Use and perceptions of pedestrian navigation apps: findings from Bologna and Porto

Pedestrian Navigation Applications (PNAs) provide assistance in terms of self-localization, space recognition, and turn-by-turn navigation. The use, motivations and perceptions associated with these applications have been under investigated due to users being insufficiently involved in their design and development. This paper analyses the extent to which PNAs are used for assisting people to walk, the frequencies and reasons of using these applications, the perceptions about them, and the barriers preventing them from being used. The study is supported by a questionnaire (N = 1438) that was administered in Bologna (Italy) and Porto (Portugal). Results indicated that 42% of the respondents use PNAs mainly on an occasional basis to find locations and the shortest routes. Google Maps was the preferred navigation service. Statistical tests showed that PNAs were more likely to be used by younger adults and students. The lack of need was the main reason for not using these apps, due to the good spatial knowledge of the cities or the non-use of the pedestrian mode for regular trips. Respondents would like to have apps that are more accurate, usable, and adjusted to pedestrian navigation. The findings described in this paper could be helpful for future designs of PNAs, especially to match pedestrian needs more effectively and to enhance the role of these apps in promoting healthier and sustainable lifestyles.JPI Urban Europe, FCT—PT (ENSUF/0004/2016), MIUR-I, FFG—A and RPF—C

Tools in and out of sight : an analysis informed by Cultural-Historical Activity Theory of audio-haptic activities involving people with visual impairments supported by technology

The main purpose of this thesis is to present a Cultural-Historical Activity Theory (CHAT) based analysis of the activities conducted by and with visually impaired users supported by audio-haptic technology.This thesis covers several studies conducted in two projects. The studies evaluate the use of audio-haptic technologies to support and/or mediate the activities of people with visual impairment. The focus is on the activities involving access to two-dimensional information, such as pictures or maps. People with visual impairments can use commercially available solutions to explore static information (raised lined maps and pictures, for example). Solu-tions for dynamic access, such as drawing a picture or using a map while moving around, are more scarce. Two distinct projects were initiated to remedy the scarcity of dynamic access solutions, specifically focusing on two separate activities.The first project, HaptiMap, focused on pedestrian outdoors navigation through audio feedback and gestures mediated by a GPS equipped mobile phone. The second project, HIPP, focused on drawing and learning about 2D representations in a school setting with the help of haptic and audio feedback. In both cases, visual feedback was also present in the technology, enabling people with vision to take advantage of that modality too.The research questions addressed are: How can audio and haptic interaction mediate activ-ities for people with visual impairment? Are there features of the programming that help or hinder this mediation? How can CHAT, and specifically the Activity Checklist, be used to shape the design process, when designing audio haptic technology together with persons with visual impairments?Results show the usefulness of the Activity Checklist as a tool in the design process, and provide practical application examples. A general conclusion emphasises the importance of modularity, standards, and libre software in rehabilitation technology to support the development of the activities over time and to let the code evolve with them, as a lifelong iterative development process. The research also provides specific design recommendations for the design of the type of audio haptic systems involved

In-Vehicle Human Machine Interface: Investigating the Effects of Tactile Displays on Information Presentation in Automated Vehicles

Background: Semi-autonomous vehicles still require human drivers to take over when the automated systems can no longer perform the driving task. Objective: The goal of this study was to design and test the effects of six meaningful tactile signal types, representing six driving scenarios (i.e., navigation, speed, surrounding vehicles, over the speed limit, headway reductions, and pedestrian status) respectively, and two pattern durations (lower and higher urgencies), on drivers\u27 perception and performance during automated driving. Methods: Sixteen volunteers participated in an experiment utilizing a medium-fidelity driving simulator presenting vibrotactile signals via 20 tactors embedded in the seat back, pan, and belt. Participants completed four separate driving sessions with 30 tactile signals presented randomly throughout each drive. Reaction times (RT), interpretation accuracy, and subjective ratings were measured. Results: Results illustrated shorter RTs and higher intuitive ratings for higher urgency patterns than lower urgency patterns. Pedestrian status and headway reduction signals were associated with shorter RTs and increased confidence ratings, compared to other tactile signal types. Lastly, among six tactile signals, surrounding vehicle and navigation signal types had the highest interpretation accuracy. Conclusion: These results will be used as preliminary data for future studies that aim to investigate the effects of meaningful tactile displays on automated vehicle takeover performance in complex situations (e.g., urban areas) where actual takeovers are required. The findings of this study will inform the design of next-generation in-vehicle human-machine interfaces

Iterative Design and Prototyping of Computer Vision Mediated Remote Sighted Assistance

Remote sighted assistance (RSA) is an emerging navigational aid for people with visual impairments (PVI). Using scenario-based design to illustrate our ideas, we developed a prototype showcasing potential applications for computer vision to support RSA interactions. We reviewed the prototype demonstrating real-world navigation scenarios with an RSA expert, and then iteratively refined the prototype based on feedback. We reviewed the refined prototype with 12 RSA professionals to evaluate the desirability and feasibility of the prototyped computer vision concepts. The RSA expert and professionals were engaged by, and reacted insightfully and constructively to the proposed design ideas. We discuss what we learned about key resources, goals, and challenges of the RSA prosthetic practice through our iterative prototype review, as well as implications for the design of RSA systems and the integration of computer vision technologies into RSA

Dynamic Bayesian Collective Awareness Models for a Network of Ego-Things

A novel approach is proposed for multimodal collective awareness (CA) of multiple networked intelligent agents. Each agent is here considered as an Internet-of-Things (IoT) node equipped with machine learning capabilities; CA aims to provide the network with updated causal knowledge of the state of execution of actions of each node performing a joint task, with particular attention to anomalies that can arise. Data-driven dynamic Bayesian models learned from multisensory data recorded during the normal realization of a joint task (agent network experience) are used for distributed state estimation of agents and detection of abnormalities. A set of switching dynamic Bayesian network (DBN) models collectively learned in a training phase, each related to particular sensorial modality, is used to allow each agent in the network to perform synchronous estimation of possible abnormalities occurring when a new task of the same type is jointly performed. Collective DBN (CDBN) learning is performed by unsupervised clustering of generalized errors (GEs) obtained from a starting generalized model. A growing neural gas (GNG) algorithm is used as a basis to learn the discrete switching variables at the semantic level. Conditional probabilities linking nodes in the CDBN models are estimated using obtained clusters. CDBN models are associated with a Bayesian inference method, namely, distributed Markov jump particle filter (D-MJPF), employed for joint state estimation and abnormality detection. The effects of networking protocols and of communications in the estimation of state and abnormalities are analyzed. Performance is evaluated by using a small network of two autonomous vehicles performing joint navigation tasks in a controlled environment. In the proposed method, first the sharing of observations is considered in ideal condition, and then the effects of a wireless communication channel have been analyzed for the collective abnormality estimation of the agents. Rician wireless channel and the usage of two protocols (i.e., IEEE 802.11p and IEEE 802.15.4) along with different channel conditions are considered as well

Overcoming Spatial Deskilling Using Landmark-Based Navigation Assistance Systems

Abstract Background The repeated use of navigation assistance systems leads to decreased spatial orienting abilities. Previous studies demonstrated that augmentation of landmarks using auditory navigation instructions can improve incidental spatial learning when driving on a single route through an unfamiliar environment. Objective Based on these results, a series of experiments was conducted to further investigate both the impairment of spatial knowledge acquisition by standard navigation instructions and the positive impact of landmark augmentation in auditory navigation instructions on incidental spatial learning. Method The first Experiment replicated the previous setup in a driving simulator without additional visual route indicators. In a second experiment, spatial knowledge was tested after watching a video depicting assisted navigation along a real-world urban route. Finally, a third Experiment investigated incidental spatial knowledge acquisition when participants actively navigated through an unrestricted real-world,urban environment. Results All three experiments demonstrated better cued-recall performance for participants navigating with landmark-based auditory navigation instructions as compared to standard instructions. Notably, standard instructions were associated with reduced learning of landmarks at navigation relevant intersections as compared to landmarks alongside straight segments and the recognition of novel landmarks. Conclusion The results revealed a suppression of spatial learning by established navigation instructions, which were overcome by landmark-based navigation instructions. This emphasizes the positive impact of auditory landmark augmentation on incidental spatial learning and its generalizability to real-life settings. Application This research is paving the way for navigation assistants that, instead of impairing orienting abilities, incidentally foster spatial learning during every-day navigation. Précis This series of three experiments replicates the suppression of spatial learning by standard navigation instructions and the positive impact of landmark augmentation in auditory navigation instructions on incidental spatial learning during assisted navigation. Three experiments with growing degree of realism revealed the applicability and generalizability to real-life settings

Personalised information services for bikers

Modal share of cycling is growing; however, information services are to be significantly improved. Our research aim was to reveal, how the available real-time data can be used to support bikers and to ease decision making by provision of personalised information. We have identified the categories of biker information services and then the route planner applications have been analysed in order to point out the exemplary solutions. The attributes of mobility and information management, as well as their correspondences have been revealed in order to develop appropriate information services. We have carried out a questionnaire survey to identify bikers’ habits and expectations towards information services. An analysis method has been elaborated which is applicable to determine the correspondences between mobility and information management attributes. The results are to be applied as bases during development of adaptive, personalised information application aiding decisions