Investigating the link between transit oriented development and sustainable travel behavior in Brisbane : a case-control study

The purpose of this research is to empirically test the prevailing view that transit oriented development enhances the use of more sustainable modes of transport using Brisbane, Australia as a case. Transit oriented development has been adopted as a new policy tool to reduce car-based travel worldwide. Despite being a billion dollar investment, the impacts of transit oriented development on promoting sustainable travel behavior is not conclusive. The research uses a case-control approach to empirically investigate this relationship based on travel behavior data collected from 88 individuals living in two contrasting neighborhoods in Brisbane: Kelvin Grove Urban Village – a transit oriented development, and Annerley – a traditional suburb (non-transit oriented development). A comparative investigation of travel behavior was subsequently conducted using distance travelled by modes and purposes between the neighborhoods. Results show that the availability of opportunity and services located within the transit oriented development reduces the car use by 5% and increases the use of active transport by 4%. The findings in this research support the implementation of TOD policies in Brisbane.

Do dissonants in transit oriented development adjust commuting travel behaviour?

Residential dissonance signifies a mismatch between an individual’s preferred and actual proximal land use patterns in residential neighbourhoods, whereas residential consonance signifies agreement between actual and preferred proximal land uses. Residential dissonance is a relatively unexplored theme in the literature, yet it acts as a barrier to the development of sustainable transport and land use policy. This research identifies mode choice behaviour of four groups living in transit oriented development (TOD) and non-TOD areas in Brisbane, Australia using panel data from 2675 commuters: TOD consonants, TOD dissonants, non-TOD consonants, and non-TOD dissonants. The research investigates a hypothetical understanding that dissonants adjust their travel attitudes and perceptions according to their surrounding land uses over time. The adjustment process was examined by comparing the commuting mode choice behaviour of dissonants between 2009 and 2011. Six binary logistic regression models were estimated, one for each of the three modes considered (e.g. public transport, active transport, and car) and one for each of the 2009 and 2011 waves. Results indicate that TOD dissonants and non-TOD consonants were less likely to use the public transport and active transport; and more likely to use the car compared with TOD consonants. Non-TOD dissonants use public transport and active transport equally to TOD consonants. The results suggest that commuting mode choice behaviour is largely determined by travel attitudes than built environment factors; however, the latter influence public transport and car use propensity. This research also supports the view that dissonants adjust their attitudes to surrounding land uses, but very slowly. Both place (e.g. TOD development) and people-based (e.g. motivational) policies are needed for an effective travel behavioural shift.

Workers' attitude towards bus rapid transit : considering Dhaka, Bangladesh

The Government of Bangladesh is planning to develop and implement Bus Rapid Transit (BRT) in Dhaka city. This paper presents a stated choice survey conducted to understand workers’ attitudes toward BRT in Dhaka. The survey data are analysed using a multinomial logit (MNL) model to scrutinize social and economic factors’ impact on participant’s mode choices. Analysis results reveal that males, and workers with higher age, education qualification, and income have greater tendency towards choosing BRT.

Workers' attitude towards bus rapid transit in Dhaka, Bangladesh

This study investigates: –how travel and socio-demographic attributes act on workers’ mode choice decisions in Dhaka –whether Dhaka’s commuters would choose BRT for their work trip once implemented •Very limited research exists on users’ perceptions of BRT in developing countries’ megacities •We adopted a discrete choice modelling approach •As BRT has not yet been implemented in Dhaka, we collected Stated Choice (SC) survey data including a hypothetical BRT mode to understand factors important to workers’ mode choice decisions •We compare the impact of travel factors between Dhaka and cities of developed countries

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.

Effects of transit quality of service characteristics on daily bus ridership

This study explores how explicit transit quality of services (TQoS) measures including service frequency, service span, and travel time ratio, along with implicit environmental predictors such as topographic grade factor influence bus ridership using a case study city of Brisbane, Australia. The primary hypothesis tested was that bus ridership is higher within suburbs with high transit quality of service than suburbs that have limited service quality. Using Multiple Linear Regression (MLR) this study identifies a strong positive relationship between route intensity (bus-km/h-km2) and bus ridership, indicating that increasing both service frequency and spatial route density correspond to higher bus ridership. Additionally, travel time ratio (in-vehicle transit travel time to in-vehicle auto travel time) is also found to have significant negative association with ridership within a suburb, reflecting a decline in transit use with increased travel time ratio. Conversely, topographic grade and service span are not found to exert any significant impact on bus ridership in a suburb. Our study findings enhance the fundamental understanding of traveller behaviour which is informative to urban transportation policy, planning and provision.

Effects of transit quality of service characteristics on daily bus ridership

This study investigates whether an Australian city’s suburbs having high transit Quality of Service (QoS) are associated with higher transit ridership than those having low transit QoS •We explore how QoS measures including service frequency, service span, service coverage, and travel time ratio, along with implicit environmental predictors such as topographic grade factor influence bus ridership •We applied Multiple Linear Regression (MLR) to examine the relationship between QoS and ridership •Its outcomes enhance our understanding of transit user behavior, which is informative to urban transportation policy, planning, and provision

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

Response of segmented bored transit tunnels to surface blast

Increasing threat of terrorism highlights the importance of enhancing the resilience of underground tunnels to all hazards. This paper develops, applies and compares the Arbitrary Lagrangian Eulerian (ALE) and Smooth Particle Hydrodynamics (SPH) techniques to treat the response of buried tunnels to surface explosions. The results and outcomes of the two techniques were compared, along with results from existing test data. The comparison shows that the ALE technique is a better method for describing the tunnel response for above ground explosion with regards to modeling accuracy and computational efficiency. The ALE technique was then applied to treat the blast response of different types of segmented bored tunnels buried in dry sand. Results indicate that the most used modern ring type segmented tunnels were more flexible for in-plane response, however, they suffered permanent drifts between the rings. Hexagonal segmented tunnels responded with negligible drifts in the longitudinal direction, but the magnitudes of in-plane drifts were large and hence hazardous for the tunnel. Interlocking segmented tunnels suffered from permanent drifts in both the longitudinal and transverse directions. Multi-surface radial joints in both the hexagonal and interlocking segments affected the flexibility of the tunnel in the transverse direction. The findings offer significant new information in the behavior of segmented bored tunnels to guide their future implementation in civil engineering applications.

Frequency independence of ultrasound transit time spectroscopy

Recent studies have shown that ultrasound transit time spectroscopy (UTTS) is an alternative method to describe ultrasound wave propagation through complex samples as an array of parallel sonic rays. This technique has the potential to characterize bone properties including volume fraction and may be implemented in clinical systems to predict osteoporotic fracture risk. In contrast to broadband ultrasound attenuation, which is highly frequency dependent, we hypothesise that UTTS is frequency independent. This study measured 1 MHz and 5 MHz broadband ultrasound signals through a set of acrylic step-wedge samples. Digital deconvolution of the signals through water and each sample was applied to derive a transit time spectrum. The resulting spectra at both 1 MHz and 5 MHz were compared to the predicted transit time values. Linear regression analysis yields agreement (R2) of 99.23% and 99.74% at 1 MHz and 5 MHz respectively indicating frequency independence of transit time spectra.

Understanding the effects of complex seasonality on suburban daily transit ridership

Fluctuations in transit ridership pattern over the year have always concerned transport planners, operators and researchers. Predominantly, metrological elements have been specified to explain variability in ridership volume. However, the outcome of this research points to new direction to explain ridership fluctuation in Brisbane. It explored the relationship between daily bus ridership, seasonality and weather variables for a one-year period, 2012. Rather than segregating the entire year’s ridership into the four calendar seasons (summer, autumn, spring, and winter), this analysis distributed the yearly ridership into nine complex seasonality blocks. These represent calendar season, school/university (academic) period and their corresponding holidays, as well as other observant holidays such as Christmas. The dominance of complex seasonality over typical calendar season was established through analysis and using Multiple Linear Regression (MLR). This research identified a very strong association between complex seasonality and bus ridership. Furthermore, an expectation that Brisbane’s subtropical summer is unfavourable to transit usage was not supported by the findings of this study. A nil association of precipitation and temperature was observed in this region. Finally, this research developed a ridership estimation model, capable of predicting daily ridership within very limited error range. Following the application of this developed model, the estimated annual time series data of each suburb was analysed using Fourier Transformation to appreciate whether any cyclical effects remained, compared with the original data.