Dynamic Visualization of Transit Information Using Genetic Algorithms for Path Schematization

Galvao, Marcelo; Ramos, Francisco; Lamar, M.V.; Taco, Pastor Willy Gonzales

doi:10.1007/978-3-319-61297-3_8

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…Almost all cities that have a metro system also provide their users with a schematic map of the network. For this reason, most of the research on schematization algorithms focused on transit networks [3,11,17,28,37,51,54]. Those methods were surveyed in [35].…”

Section: Route and Polygon Schematization Methodsmentioning

confidence: 99%

Route schematization with landmarks

Galvão¹,

Krukar²,

Nöllenburg³

et al. 2020

JOSIS

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Modern navigation applications make use of a turn-by-turn instructions approach and are mostly supported by digital devices with limited display size. This combination does little to improve users' orientation or spatial knowledge acquisition. Considering this limitation, we propose a route schematization method to facilitate the readability of route information and survey knowledge acquisition. Current schematization methods focus on the route path and ignore context information, specially polygonal landmarks such as lakes, parks, and regions, which is crucial for promoting orientation. Our schematization method, in addition to the route path, takes as input: adjacent streets, point-like landmarks, and polygonal landmarks. Moreover, the schematic layout highlights spatial relations between route and context information, improves the readability of turns at decision points, and the visibility of the surroundings. The focus of the paper is the schematization method that combines geometric transformations and integer linear programming to produce the maps. Two routes are used as examples to present the execution information and the outputs. We complement our results with a user study that indicates a preference for our schematic layout in matching textual route instructions. The contribution of this paper is a method that produces schematic route maps with context information to support the user in wayfinding and orientation.

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Section: Route and Polygon Schematization Methodsmentioning

confidence: 99%

Route schematization with landmarks

Galvão¹,

Krukar²,

Nöllenburg³

et al. 2020

JOSIS

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“…In the last two decades, researchers from multiple disciplines, such as cartography, GIS, computational geometry, transportation, and psychology, have carried out a large number of studies for schematic maps. The literature presents three primary themes: (1) effective design rules, principles, and/or frameworks for automated generation (e.g., Avelar & Hurni, 2006;Burch, Woods, Netzel, & Weiskopf, 2016;Li, 2015;Roberts, 2014b); (2) automated generation methods (e.g., Anand, Avelar, Ware, & Jackson, 2007;Brands, 2016;Galvao, Ramos, Lamar, & Taco, 2017;Hong, Merrick, & Nascimento, 2006;Lan, Li, & Ti, 2019;Li & Dong, 2010;Nöllenburg & Wolff, 2011;Stott, Rodgers, Martinez-Ovando, & Walker, 2011;Ti & Li, 2014;Ti, Li, & Xu, 2015;Ware, Taylor, Anand, & Thomas, 2006); and (3) usability and cognition issues (e.g., Burch, Kurzhals, Raschke, Blascheck, & Weiskopf, 2014;Delazari, Anand, Morley, 2014;Gallotti, Porter, & Barthelemy, 2016;Guo, 2011;Lloyd, Rodgers, & Roberts, 2018;Netzel et al, 2017;Roberts, 2014a;Roberts, Gray, & Lesnik, 2017;Roberts et al, 2013). This study focuses on the automated generation methods of schematic maps.…”

Section: Introductionmentioning

confidence: 99%

Automated labeling of schematic maps by optimization with knowledge acquired from existing maps

Lan

Pan

et al. 2020

Transactions in GIS

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Schematic maps are simplified representations of line networks, aiming to help people quickly and accurately perform route planning and orientation tasks. The automated generation of such maps is generally treated as an optimization problem. Most researchers prefer to optimize network layouts and name labels separately, because optimizing them simultaneously is still intractable. It is found that optimizing network layouts is extensively studied, while optimizing name labels is rarely considered. In the optimization of name labels, constraints can be established with rules from cartographic experts, literature (e.g., specification and technical documents), and/or existing maps. However, some rules from experts and literature cannot be explicitly and mathematically expressed. This study aims to develop an automated labeling method with rules from existing maps. We first acquire the rules (i.e., the potential positions and the preferences of these positions) from some existing schematic maps and then integrate them into an optimization algorithm. Experimental evaluation is conducted by a questionnaire in terms of “ease level of finding name labels,” “congestion level,” and “satisfaction level” using Tianjin and Hong Kong metro schematic maps and the labels of our method. The results show that the proposed method can automatically generate effective labels.

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“…It is time-consuming to solve this optimization problem due to its NP-hard nature [11]. To achieve the optimal result within an acceptable time, various optimization algorithms (e.g., simulated annealing algorithms, genetic algorithms, and hill-climbing algorithms) are used with one or more constraints [2,[11][12][13][14][15]. On the other hand, the utility improvement of schematic maps has gained a great deal of attention.…”

mentioning

confidence: 99%

Assessing the Suitability of Fractal Dimension for Measuring Graphic Complexity Change in Schematic Metro Networks

Lan,

Wu,

Sun

et al. 2024

IJGI

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Schematization is a process of generating schematic network maps (e.g., metro network maps), where the graphic complexity of networks is usually reduced. In the past two decades, various automated schematization methods have been developed. A quantitative and accurate description of the complexity variation in the schematization is critical to evaluate the usability of schematization methods. It is noticed that fractal dimension (F) has been widely used to analyze the complexity of geographic objects, and this indicator may be appropriate for this purpose. In some existing studies, although F has been employed to describe the complexity variation, the theoretical and experimental basis for adopting this approach is inadequate. In this study, experiments based on 26 Chinese cities’ metro networks showed that the F of all these metro networks have decreased in schematization, and a significant positive correlation exists between the F of original networks and the reduction of F after schematization. The above results were verified to have similar trends with the subjective opinions of participants in a psychological questionnaire. Therefore, it can be concluded that F can quantitatively measure the complexity change of networks in schematization. These discoveries provide the basis for using F to evaluate the usability of schematization methods.

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Dynamic Visualization of Transit Information Using Genetic Algorithms for Path Schematization

Cited by 4 publications

References 9 publications

Route schematization with landmarks

Route schematization with landmarks

Automated labeling of schematic maps by optimization with knowledge acquired from existing maps

Assessing the Suitability of Fractal Dimension for Measuring Graphic Complexity Change in Schematic Metro Networks

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