Passenger experience and their implications for airports retail environment design

This project develops new knowledge on the full range of activities and interactions that make up airport passengers' retail experiences. The practical application of this new knowledge will improve the design of airport retail environments and will, in turn, improve passenger experiences, leading to further growth in the airport retail market. The novel methodological approach developed allowed for a new and deeper understanding of how passengers actually experience airport retail environments. Four significant outcomes were discovered: (i) the categorisation of the full range of retail activities and interactions passengers actually undertake, (ii) a new understanding of how passengers use and experience their free airport time, (iii) two new passenger market segments, and (iv) two passenger retail experience tools, with these identifying the broad range of airport-specific factors which influence passengers retail experiences.

Modelling airport passenger group dynamics using an agent-based method

This thesis investigates the influence of passenger group dynamics on passengers' behaviour in an international airport. A simulation model is built to analyse passengers' behaviour during airport departure processes and during an emergency event. Results from the model showed that passengers' group dynamics have significant influences on the performance and utilisation of airport services. The agent-based model also provides a convenient way to investigate the effectiveness of space design and service allocations, which may contribute to the enhancement of passenger airport experiences.

A comparative investigation of C6-C15 hydrocarbons emitted from a passenger car powered by unleaded petrol and 10% ethanol fuel

Twenty-three non-methane hydrocarbons were captured from the exhaust of a car operating on unleaded petrol (ULP) and 10% ethanol fuels at steady speed on a chassis dynamometer. The compounds were identified and quantified by GC/MS/FID and their emission concentrations at 60 km/h, 80km/h and idle speed were evaluated. The most abundant compounds in the exhaust included n-hexane, n-heptane, benzene, toluene, ethyl benzene, m- and p-xylenes, and methylcyclopentane. Because of the large number of compounds involved, no attempt was made to compare the emission concentrations of the compounds. Rather the sum of the emission concentrations for the suite of compounds identified was compared when the car was powered by ULP and 10% ethanol fuel. It was evident from the results that the emission concentrations and factors were generally higher with ULP than with 10% ethanol fuel. The total emission concentrations with the ULP fuel were 2.8, 4.2 and 2.6 times the corresponding values for the 10% ethanol fuel at 60km/h, 80km/h and idle speed, respectively. The implications of the results on the environment are discussed in the paper.

Seat Comfort. M4-M6.

Hardness is defined as the resistance and load bearing capability of an item. Seat hardness is an important factor in seat comfort as it impacts on a number of variables including seat postural stability, postural control, pressure comfort as a result of tissue deformation, and occupant vibration. The development of the test rig further on described in this report will enable Futuris Automotive to develop their current comfort testing procedures and thus increase the comfort of their automotive seats. The test rig consists of a buttock indenter, which produces a controlled application of a load to a seat cushion with measured displacement via a linear indenter. In parallel with the physical property presented, an analytic (software) finite element tool was developed to simulate seat pressure in an ANSYS Workbench V13 environment. This report also details the procedure required for Futuris to accurately and precisely measure cushion hardness which will enhance their comfort testing procedures, product development and target settings. The report is divided into three main sections: 1 Test equipment specification (M4) - A detailed description of the process used to build the seat cushion indenter and a description of the indenter mechanical structure and electrical functionality (chapter 2). 2 Analytic tool specification (M5) – A detailed description of the CAE seat and indenter software tool, developed as a finite element model (FEM) under ANSYS Workbench V13 to simulate indentation of a physical seat cushion similar to the hardware tool (chapter 3). 3 Product Development and Comfort Design Procedure (M6) - The cushion hardness testing procedure to be used with the physical indenter. This milestone is partially incomplete, as it covers a description of the test procedure to be applied, however not the operating system (control software) required to operate the physical property (chapter 4). Although outside the scope of this project, this report also details the testing procedures required to measure overall seatback hardness.

Seat Comfort. M2-M3

This (seat) attribute target list and Design for Comfort taxonomy report is based on the literature review report (C3-21, Milestone 1), which specified different areas (factors) with specific influence on automotive seat comfort. The attribute target list summarizes seat factors established in the literature review (Figure 1) and subsumes detailed attributes derived from the literature findings within these factors/classes. The attribute target list (Milestone 2) then provides the basis for the “Design for Comfort��� taxonomy (Milestone 3) and helps the project develop target settings (values) that will be measured during the testing phase of the C3-21 project. The attribute target list will become the core technical description of seat attributes, to be incorporated into the final comfort procedure that will be developed. The Attribute Target List and Design for Comfort Taxonomy complete the target definition process. They specify the context, markets and application (vehicle classes) for seat development. As multiple markets are addressed, the target setting requires flexibility of variables to accommodate the selected customer range. These ranges will be consecutively filled with data in forthcoming studies. The taxonomy includes how and where the targets are derived, reference points and standards, engineering and subjective data from previous studies as well as literature findings. The comfort parameters are ranked to identify which targets, variables or metrics have the biggest influence on comfort. Comfort areas included are seat kinematics (adjustability), seat geometry and pressure distribution (static comfort), seat thermal behavior and noise/vibration transmissibility (cruise comfort) and eventually material properties, design and features (seat harmony). Data from previous studies is fine tuned and will be validated in the nominated contexts and markets in follow-up dedicated studies.

Seat Comfort. M1

This literature review reports on high quality research studies focused on measuring occupant comfort in automotive vehicles. The review covers the most important variables in automotive seating design that impact on occupant comfort. These findings will help Futuris and the University develop the target settings that will be measured during the testing phase of the C3-21 project. The review also provides valuable information that may be incorporated into the final comfort procedure that will be developed.

Better cars or older cars?: Assessing CO2 emission reduction potential of passenger vehicle replacement programs

The primary motivation for the vehicle replacement schemes that were implemented in many countries was to encourage the purchase of new cars. The basic assumption of these schemes was that these acquisitions would benefit both the economy and the environment as older and less fuel-efficient cars were scrapped and replaced with more fuel-efficient models. In this article, we present a new environmental impact assessment method for assessing the effectiveness of scrappage schemes for reducing CO2 emissions taking into account the rebound effect, driving behavior for older versus new cars and entire lifecycle emissions for during the manufacturing processes of new cars. The assessment of the Japanese scrappage scheme shows that CO2 emissions would only decrease if users of the scheme retained their new gasoline passenger vehicles for at least 4.7 years. When vehicle replacements were restricted to hybrid cars, the reduction in CO2 achieved by the scheme would be 6-8.5 times higher than the emissions resulting from a scheme involving standard, gasoline passenger vehicles. Cost-benefit analysis, based on the emission reduction potential, showed that the scheme was very costly. Sensitivity analysis showed that the Japanese government failed to determine the optimum, or target, car age for scrapping old cars in the scheme. Specifically, scrapping cars aged 13 years and over did not maximize the environmental benefits of the scheme. Consequently, modifying this policy to include a reduction in new car subsidies, focused funding for fuel-efficient cars, and modifying the target car age, would increase environmental benefits. © 2013 Elsevier Ltd.

Best practice in peer-led curriculum content : informing an interactive program to improve passenger safety among high school seniors

Despite ongoing improvements in behaviour change strategies, licensing models and road law enforcement measures young drivers remain significantly over-represented in fatal and non-fatal road related crashes. This paper focuses on the safety of those approaching driving age and identifies both high priority road safety messages and relevant peer-led strategies to guide the development school programs. It summarises the review in a program logic model built around the messages and identified curriculum elements, as they may be best operationalised within the licensing and school contexts in Victoria. This paper summarises a review of common deliberate risk-taking and non-deliberate unsafe driving behaviours among novice drivers, highlighting risks associated with speeding, driving while fatigued, driving while impaired and carrying passengers. Common beliefs of young people that predict risky driving were reviewed, particularly with consideration of those beliefs that can be operationalised in a behaviour change school program. Key components of adolescent risk behaviour change programs were also reviewed, which identified a number of strategies for incorporation in a school based behaviour change program, including: a well-structured theoretical design and delivery, thoughtfully considered peer-selected processes, adequate training and supervision of peer facilitators, a process for monitoring and sustainability, and interactive delivery and participant discussions. The research base is then summarised in a program logic model with further discussion about the quality of the current state of knowledge of evaluation of behaviour change programs and the need for considerable development in program evaluation.

Passenger segmentation using smart card data

Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.

A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Stochastic analysis of transit route segments' passenger load variation for capacity and quality of service assessment

This paper investigates stochastic analysis of transit segment hourly passenger load factor variation for transit capacity and quality of service (QoS) analysis using Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia. It compares stochastic analysis to traditional peak hour factor (PHF) analysis to gain further insight into variability of transit route segments’ passenger loading during a study hour. It demonstrates that hourly design load factor is a useful method of modeling a route segment’s capacity and QoS time history across the study weekday. This analysis method is readily adaptable to different passenger load standards by adjusting design percentile, reflecting either a more relaxed or more stringent condition. This paper also considers hourly coefficient of variation of load factor as a capacity and QoS assessment measure, in particular through its relationships with hourly average and design load factors. Smaller value reflects uniform passenger loading, which is generally indicative of well dispersed passenger boarding demands and good schedule maintenance. Conversely, higher value may be indicative of pulsed or uneven passenger boarding demands, poor schedule maintenance, and/or bus bunching. An assessment table based on hourly coefficient of variation of load factor is developed and applied to this case study. Inferences are drawn for a selection of study hours across the weekday studied.

Stochastic analysis of transit route segments' passenger load variation for capacity & quality of service assessment

This study uses weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia •Stochastic analysis is compared to peak hour factor (PHF) analysis for insight into passenger loading variability •Hourly design load factor (e.g. 88th percentile) is found to be a useful method of modeling a segment’s passenger demand time-history across a study weekday, for capacity and QoS assessment •Hourly coefficient of variation of load factor is found to be a useful QoS and operational assessment measure, particularly through its relationship with hourly average load factor, and with design load factor •An assessment table based on hourly coefficient of variation of load factor is developed from the case study

Measuring in-vehicle child comfort to study barriers to appropriate and correct use of restraints

Traffic crashes are the leading cause of death and injury among children aged between 4-14 years1,2 and premature graduation to adult seat belts2,3 and restraint misuse4 are common and known risk factors. Children are believed to prematurely graduate to adult belts and misuse the seat belt in booster seats if uncomfortable2,5,6. Although research has concentrated on educating parents and designing better restraints to reduce errors in use, comfort of the child in the restraint has not been studied. Currently there is no existing method for studying comfort in children in restraint systems, although self-report survey tools and pressure distribution mapping is commonly used to measure comfort among adult in vehicle seats. This poster presents preliminary results from work aimed at developing an appropriate method to measure comfort of children in vehicle restraint systems. The specific aims are to: 1. Examine the potential of using modified adult self-report/survey and pressure distribution mapping in children 2. Develop a video based, objective measure of comfort in children.

Analysis of passenger group behaviour and its impact on passenger flow using an agent-based model

Group interaction within crowds is a common phenomenon and has great influence on pedestrian behaviour. This paper investigates the impact of passenger group dynamics using an agent-based simulation method for the outbound passenger process at airports. Unlike most passenger-flow models that treat passengers as individual agents, the proposed model additionally incorporates their group dynamics as well. The simulation compares passenger behaviour at airport processes and discretionary services under different group formations. Results from experiments (both qualitative and quantitative) show that incorporating group attributes, in particular, the interactions with fellow travellers and wavers can have significant influence on passengers activity preference as well as the performance and utilisation of services in airport terminals. The model also provides a convenient way to investigate the effectiveness of airport space design and service allocations, which can contribute to positive passenger experiences. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.