Wayfinding and Navigation for People with Disabilities Using Social Navigation Networks

To achieve safe and independent mobility, people usually depend on published information, prior experience, the knowledge of others, and/or technology to navigate unfamiliar outdoor and indoor environments. Today, due to advances in various technologies, wayfinding and navigation systems and services are commonplace and are accessible on desktop, laptop, and mobile devices. However, despite their popularity and widespread use, current wayfinding and navigation solutions often fail to address the needs of people with disabilities (PWDs). We argue that these shortcomings are primarily due to the ubiquity of the compute-centric approach adopted in these systems and services, where they do not benefit from the experience-centric approach. We propose that following a hybrid approach of combining experience-centric and compute-centric methods will overcome the shortcomings of current wayfinding and navigation solutions for PWDs

CampusPartner: An assistive technology for pedestrians with mobility impairments

Route-planning applications such as Google Maps and Apple Maps are used by millions of people each month. However, these mapping applications are optimized for vehicle navigation, and although they provide pedestrian routing, the route customization options aren’t sufficient for pedestrian users, especially those with mobility impairments. CampusPartner is an assistive mobile application that was designed with the purpose of supporting people with mobility impairments in planning and previewing their walking routes. By viewing routes in advance, users can see an overview and detailed information about them as well as turn-by-turn instructions. CampusPartner integrates existing services, GraphHopper, OpenStreetMap, and Mapbox, to provide navigation functionality. Users are able to create a profile upon opening the app, which will include information such as obstacles and road types to avoid, as well as their bookmarked or most commonly used routes. For example, if someone was looking for a route from one side of campus to the other and they couldn’t take stairs due to a mobility impairment, this app would assist them in determining the best route to take or notify them if they should look for an alternative form of transportation, such as a bus. Additionally, users are able to correct missing or inaccurate information, such as the absence of stairs on the map or temporary obstacles

Wheelmap: the wheelchair accessibility crowdsourcing platform

Crowdsourcing (geo-) information and participatory GIS are among the current hot topics in research and industry. Various projects are implementing participatory sensing concepts within their workflow in order to benefit from the power of volunteers, and improve their product quality and efficiency. Wheelmap is a crowdsourcing platform where volunteers contribute information about wheelchair-accessible places. This article presents information about the technical framework of Wheelmap, and information on how it could be used in projects dealing with accessibility and/or multimodal transportation

Integrating Haptic Feedback into Mobile Location Based Services

Haptics is a feedback technology that takes advantage of the human sense of touch by applying forces, vibrations, and/or motions to a haptic-enabled device such as a mobile phone. Historically, human-computer interaction has been visual - text and images on the screen. Haptic feedback can be an important additional method especially in Mobile Location Based Services such as knowledge discovery, pedestrian navigation and notification systems. A knowledge discovery system called the Haptic GeoWand is a low interaction system that allows users to query geo-tagged data around them by using a point-and-scan technique with their mobile device. Haptic Pedestrian is a navigation system for walkers. Four prototypes have been developed classified according to the user’s guidance requirements, the user type (based on spatial skills), and overall system complexity. Haptic Transit is a notification system that provides spatial information to the users of public transport. In all these systems, haptic feedback is used to convey information about location, orientation, density and distance by use of the vibration alarm with varying frequencies and patterns to help understand the physical environment. Trials elicited positive responses from the users who see benefit in being provided with a “heads up” approach to mobile navigation. Results from a memory recall test show that the users of haptic feedback for navigation had better memory recall of the region traversed than the users of landmark images. Haptics integrated into a multi-modal navigation system provides more usable, less distracting but more effective interaction than conventional systems. Enhancements to the current work could include integration of contextual information, detailed large-scale user trials and the exploration of using haptics within confined indoor spaces

Improving accessibility for pederstrians with geographic information

Osajulkaisut: Publication 1: Mari Laakso, Tapani Sarjakoski, and L. Tiina Sarjakoski. 2011. Improving accessibility information in pedestrian maps and databases. Cartographica, volume 46, number 2, pages 101-108. University of Toronto. DOI:10.3138/carto.46.2.101 Publication 2: L. Tiina Sarjakoski, Pyry Kettunen, Hanna-Marika Flink, Mari Laakso, Mikko Rönneberg, and Tapani Sarjakoski. 2012. Analysis of verbal route descriptions and landmarks for hiking. Personal and Ubiquitous Computing, volume 16, number 8, pages 1001-1011. DOI:10.1007/s00779-011-0460-7 Publication 3: Mari Laakso, Tapani Sarjakoski, Lassi Lehto, and L. Tiina Sarjakoski. 2013. An information model for pedestrian routing and navigation databases supporting universal accessibility. Cartographica, volume 48, number 2, pages 89-99. University of Toronto. DOI:10.3138/carto.48.2.1837 Publication 4: Mari Laakso and L. Tiina Sarjakoski. 2010. Sonic maps for hiking—Use of sound in enhancing the map use experience. The Cartographic Journal, volume 47, number 4, pages 300-307. DOI:10.1179/000870410X12911298276237 Publication 5: Mari Laakso, Hanna-Marika Halkosaari, Tapani Sarjakoski, and L. Tiina Sarjakoski. 2013. User experiences with voice-based descriptive map content in a hiking context. In: Thomas Jekel, Adrijana Car, Josef Strobl, and Gerald Griesebner (editors). Creating the GISociety. Proceedings of the GI_Forum 2013 Conference. Salzburg, Austria. 2-5 July 2013. Berlin / Offenbach, Germany. Herbert Wichmann Verlag, VDE Verlag. Pages 49-58. ISBN 978-3-87907-532-4. DOI:10.1553/giscience2013s49Environments can be made more accessible by offering users information about barriers and objects that might hinder their progress, thus enabling more information about accessible routes. The study delineates the relevant geospatial information needed to describe the accessibility of an environment. Even though laws, acts and regulations give thorough building requirements for creating accessible environments, there is no holistic approach in geospatial data collection to represent the accessibility of geographical spaces. In this thesis, an information model is presented for representing the pedestrian environment. The model allows for accessibility issues and enables the use of geospatial information in pedestrian navigation applications. In addition to data contents and data modelling, this research studies how accessibility can be further increased by way of sound when communicating geospatial information. By communicating the geospatial information via sound the information content can be enhanced and usability improved. Sonic maps create remote access to nature and enhance the accessibility of a place. In this thesis, the fundamental aim was to study the information requirements in particular situations where different kinds of pedestrian users determine which route they might successfully complete. The results of the thesis will help data providers collect and store geospatial information, while taking accessibility issues into account, and hopefully it will raise awareness about issues pertaining to universal accessibility. Albeit, the main effort should focus on building accessible environments; in certain situations, people face hindrances and geospatial information could enable users overcome them.Ympäristöistä voidaan tehdä saavutettavampia tarjoamalla käyttäjille tietoa mahdollisista esteistä tai muista kulkua vaikeuttavista kohteista. Tässä tutkimuksessa määritellään tarvittava paikkatieto, jolla jalankulkijan ympäristö ja sen esteettömyys voidaan kuvata. Esteettömien ympäristöjen luomiseksi on olemassa joukko lakeja ja asetuksia, mutta ympäristön esteettömyyden kuvaamiseksi tarvittavalle paikkatiedolle ei ole määritelty kattavaa keräys- ja esitysmuotoa. Tässä väitöskirjassa esitellään tietomalli, jolla jalankulkijan ympäristö ja sen esteettömyys voidaan kuvata. Malliin voidaan sisällyttää esteettömyyttä kuvaavia tietoja ja se mahdollistaa tämän tiedon käytön myös navigointisovelluksilla. Tietosisällön ja sen mallintamisen lisäksi tässä työssä on tutkittu kuinka ympäristön saavutettavuutta voidaan lisätä kommunikoimalla paikkatietoa myös äänen avulla. Äänen avulla voidaan paikkatiedon määrää ja laatua sekä sen käytettävyyttä lisätä. Äänikartoilla voidaan luoda eräänlainen etäyhteys kuvattuun ympäristöön ja sen avulla lisätä ympäristön saavutettavuutta. Tämän väitöskirjan tavoitteena on määrittää erilaisten käyttäjien vaatima paikkatieto tilanteissa, joissa heidän on tehtävä päätös pystyvätkö he kulkemaan valitsemansa reitin. Tämän työn tulokset auttavat paikkatiedon tarjoajia keräämään ja tallentamaan paikkatietoa niin, että se kuvaa myös ympäristön esteettömyyttä. Ympäristöjen esteettömäksi rakentamisen tulisi edelleen olla ensisijainen tavoite, mutta koska jotkut käyttäjät tietyissä tilanteissa edelleen kohtaavat esteettömyysongelmia, heitä voitaisiin paikkatiedon avulla auttaa väistämään ne

Methodology and Algorithms for Pedestrian Network Construction

With the advanced capabilities of mobile devices and the success of car navigation systems, interest in pedestrian navigation systems is on the rise. A critical component of any navigation system is a map database which represents a network (e.g., road networks in car navigation systems) and supports key functionality such as map display, geocoding, and routing. Road networks, mainly due to the popularity of car navigation systems, are well defined and publicly available. However, in pedestrian navigation systems, as well as other applications including urban planning and physical activities studies, road networks do not adequately represent the paths that pedestrians usually travel. Currently, there are no techniques to automatically construct pedestrian networks, impeding research and development of applications requiring pedestrian data. This coupled with the increased demand for pedestrian networks is the prime motivation for this dissertation which is focused on development of a methodology and algorithms that can construct pedestrian networks automatically. A methodology, which involves three independent approaches, network buffering (using existing road networks), collaborative mapping (using GPS traces collected by volunteers), and image processing (using high-resolution satellite and laser imageries) was developed. Experiments were conducted to evaluate the pedestrian networks constructed by these approaches with a pedestrian network baseline as a ground truth. The results of the experiments indicate that these three approaches, while differing in complexity and outcome, are viable for automatically constructing pedestrian networks

Scalable Methods to Collect and Visualize Sidewalk Accessibility Data for People with Mobility Impairments

Poorly maintained sidewalks pose considerable accessibility challenges for people with mobility impairments. Despite comprehensive civil rights legislation of Americans with Disabilities Act, many city streets and sidewalks in the U.S. remain inaccessible. The problem is not just that sidewalk accessibility fundamentally affects where and how people travel in cities, but also that there are few, if any, mechanisms to determine accessible areas of a city a priori. To address this problem, my Ph.D. dissertation introduces and evaluates new scalable methods for collecting data about street-level accessibility using a combination of crowdsourcing, automated methods, and Google Street View (GSV). My dissertation has four research threads. First, we conduct a formative interview study to establish a better understanding of how people with mobility impairments currently assess accessibility in the built environment and the role of emerging location-based technologies therein. The study uncovers the existing methods for assessing accessibility of physical environment and identify useful features of future assistive technologies. Second, we develop and evaluate scalable crowdsourced accessibility data collection methods. We show that paid crowd workers recruited from an online labor marketplace can find and label accessibility attributes in GSV with accuracy of 81%. This accuracy improves to 93% with quality control mechanisms such as majority vote. Third, we design a system that combines crowdsourcing and automated methods to increase data collection efficiency. Our work shows that by combining crowdsourcing and automated methods, we can increase data collection efficiency by 13% without sacrificing accuracy. Fourth, we develop and deploy a web tool that lets volunteers to help us collect the street-level accessibility data from Washington, D.C. As of writing this dissertation, we have collected the accessibility data from 20% of the streets in D.C. We conduct a preliminary evaluation on how the said web tool is used. Finally, we implement proof-of-concept accessibility-aware applications with accessibility data collected with the help of volunteers. My dissertation contributes to the accessibility, computer science, and HCI communities by: (i) extending the knowledge of how people with mobility impairments interact with technology to navigate in cities; (ii) introducing the first work that demonstrates that GSV is a viable source for learning about the accessibility of the physical world; (iii) introducing the first method that combines crowdsourcing and automated methods to remotely collect accessibility information; (iv) deploying interactive web tools that allow volunteers to help populate the largest dataset about street-level accessibility of the world; and (v) demonstrating accessibility-aware applications that empower people with mobility impairments