CROWDSOURCING BASED MICRO NAVIGATION SYSTEM FOR VISUALLY IMPAIRED

Mobility and safety are primary concerns for blind and visually impaired (BVI) users when navigating in unfamiliar environments. Typically, a sighted person can locate a place of interest if they are provided guidance while approaching within a few meters of the location. However, this resolution of guidance is often insufficient for blind travelers. In this thesis, we propose a crowdsourcing based micro navigation system for BVI users in both indoor and outdoor environments. To achieve this goal, our system includes three parts: crowdsourcing reports generated by volunteers using the volunteer application, landmarks validation performed by the system administrator using the admin application, and the BVI user navigation obtained through the BVI user application. In addition, we provide accessible audio navigation for indoor and outdoor environments required to deliver real time step by step landmark information to BVI users. Crowdsourcing is enabled by the contribution of many volunteers which use the proposed volunteer application to report specific landmarks in the environment including their location, description and surrounding landmarks. These reports which are uploaded to the server database, are validated by the admin application which updates the server database and deploy BLE tags for indoor environment. The BVI user application localizes users by GPS outdoors and BLE proximity technology indoors. Using the real-time location of users and the landmark node graph we built from updated server database, this application provides the shortest route to the destination and real time “micro-navigation” information describing how to get to the next landmark’s location with corresponding distance & orientation. This information is used ix to make users well aware of where they are, and guide users to their chosen destination within a cane’s distance. This application will improve the confidence and safety of BVI users by enabling them to explore and get navigation in both indoor and outdoor environments

Assisted spatial navigation: new directions

Blockchain technology brings new possibilities in assisted spatial navigation. Decentralized map building enables collaboration between users around the world, while providing researchers with a common reference map for extending the capabilities of navigational systems towards more intuitive and accurate landmark navigation assistance. Research on landmark navigation has been mainly focused on the visual characteristics of landmarks. Human behavior, however, has systematically been shown to be enhanced in the presence of multisensory unified events. We propose, therefore, the enhancement of spatial assisted navigation by utilizing landmarks that are multisensory and semantically congruent. Further, our research will provide insights in terms of the auditory parameters that could be combined with a given visual landmark, so as to facilitate landmark retrieval algorithms and user satisfaction during assisted spatial navigation

Inclusive Landmark based Pedestrian Wayfinding via Multi-modal Directions

Navigational skills are fundamental to travelling from place to place, personal independence and community integration [2]. Current research in pedestrian wayfinding suggests that people vary significantly in their choice of navigation modalities [6, 7, 25]. In addition, pedestrians with learning disabilities find it difficult to recall routes travelled daily and stay oriented while enroute to unknown locations. This paper proposes a wayfinding interface that has 2 components: 1) temporary poly-coated cardboard signage along with imprinted information indicating a specific destination, minutes by foot, directional arrow and a QR code; 2) online interactive website to provide additional contextualized navigation instructions for pedestrians through various modalities. The University of Toronto Scarborough campus (UTSC) is being used as the physical environment to implement and test the proposed wayfinding interface. The QR code tags link the cardboard signage to the online interface and generate streaming of route instructions in the modes of panoramic video, photographs, aerial map, audio or text. The goal of the proposed wayfinding system is to aid UTSC pedestrians - especially those with learning disabilities - to orient themselves and navigate to their destination through multi-modal landmark-based, turn-by-turn directions

DYNAMICS OF COLLABORATIVE NAVIGATION AND APPLYING DATA DRIVEN METHODS TO IMPROVE PEDESTRIAN NAVIGATION INSTRUCTIONS AT DECISION POINTS FOR PEOPLE OF VARYING SPATIAL APTITUDES

Cognitive Geography seeks to understand individual decision-making variations based on fundamental cognitive differences between people of varying spatial aptitudes. Understanding fundamental behavioral discrepancies among individuals is an important step to improve navigation algorithms and the overall travel experience. Contemporary navigation aids, although helpful in providing turn-by-turn directions, lack important capabilities to distinguish decision points for their features and importance. Existing systems lack the ability to generate landmark or decision point based instructions using real-time or crowd sourced data. Systems cannot customize personalized instructions for individuals based on inherent spatial ability, travel history, or situations. This dissertation presents a novel experimental setup to examine simultaneous wayfinding behavior for people of varying spatial abilities. This study reveals discrepancies in the information processing, landmark preference and spatial information communication among groups possessing differing abilities. Empirical data is used to validate computational salience techniques that endeavor to predict the difficulty of decision point use from the structure of the routes. Outlink score and outflux score, two meta-algorithms that derive secondary scores from existing metrics of network analysis, are explored. These two algorithms approximate human cognitive variation in navigation by analyzing neighboring and directional effect properties of decision point nodes within a routing network. The results are validated by a human wayfinding experiment, results show that these metrics generally improve the prediction of errors. In addition, a model of personalized weighting for users\u27 characteristics is derived from a SVMrank machine learning method. Such a system can effectively rank decision point difficulty based on user behavior and derive weighted models for navigators that reflect their individual tendencies. The weights reflect certain characteristics of groups. Such models can serve as personal travel profiles, and potentially be used to complement sense-of-direction surveys in classifying wayfinders. A prototype with augmented instructions for pedestrian navigation is created and tested, with particular focus on investigating how augmented instructions at particular decision points affect spatial learning. The results demonstrate that survey knowledge acquisition is improved for people with low spatial ability while decreased for people of high spatial ability. Finally, contributions are summarized, conclusions are provided, and future implications are discussed

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