Content uploaded by Matt Duckham
Author content
All content in this area was uploaded by Matt Duckham
Content may be subject to copyright.
A preview of the PDF is not available
Including landmarks in routing instructions
Abstract and Figures
This article addresses the problem of incorporating cognitively salient landmarks in computer-generated navigation instructions. On the basis of a review of the existing literature in the domain of navigation with landmarks, the article develops algorithms for generating routing instructions that include references to landmarks. The most basic algorithm uses a new weighting model to annotate simple routes with references to landmarks. A key novel feature of this algorithm is that it depends only on commonly available data and generic capabilities of existing web mapping environments. A suite of extensions are also proposed for improving the cognitive ergonomics of the basic landmark instructions. A case study, implemented within a national online routing system, demonstrates practicality of the approach. The article then concludes by reviewing a range of further issues for future work.
Figures - uploaded by Matt Duckham
Author content
All figure content in this area was uploaded by Matt Duckham
Content may be subject to copyright.
... Filomena and Verstegen (2021) define landmarks as "fixed environmental features that are known and remembered for their distinctiveness within a specific environment". Duckham et al. (2010) argue that people imagine the city by using cognitively salient elements and landmarks are considered one such element. Moreover, Richter and Winter (2014) conclude that landmarks form cognitive anchors, marks or reference points for orientation, wayfinding and communication. ...
... Dong et al. (2020) present a quantitative method (computer vision model) to compare the roles of landmarks' visual salience and semantic salience. At the same time, Raubal and Winter (2002), Duckham et al. (2010) and Quesnot and Roche (2015) also compute landmarks salience by using models. In contrast, this research followed a qualitative research approach. ...
The concepts of imageability and legibility are important aspects of urban design. Many scholars use the terms “imageability” and “legibility” interchangeably, usually examining one concept and applying the implications to the other. This research explores the relationship between these two concepts by answering the research questions: 1. how do people perceive the saliency of landmarks (imageability) and 2. how does the spatial configuration facilitate the visibility level of landmarks (legibility)? The Galle Heritage City in Sri Lanka is considered as the case study. The first part of the empirical study is to assess the level of imageability of urban space users by completing 100 cognitive maps and producing a composite cognitive map that indicates the structural landmarks’ salience or the level of imageability. The second part is the level of legibility of the landmarks by employing the visibility assessment process and the third part compares the two results with a concurrence matrix. The findings highlight that there is a positive relationship between people’s perception (imageability) and level of visibility (legibility). Further, imageability mostly depends on semantic properties than legibility, but legibility predominantly depends on structural properties and visual properties are almost equally important to both concepts.
... Such features can be extracted in various ways, either through intuitive visual information (e.g., sign or billboard of a well-known brand/shop) or indirectly through other data sources (e.g., geographic information data or social media data). For example, POIs are geospatial objects that carry semantic information in the environment and play an important role in navigation and spatial cognition tasks (Duckham, Winter, & Robinson, 2010;Quesnot & Roche, 2015). In particular, those well-known POIs with prominent historical, economic-social, and cultural features, such as famous and influential commercial brands, companies, stores, restaurants, social organizations, and institutions, are more likely to attract people's attention and effectively contribute to the perception and understanding of the streetscape environment. ...
The complexity of urban physical environments at road intersections is a primary factor characterizing the difficulty of wayfinding, which is a fundamental spatial activity of human beings in cities. A complex intersection may increase the difficulty of understanding the environment, which may result in incorrect turning decisions and even bring road safety issues. Existing methods measure the complexity of road intersections by solely considering their visual or structural features. More importantly, they only output a single complexity value for each intersection, failing to differentiate the decision-making complexity based on the specific entry/exit branches of a passing branches. This study proposes a computational model to quantify the fine-grained decision-making complexity of road intersections for the navigation data models and navigation systems based on specific passing branches, using the visual, structural, and semantic features from human perspectives. For each pair of two branches (i.e., one entry and one exit) passing through the road intersection, the model will output a specific decision-making complexity score. Furthermore, this study develops a route planning algorithm for generating the minimum complexity route to serve relevant navigation applications. This study contributes to human-centered route planning and communication, as well as enabling potential innovative applications in traffic safety studies and sustainable urban and environmental development.
... More recently, attention has also been drawn to reduce the adverse effects of GPS-enabled navigation aids on spatial learning, e.g., by geographic information scientists (GIScientists) (Wenig et al., 2017), cognitive scientists (Ruginski et al., 2019), and map user interface (UI/UX) designers (Ricker and Roth, 2018;Thrash et al., 2019;Li, 2020;Fabrikant, 2022). Among the ideas proposed, the appropriate inclusion and display of landmarks on GPS-enabled mobile maps has gained particular traction among cartographers and navigation researchers in GIScience (Raubal and Winter, 2002;Duckham et al., 2010;Credé et al., 2020;Keil et al., 2020;Liu et al., 2022). ...
The continuous assessment of pedestrians’ cognitive load during a naturalistic mobile map-assisted navigation task is challenging because of limited experimental control over stimulus presentation, human-map-interactions, and other participant responses. To overcome this challenge, the present study takes advantage of navigators’ spontaneous eye blinks during navigation to serve as event markers in continuously recorded electroencephalography (EEG) data to assess cognitive load in a mobile map-assisted navigation task. We examined if and how displaying different numbers of landmarks (3 vs. 5 vs. 7) on mobile maps along a given route would influence navigators’ cognitive load during navigation in virtual urban environments. Cognitive load was assessed by the peak amplitudes of the blink-related fronto-central N2 and parieto-occipital P3. Our results show increased parieto-occipital P3 amplitude indicating higher cognitive load in the 7-landmark condition, compared to showing 3 or 5 landmarks. Our prior research already demonstrated that participants acquire more spatial knowledge in the 5- and 7-landmark conditions compared to the 3-landmark condition. Together with the current study, we find that showing 5 landmarks, compared to 3 or 7 landmarks, improved spatial learning without overtaxing cognitive load during navigation in different urban environments. Our findings also indicate a possible cognitive load spillover effect during map-assisted wayfinding whereby cognitive load during map viewing might have affected cognitive load during goal-directed locomotion in the environment or vice versa. Our research demonstrates that users’ cognitive load and spatial learning should be considered together when designing the display of future navigation aids and that navigators’ eye blinks can serve as useful event makers to parse continuous human brain dynamics reflecting cognitive load in naturalistic settings.
... It showcases that real-time route calculation is tractable in a client server framework with several thousand requests per day, many of them concurrently. For routing instructions, URWalking according to recent findings in the literature [1,5,12,26] generates instructions incorporating the most salient landmark close to the user. The instructions are generated completely automatically by inspecting their properties for being visible in advance [13,22]. ...
In this report, we present the project URWalking conducted at the University of Regensburg. We describe its major outcomes: Firstly, an indoor navigation system for pedestrians as a web application and as an Android app with position tracking of users in indoor and outdoor environments. Our implementation showcases that a variant of the $$A^*$$ A ∗ -algorithm by Ullmann (tengetriebene optimierung präferenzadaptiver fußwegrouten durch gebäudekomplexe https://epub.uni-regensburg.de/43697/ , 2020) can handle the routing problem in large, levelled indoor environments efficiently. Secondly, the apps have been used in several studies for a deeper understanding of human wayfinding. We collected eye tracking and synchronized video data, think aloud protocols, and log data of users interacting with the apps. We applied state-of-the-art deep learning models for gaze tracking and automatic classification of landmarks. Our results indicate that even the most recent version of the YOLO image classifier by Redmon and Farhadi (olov3: An incremental improvement. arXiv, 2018) needs finetuning to recognize everyday objects in indoor environments. Furthermore, we provide empirical evidence that appropriate machine learning models are helpful to bridge behavioural data from users during wayfinding and conceptual models for the salience of objects and landmarks. However, simplistic models are insufficient to reasonably explain wayfinding behaviour in real time—an open issue in GeoAI. We conclude that the GeoAI community should collect more naturalistic log data of wayfinding activities in order to build efficient machine learning models capable of predicting user reactions to routing instructions and of explaining how humans integrate stimuli from the environment as essential information into routing instructions while solving wayfinding tasks. Such models form the basis for real-time wayfinding assistance.
... Mental maps to support wayfinding (Downs & Stea, 1973;Golledge, 1999;Lynch, 1960;Meilinger, 2008;Siegel & White, 1975) (Hannes et al., 2012;Kuipers, 1978;McDermott & Davis, 1984) Computational models of mental maps (Duckham et al., 2010;Quesnot & Roche, 2015;Sadeghian & Kantardzic, 2008) Computational models of landmark salience ...
Spatial language incorporates descriptions of locations, routes, and landscapes, and is used by humans daily. Research has addressed a wide range of aspects of spatial language, including its form; the ways in which it is selected and applied; and cognitive, geometric, and functional factors affecting its use. Furthermore, much work has been done on the automation of spatial language extraction, analysis, interpretation, and generation. To introduce the Special Issue on this broad topic, this paper reviews spatial language research framed by an extension to the well-known semantic triangle, the “spatial semantic pyramid,” which represents both human spatial language and relevant computational research. By introducing it, we hope to stimulate discussion about gaps and future directions in this important research field.
... Landmarks can take different forms such as sculptures and distinct interior decorations. Large-size wall-mounted pictures have been successfully applied as landmarks in multiple previous studies (Balaban et al., 2017;Caduff & Timpf, 2008;Duckham et al., 2010;Fellner et al., 2017) and, therefore, were used in this research. The pictures were of two different sizes-3.6 ...
Objective
This study examined the influences of healthcare facility interior features on users’ wayfinding performance and the relationship between stress and wayfinding.
Background
General hospitals in China always present significant wayfinding problems due to their sizes and complexity. Poor wayfinding often leads to a frustrating and stressful user experience. It has not been fully understood how hospital indoor features affect wayfinding and whether an individual’s stress levels are associated with wayfinding performance.
Method
We conducted an experiment in which 117 college students, aged 18–33 ( M = 21.88, SD = 3.01), performed two tasks in virtual reality environments of outpatient clinics. Stress (skin conductance response) and wayfinding performance (distance ratio and time ratio) were measured. Participants’ sense of orientation, navigation ability, distance estimation, and spatial anxiety were captured by a survey.
Results
Male participants reported a significantly better sense of orientation and less spatial anxiety than females. Participants’ stress levels were lower with outdoor window views compared to those without outdoor views. With more environmental features (landmarks and outdoor window views) added to the environments, participants showed significantly better wayfinding performance. No significant relationship was found between wayfinding performance and participants’ stress levels in this study.
Conclusion
While individual environmental factors might not have a significant influence, combining multiple elements such as window views and landmarks could lead to better wayfinding performance. More research is needed to examine the relationship between stress and wayfinding.
... They build auxiliary graphs and use a standard shortest route algorithm to find an optimal route. Duckham, Winter, and Robinson (2010) develop an algorithm for the generation of route instructions with references to landmarks. They use a weighting model to annotate simple routes with landmark references. ...
Landmarks play an important role in spatial cognition, and therefore should be considered as a part of pedestrian navigation. This research addressed the question of human preference for landmark routes that are generated based on landmarks over shortest-distance optimized routes. We investigated whether there are differences regarding navigation behavior, navigation satisfaction, route memorization, route communication, and route comparison between the shortest and the landmark route. We did not observe any differences for navigation behavior, route memorization, and route communication. We observed that for the landmark route the participants were significantly faster in reversing the route. Generally, we found out that the participants were more satisfied with the shortest route and preferred the shortest route. We found hints that this might result from environmental parameters, which seemed to have an impact on navigation satisfaction. Additionally, the participants perceived the routes to be longer than they really were.
Although numerous studies have shown that landmarks are important for navigation, almost all navigation systems implement a shortest-route algorithm without considering landmarks. Which options do we have to integrate landmarks into a route calculation? How would the resulting routes differ from shortest routes? We propose a weighting method for Dijkstra’s shortest route algorithm to generate “landmark routes” and compare them to their corresponding shortest routes. We show that the extra distance and time needed to walk the landmark routes is acceptable in most of the routes. The main contribution is a thorough discussion of the differences between the two types of routes. Since the results are promising, we discuss variations in computing the weights as well as recommend human subject tests.
People navigating in unfamiliar environments rely on wayfinding directions, either given by people familiar with the place, or given by maps or wayfinding services. The essential role of landmarks in human route communication is well-known. However, mapping the human ability to select landmarks ad hoc for route directions to a computational model was never tried before. Wayfinding services manage the problem by using predefined points of interest. These points are not automatically identified, and they are not related to any route. In contrast, here a computational model is presented that selects salient features along a route where needed, e.g., at decision points. We propose measures to formally specify the salience of a feature. The observed values of these measures are subject to stochastical tests in order to identify the most salient features from datasets. The proposed model is implemented and checked for computability with a use case from the city of Vienna. It is also crosschecked with a human subject survey for landmarks along a given route. The survey provides evidence that the proposed model selects features that are strongly correlated to human concepts of landmarks. Hence, integrating the selected salient features in wayfinding directions will produce directions with lower cognitive workload and higher success rates, compared to directions based only on geometry, or on geometry and static points of interest.
In order to support pedestrians in the tasks of orientation and wayfinding with mobile devices appropriate visualizations of their location, its surrounding, and background information are needed. In this paper we present two complementary concepts for the combination of realistic views and location specific information that can be implemented with current generation PDAs and next generation cellular phones. The first employs video clips that were taken along every path in a city which are augmented by location information. It is shown how multimedia clips consisting of videos and textual information can be stored and transferred using the SMIL standard from the W3C consortium. The second approach supports navigation by the overlay of virtual signposts in panoramic images taken for every decision point, i.e. street junctions, in a city. We argue that the location- and orientation-synchronized presentation of (previously recor- ded) realistic views in combination with location specific information is an intuitive complement to map based visualization on the one hand and less invasive and resource demanding than augmented reality systems with head mounted displays on the other hand.
Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest category cue validity, and are, thus, the most differentiated from one another. The four experiments of Part I define basic objects by demonstrating that in taxonomies of common concrete nouns in English based on class inclusion, basic objects are the most inclusive categories whose members: (a) possess significant numbers of attributes in common, (b) have motor programs which are similar to one another, (c) have similar shapes, and (d) can be identified from averaged shapes of members of the class. The eight experiments of Part II explore implications of the structure of categories. Basic objects are shown to be the most inclusive categories for which a concrete image of the category as a whole can be formed, to be the first categorizations made during perception of the environment, to be the earliest categories sorted and earliest named by children, and to be the categories most codable, most coded, and most necessary in language.
Destination descriptions are route descriptions focusing on the “where” of the destination instead of the “how” to reach it. They provide first a coarse reference to the destination, and then increasingly more detailed ones as the description proceeds. We introduce a definition of destination descriptions, along with an analysis of the construction and interpretation of destination descriptions grounded in pragmatic communication theory. We present a formal model enabling the selection of references for destination descriptions from models of experiential hierarchies of urban environments. This model generates route directions for people with some knowledge of the environment. Destination descriptions are usually shorter and we conjecture that the cognitive workload required during their use is lower than for equivalent turn-based directions.
Our paper on the use of heuristic information in graph searching defined a path-finding algorithm, A*, and proved that it had two important properties. In the notation of the paper, we proved that if the heuristic function ñ (n) is a lower bound on the true minimal cost from node n to a goal node, then A* is admissible; i.e., it would find a minimal cost path if any path to a goal node existed. Further, we proved that if the heuristic function also satisfied something called the consistency assumption, then A* was optimal; i.e., it expanded no more nodes than any other admissible algorithm A no more informed than A*. These results were summarized in a book by one of us.