line length.

Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.