Route Descriptions Research Articles

Landmark-Based Indoor Navigation Model through Human Route Descriptions

Landmark-Based Indoor Navigation Model through Human Route Descriptions

Imagery and Verbal Strategies in Spatial Memory for Route and Survey Descriptions.

Being able to represent and remember verbally-encoded information about spatial environments from different perspectives is important for numerous daily activities. The present study examined how frequently individuals spontaneously engage in visual mental imagery and verbal rehearsal strategies in memory recall of spatial descriptions, and whether using certain strategies is associated with better recall performance. Memory recall for route (person-centred) and survey (object-centred) spatial descriptions was examined in a sample of 105 neurotypical individuals, who also reported to what extent they used route- and survey-based mental imagery and verbal rehearsal strategies in each description. Results showed that participants favoured a path visualisation strategy to recall the route description and a map visualisation strategy to recall the survey description. Regression models further showed that employing both imagery and verbal strategies was associated with better recall for both route and survey descriptions, although imagery strategies held a higher predictive power. The present findings highlight the fact that the spontaneous use of internal strategies in the form of visual imagery and verbal rehearsal is ubiquitous when recalling spatial descriptions and a core part of efficient spatial memory functioning.

Indoor view graph: A model to capture route and configurational information

This paper presents a graph model that simultaneously stores route and configurational information about indoor spaces. Existing indoor information models either capture route information to compute shortest paths and to generate route descriptions (i.e., answering how-to-get-to questions), or they store configurational information about objects and places and their spatial relationships to enable spatial querying and inference (i.e., answering where-questions). Consequently, multiple representations of an indoor environment must be stored in information systems to address the various information needs of their users. In this paper, we propose a graph that can capture both configurational and route information in a unified manner. The graph is the dual representation of connected lines of sight, or views. Views can represent continuous movement in an indoor environment, and at the same time, the visible configurational information of each view can be explicitly captured. In this paper, we discuss the conceptual design of the model and an automatic approach to derive the view graph from floorplans. Finally, we demonstrate the capabilities of our model in performing different tasks such as calculating shortest paths, generating route descriptions, and deriving place graphs.

Cognitive mapping of indoor environments: constructing an indoor navigation network from crowdsourced indoor route descriptions

ABSTRACT Indoor navigation networks provide an effective solution for modeling indoor environments for navigational purposes. In comparison to pure geometric structures, network structures that are aligned with the user’s cognitive map are perceived as more intuitive. However, there has been limited research conducted on constructing indoor navigation networks that align with user’s cognitive maps. Human route descriptions contain valuable insights into how individuals recognize their surroundings and how humans structure spatial information cognitively. Using crowdsourced route descriptions to construct indoor navigation networks can provide an approximation of people’s cognitive maps. This study proposes a graph-based method to solve the problem of merging human indoor route descriptions. It models indoor route descriptions as directed attributed graphs and transforms the challenges into a graph merging problem. This method relies on order and direction information between references. In a case study with human indoor route descriptions, an indoor navigation network was generated by merging crowdsourced indoor route descriptions. The network has the potential to facilitate a comparison between existing indoor network models and identify the indoor navigation network that best matches the network derived from crowdsourced route descriptions. Additionally, the network could be used to generate more intuitive indoor route descriptions.

Aligning indoor human route descriptions to facilitate the use of crowdsourced indoor navigation systems

ABSTRACT Crowdsourced indoor route descriptions are increasingly used to provide user-friendly navigation services at low cost. In this study, we propose an approach for aligning indoor route descriptions and use the triangular model to visualize the aligned route descriptions. Linear route segments are represented as two-dimensional triangles, allowing navigation knowledge to be derived. The results show that the proposed approach can help to represent the hierarchical structure of multiple indoor route descriptions, identify the critical decision points that users frequently describe, and aggregate indoor route descriptions from different people to generate new route descriptions.

Automatic translation of human route descriptions into schematic maps for indoor navigation

ABSTRACT People create route descriptions based on their mental maps to provide route guidance, which represents their knowledge of the environment. Recent studies have attempted to model navigation knowledge from human route descriptions to facilitate route communication. However, they mainly focus on outdoor environments and do not address the representation of human descriptions of indoors in the form of schematic maps through the automatic extraction of spatial knowledge. Schematic maps have been commonly applied for public transportation by utilizing abstract representations to reduce cognitive load. Compared to route descriptions, schematic maps can provide easy-to-understand navigation guidance. In this paper, we present a novel NLP-based pipeline to automatically generate schematic maps from human route descriptions for indoor navigation. The experimental data consists of a set of crowdsourced route descriptions that follow a common template for a test building of the Soleway indoor navigation web service. The route descriptions and the generated schematic maps were presented to human participants in an online survey, and it was found that 92% of the generated schematic maps matched well with the corresponding human route descriptions. Thus, the proposed method is an effective and reliable approach for modeling route descriptions through schematic maps in indoor route communication.

Developing a database of Australian grasshopper occurrences from historic field survey notebooks spanning 54 years (Orthoptera: Acrididae, Morabidae, Pyrgomorphidae, Tetrigidae)

AbstractThe baseline distribution data for all species of a given group in a region can provide fundamental insights into biogeographic questions about historic patterns of species richness, population trends and extinction. Grasshoppers are one major group of insects for which a continent‐wide perspective on their geographic distribution can be obtained. This is because they were extensively surveyed in Australia for 54 years (1936–1989) as part of Commonwealth expeditions to obtain specimens for the Australian National Insect Collection (ANIC). Field notebooks recorded from those surveys, under the direction of ANIC curator and director K. H. L. Key, form the principal source of historic distribution records for grasshoppers in Australia. We digitised all the 223 notebooks (2486 pages) and transcribed all the field trips conducted in Western Australia (WA) and Tasmania (47 notebooks, 590 pages). We then carefully geocoded all sampling sites of the transcribed notebooks, following the odometer readings and descriptions of routes from a suitable reference point using historic topographic maps and Google Earth. In total, we extracted 8975 geographic coordinates for 477 species having a confirmed or putative taxonomic name at genus or species level (only 170 of these species have been formally described). We found that species richness varied spatially, with highest richness in arid interior and north of WA. Historic grasshopper surveys were non‐randomly distributed across both WA and Tasmania with the highest survey intensity around coastal regions. Variation was observed among surveyors in terms of the number of species detected per site, between‐site distance and the season of survey being conducted. Overall, however, the dataset is among the most comprehensive continent‐wide surveys of Australian invertebrates and will greatly facilitate future work on their ecology, biogeography, conservation and responses to environmental change.

Route Descriptions, Spatial Knowledge and Spatial Representations of Blind and Partially Sighted People: Improved Design of Electronic Travel Aids

The results presented here were obtained from an experimental study of blind people's experiences on two routes with very different characteristics. They are intended to answer three research questions on how blind people identify environmental features while travelling and use environmental information to form spatial representations, and the implications for the design of electronic travel aids to better support mental mapping of space. The results include detailed discussions of the mainly tactile and auditory information used by blind people to identify objects, as well as the different combinations of sensory information used in forming mental maps, the approaches participants used to do this, and the sensory modalities involved. They also provide a categorisation of the main features in participants’ descriptions of the two routes. The answers to the three questions include a discussion of the relationship between the sensory information used in route descriptions and mental maps, and the implications of the results for the design of electronic travel aids to support mental mapping, including suggestions for new types of aids and guidelines for aid design.

The Impact of Route Descriptions on Human Expectations for Robot Navigation

As robots are deployed to work in our environments, we must build appropriate expectations of their behavior so that we can trust them to perform their jobs autonomously as we attend to other tasks. Many types of explanations for robot behavior have been proposed, but they have not been fully analyzed for their impact on aligning expectations of robot paths for navigation. In this work, we evaluate several types of robot navigation explanations to understand their impact on the ability of humans to anticipate a robot’s paths. We performed an experiment in which we gave participants an explanation of a robot path and then measured (i) their ability to predict that path, (ii) their allocation of attention on the robot navigating the path versus their own dot-tracking task, and (iii) their subjective ratings of the robot’s predictability and trustworthiness. Our results show that explanations do significantly affect people’s ability to predict robot paths and that explanations that are concise and do not require readers to perform mental transformations are most effective at reducing attention to the robot.

Особливості проєктування екологічних стежок Надслучанського регіонального ландшафтного парку за матеріалами дистанційних знімань та засобів ГІС

The purpose of this work is to design the routes of ecological trails according to modern technologies (for example, Nadsluchansky Regional Landscape Park) for recreational development and use of territories. The park itself is located in the Rivne region in the valley of the river Sluch, covers an area of over 17 thousand hectares and includes many sites of environmental, historical and recreational importance. Method. Preliminary design of ecological trails was performed on the basis of satellite imagery (radar images Sentinel-1 and multispectral Sentinel-2), which are distinguished by many important features, among which, above all, note the high frequency of imaging, global coverage, the availability of and free access to research. To perform this task, digital terrain models, thematic and index maps, composite images were obtained. At the final stage of modeling, specialized ArcGIS software was used. Results. As a result of the performed work, 5 routes of pedestrian and 2 equestrian health-cognitive ecological trails with corresponding maps, profiles, catalogs of coordinates, descriptions of routes and viewpoints, photos, etc. were designed. Scientific novelty and practical significance. To create routes of ecological trails, the proposed technique was implemented for the first time and proved its effectiveness. It allowed to achieve a significant reduction in the duration of work, the cost of field research and take into account the necessary features of the territory. Prior to that, there were no such trails in the Nadsluchansky Landscape Park. As the ecological tourist network in Ukraine has not yet been formed, the use of this approach at other sites of environmental importance will allow faster and more efficient development of this important segment, and it will help solve a number of environmental, cultural, social and economic problems. The information provided also provides an opportunity for those wishing to use such smartphones to make such trips on their own.

Animate Orientation Based on Visual Landmarks and Scene Recognition

A biologically-inspired approach to robot route following is presented. The ant of the genus Formica rufa (a red forest ant) is used as a model species. These ants actively use collective foraging, unlike many other ant species. The scout ant remembers the route to food and can transmit information about the food location to foraging ants. Foragers can independently reach this place using this data and return home. The basis of the proposed method is the memorization the way by visual landmarks and fuzzy control. The animate path description model consists of a sequence of scenes and includes compass to account for the direction. The behavior of the animate-scout is implemented using an algorithm that simulates the foraging behavior of ants. The animate-forager performs actions to reproduce the route, applying the developed set of rules. The forager behavior is based on the same principles as that of a scout. But the scout remembers the scenes, and the forager recognizes and compares the visible scene and the scene from the route description. The actions of animates are presented in the form of elementary behavioral procedures. Each behavioral procedure is implemented using a finite state machine. The experiments for solving the foraging problem were carried out using a modeling system based on the ROS framework. The simulation results confirm the effectiveness of the proposed method. The method does not require large computing power and advanced sensory capabilities from the robot. It can also be used in reconnaissance and patrol tasks.

SpeakNav

Many navigation applications take natural language speech as input, which avoids users typing in words and thus improves traffic safety. However, navigation applications often fail to understand a user's free-form description of a route. In addition, they only support input of a specific source or destination, which does not enable users to specify additional route requirements. We propose a SpeakNav framework that enables users to describe intended routes via speech and then recommends appropriate routes. Specifically, we propose a novel Route Template based Bidirectional Encoder Representation from Transformers (RT-BERT) model that supports the understanding of natural language route descriptions. The model enables extraction of information of intended POI keywords and related distances. Then we formalize a template-driven path query that uses the extracted information. To enable efficient query processing, we develop a hybrid label index for computing network distances between POIs, and we propose a branch-and-bound algorithm along with a pivot reverse B-tree (PB-tree) index. Experiments with real and synthetic data indicate that RT-BERT offers high accuracy and that the proposed algorithm is capable of outperforming baseline algorithms.

Design Verification of an Optimized Wayfinding Map in a Station

Passengers were unsatisfied with the navigation signs in Taipei station based on the Report on the Taiwan Railway Passenger Survey. This study conducted two experiments. Experiment 1 involved 14 participants using the present Taipei Main Station floor map to wayfinding, plan routes, and provide route descriptions for four specified destinations in the station. All participants were requested to recall the route that had just been taken and draw a cognitive map. In Experiment 2, 14 other participants were asked to perform the same tasks as Experiment 1 but with the new map. This study’s results showed that the codes used by the participants in Experiment 1 revealed the differences in walking route distance and number of turns. Escalators and stairs that connected floors were often used as reference landmarks for wayfinding. In Experiment 2, the overall wayfinding performance of the participants was improved by using the new map. The wayfinding time was reduced and the time spent in wayfinding among users was more uniform, and their route planning strategies used became consistent. The new map that facilitates consistent action strategies among users and corresponds perfectly to the actual environment is able to create useful spatial knowledge for users.

Aeration of the Human Prussak's Space: A 3D Synchrotron Imaging Study.

Prussak's space (PS) is an intricate middle ear region which may play an essential role in the development of middle ear disease. The three-dimensional (3D) anatomy of the human PS and its drainage routes remain relatively unknown. Earlier studies have histologically analyzed PS, by micro-dissection and endoscopy. Here, we used synchrotron-radiation phase-contrast imaging (SR-PCI), 3D reconstructions, and modeling to study the framework of the human PS, including aeration pathways. It may lead to increased understanding of development of middle ear pathology. Nine human temporal bone specimens underwent in-line SR-PCI at the Canadian Light Source in Saskatoon, Saskatchewan, Canada. Data were processed with volume-rendering software to create 3D reconstructions using scalar opacity mapping and segmentations to visualize its walls in fixed, undecalcified human temporal bones. The PS was found to be an irregular, variably shaped chamber with different aeration systems. Three different drainage pathways were found: 1) via the posterior malleolar pouch of von Tröltsch in seven of nine ears; 2) directly posterior-inferior into the mesotympanum medial to the posterior malleolar pouch in one ear; and 3) anteriorly in another. The posterior-inferior communications depended on the anatomy of the posterior malleolar fold. In one bilateral case, the aeration differed between the ears. Earlier descriptions of upper ventilation routes between the PS and the epitympanic spaces could not be substantiated. The 3D anatomy of the membrane folds organizing the PS in humans was demonstrated for the first time using in-line SR-PCI. The PS was always aerated into the mesotympanum, suggesting its relative independence of attic ventilation. The impact of its various drainage routes on middle ear ventilation and disease were discussed.

Dynamic Model and Graphical User Interface: A Solution for the Distribution Process of Regional Products

Organizations in the agroindustry sector face shorter delivery schedules; therefore, they are seeking ways to conduct more effective and less costly product distribution. Supply chain management efforts have focused on improving the flow of both products and information. Thus, the aim of this case study was to build a graphical user interface to enable decision-making based on quantitative information for a food distribution process. The problem to be solved was associated with the development of a technological solution to reduce and control variations in transportation times, delivery costs and capacities in cold and dry food distribution. An eight-step system for a dynamics methodology was used: (1) distribution process analysis, (2) route description, (3) variable and parameter description, (4) causal loop diagram creation, (5) current model simulation, (6) validation, (7) quantitative scenario construction based on key performance indicators, and (8) graphical user interface development. The main findings of this research were that the graphical user interface and simulation showed information that represented on average 56.49% of the total distribution costs regarding fuel and that maintenance and tire wearing costs had less of an impact on total costs, representing 9.21% and 3.66% of the total costs, respectively. Additionally, the technological solution—created for the supply chain in the distribution process against the background of changes in policies—makes it possible to improve decision-making based on different scenarios supported by a graphical interface according to key performance indicators. This solution could be used by different organizations who aim to reduce logistics and transportation costs. The main implications of this research were the available and organized information and the restructuring of the distribution process.

An algorithm for the selection of route dependent orientation information

Landmarks are important features of spatial cognition and are naturally included in human route descriptions. In the past algorithms were developed to select the most salient landmarks at decision points and automatically incorporate them in route instructions. Moreover, it was shown that human route descriptions contain a significant amount of orientation information, which support the users to orient themselves regarding known environmental information, and it was shown that orientation information support the acquisition of survey knowledge. Thus, there is a need to extend the landmarks selection to automatically select orientation information. In this work, we present an algorithm for the computational selection of route dependent orientation information, which extends previous algorithms and includes a salience calculation of orientation information for any location along the route. We implemented the algorithm and demonstrate the functionality based on OpenStreetMap data.

Support Vector Machine Based Route Classification and Description

Traveling is very much important in one's life. Location-based services have developed a lot due to the development of communication technologies. It confines services that execute programs that use geographical data. Map services authorize travelers to look for the information surrounding them and organize an outing to his/her best-loved spot. Google Maps API is convenient for locating the shortest route information. However, the map system doesn't supply any illustration about air quality or congestion in a path. At times, a substitute route with less congestion can take you quickly to your spot than a shorter route. Numerous crucial health concerns for human beings are caused due to pollution. The motive is to develop a system that offers the textual explanation of routes utilizing the sub-routes information from Google map and BreezoMeter. The end-user can choose the starting and ending points of his/her travel and the route map showing various routes from source to destination is exhibited along with a small description of each route. The illustration of the routes is obtained depending on three factors such as air quality, congestion and distance gathered from BreezoMeter, Google map traffic API and distance matrix API respectively. Multicategory Support Vector Machine (SVM) is an organized and guided categorization technique and is used here to classify factors into various levels. Since the textual illustration of the route is accessible, the end-user can effortlessly understand the details about the route and they can choose a particular route.

Support Vector Machine Based Route Classification and Description

Traveling is very much important in one's life. Location-based services have developed a lot due to the development of communication technologies. It confines services that execute programs that use geographical data. Map services authorize travelers to look for the information surrounding them and organize an outing to his/her best-loved spot. Google Maps API is convenient for locating the shortest route information. However, the map system doesn't supply any illustration about air quality or congestion in a path. At times, a substitute route with less congestion can take you quickly to your spot than a shorter route. Numerous crucial health concerns for human beings are caused due to pollution. The motive is to develop a system that offers the textual explanation of routes utilizing the sub-routes information from Google map and BreezoMeter. The end-user can choose the starting and ending points of his/her travel and the route map showing various routes from source to destination is exhibited along with a small description of each route. The illustration of the routes is obtained depending on three factors such as air quality, congestion and distance gathered from BreezoMeter, Google map traffic API and distance matrix API respectively. Multicategory Support Vector Machine (SVM) is an organized and guided categorization technique and is used here to classify factors into various levels. Since the textual illustration of the route is accessible, the end-user can effortlessly understand the details about the route and they can choose a particular route.

Анализ технологической подготовки предприятий по техническому обслуживанию и ремонту вагонов

The paper analyzes the technological preparation of production at the railcar enterprises in terms of developing technological processes and processing sets of technological documents. Factors affecting the quality of technological preparation of production for maintenance and repair of rolling stock are considered. In contrast to the previously performed works, where the assessment of the level of technological training was carried out by experts of a scientific organization, the initial data in the article were the results of a survey of specialists of technical departments of structural divisions of the car industry of the Sverdlovsk and South Ural Railways. Based on the method of expert qualimetry, the weight of factors that have the greatest impact on the quality of technological processes is estimated. As a result of the survey, a low level of automation of design processes was established, which consists mainly in the design of technological documentation. It is shown that the degree of depth of development and detail of technological processes is at the level of the route description

АВТОМАТИЗОВАНА СИСТЕМА МАРШРУТИЗАЦІЇ ЛОГІСТИЧНИХ ПОТОКІВ ТОРГОВЕЛЬНОГО ПІДПРИЄМСТВА

The article addresses one of the most pressing problems for a trading enterprise, namely the problem of routing logistics flows for efficient enterprise management. To optimize itineraries, we use state-of-the-art electronic navigation and mapping systems that can be implemented in modern computer technology, from online services available on any computer to mobile devices. Navigation and mapping systems are distributed software complexes with an array of information stored in database management systems. They involve millions of static objects and huge amounts of dynamic data around the world. To optimize the logistics flows, an algorithm for an automated routing system is described. This system solves the problems of automatic calculation of the construction and recognition of the optimal route between the specified points of its beginning and the end, tracking of movement on a given route and, in the case of congested roads, redirection of logistics flows. Based on the researches and experiments on the formation of a cognitive map in the human mind and the perception of the route description, an algorithm for storing and displaying route data is considered. This algorithm takes into account the personal psychology of perception of cartographic information. Developing an algorithm for describing the routing of trading enterprise traffic flows is creating a model of automatically found path between the predetermined points of its beginning and end. This mapping information is personalized, easy to read, fast to remember, and insensitive to user errors. The proposed algorithm is universal and can be used to solve a wide range of problems of logistic flows optimization.