Shortcut suggestion based on collaborative user feedback for suitable wheelchair route planning

Minetto, Rodrigo; Kozievitch, Nádia P.; Silva, Ricardo Dutra da; Almeida, Leonelo Dell Anhol; Santi, Juliana de

doi:10.1109/itsc.2016.7795938

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…Several studies indicate that RP can be useful for individuals with disabilities or the elderly. Most of them are dedicated to RP for wheelchair users formulated: (1) in a graph-based approach [34] employing a greedy algorithm, Floyd-Warshall algorithm [35], to minimize the average shortest path length by selecting the nearly best shortcut edges to be inserted in the refined graph; (2) in a bottom-up graph approach [36] with integrated geographic information system (GIS) maps; and (3) in a framework incorporating a data model for both indoor and outdoor accessibility, based on modified Dijkstra algorithm [37]. In [38], a working prototype for a mobile RP for people aging with mobility disabilities was presented.…”

Section: Related Work For Route Planning Modelingmentioning

confidence: 99%

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A route planning framework for smart wearable assistive navigation systems

Ntakolia

Iakovidis

2021

SN Appl. Sci.

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Route planning (RP) enables individuals to navigate in unfamiliar environments. Current RP methodologies generate routes that optimize criteria relevant to the traveling distance or time, whereas most of them do not consider personal preferences or needs. Also, most of the current smart wearable assistive navigation systems offer limited support to individuals with disabilities by providing obstacle avoidance instructions, but often neglecting their special requirements with respect to the route quality. Motivated by the mobility needs of such individuals, this study proposes a novel RP framework for assistive navigation that copes these open issues. The framework is based on a novel mixed 0–1 integer nonlinear programming model for solving the RP problem with constraints originating from the needs of individuals with disabilities; unlike previous models, it minimizes: (1) the collision risk with obstacles within a path by prioritizing the safer paths; (2) the walking time; (3) the number of turns by constructing smooth paths, and (4) the loss of cultural interest by penalizing multiple crossovers of the same paths, while satisfying user preferences, such as points of interest to visit and a desired tour duration. The proposed framework is applied for the development of a system module for safe navigation of visually impaired individuals (VIIs) in outdoor cultural spaces. The module is evaluated in a variety of navigation scenarios with different parameters. The results demonstrate the comparative advantage of our RP model over relevant state-of-the-art models, by generating safer and more convenient routes for the VIIs.

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Section: Related Work For Route Planning Modelingmentioning

confidence: 99%

“…The shortest path for users with wheelchair [34] A graph-based model Greedy Floyd-Warshall algorithm…”

Section: Route Planning Models With Disability Aspectsmentioning

confidence: 99%

A route planning framework for smart wearable assistive navigation systems

Ntakolia

Iakovidis

2021

SN Appl. Sci.

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“…The development of efficient tools for querying and evolving data graphs under different kinds of constraints is essential in this context. Examples of user-defined constraints in this context include routes with a limit on carbon footprint, or that are accessible for wheelchair users ( [4]).…”

Section: Introductionmentioning

confidence: 99%

Graph Constraints in Urban Computing: Dealing with Conditions in Processing Urban Data

d’Orazio

Ferrari

Hara

et al. 2017

2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and I

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Smart Cities is a worldwide initiative leading to better exploit the resources in a city in order to offer higher level services to people. In this context, urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, traffic devices, vehicles, buildings, and humans, to tackle the major issues that cities face, e.g. air pollution, increased energy consumption and traffic congestion. The majority of these information can be represented as graphs, such as the transportation network, in which places (nodes) are connected by some form of public transportation (edges). A vision of the "city of the future", or even the city of the present, rests on the integration of science and technology through information systems. This vision requires a rethinking of the relationships between technology, government, city managers, business, academia and the research community. This position paper presents our views towards developing techniques for querying and evolving graph-modeled datasets based on userdefined constraints. Our focus is to show how these techniques can be applied to effectively retrieve urban data and have automated mechanisms that guarantee data consistency.

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