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.

Analyzing busway station potential capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.

Analysing busway station capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.

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.

A new model for airport passenger segmentation

Recent changes in the aviation industry and in the expectations of travellers have begun to alter the way we approach our understanding, and thus the segmentation, of airport passengers. The key to successful segmentation of any population lies in the selection of the criteria on which the partitions are based. Increasingly, the basic criteria used to segment passengers (purpose of trip and frequency of travel) no longer provide adequate insights into the passenger experience. In this paper, we propose a new model for passenger segmentation based on the passenger core value, time. The results are based on qualitative research conducted in-situ at Brisbane International Terminal during 2012-2013. Based on our research, a relationship between time sensitivity and degree of passenger engagement was identified. This relationship was used as the basis for a new passenger segmentation model, namely: Airport Enthusiast (engaged, non time sensitive); Time Filler (non engaged, non time sensitive); Efficiency Lover (non engaged, time sensitive) and Efficient Enthusiast (engaged, time sensitive). The outcomes of this research extend the theoretical knowledge about passenger experience in the terminal environment. These new insights can ultimately be used to optimise the allocation of space for future terminal planning and design.

Deconstructing expected passenger experience in airports

The effect of passenger satisfaction on airport profitability has been widely acknowledged in the aviation industry. As a result, there has been much attention directed towards developing a deeper understanding of the factors that influence the passenger experience. In this paper, we explore passenger experience from a novel perspective - that of the activities expected to be undertaken by passengers while in the airport terminal building. Using the Taxonomy of Passenger Experience (TOPA) as our framework, we look at the pre-travel interview data of 48 participants. The results of our analysis are used to construct an activity-centred account of the expected passenger experience for international departures. Our exploration of the expected passenger experienced revealed that not all of the TOPA activities have an equal impact on the passengers' expected experience. The processing, consumptive, preparatory and queuing activity groups featured most prominently in passengers' accounts of their upcoming airport experiences. Of these, the preparatory category was found to have the most direct impact on passenger satisfaction. Additionally, our analysis indicated that utilising queue time to prepare passengers for upcoming processing activities could have a positive effect on both satisfaction and processing efficiency. A further outcome of this research was the observation that "shopping" did not form a part of the expected experience of any of the interviewed participants. The outcomes of this study can be used by airports to assist in the management of passengers' expected experience in the terminal building. As passenger expectations and passenger satisfaction are intrinsically linked, understanding which activities have the most impact on satisfaction provides a basis from which alternate design choices can be evaluated when constructing, or fine-tuning, airport terminal designs.

Principles of experience design for airport terminals

In this thesis, the issue of airport terminal design is examined from a novel perspective: that of the passenger rather than the airport operator. A qualitative approach, based on interviews with 199 passengers at Brisbane International Terminal was adopted. The outcomes of this research make the following three key contributions to existing knowledge: (i) identification of a paradox in the Level of Service metrics, (ii) development of a conceptual model of passenger experience and six design principles and (iii) contribution towards advancing the theoretical knowledge about passengers and their experience in airport terminals.

Technology-mediated tools for shaping experiences in urban commuter trains

This thesis presents the results of a study into ways that technology can be appropriated and designed to support urban rail commuters in their daily journeys. The study evaluated a mobile application prototype deployed along the Brisbane passenger rail network. This prototype was designed to support social interaction between passengers sharing the same trains. This thesis provides a step forward in showing the relevance of increasingly creating solutions that contribute to a more enjoyable and attractive public transport service.

TrainYarn: Probing perceptions of social space in urban commuter trains

We studied the ways that urban commuter train passengers experience their journeys. We present the design process and in-situ evaluation of TrainYarn, a mobile app prototype designed to facilitate social interaction between co-located urban train passengers. Through the deployment of the prototype, we sought to probe perceptions of social space with a view to positively impact the assessment of public transport. Our results support that our target users saw value in the use of TrainYarn, perceiving it as emancipatory, in alignment with their communicative needs, and having the ability to transform their perceptions of social space. To further inform future research and practice, we put forward a series of design recommendations.

In-vehicle filming of driver fatigue on YouTube: Vlogs, crashes and bad advice

Background: Driver fatigue contributes to 15-30% of crashes, however it is difficult to objectively measure. Fatigue mitigation relies on driver self-moderation, placing great importance on the necessity for road safety campaigns to engage with their audience. Popular self-archiving website YouTube.com is a relatively unused source of public perceptions. Method: A systematic YouTube.com search (videos uploaded 2/12/09 - 2/12/14) was conducted using driver fatigue related search terms. 442 relevant videos were identified. In-vehicle footage was separated for further analysis. Video reception was quantified in terms of number of views, likes, comments, dislikes and times duplicated. Qualitative analysis of comments was undertaken to identify key themes. Results: 4.2% (n=107) of relevant uploaded videos contained in-vehicle footage. Three types of videos were identified: (1) dashcam footage (n=82); (2) speaking directly to the camera - vlogs (n=16); (3) passengers filming drivers (n=9). Two distinct types of comments emerged, those directly relating to driver fatigue and those more broadly about the video or its uploader. Driver fatigue comments included: attribution of behaviour cause, emotion experienced when watching the video and personal advice on staying awake while driving. Discussion: In-vehicle footage related to driver fatigue is prevalent on YouTube.com and is actively engaged with by viewers. Comments were mixed in terms of criticism and sympathy for drivers. Willingness to share advice on staying awake suggests driver fatigue may be seen as a common yet controllable occurrence. This project provides new insight into driver fatigue perception, which may be considered by safety authorities when designing education campaigns.

A road safety strategy for Norfolk Island, an Australian external territory

Norfolk Island is an Australian external territory in Oceania. The significant road safety reforms in Australia from the 1970s onward bypassed the island, and most road safety ‘silver bullets’ adopted in other Australian jurisdictions were not introduced. While legislative amendments in 2010 introduced mandatory seat belt wearing for vehicle occupants on Norfolk Island, other critical issues face the community including drink driving by residents and visitors, occupant protection for vehicle passengers, and the provision of a more protective road environment. The release of the first Norfolk Island road safety strategy 2014-2016 proposed, inter alia: • a lower BAC of 0.05 and the introduction of compulsory driver alcohol and drug testing by police; • targeted enforcement of occupant protection for vehicle passengers, particularly for passengers riding on vehicle tray backs; • education interventions to challenge values held by some members of the community that support unsafe road use; • ensuring that driver information, training and testing is adequate for all drivers; • identification and rectification of hazardous roadside infrastructure, particularly barrier protection at “high drop locations” within the road network; and • developing a specification for vehicle standards for vehicles imported into Norfolk Island. Norfolk Island is engaging in a process of integration with the Australian community, and wider issues relating to funding and resources have impacted on the implementation of the road safety strategy. The response to the strategy will be discussed, particularly in terms of current attempts to address drink driving and the provision of a safer road environment.

Questionnaire design for airport passenger experience survey

Assessing airport service performance requires understanding of a complete set of passenger experiences covering all activities from departures to arrivals. Weight-based indicator models allow passengers to express their priority on certain evaluation criteria (airport domains) and their service attributes over the others. The application of multilevel regression analysis in questionnaire design is expected to overcome limitations of traditional questionnaires, which require application of all indicators with equal weight. The development of a Taxonomy of Passenger Activities (TOPA), which captures all passenger processing and discretionary activities, has provided a novel perspective in understanding passenger experience in various airport domains. Based on further literature reviews on various service attributes at airport passenger terminals, this paper constitutes questionnaire design to employ a weighting method for all activities from the time passengers enter an airport domain at the departure terminal until leaving the arrival terminal (i.e. seven airport domains for departure, four airport domains during transit, and seven airport domains for arrival). The procedure of multilevel regression analysis is aimed not only at identifying the ranking of each evaluation criterion from the most important to the least important but also to explain the relationship between service attributes in each airport domain and overall service performance.

Assessment of transit quality of service with occupancy load factor and passenger travel time measures

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.

Factors related to seat belt use : A Turkish case

Seat belts are effective safety devices used to protect car occupants from severe injuries and fatalities during road vehicle accidents. Despite the proven effectiveness of seat belts, seat belt use rates are quite low, especially in developing countries, such as Turkey. The general aim of the present study was to investigate a large variety of factors related to seat belt use among Turkish car occupants using different perspectives and methods and therefore, to contribute to the design of effective seat belt use interventions for increasing seat belt use rates in Turkey. Five sub-studies were conducted within the present study. In the first sub-study, environmental (e.g., road type) and psycho-social factors (e.g., belt use by other car occupants) related to the seat belt use of front-seat occupants were investigated using observation techniques. Being male, of a young age, and traveling on city roads were the main factors negatively related to seat belt use. Furthermore, seat belt use by the drivers and front-seat passengers was highly correlated and a significant predictors of each other. In the second sub-study, the motivations of the car occupants for seat belt use and non-use were investigated using interview techniques. Situational conditions, such as traveling on city roads and for short distances, and not believing in the effectiveness and relevance of seat belt use for safety, were the most frequently reported reasons for not using a seat belt. Safety, habit and avoiding punishment were among the most frequently reported reasons for using a seat belt. In the third sub-study, the Theory of Planned Behavior (TPB) and the Health Belief Model (HBM) were applied to seat belt use using Structural Equation Modeling techniques. The TPB model showed a good fit to the data, whereas the HBM showed a poor fit to the data. Within the TPB model, attitude and subjective norm were significant predictors of intentions to use a seat belt on both urban and rural roads. In the fourth sub-study, seat belt use frequency and motivations for seat belt use among taxi drivers were investigated and compared between free-time and work-time driving using a survey. The results showed that taxi drivers used seat belts more when driving a private car in their free-times compared to when driving a taxi during their work-times. The lack of a legal obligation to use a seat belt in city traffic and fear of being attacked or robbed by the passengers were found as two specific reasons for not using a seat belt when driving a taxi. Lastly, in the fifth sub-study, the relationship of seat belt use to driver and health behaviors was investigated using a survey. Although seat belt use was related both to health and driver behaviors, factor analysis results showed that it grouped with driver behaviors. Based on the results of the sub-studies, a tentative empirical model showing different predictors of seat belt use was proposed. According to the model, safety and normative motivations and perceived physical barriers related to seat belt use are the three important predictors of seat belt use. Keywords: Seat belt use; environmental factors; psycho-social factors; safety and normative motivations; the Theory of Planned Behavior; the Health Belief Model; health behaviors; driver behaviors; front-seat occupants; taxi drivers; Turkey.