Caitlin Cottrill

Transportation is a spatial activity. The geographic Information System (GIS) is the process of capturing, managing, analyzing, and presenting spatial data. GIS techniques are essential to the study of various aspects of transportation. In this entry, the state of knowledge regarding atomized transportation modes is presented. Atomized transportation modes are defined as transportation modes which deal with low passenger numbers.

A number of governmental and nongovernmental organizations have made significant efforts to encourage the development of artificial intelligence in line with a series of aspirational concepts such as transparency, interpretability, explainability, and accountability. The difficulty at present, however, is that these concepts exist at a fairly abstract level, whereas in order for them to have the tangible effects desired they need to become more concrete and specific. This article undertakes precisely this process of concretisation, mapping how the different concepts interrelate and what in particular they each require in order to move from being high-level aspirations to detailed and enforceable requirements. We argue that the key concept in this process is accountability, since unless an entity can be held accountable for compliance with the other concepts, and indeed more generally, those concepts cannot do the work required of them. There is a variety of taxonomies of accountability in the literature. However, at the core of each account appears to be a sense of “answerability”; a need to explain or to give an account. It is this ability to call an entity to account which provides the impetus for each of the other concepts and helps us to understand what they must each require.

Active travel (AT) has the potential to integrate with, or in some cases substitute for, trips taken by motorized transportation. In this paper we review relevant research on AT outcomes to address the potential of AT and emerging data sources in supporting the transport paradigm shift toward AT. Our analysis identifies physical, mental, built and physical environmental, monetary, and societal outcomes. Traditional methods used to acquire AT data can be divided into manual methods that require substantial user input and automated methods that can be employed for a lengthier period and are more resilient to inclement weather. Due to the proliferation of information and communication technology, emerging data sources are prevailing and can be grouped into social fitness networks, in-house developed apps, participatory mapping, imagery, bike sharing systems, social media, and other types. We assess the emerging data sources in terms of their applications and potential limitations. Furthermore, we identify developing policies and interventions, the potential of imagery, focusing on non-cycling modes and addressing data biases. Finally, we discuss the challenges of data ownership within emerging AT data and the corresponding directions for future work.

Given the numerous benefits of active travel (human-powered transportation), in this paper, we argue that using crowdsourced data and a spatial heterogeneity treatment enhances the predictive performance of data modelling. Using such an approach thus increases the amount of insight that can be obtained to improve active travel decision-making. In particular, we model cyclists’ route choices using data on cycling trips and street network centralities obtained from Strava and OSMnx, respectively. It was found that: i) the number of cyclist trips is spatially clustered; and ii) the spatial error model exhibits a better predictive performance than spatial lag and ordinary least squares models. The results demonstrate the ability of the fine-grained resolution of crowdsourced data to provide more insights on active travel compared to traditional data.

As Internet of Things (IoT) technologies become embedded in public infrastructure, it is important that we consider how they may introduce new challenges in areas such as privacy and governance. Public technology implementations can be more democratically developed by facilitating citizen participation during the design process, but this can be challenging. This work demonstrates a novel method for participatory research considering the privacy implications of IoT deployments in public spaces, through the use of worldbuilding design fictions. Using three fictional contexts and their associated tangible design fiction objects, we report on findings to inform transparency and governance in public space IoT deployments.