Prediction intervals to account for uncertainties in travel time prediction

The accurate prediction of travel times is desirable but frequently prone to error. This is mainly attributable to both the underlying traffic processes and the data that are used to infer travel time. A more meaningful and pragmatic approach is to view travel time prediction as a probabilistic inference and to construct prediction intervals (PIs), which cover the range of probable travel times travelers may encounter. This paper introduces the delta and Bayesian techniques for the construction of PIs. Quantitative measures are developed and applied for a comprehensive assessment of the constructed PIs. These measures simultaneously address two important aspects of PIs: 1) coverage probability and 2) length. The Bayesian and delta methods are used to construct PIs for the neural network (NN) point forecasts of bus and freeway travel time data sets. The obtained results indicate that the delta technique outperforms the Bayesian technique in terms of narrowness of PIs with satisfactory coverage probability. In contrast, PIs constructed using the Bayesian technique are more robust against the NN structure and exhibit excellent coverage probability.

A dynamic time warped clustering technique for discrete event simulation-based system analysis

Abstract This paper introduces a novel approach for discrete event simulation output analysis. The approach combines dynamic time warping and clustering to enable the identification of system behaviours contributing to overall system performance, by linking the clustering cases to specific causal events within the system. Simulation model event logs have been analysed to group entity flows based on the path taken and travel time through the system. The proposed approach is investigated for a discrete event simulation of an international airport baggage handling system. Results show that the method is able to automatically identify key factors that influence the overall dwell time of system entities, such as bags that fail primary screening. The novel analysis methodology provides insight into system performance, beyond that achievable through traditional analysis techniques. This technique also has potential application to agent-based modelling paradigms and also business event logs traditionally studied using process mining techniques.

Accessibility impact of proposed Australian high speed rail

High speed rail (also commonly known as HSR) is highly regarded as one of the most significant innovation for mass passenger transportation to travellers willing to pay for reduced travel impediments (shorter travel time, convenience, safety, security, comfort, reliability, flexibility, uniqueness and attractiveness). The transport policy in Australia has until now focused primarily on private passenger car transport and air transportation to the degree that State and Federal Governments’ commitments and actions of rail-oriented mass transportation system still remains sketchy in spite of occasional political and public attentions into it. This has resulted in a limited use of passenger rail as a regional transport system. Using one of the several alternative HSR alignments proposed for the South-Eastern Coast of Australia connecting Melbourne, Canberra, Sydney and Brisbane, this study assesses the regional accessibility impacts of Australian HSR system by means of four indicators: location accessibility, economic potential accessibility, daily accessibility and commuting accessibility. These indicators are commonly used in transport geography literature and they offer different concepts of changes in regional accessibility conditions due to a long distance transport system. The results provide an understanding of differential effects on regional accessibility based on the geographical location and size of urban areas along HSR corridor.

Wellbeing of Australians : mortgage payments and home ownership

The Australian Unity Wellbeing Index monitors the subjective wellbeing of the Australian population. Our first survey was conducted in April 2001 and this report concerns the 16th survey, undertaken in October 2006. Our previous survey had been conducted five months earlier in May 2006. This intervening period was relatively uneventful in terms of events likely to change population wellbeing. In March 2006, the new Industrial Relations legislation came into force. Each survey involves a telephone interview with a new sample of 2,000 Australians, selected to represent the national population geographic distribution. These surveys comprise the Personal Wellbeing Index, which measures people’s satisfaction with their own lives, and the National Wellbeing Index, which measures how satisfied people are with life in Australia. Other items include a standard set of demographic questions and other survey-specific questions. The specific topics for Survey 16 are home location and travel time, and expenditure on mortgage or rent.

Simulation-based input loading condition optimisation of airport baggage handling systems

Scheduling check-in station operations are a challenging problem within airport systems. Prior to determining check-in resource schedules, an important step is to estimate the Baggage Handling System (BHS) operating capacity under non-stationary conditions. This ensures that check-in stations are not overloaded with bags, which would adversely affect the system and cause cascade stops and blockages. Cascading blockages can potentially lead to a poor level of service and in worst scenario a customer may depart without their bags. This paper presents an empirical study of a multiobjective problem within a BHS system. The goal is to estimate near optimal input operating conditions, such that no blockages occurs at check-in stations, while minimising the baggage travel time and maximising the throughput performance measures. We provide a practical hybrid simulation and binary search technique to determine a near optimal input throughput operating condition. The algorithm generates capacity constraint information that may be used by a scheduler to plan check-in operations based on flight arrival schedules.

Estimating performance indexes of a baggage handling system using metamodels

In this study, we develop some deterministic metamodels to quickly and precisely predict the future of a technically complex system. The underlying system is essentially a stochastic, discrete event simulation model of a big baggage handling system. The highly detailed simulation model of this is used for conducting some experiments and logging data which are then used for training artificial neural network metamodels. Demonstrated results show that the developed metamodels are well able to predict different performance measures related to the travel time of bags within this system. In contrast to the simulation models which are computationally expensive and expertise extensive to be developed, run, and maintained, the artificial neural network metamodels could serve as real time decision aiding tools which are considerably fast, precise, simple to use, and reliable.

Using geographic information systems (GIS) to assess the role of the built environment in influencing obesity : a glossary

Features of the built environment are increasingly being recognised as potentially important determinants of obesity. This has come about, in part, because of advances in methodological tools such as Geographic Information Systems (GIS). GIS has made the procurement of data related to the built environment easier and given researchers the flexibility to create a new generation of environmental exposure measures such as the travel time to the nearest supermarket or calculations of the amount of neighbourhood greenspace. Given the rapid advances in the availability of GIS data and the relative ease of use of GIS software, a glossary on the use of GIS to assess the built environment is timely. As a case study, we draw on aspects the food and physical activity environments as they might apply to obesity, to define key GIS terms related to data collection, concepts, and the measurement of environmental features.

Shared care for chronic eye diseases : perspectives of ophthalmologists, optometrists and patients

Objective: To report the perspectives of optometrists, ophthalmologists and patients on a model of shared care for patients with chronic eye diseases.

Design, setting and participants: Qualitative study of a model of shared care between optometrists and ophthalmologists for patients with stable age-related macular degeneration, diabetic retinopathy and glaucoma, trialled by the Royal Victorian Eye and Ear Hospital in Melbourne during 2007–2009. Semi-structured interviews were conducted with optometrists, ophthalmologists and patients at completion of the project to obtain their perspectives on this model.

Results: Seventeen optometrists submitted expressions of interest to participate, and 12 completed web-based training modules and clinical observerships and adhered to specified examination and reporting protocols. All five participating ophthalmologists and 11 of the optometrists were interviewed. Ninety-eight patients participated and 37 were interviewed. Optometrists not only met ophthalmologists’ expectations but exceeded them, appropriately detecting and referring patients with additional, previously undetected conditions. Patients reported savings in travel time and were satisfied with the quality of care they received. Optometrists, ophthalmologists and patients indicated a general acceptance of shared care arrangements, although there were some issues relating to interprofessional trust.

Conclusions: Shared care between local optometrists and hospital-based ophthalmologists can help to reduce patient waiting time for review and offers an opportunity for these two groups of eye care professionals to collaborate in providing localised care for the benefit of patients. However, trust and relationship building need to be further developed.

Upgrading arc median shortest path problem for an urban transportation network

In this paper, we propose an algorithm for an upgrading arc median shortest path problem for a transportation network. The problem is to identify a set of nondominated paths that minimizes both upgrading cost and overall travel time of the entire network. These two objectives are realistic for transportation network problems, but of a conflicting and noncompensatory nature. In addition, unlike upgrading cost which is the sum of the arc costs on the path, overall travel time of the entire network cannot be expressed as a sum of arc travel times on the path. The proposed solution approach to the problem is based on heuristic labeling and exhaustive search techniques, in criteria space and solution space, respectively. The first approach labels each node in terms of upgrading cost, and deletes cyclic and infeasible paths in criteria space. The latter calculates the overall travel time of the entire network for each feasible path, deletes dominated paths on the basis of the objective vector and identifies a set of Pareto optimal paths in the solution space. The computational study, using two small-scale transportation networks, has demonstrated that the algorithm proposed herein is able to efficiently identify a set of nondominated median shortest paths, based on two conflicting and noncompensatory objectives.

An algorithm to median shortest path problem (MSPP) in the design of urban transportation networks

This paper proposes an efficient solution algorithm for realistic multi-objective median shortest path problems in the design of urban transportation networks. The proposed problem formulation and solution algorithm to median shortest path problem is based on three realistic objectives via route cost or investment cost, overall travel time of the entire network and total toll revenue. The proposed solution approach to the problem is based on the heuristic labeling and exhaustive search technique in criteria space and solution space of the algorithm respectively. The first labels each node in terms of route cost and deletes cyclic and infeasible paths in criteria space imposing cyclic break and route cost constraint respectively. The latter deletes dominated paths in terms of objectives vector in solution space in order to identify a set of Pareto optimal paths. The approach, thus, proposes a non-inferior solution set of Pareto optimal paths based on non-dominated objective vector and leaves the ultimate decision to decision-makers for purpose specific final decision during applications. A numerical experiment is conducted to test the proposed algorithm using artificial transportation network. Sensitivity analyses have shown that the proposed algorithm is advantageous and efficient over existing algorithms to find a set of Pareto optimal paths to median shortest paths problems.

Expansion of congested railway capacity using triple-track line operation based on hourly passenger demand

This paper proposes a method of improving level of service in congested urban railways by means of a triple-track line operation for a highly dense urban area with special travel demand characteristics. Where the future travel demand forecasts show sluggish growth or no growth at all, there is little to no incentives for heavy railway investments like quadruple-track extension and construction of new railway routes to alleviate current railway congestion problems. In such a situation, triple-track line operation can be the best alternative due to its moderate investment cost and ease in land acquisition for just an additional single track along the existing tracks. Our simulation investigation in one of the congested railway lines in Tokyo showed that triple track line operation increases railway capacity by 26% and shortens travel time by 38% in peak direction during morning peak hours. These results are encouraging and are useful for removing current railways problems in Tokyo and in similar urban situations elsewhere.

Alternative service delivery models for families with a new speech generating device: perspectives of parents and therapists

Purpose: Research has revealed limitations in the provision of in-person services to families with a new speech generating device (SGD), both in Australia and overseas. Alternative service models such as parent training, peer support and telepractice may offer a solution, but their use with this population has not been researched to date.

Method: Using interviews and focus groups, this study explored the experiences and opinions of 13 speech-language pathologists and seven parents regarding alternatives to in-person support and training for families with a new SGD. Data were analysed using grounded theory. Themes explored in this paper include the benefits and drawbacks of alternative service models as well as participants’ suggestions for the optimal implementation of these approaches.

Result: Participants confirmed the utility of alternative service models, particularly for rural/remote and underserviced clients. Benefits of these models included reduced travel time for families and therapists, as well as enhanced information access, support and advocacy for parents.

Conclusion: Participants viewed the provision of ongoing professional support to families as critical, regardless of service modality. Additional issues arising from this study include the need for development of organizational policies, resources and training infrastructure to support the implementation of these alternative service models.