Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.

A framework for freeway incident modeling and traffic re-routing

This paper proposes an analytical Incident Traffic Management framework for freeway incident modeling and traffic re-routing. The proposed framework incorporates an econometric incident duration model and a traffic re-routing optimization module. The incident duration model is used to estimate the expected duration of the incident and thus determine the planning horizon for the re-routing module. The re-routing module is a CTM-based Single Destination System Optimal Dynamic Traffic Assignment model that generates optimal real-time strategies of re-routing freeway traffic to its adjacent arterial network during incidents. The proposed framework has been applied to a case study network including a freeway and its adjacent arterial network in South East Queensland, Australia. The results from different scenarios of freeway demand and incident blockage extent have been analyzed and advantages of the proposed framework are demonstrated.

Changing travel patterns and journeys to health services in Great Britain 1985-2012: An examination health service utilisation using the National Travel Survey

Background This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2012). The National Travel Survey (NTS) is a series of household surveys designed to provide data on personal travel and monitor changes in travel behaviour over time. The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Methods Variables from the PSU, households, and individuals datasets were used as explanatory variables. Whereas, variables extracted from the journeys dataset were used as dependent variables to identify patterns of utilisation i.e. the proportion of journeys made by different groups to access health facilities in a particular journey distance or time band or by mode of transport; and geographic access to health services. A binary logistic regression analysis was conducted to identify the utilisation rate over the different time periods between different groups. This analysis shows the Odds Ratios (ORs) for different groups making a trip to utilise health services compared to their respective counterparts. Linear multiple regression analyses were conducted to then identify patterns of change in the accessibility and mobility level. Results Analysis of the data has shown that that journey distances to health facilities were signi fi cantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. Although rates of utilisation of health services we re Oral Abstracts / Journal of Transport & Health 2 (2015) S5 – S63 S43 signi fi cantly lower because of longer journey times. These fi ndings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension. Conclusions This fi nding, therefore, suggests the need to improve geographic access to services together with an enhanced mobility option for disadvantaged groups in order for them to have improved levels of access to health facilities. This research has also found that the volume of car trips to health services also increased steadily over the period 1985-2012 while all other modes accounted for a smaller number of trips. However, it is dif fi cult to conclude from this research whether this increase in the volume of car trips was due to a lack of alternative transport or due to an increase in the level of car-ownership.

Destination image: identifying baseline perceptions of Brazil, Argentina and Chile in the nascent Australian long haul travel market

While the popularity of destination image research has increased exponentially in the literature, there has been relatively little published about perceptions held by international consumers of destinations in South America. The purpose of this paper is to report the findings of a research project that aimed to identify the baseline market perceptions of Brazil, Argentina and Chile amongst Australian residents, at the time of the emergence of this long haul market. Of interest was the extent to which Australians differentiate the three distinct countries versus perceiving the continent as a gestalt. These baseline perceptions enable the effectiveness of future marketing communications in Australia by the three national tourism offices to be monitored over time. Importance-Performance Analysis (IPA) is used as a practical analytical tool to guide decision makers. In terms of operationalising destination image, a key research finding was the very high ratio or participants using the ‘Don’t know’ (DK) option for each destination performance scale item. This finding has practical implications for the destination marketers, as well as for researchers engaged in destination image research in long haul and/or emerging markets.

Past-day recall of sedentary time: Validity of a self-reported measure of sedentary time in a university population

Background Sedentary behaviour is associated with several deleterious health consequences. Although device-based measures of sedentary time are available, they are costly and do not provide a measure of domain specific sedentary time. High quality self-report measures are necessary to accurately capture domain specific sedentary time, and to provide an alternative to devices when cost is an issue. In this study, the Past-day Adults’ Sedentary Time (PAST) questionnaire, previously shown to have acceptable validity and reliability in a sample of breast cancer survivors, was modified for a university sample and validity of the modified questionnaire was examined compared with activPAL. Methods Participants (n = 58, age = 18–55 years, 48% female, 66% students) were recruited from the University of Queensland (students and staff). They answered the PAST questionnaire, which asked about time spent sitting or lying down for work, study, travel, television viewing, leisure-time computer use, reading, eating, socialising and other purposes, during the previous day. Time reported for these questions was summed to provide a measure of total sedentary time. Participants also wore an activPAL device for the full day prior to completing the questionnaire and recorded their wake and sleep times in an activity log. Total waking sedentary time derived from the activPAL was used as the criterion measure. Correlation (Pearson's r) and agreement (Bland–Altman plots) between PAST and activPAL sedentary time were examined. Results Participants were sedentary (activPAL-determined) for approximately 66% of waking hours. The correlation between PAST and activPAL sedentary time for the whole sample was r = 0.50 [95% confidence interval (CI) = 0.28–0.67]; and higher for non-students (r = 0.63, 95% CI = 0.26–0.84) than students (r = 0.46, 95% CI = 0.16–0.68). Bland–Altman plots revealed that the mean difference between the two measures was 19 min although limits of agreement were wide (95% limits of agreement −4.1 to 4.7 h). Discussion The PAST questionnaire provides an acceptable measure of sedentary time in this population, which included students and adults with high workplace sitting. These findings support earlier research that questionnaires employing past-day recall of sedentary time provide a viable alternative to existing sedentary behaviour questionnaires.

Understanding urban rail travel for improved patronage forecasting

Improved forecasting of urban rail patronage is essential for effective policy development and efficient planning for new rail infrastructure. Past modelling and forecasting of urban rail patronage has been based on legacy modelling approaches and often conducted at the general level of public transport demand, rather than being specific to urban rail. This project canvassed current Australian practice and international best practice to develop and estimate time series and cross-sectional models of rail patronage for Australian mainland state capital cities. This involved the implementation of a large online survey of rail riders and non-riders for each of the state capital cities, thereby resulting in a comprehensive database of respondent socio-economic profiles, travel experience, attitudes to rail and other modes of travel, together with stated preference responses to a wide range of urban travel scenarios. Estimation of the models provided a demonstration of their ability to provide information on the major influences on the urban rail travel decision. Rail fares, congestion and rail service supply all have a strong influence on rail patronage, while a number of less significant factors such as fuel price and access to a motor vehicle are also influential. Of note, too, is the relative homogeneity of rail user profiles across the state capitals. Rail users tended to have higher incomes and education levels. They are also younger and more likely to be in full-time employment than non-rail users. The project analysis reported here represents only a small proportion of what could be accomplished utilising the survey database. More comprehensive investigation was beyond the scope of the project and has been left for future work.

Detailed analysis of a conservative difference approximation for the time fractional diffusion equation

Diffusion equations that use time fractional derivatives are attractive because they describe a wealth of problems involving non-Markovian Random walks. The time fractional diffusion equation (TFDE) is obtained from the standard diffusion equation by replacing the first-order time derivative with a fractional derivative of order α ∈ (0, 1). Developing numerical methods for solving fractional partial differential equations is a new research field and the theoretical analysis of the numerical methods associated with them is not fully developed. In this paper an explicit conservative difference approximation (ECDA) for TFDE is proposed. We give a detailed analysis for this ECDA and generate discrete models of random walk suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation. The stability and convergence of the ECDA for TFDE in a bounded domain are discussed. Finally, some numerical examples are presented to show the application of the present technique.

Determination of preventive maintenance lead time using hybrid analysis

The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.

Effective Cell-Centred Time-Domain Maxwell's Equations Numerical Solvers

This research work analyses techniques for implementing a cell-centred finite-volume time-domain (ccFV-TD) computational methodology for the purpose of studying microwave heating. Various state-of-the-art spatial and temporal discretisation methods employed to solve Maxwell's equations on multidimensional structured grid networks are investigated, and the dispersive and dissipative errors inherent in those techniques examined. Both staggered and unstaggered grid approaches are considered. Upwind schemes using a Riemann solver and intensity vector splitting are studied and evaluated. Staggered and unstaggered Leapfrog and Runge-Kutta time integration methods are analysed in terms of phase and amplitude error to identify which method is the most accurate and efficient for simulating microwave heating processes. The implementation and migration of typical electromagnetic boundary conditions. from staggered in space to cell-centred approaches also is deliberated. In particular, an existing perfectly matched layer absorbing boundary methodology is adapted to formulate a new cell-centred boundary implementation for the ccFV-TD solvers. Finally for microwave heating purposes, a comparison of analytical and numerical results for standard case studies in rectangular waveguides allows the accuracy of the developed methods to be assessed.