As the future of the world’s oil reserves becomes progressively more uncertain, it is becoming increasingly important that steps are taken to ensure that there are viable, attractive alternatives to travel by private motor vehicle. As with many of New Zealand’s major urban centres, Christchurch is still exceptionally reliant on private motor vehicles; although a significant proportion of the population indicate that they would like to cycle more, cycling is still an underutilised mode of transport. Following a series of fatal earthquakes that struck the city in 2010 and 2011, there has been the need to significantly redevelop much of the city’s horizontal infrastructure – subsequently providing the perfect platform for significant changes to be made to the road network. Many of the key planning frameworks governing the rebuild process have identified the need to improve Christchurch’s cycling facilities in order to boost cycling numbers and cyclist safety. The importance of considering future growth and travel patterns when planning for transport infrastructure has been highlighted extensively throughout literature. Accordingly, this study sought to identify areas where future cycle infrastructure development would be advantageous based on a number of population and employment projections, and likely future travel patterns throughout the city. Through the use of extensive GIS analysis, future population growth, employment and travel patterns for Christchurch city were examined in order to attain an understanding of where the current proposed major cycleways network could be improved, or extended. A range of data and network analysis were used to derive likely travel patterns throughout Christchurch in 2041. Trips were derived twice, once with a focus on simply finding the shortest route between each origin and destination, and then again with a focus on cyclist safety and areas where cyclists were unlikely to travel. It was found that although the proposed major cycleways network represents a significant step towards improving the cycling environment in Christchurch, there are areas of the city that will not be well serviced by the current proposed network in 2041. These include a number of key residential growth areas such as Halswell, Belfast and Prestons, along with a number of noteworthy key travel zones, particularly in areas close to the central city and key employment areas. Using network analysis, areas where improvements or extensions to the proposed network would be most beneficial were identified, and a number of potential extensions in a variety of areas throughout the city were added to the network of cycle ways. Although it has been found that filling small gaps in the network can have considerable positive outcomes, results from the prioritisation analysis suggested that initially in Christchurch demand is likely to be for more substantial extensions to the proposed major cycleways network.
The context of this study is the increasing need for public transport as issues over high private vehicle usage are becoming increasingly obvious. Public transport services need to compete with private transport to improve patronage, and issues with reliability need to be addressed. Bus bunching affects reliability through disruptions to the scheduled headways. The purpose of this study was to collect and analyse data to compare how travel time and dwell time vary, to explore the variation of key variables, and to better understand the sources of these variations. The Orbiter bus service in Christchurch was used as a case study, as it is particularly vulnerable to bus bunching. The dwell time was found to be more variable than travel time. It appeared the Canterbury earthquake had significantly reduced the average speeds for the Orbiter service. In 1964, Newell and Potts described a basic bus bunching theory, which was used as the basis for an Excel bus bunching model. This model allows input variables to vary stochastically. Random values were generated from four specified distributions derived from manually collected data, allowing variance across all bus platforms and buses. However the complexity resulted in stability and difficulty in achieving convergence, so the model was run in single Monte Carlo simulations. The outputs were realistic and showed a higher degree of bunching behaviour than previous models. The model demonstrated bunching phenomena that had not been observed in previous models, including spontaneously un-pairing, overtaking of buses delayed at platforms, and odd-numbered bunches of three buses. Furthermore, the study identified areas of further research for data collection and model development.
This study explores the impact post-earthquake images from Christchurch, New Zealand inserted into a task requiring sustained attention or vigilance have on performance, selfreports of task-focus, and cerebra activity using functional near-infrared spectroscopy (fNIRS). The images represent the current state of Christchurch; a city struggling to recover from devastating earthquakes that peaked in February, 2011, killing 185 people, injuring hundreds more and causing widespread and massive damage to infrastructure, land and building in the region. Crowdsourcing was used to gather a series of positive and negative photos from greater Christchurch to be employed in the subsequent experiment. Seventy-one Christchurch resident participants (51 women, 20 men) then took part in a vigilance task with the sourced images embedded to assess possible cognitive disruptions. Participants were randomly assigned to one of three conditions: embedded positive pictures, embedded negative pictures, or embedded scrambled image controls. Task performance was assessed with signal detection theory metrics of sensitivity A’ and β’’. Individuals viewing the positive images, relating to progress, rebuild, or aesthetic aspects within the city, were overall more conservative or less willing to respond than those in the other conditions. In addition, positive condition individuals reported lower task focus, when compared to those in the control condition. However, indicators of cerebral activity (fNIRS) did not differ significantly between the experimental groups. These results combined, suggest that mind wandering events may be being generated when exposed to positive post-earthquake images. This finding fits with recent research which indicates that mind-wandering or day dreaming tends to be positive and future oriented. While positive recovery images may initiate internal thoughts, this could actually prove problematic in contexts in which external attention is required. While the actual environment, of course, needs to recover, support agencies may want to be careful with employing positive recovery imagery in contexts where people actually should be paying attention to something else, like operating a vehicle or machinery.
School travel is a major aspect of a young person’s everyday activity. The relationship between the built environment that youth experience on their way to and from school, influences a number of factors including their development, health and wellbeing. This is especially important in low income areas where the built environment is often poorer, but the need for it to be high quality and accessible is greater. This study focusses on the community of Aranui, a relatively low income suburb in Christchurch, New Zealand. It pays particular attention to Haeata Community Campus, a state school of just under 800 pupils from year one through to year thirteen (ages 5-18). The campus opened in 2017 following the closure of four local schools (three primary and one secondary), as part of the New Zealand Government’s Education Renewal scheme following the Christchurch earthquakes of 2010/11. Dedicated effort toward understanding the local built environment, and subsequent travel patterns has been argued to be insufficiently considered. The key focus of this research was to understand the importance of the local environment in encouraging active school travel. The present study combines geospatial analysis, quantitative survey software Maptionnaire, and statistical models to explore the features of the local environment that influence school travel behaviour. Key findings suggest that distance to school and parental control are the most significant predictors of active transport in the study sample. Almost 75% of students live within two kilometres of the school, yet less than 40% utilise active transport. Parental control may be the key contributing factor to the disproportionate private vehicle use. However, active school travel is acknowledged as a complex process that is the product of many individual, household, and local environment factors. To see increased active transport uptake, the local environment needs to be of greater quality. Meaning that the built environment should be improved to be youth friendly, with greater walkability and safe, accessible cycling infrastructure.
