Architecture, Building and Planning - Research Publications
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ItemThe Effectiveness of Sentiment Analysis for Detecting Fine-grained Service Quality(University of Auckland, 2019-09-21)Improving public transport relies on the development of appropriate tools for measuring and monitoring service quality. While there are several studies exploring perceived service quality, these works are mainly based on surveys, which are limited to a pre-defined period and do not enable to constantly observe and analyze the respond of passengers to different events. As a result, they may miss events affecting service quality in a transport hub. In contrast, social media feeds provide an opportunity to constantly look for events that may affect the service quality. However, in a confined geographic area like a transport hub, the sparsity of data considerably reduce the effectiveness of straight-forward event detection methods. In contrast to earlier works and in order to face these challenges, in this paper, we explore the effectiveness of sentiment analysis to detect events impacting perceived service quality in a confined location. Southern Cross Station, a major transport hub in Melbourne, Australia, is selected as a case study. Moreover, a statistical approach to combine and integrate sentiment-based and frequency-based event detection is proposed. Main findings confirm the effectiveness of sentiment analysis for detecting events affecting service quality in a transport hub. Additionally, the results prove that the proposed method can improve the sensitivity of event detection for events affecting service quality.
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ItemComparing the costs of pedestrian wayfinding heuristics across different urban network morphologies.(University of Auckland, 2019-09-21)During wayfinding, pedestrians do not always choose the shortest available route. Instead, route choices are guided by several well-known wayfinding strategies or heuristics. These heuristics minimize cognitive effort and usually lead to satisfactory route choices. The length of the route obtained from applying a wayfinding heuristic is dependent on the spatial arrangement or morphology of the urban pedestrian network. This study evaluates the cost of four popular wayfinding heuristics across nine different urban network morphologies. It observes that the cost of these wayfinding heuristics vary significantly and individually differently with morphology, supporting the assumption that people choose heuristics by environment.
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ItemRoad traffic injury in urban areas: understanding the complex city.(ICoRSI, 2019)Over the past 4 decades considerable efforts have been taken to mitigate the growing burden of road injury. With increasing urbanisation along with global mobility that demands not only safety but equitable, efficient and clean (reduced carbon footprint) transport, the responses to dealing with the burgeoning road traffic injury in low- and middle-income countries has become increasingly complex. In this paper, we apply unique methods to identify important strategies that could be implemented to reduce road traffic injury in the Asia and Pacific region; a region comprising large middle-income countries (China and India) that are currently in the throes of rapid motorization. Using a convolutional neural network approach, we classified cities around the world based on urban characteristics related to private motor vehicles and public transport networks. We then identified 689 cities situated within the Asia-Pacific region and assessed the global burden of disease attributed to road traffic injury for urban design clusters. The modelling identified 9 urban cluster types. The majority (64%) of cities in the Asia-Pacific region fall within Clusters 1 and 2 namely, urban form that is sparse with low capacity road infrastructure and limited public transport. Clusters 1 and 2 comprises cities predominantly from China and South Asia with many low- to middle-income cities that are in the throes of considerable urban development. Urban cluster types with both dense road networks (e.g., Clusters Intense and Cul de sac) and public transport (e.g., Clusters High Transit and Motor City) demonstrated lower rates of DALYs lost per 100,000 population for road traffic injury. This study demonstrates the utility of employing image recognition methods to discover new insights to better understand the complex city and how it relates to road traffic injury.
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