149 research outputs found
How does the design of landmarks on a mobile map influence wayfinding expertsâ spatial learning during a real-world navigation task?
Humans increasingly rely on GPS-enabled mobile maps to navigate novel environments. However, this reliance can negatively affect spatial learning, which can be detrimental even for expert navigators such as search and rescue personnel. Landmark visualization has been shown to improve spatial learning in general populations by facilitating object identification between the map and the environment. How landmark visualization supports expert usersâ spatial learning during map-assisted navigation is still an open research question. We thus conducted a real-world study with wayfinding experts in an unknown residential neighborhood. We aimed to assess how two different landmark visualization styles (abstract 2D vs. realistic 3D buildings) would affect expertsâ spatial learning in a map-assisted navigation task during an emergency scenario. Using a between-subjects design, we asked Swiss military personnel to follow a given route using a mobile map, and to identify five task-relevant landmarks along the route. We recorded expertsâ gaze behavior while navigating and examined their spatial learning after the navigation task. We found that expertsâ spatial learning improved when they focused their visual attention on the environment, but the direction of attention between the map and the environment was not affected by the landmark visualization style. Further, there was no difference in spatial learning between the 2D and 3D groups. Contrary to previous research with general populations, this study suggests that the landmark visualization style does not enhance expert navigatorsâ navigation or spatial learning abilities, thus highlighting the need for population-specific mobile map design solutions
Landmark Visualization on Mobile Maps â Effects on Visual Attention, Spatial Learning, and Cognitive Load during Map-Aided Real-World Navigation of Pedestrians
Even though they are day-to-day activities, humans find navigation and wayfinding to be cognitively challenging. To facilitate their everyday mobility, humans increasingly rely on ubiquitous mobile maps as navigation aids. However, the over-reliance on and habitual use of omnipresent navigation aids deteriorate humans' short-term ability to learn new information about their surroundings and induces a long-term decline in spatial skills. This deterioration in spatial learning is attributed to the fact that these aids capture users' attention and cause them to enter a passive navigation mode. Another factor that limits spatial learning during map-aided navigation is the lack of salient landmark information on mobile maps.
Prior research has already demonstrated that wayfinders rely on landmarksâgeographic features that stand out from their surroundingsâto facilitate navigation and build a spatial representation of the environments they traverse. Landmarks serve as anchor points and help wayfinders to visually match the spatial information depicted on the mobile map with the information collected during the active exploration of the environment. Considering the acknowledged significance of landmarks for human wayfinding due to their visibility and saliency, this thesis investigates an open research question: how to graphically communicate landmarks on mobile map aids to cue wayfinders' allocation of attentional resources to these task-relevant environmental features. From a cartographic design perspective, landmarks can be depicted on mobile map aids on a graphical continuum ranging from abstract 2D text labels to realistic 3D buildings with high visual fidelity. Based on the importance of landmarks for human wayfinding and the rich cartographic body of research concerning their depiction on mobile maps, this thesis investigated how various landmark visualization styles affect the navigation process of two user groups (expert and general wayfinders) in different navigation use contexts (emergency and general navigation tasks). Specifically, I conducted two real-world map-aided navigation studies to assess the influence of various landmark visualization styles on wayfinders' navigation performance, spatial learning, allocation of visual attention, and cognitive load.
In Study I, I investigated how depicting landmarks as abstract 2D building footprints or realistic 3D buildings on the mobile map affected expert wayfinders' navigation performance, visual attention, spatial learning, and cognitive load during an emergency navigation task. I asked expert navigators recruited from the Swiss Armed Forces to follow a predefined route using a mobile map depicting landmarks as either abstract 2D building footprints or realistic 3D buildings and to identify the depicted task-relevant landmarks in the environment. I recorded the experts' gaze behavior with a mobile eye-tracer and their cognitive load with EEG during the navigation task, and I captured their incidental spatial learning at the end of the task. The wayfinding experts' exhibited high navigation performance and low cognitive load during the map-aided navigation task regardless of the landmark visualization style. Their gaze behavior revealed that wayfinding experts navigating with realistic 3D landmarks focused more on the visualizations of landmarks on the mobile map than those who navigated with abstract 2D landmarks, while the latter focused more on the depicted route. Furthermore, when the experts focused for longer on the environment and the landmarks, their spatial learning improved regardless of the landmark visualization style. I also found that the spatial learning of experts with self-reported low spatial abilities improved when they navigated with landmarks depicted as realistic 3D buildings.
In Study II, I investigated the influence of abstract and realistic 3D landmark visualization styles on wayfinders sampled from the general population. As in Study I, I investigated wayfinders' navigation performance, visual attention, spatial learning, and cognitive load. In contrast to Study I, the participants in Study II were exposed to both landmark visualization styles in a navigation context that mimics everyday navigation. Furthermore, the participants were informed that their spatial knowledge of the environment would be tested after navigation. As in Study I, the wayfinders in Study II exhibited high navigation performance and low cognitive load regardless of the landmark visualization style. Their visual attention revealed that wayfinders with low spatial abilities and wayfinders familiar with the study area fixated on the environment longer when they navigated with realistic 3D landmarks on the mobile map. Spatial learning improved when wayfinders with low spatial abilities were assisted by realistic 3D landmarks. Also, when wayfinders were assisted by realistic 3D landmarks and paid less attention to the map aid, their spatial learning improved.
Taken together, the present real-world navigation studies provide ecologically valid results on the influence of various landmark visualization styles on wayfinders. In particular, the studies demonstrate how visualization style modulates wayfinders' visual attention and facilitates spatial learning across various user groups and navigation use contexts. Furthermore, the results of both studies highlight the importance of individual differences in spatial abilities as predictors of spatial learning during map-assisted navigation. Based on these findings, the present work provides design recommendations for future mobile maps that go beyond the traditional concept of "one fits all." Indeed, the studies support the cause for landmark depiction that directs individual wayfinders' visual attention to task-relevant landmarks to further enhance spatial learning. This would be especially helpful for users with low spatial skills. In doing so, future mobile maps could dynamically adapt the visualization style of landmarks according to wayfinders' spatial abilities for cued visual attention, thus meeting individuals' spatial learning needs
Nutzerzentrierte Indoor-Positionierung fĂŒr smartphonegestĂŒtzte FuĂgĂ€ngernavigation
ZuverlĂ€ssige Positionsbestimmung ist eine wichtige Voraussetzung fĂŒr Navigationssysteme, um am richtigen Ort und zur richtigen Zeit Assistenz leisten zu können. Im Gegensatz zu satellitengestĂŒtzter Positionierung in AuĂenbereichen existiert innerhalb von GebĂ€uden keine Ă€hnlich ubiquitĂ€r verfĂŒgbare Technologie. Diese Arbeit handelt von der Entwicklung eines Indoor-Positionierungssystems fĂŒr smartphonebasierte FuĂgĂ€ngernavigation, mit speziellem Fokus auf der BerĂŒcksichtigung von realem Nutzerverhalten.
Aufbauend auf dem Stand der Technik wird zunĂ€chst ein Basis-Positionierungssystem entwickelt, welches mithilfe eines Partikelfilters die Benutzerposition innerhalb eines graphbasierten Umgebungsmodells bestimmt. In zwei Vorstudien erfolgt anschlieĂend unter kontrollierten Bedingungen die Evaluation der grundlegenden FunktionalitĂ€t sowie mehrerer Erweiterungen zur Anpassung an Benutzereigenschaften.
Parallel dazu werden mithilfe der Campus-Navigations-App URwalking Nutzungsdaten erhoben, um das fĂŒr die Positionsbestimmung relevante Navigationsverhalten der BenutzerInnen unter realistischen Bedingungen zu untersuchen. Die Merkmale der abgerufenen Routen erlauben RĂŒckschlĂŒsse auf die wĂ€hrend der Navigation zu erwartenden BenutzeraktivitĂ€ten. Eine Studie an einer heuristisch gefilterten Untermenge des Datensatzes (N = 351) gibt unter anderem Aufschluss ĂŒber vorherrschende GerĂ€tepositionen sowie ĂŒber Pausen und Unterbrechungen im Navigationsvorgang.
Basierend auf diesen Erkenntnissen wird ein Datensatz erhoben, welcher Sensordaten fĂŒr eine Vielzahl von navigationsrelevanten AktivitĂ€ten und GerĂ€tepositionen enthĂ€lt. Dieser wiederum dient als Grundlage fĂŒr das Training von Deep-Learning-Modellen zur AktivitĂ€tserkennung. Nach Integration der AktivitĂ€tserkennungskomponente in das Basissystem wird die Positionierungsgenauigkeit wĂ€hrend eines Navigationstasks auf einer fĂŒr den realen Betrieb reprĂ€sentativen Route in einer abschlieĂenden Studie (N = 69) untersucht. Durch geschickte Nutzung der AktivitĂ€tsinformationen und gezielte BerĂŒcksichtigung menschlichen Verhaltens wĂ€hrend der Navigation bleibt die Positionsverfolgung hier auch ohne externe Infrastruktur lĂ€ngerfristig stabil
Adaptivity as a key feature of mobile maps in the digital era
Mobile maps are an important tool for mastering modern digital life. In this paper, we outline our perspective on the challenges and opportunities associated with designing adaptive mobile maps that are useful, usable, and accessible to a wide range of users in different contexts. If we claim for adaptive mobile maps to be successful, we need to expand our understanding of map use context, including the physical and digital spaces, user behavior, and individual differences. We identify key challenges, such as the scarcity of knowledge about mobile map use behavior, the need for effective adaptation methods and strategies, user acceptance of adaptive maps, and issues related to control, privacy, trust, and transparency. We finally suggest research opportunities, such as studying mobile map usage, employing AI-based adaptation methods, leveraging the power of visual communication through maps, and ensuring user acceptance through user control and privacy
The values of urban design - spatial models
Urban network morphometrics (UNeMos) is a research technique and a design decision aid in urban design. UNeMOS are network science-based configurational metrics of urban morphology that can inform urban designing decision-making, helping designers to discriminate between different 2D and 3D design options. However, some UNeMOS differ from the standard link/node network encoding by using a transport networkâs specific encoding, thus lacking usability in mainstream transport and transport geography and analytical power in 3D. There is also a lack of comparison between these encodings and whether the transport geography combination of standard encoding/closeness centrality analysis using Euclidean, angular, or combination thereof are as discriminant or more of urban design network layout in 2D and 3D. The commentary addresses this research gap by reflecting on how the research original contributions reported in the collected publications have deployed diverse combinations of transport network encoding and spatial models of distance to evaluate the values of transport network configuration. The commentary critically contextualises the publicationsâ original contributions with reference to a leading research question and a sub-question:
How well does UNeMOS, as a standard link/node spatial model and nonstandard spatial model, discriminate urban network configurations in 2D or 3D to capture urban design values?
The publications cover urban morphology, form, property pricing, transport planning, spatial distribution, high-density city areas, urban design, and network analysis. The publications demonstrate a deep understanding of various aspects of intra-urban and urban studies, including historical morphological roots, challenges for future research, and their practical applications in urban design and planning.
The methods employed in these studies involve a variety of quantitative and qualitative approaches. These include, among others, hedonic pricing modelling, multivariate models, road and metro network encoding, 2D and 3D spatial Design Network Analysis (sDNA) software, pedestrian standard path centre line network encoding, and value-based urban design. These methods have investigated the association between urban morphology, property prices, transport access, land-use resources, and pedestrian flows in contrasted urban contexts.
The approaches in the publications demonstrate a comprehensive understanding of the complexities and interdependencies in intra-urban and urban studies. The research explores various spatial scales, from local urban design to macro-meso transport planning, and investigates the relationship between outdoor and indoor 3D pedestrian networks in high-density urban areas.
Overall, the breadth and depth of the research in these publications and their original contributions showcase a strong foundation in intra-urban and urban studies, highlighting the importance of understanding urban environmentsâ spatial, socioeconomic, and morphological aspects for effective planning and design.
Summary of the publications and contributions:
Publication 1: Chiaradia, A., 2019. Urban Morphology/Urban Form. In: A. Orum, ed. The Wiley Blackwell Encyclopedia of Urban and Regional Studies. Hoboken, NJ: WileyBlackwell, pp. 1-6.
The paper contextualises and traces succinctly, from 1830 to 2019, the historical roots of urban morphology, including street network focus. The article provides a general introduction to critical concepts. Space syntax is contextualised as performative urban morphology and referenced to the early work of StĂŒbben (1911).
The main contribution is the identification of three key challenges for future research: epistemological embedding, qualitative ontology, and a unified approach that bridges descriptive/explanatory and prescriptive/normative aspects.
Publication 2: Chiaradia, A.*, Hillier, B., Schwander, C. and Barnes, Y., 2013.
Compositional and urban form effects on residential property value patterns in Greater London. Proceedings of the Institution of Civil Engineers-Urban Design and Planning, 166(3), pp.176-199.
This research used a hedonic pricing modelling framework. The road network encoding uses standard road centre line encoding transformed by space syntax software and centralities metrics quantitative spatial characterisation of road network shape/accessibility to investigate the association with property price of a large sample of adjacent properties (â100,000). Findings are aligned with extant theory related to the hedonic modelling of the residential property price; dwelling size is the most important.
The research reveals the importance of road network shape and accessibility characteristics in determining residential property prices in Greater London. The main contribution is the identification of two spatial scales associated with property prices: a local urban design scale (= 2,000 m).
Publication 3: Chiaradia, A.*, Hillier, B., Schwander, C. and Wedderburn, M., 2012. Compositional and urban form effects on centres in Greater London. Proceedings of the Institution of Civil Engineers-Urban Design and Planning, 165(1), pp.21-42.
This research used a multi-variate model, using standard road centre line encoding transformed by space syntax software and centralities metrics quantitative spatial characterisation of road network shape/accessibility and socio-economic variables to investigate the association with commercial rental values of a large sample of commercial property located in designated sub-centres.
Findings show that a sub-centre can be spatially distinguished from its non-centre surroundings. A sub-centrality spatial signature: sub-centre spatial and socio-economic typology are identified. Of the two main space syntax spatial variables associated with the sub-centres signatures, one would be the remit or urban design (local spatial scale, walking scale <= 800 m) and the other (meso-scale, <= 2,000 m) would be the remit of transport planning.
Publication 4: Zhang, L., Chiaradia, A.* & Zhuang, Y. A., 2015. Configurational Accessibility Study of Road and Metro Network in Shanghai. In: Q. Pan & J. Cao, eds. Recent Developments in Chinese Urban Planning. Heidelberg: Springer, pp. 219-245.
This research deployed standard road centre line encoding, metro network topological encoding and 2D spatial Design Network Analysis (sDNA) software quantitative spatial characterisation of road network and metro network shape/accessibility to investigate the probability density function of spatial distribution of metro system access points, bus access points and commercial land use in a Mega City.
The research shows the uneven spatial distribution of metro access points, bus access points, and commercial land use in Shanghai, with 60-70% associated with the top three deciles of road and metro network shape/accessibility. The main contribution is the comprehensive analysis of the spatial distribution of transport and land-use resources in a mega-city context.
Publication 5: Zhang, L. & Chiaradia, A.*, 2019. Three-dimensional Spatial Network Analysis and Its Application in a High Density City Area, Central Hong Kong (In Chinese). Urban Planning International, 33(1), pp. 46-53.
This research used 3D pedestrian standard path centre line network encoding and 3D sDNA software quantitative spatial characterisation of outdoor and indoor multi-level pedestrian network shape/accessibility to investigate their association with pedestrian flow level in one of the most complex multi-level-built environments.
The research reveals a high association between the standard spatial characterisation of outdoor and indoor multi-level pedestrian network shape/accessibility and pedestrian flow levels in a complex built environment. The main contribution is the demonstration of the interdependence between outdoor and indoor pedestrian networks in a high-density urban context.
Publication 6: Chiaradia, A.*, Sieh, L. and Plimmer, F., 2017. Values in urban design: A design studio teaching approach. Design Studies, 49, pp. 66-100.
The paper refers to physical configurations in general and the movement network that UNeMos are measuring. It articulates a theoretical bridge between the technicalities of measuring urban morphology and the creative application of resulting insights about the impact of any proposed, designed urban shape on the performance of the urban âplaceâ of which it is a part. The basis of the bridge is the concept of value. This is not simply âpriceâ but an interdisciplinary social scientific compound construct inspired by an extensive anthropological meta-review of value: âthat which matters, and the extent to which that matters.â
The research establishes a theoretical bridge between urban morphology measurement and urban design creativity through the concept of value, which is adapted from Graeberâs general conceptualisation. The main contribution is developing a value-based approach to urban design, as demonstrated through the analysis of student work in an urban design studio.
Publication 7: Chiaradia, A., Cooper, C., Webster, C., 2011, spatial Design Network Analysis Software, & Cooper, C.H. and Chiaradia, A.J., 2020. sDNA: 3D spatial network analysis for GIS, CAD, Command Line & Python. SoftwareX, 12, p.100525.
Spatial Design Network Analysis (sDNA) is a toolbox for 2D and 3D spatial network analysis, especially street/path/urban network analysis, motivated by a need to use standard network links/nodes as the principal unit of analysis to analyse existing and projected network data. sDNA is usable from QGIS & ArcGIS geographic information systems, AutoCAD, Rhino Gh, and the command line via its own Python API. It computes measures of accessibility (reach, mean distance/closeness centrality, gravity), flows (bidirectional betweenness centrality) and efficiency (circuity) as well as convex hull properties, localised within lower- and upper-bounded radial bands. Weighting is flexible and can use geometric properties, data attached to links, zones, matrices or combinations of the above. Motivated by a desire to base network analysis on route choice and spatial cognition, distance can be network-Euclidean, angular, a mixture of both, custom, or specific to cyclists (avoiding slope and motorised traffic). In addition to statistics on network links, the following outputs can be computed: geodesics, network buffers, accessibility maps, convex hulls, flow bundles and skim matrices.
Further tools assist with network preparation and calibration of network models to observed data. To date, sDNA has been used mainly for urban network analysis by academics and city planners/engineers for tasks including predicting pedestrian, cyclist, vehicle and metro flows and mode choice and quantifying the built environment for epidemiology and urban planning & design. The main contribution is developing a user-friendly and flexible software tool that supports various types of 3D network analysis, including accessibility, flows, efficiency measures, and various output formats and tools.
The commentary critically introduces, compares, and analyses various spatial models of distance using the closeness centrality of a network, combinations of transport network encoding and topological, Euclidean, angular and hybrid distances for their capacity and limitations to discriminate transport network layout. It contextualised the issues related to how and what could be âcounted so as to reveal the differences between one settlement structure and another?â (Hillier & Hanson, 1984) in 2D or 3D to capture urban design values.
The main findings are as follows:
âą Topologic distance is inferior at measuring and discriminating distinct layout configurations of the transport networks.
âą To a very good extent, Euclidean distance measures and discriminates distinct layout configurations of transport networks, yet mainly grid-like layout.
âą Angular distance remedies the issues of Euclidean distance related to a deformed grid yet introduces errors that can be resolved by Hybrid distance.
The link/node model of encoding transport network combined with closeness centrality of the network using spatial models of distance seems valid in discriminating distinct layout configurations of 2D and 3D transport networks. The publicationsâ original contributions demonstrate that these techniques empirically capture 2D and 3D urban design values
Play Among Books
How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an âinfinite flowâ of real books
Uncovering Pacific Pasts
Objects have many stories to tell. The stories of their makers and their uses. Stories of exchange, acquisition, display and interpretation. This book is a collection of essays highlighting some of the collections, and their object biographies, that were displayed in the Uncovering Pacific Pasts: Histories of Archaeology in Oceania (UPP) exhibition. The exhibition, which opened on 1 March 2020, sought to bring together both notable and relatively unknown Pacific material culture and archival collections from around the globe, displaying them simultaneously in their home institutions and linked online at www.uncoveringpacificpasts.org. Thirtyâeight collecting institutions participated in UPP, including major collecting institutions in the United Kingdom, continental Europe and the Americas, as well as collecting institutions from across the Pacific
Indoor Positioning and Navigation
In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot
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