Sustainability in post disaster road infrastructure recovery projects in Queensland, Australia

Between mid 2010 and early 2013, Queensland road related infrastructures were devastated by flood and cyclone related natural disasters. Responding to these recent events and in preparing for more regular and intense climate-change induced events in future, the Queensland Government is now reviewing how post-disaster road infrastructure recovery projects are planned and delivered. In particular, there is awareness that rebuilding such infrastructure need sustainable strategies across economic, environmental and social dimensions. A comprehensive sustainability assessment framework for pre and post disaster situations can minimize negative impact on our communities, economy and environment. This research is underway to develop a comprehensive sustainability element frame work for post disaster management in road infrastructures in Queensland, Australia. Analyzing the implications of disruption to transport network and associated services is an important part of preparing local and regional responses to the impacts of natural disasters. This research can contribute to strategic planning, management leading to safe, efficient and integrated transport system that supports sustainable economic, social and environmental outcomes in Queensland. Within this context, this paper provides an overview of the qualitative mixed-method research approach involving literature reviews and case studies to explore and evaluate a number of sustainability elements with a view to develop operational strategies for disaster recovery road projects.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Measurement of transit network accessibility based on access stop choice behaviour

This research improved the measurement of public transport accessibility by capturing; travellers' behaviour; diversity of public transport mode; and the subjectivity of travellers' decision in the complex transport networks. The results of this research not only highlighted the importance of considering public transport network characteristics but also, revealed the impact of public transport diversity in the modelling of public transport accessibility. The research developed a hybrid discrete choice model with a nested logit structure to treat the correlation among the public transport mode choices and, a logit correction factor to rectify the correlation among the stop choices.

Evaluation of distributed control signaling protocols in GMPLS

GMPLS is a generalized form of MPLS (MultiProtocol Label Switching). MPLS is IP packet based and it uses MPLS-TE for Packet Traffic Engineering. GMPLS is extension to MPLS capabilities. It provides separation between transmission, control and management plane and network management. Control plane allows various applications like traffic engineering, service provisioning, and differentiated services. GMPLS control plane architecture includes signaling (RSVP-TE, CR-LDP) and routing (OSPF-TE, ISIS-TE) protocols. This paper provides an overview of the signaling protocols, describes their main functionalities, and provides a general evaluation of both the protocols.

Wild weather hampers Brisbane’s popular CityCat services

The heavy rain falls that we have been experiencing have had their impact on the public transport system, especially the ferries. September 2010 was the Brisbane area’s wettest on record, and early to mid October has shaped up much the same. So much so that the South East Queensland’s main water storages, the Wivenhoe and Somerset Dams, which are fed by the Stanley and Brisbane Rivers’ upper catchments, have filled to capacity. SEQ Water consequently released the floodgates on the Wivenhoe Dam for the first time in almost a decade, with bipartisan support of State and Local Governments.

A comparison of perceived crash risk among cyclists and drivers in Brisbane

The Queensland Government has implemented strategies promoting a shift from individual car use to active transport, a transition which requires drivers to adapt to sharing the road with increased numbers of people cycling through transport network. For this to occur safely, changes in both road infrastructure and road user expectations and behaviors will be needed. Creating separate cycle infrastructure does not remove the need for cyclists to commence, cross or finish travel on shared roads. Currently intersections are one of the predominant shared road spaces where crashes result in cyclists being injured or killed. This research investigates how Brisbane cyclists and drivers perceive risk when interacting with other road users at intersections. The current study replicates a French study conducted by co-authors Chaurand and Delhomme in 2011 and extends it to assess gender effects which have been reported in other Australian cycling research. An online survey was administered to experienced cyclists and drivers. Participants rated the level of risk they felt when imagining a number of different road situations. Based on the earlier French study it is expected that perceived crash risk will be influenced both by the participant’s mode of travel and the type of interacting vehicle and perceived risk will be greater when the interaction is with a car than a bicycle. It is predicted that risk perception will decrease as the level of experience increases and that male participants will have a higher perception of skill and lower perception of risk than females. The findings of this Queensland study will provide a valuable insight into perceived risk and the traffic behaviours of drivers and cyclists when interacting with other road users and results will be available for presentation at the Congress.

Benefits and issues for bus travel time estimation and prediction

Bus travel time estimation and prediction are two important modelling approaches which could facilitate transit users in using and transit providers in managing the public transport network. Bus travel time estimation could assist transit operators in understanding and improving the reliability of their systems and attracting more public transport users. On the other hand, bus travel time prediction is an important component of a traveller information system which could reduce the anxiety and stress for the travellers. This paper provides an insight into the characteristic of bus in traffic and the factors that influence bus travel time. A critical overview of the state-of-the-art in bus travel time estimation and prediction is provided and the needs for research in this important area are highlighted. The possibility of using Vehicle Identification Data (VID) for studying the relationship between bus and cars travel time is also explored.

Understanding the enhancement in photoelectrochemical properties of photocatalytically prepared TiO2-reduced graphene oxide composite

Solution-phase photocatalytic reduction of graphene oxide to reduced graphene oxide (RGO) by titanium dioxide (TiO2) nanoparticles produces an RGO-TiO2 composite that possesses enhanced charge transport properties beyond those of pure TiO2 nanoparticle films. These composite films exhibit electron lifetimes up to four times longer than that of intrinsic TiO2 films due to RGO acting as a highly conducting intraparticle charge transport network within the film. The intrinsic UV-active charge generation (photocurrent) of pure TiO2 was enhanced by a factor of 10 by incorporating RGO; we attribute this to both the highly conductive nature of the RGO and to improved charge collection facilitated by the intimate contact between RGO and the TiO2, uniquely afforded by the solution-phase photocatalytic reduction method. Integrating RGO into nanoparticle films using this technique should improve the performance of photovoltaic devices that utilize nanoparticle films, such as dye-sensitized and quantum-dot-sensitized solar cells.

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.

Functional encryption for threshold functions (or fuzzy IBE) from lattices

Cryptosystems based on the hardness of lattice problems have recently acquired much importance due to their average-case to worst-case equivalence, their conjectured resistance to quantum cryptanalysis, their ease of implementation and increasing practicality, and, lately, their promising potential as a platform for constructing advanced functionalities. In this work, we construct “Fuzzy” Identity Based Encryption from the hardness of the Learning With Errors (LWE) problem. We note that for our parameters, the underlying lattice problems (such as gapSVP or SIVP) are assumed to be hard to approximate within supexponential factors for adversaries running in subexponential time. We give CPA and CCA secure variants of our construction, for small and large universes of attributes. All our constructions are secure against selective-identity attacks in the standard model. Our construction is made possible by observing certain special properties that secret sharing schemes need to satisfy in order to be useful for Fuzzy IBE. We also discuss some obstacles towards realizing lattice-based attribute-based encryption (ABE).

Critical review of time-dependent shortest path algorithms: A multimodal trip planner perspective

A multimodal trip planner that produces optimal journeys involving both public transport and private vehicle legs has to solve a number of shortest path problems, both on the road network and the public transport network. The algorithms that are used to solve these shortest path problems have been researched since the late 1950s. However, in order to provide accurate journey plans that can be trusted by the user, the variability of travel times caused by traffic congestion must be taken into consideration. This requires the use of more sophisticated time-dependent shortest path algorithms, which have only been researched in depth over the last two decades, from the mid-1990s. This paper will review and compare nine algorithms that have been proposed in the literature, discussing the advantages and disadvantages of each algorithm on the basis of five important criteria that must be considered when choosing one or more of them to implement in a multimodal trip planner.

Performance profiling for predictive train schedules

In this article an alternate sensitivity analysis is proposed for train schedules. It characterises the schedules robustness or lack thereof and provides unique profiles of performance for different sources of delay and for different values of delay. An approach like this is necessary because train schedules are only a prediction of what will actually happen. They can perform poorly with respect to a variety of performance metrics, when deviations and other delays occur, if for instance they can even be implemented, and as originally intended. The information provided by this analytical approach is beneficial because it can be used as part of a proactive scheduling approach to alter a schedule in advance or to identify suitable courses of action for specific “bad behaviour”. Furthermore this information may be used to quantify the cost of delay. The effect of sectional running time (SRT) deviations and additional dwell time in particular were quantified for three railway schedule performance measures. The key features of this approach were demonstrated in a case study.

Empirical evaluation of the travel time reliability indicators: A case study for Brisbane corridor under recurrent and non-recurrent conditions

This research quantifies traffic congestion and travel time reliability with case study on a major arterial road in Brisbane. The focus is on the analysis of impact of incidents (e.g., road accidents) on travel time reliability. Real traffic (Bluetooth) and incident records from Coronation Drive, Brisbane are utilized for the study. The findings include significant impact of incidents on traffic congestion and travel time reliability. The knowledge gained is useful in various applications such as traveler information systems, and cost-benefit analysis of various strategies to reduce the traffic incidents and its' impacts.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.