Ride-sourcing compared to its public-transit alternative using big trip data

Ride-sourcing risks increasing\ua0GHG emissions\ua0by replacing public transit (PT) for some trips therefore, understanding the relation of ride-sourcing to PT in urban mobility is crucial. This study explores the competition between ride-sourcing and PT through the lens of big data analysis. This research uses 4.3 million ride-sourcing trip records collected from Chengdu, China over a month, dividing these into two categories, transit-competing (48.2%) and non-transit-competing (51.8%). Here, a ride-sourcing trip is labelled transit-competing if and only if it occurs during the day and there is a PT alternative such that the walking distance associated with it is less than 800\ua0m for access and egress alike. We construct a glass-box model to characterise the two ride-sourcing trip categories based on trip attributes and the built environment from the enriched trip data. This study provides a good overview of not only the main factors affecting the relationship between ride-sourcing and PT, but also the interactions between those factors. The built environment, as characterised by points of interest (POIs) and transit-stop density, is the most important aspect followed by travel time, number of transfers, weather, and a series of interactions between them. Competition is more likely to arise if: (1) the travel time by ride-sourcing <15\ua0min or the travel time by PT is disproportionately longer than ride-sourcing; (2) the PT alternative requires multiple transfers, especially for the trips happening within the transition area between the central city and the outskirts; (3) the weather is good; (4)\ua0land use\ua0is high-density and high-diversity; (5) transit access is good, especially for the areas featuring a large number of business and much real estate. Based on the main findings, we discuss a few recommendations for transport planning and policymaking

Modelling the Interactions between Information and Communication Technologies and Travel Behaviour

The growing capabilities and widespread proliferation of information and communication technologies (ICT) into virtually every aspect of lifestyle, combined with the continuing challenges faced by transport systems, has ensured ongoing interest in the interactions between ICT and travel behaviour. Yet, despite more than three decades of efforts to understand these relationships, few point of consensus have so far emerged, partly due to the rapidly evolving character of ICT, and partly due to the inherent complexity of such interactions. This thesis seeks to develop novel understandings of such interactions by introducing a number of extensions to the existing modelling frameworks. This is achieved through three interrelated research objectives which seek to explore the topic from macro, micro, and temporal perspectives. The macro perspective takes the form of a structural equation analysis of the relationships between ICT use and travel behaviour across four countries: Canada, the United States, the United Kingdom, and Norway, with the data for the latter three obtained by pooling separate datasets on ICT use and travel behaviour. The micro perspective seeks to develop a microeconomic model of an individual maximising utility through joint choice of activities, including in-travel activities, ICT use, as well as the choice of travel mode, timing and route, with the decisions motivated by contribution towards satisfaction, productivity, and consumption. The model is subsequently tested in the empirical contexts of rail business travel time, business travel time valuation, and conceptualisation of the ICT and travel behaviour interaction scenarios reported elsewhere in the literature. The final, temporal perspective analyses the comparatively least explored topic of evolution in the relationships between ICT use and travel behaviour over time. This is achieved by analysing repeated cross-sectional data using structural equation modelling, and interpreted with reference to the theory of diffusion of innovations. The thesis also discusses a number of potential research, policy and industrial applications of its empirical and theoretical contributions.Open Acces

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity