Planes, trains, automobiles and the action per quod servitium amisit

The action per quod servitium amisit compensates an employer for the loss of an employee’s services, where such loss is caused due to the commission of a tort by a third party which injures the employee. Although not commonly pleaded, such actions often arise when employees are harmed due to transportation accidents. For example, where allowed, physical injury caused by the negligent driving of automobiles, and the psychiatric injury suffered by an engine driver upon averting a collision with a motorcyclist crossing before an oncoming train...

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 test rig for the condition-based maintenance application on the traction chain of very high speed trains

The preventive maintenance of traction equipment for Very High Speed Trains (VHST) nowadays is becoming very expensive owing to the high complexity and quality of these components that require high reliability. An efficient maintenance approach like the Condition-Based Maintenance (CBM) should be implemented to reduce the costs. For this purpose, an experimental full-scale test rig for the CBM of VHST traction equipment has been designed to investigate in detail failures in the main mechanical components of system, i.e. motor, bearings and gearbox. The paper describes the main characteristics of this unique test rig, able to reproduce accurately the train operating conditions, including the relative movements of the motor, the gearbox and the wheel axle. Gearbox, bearing seats and motor are equipped by accelerometers, thermocouples, torque meter and other sensors in different positions. The testing results give important information about the most suitable sensor position and type to be installed for each component and show the effectiveness of the techniques used for the signal analysis in order to identify faults of the gearbox and motor bearings.

Diagnostics of rolling element bearings for the traction system of high speed trains : experimental evidences

Monitoring of the integrity of rolling element bearings in the traction system of high speed trains is a fundamental operation in order to avoid catastrophic failures and to implement effective condition-based maintenance strategies. Diagnostics of rolling element bearings is usually based on vibration signal analysis by means of suitable signal processing techniques. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in industrial applications, particularly in the field of rail transport, remains scarcely investigated. This paper will address the diagnostics of bearings taken from the service after a long term operation on a high speed train. These worn bearings have been installed on a test-rig, consisting of a complete full-scale traction system of a high speed train, able to reproduce the effects of wheel-track interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is also proposed.

Experimental evidences in bearing diagnostics for traction system of high speed trains

Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

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.

Determinants of second row passenger comfort

China is becoming an increasingly important automotive market. Customer’s vehicle usage, preferences and requirements differ from traditional western markets in a number of aspects – rear seat usage rates are higher, vehicles are used for business purposes as well as for private transport and rear seat usage is generally more important to Chinese customers compared to their western counterparts. The purpose of this project is to dimension and investigate these differences from an ergonomics perspective and use these results to guide the design of future products. The focus for this project will be specific to vehicles in the CD segment. More specifically, this project focuses on the second row ‘ambience’. Ambience refers to the global feeling perceived by second row passengers, and the main factors contributing to ambience are: ingress and egress comfort, seat comfort, roominess, and ease of use of the controls. In order to investigate the aforementioned parameters, an experimental study has been conducted in Shanghai, China. This experiment involved 80 healthy Chinese CD- and D-car customers. These subjects were asked to evaluate different features present in the second row environment of three different cars: A Ford Mondeo, Toyota Camry and Mercedes S-class. Various data has been collected during this experiment: First, the anthropometric dimensions of the subjects have been measured. The subjects were also asked to fill a questionnaire about demographics, their own car usage, and their perception of a various number of features present in the three tested cars. A great amount of technical data was also collected. The first part of this report presents the results given by the questionnaires. It includes Chinese demographics, vehicle usage habits, and the subjective perception of the features present in the tested cars. It also presents the results of the anthropometric measurements. This gives a first insight into Chinese customers’ habits and preferences. The second part deals with the technical data recorded during the experiment: second row seat adjustment ranges, roominess, optimal location of controls, and pressure mapping analysis. Analysis of technical data allows a deeper understanding of the factors contributing to comfort and ambience perception. Using the technical data together with the comfort ratings given by the subjects in the questionnaire, recommendations on several design parameters were provided. Finally, an experimental study of car ingress-egress has been conducted in a University laboratory controlled environment. During this study, the ingress and egress motion of 20 customers from Chinese origin was recorded using a motion capture system. The last part of this report presents the protocol and data processing that led to building an ingress-egress motion database that was provided to Ford.

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.

Transit route occupancy load factor and passenger average travel time for quality of service assessment

This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Transit route occupancy load factor and passenger average travel time for quality of service assessment

This presentation investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

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.