scholarly journals User-Specific Route Planning for People with Motor Disabilities: A Fuzzy Approach

2021 ◽  
Vol 10 (2) ◽  
pp. 65
Author(s):  
Amin Gharebaghi ◽  
Mir-Abolfazl Mostafavi ◽  
Geoffrey Edwards ◽  
Patrick Fougeyrollas
Keyword(s):  
Route Planning ◽  
Quebec City ◽  
Navigation Systems ◽  
Fuzzy Approach ◽  
Wheelchair Users ◽  
Motor Disabilities ◽  
Confidence Levels ◽  
Novel Approach ◽  
Pedestrian Networks ◽  
Difficulty Walking

Mobility is fundamental for social participation. Everyone benefits from pedestrian networks for their mobility and daily activities. People without disabilities may have little difficulty walking on narrow sidewalks, over potholes, and so on. However, people with motor disabilities (PWMD) may find it more difficult to deal with such conditions. For PWMD, even routine trips are often fraught with problems, with many different obstacles restricting their mobility and consequently rendering their participation in social and recreational activities difficult. The potential problems and risks associated with mobility for PWMD could be significantly reduced if navigation systems provided them with appropriate accessible routes. These routes should consider PWMD’s personal capabilities as well as sidewalk-network conditions. In this paper, we propose a novel approach for computing a user-specific route for PWMD. Such a route is personalized based on the user’s confidence to deal with obstacles such as slopes, uneven pavement, etc. We show how user reported confidence levels could be used to aggregate sidewalk conditions in a routing model to offer user-specific routes. The proposed methodology was developed using a fuzzy approach and is evaluated by manual wheelchair users in Quebec City.

scholarly journals "Improved Geometric Network Model" (IGNM): a novel approach for deriving Connectivity Graphs for Indoor Navigation

2014 ◽  
Vol II-4 ◽  
pp. 45-51 ◽  
Author(s):  
F. Mortari ◽  
S. Zlatanova ◽  
L. Liu ◽  
E. Clementini
Keyword(s):  
Route Planning ◽  
Research Area ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Indoor Space ◽  
The Past ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Floor Plans ◽  
Algorithmic Strategy

Over the past few years Personal Navigation Systems have become an established tool for route planning, but they are mainly designed for outdoor environments. Indoor navigation is still a challenging research area for several reasons: positioning is not very accurate, users can freely move between the interior boundaries of buildings, path network construction process may not be easy and straightforward due to complexity of indoor space configurations. Therefore the creation of a good network is essential for deriving overall connectivity of a building and for representing position of objects within the environment. This paper reviews current approaches to automatic derivation of route graphs for indoor navigation and discusses some of their limitations. Then, it introduces a novel algorithmic strategy for extracting a 3D connectivity graph for indoor navigation based on 2D floor plans.

The Most Preferred Route of the Car Navigation System: A Systems Engineering Approach

2013 ◽  
Vol 712-715 ◽  
pp. 2680-2685
Author(s):  
Kyung Il Choe
Keyword(s):  
Systems Engineering ◽  
Route Planning ◽  
Point Of View ◽  
Navigation Systems ◽  
Engineering Approach ◽  
System A ◽  
Shortest Route ◽  
Baseline System ◽  
Baseline Component ◽  
Car Navigation

The typical route planning of on-board car navigation systems (CNS) attempts to find the shortest route without considering users preferences and driving contexts. However it is more effective for a user to find the most preferred route rather than the shortest one. We propose a systems engineering approach for finding the most preferred route by considering and tracking the requirements of CNS route planning from the business point of view. Our approach consists of 4 baselines: customer baseline, system baseline component baseline, and design baseline. The architecture of a route planning engine is suggested according to the baselines.

scholarly journals A novel approach for detail surveys by the motorized GPSSIT concept in residentials areas and its application

2014 ◽  
Vol 20 (1) ◽  
pp. 70-83
Author(s):  
Ibrahim Kalayci ◽  
Sermet Ogutcu
Keyword(s):  
Tall Buildings ◽  
Satellite Navigation ◽  
Navigation Systems ◽  
Residential Areas ◽  
Novel Approach ◽  
Stop And Go ◽  
Housing Area ◽  
Gnss Receivers ◽  
Survey Instruments ◽  
Satellite Navigation Systems

This paper introduces the usage and reliability of Motorized GPSSIT technique which is a novel approach for surveying. It reviews the advantages of Motorized GPSSIT concept and also considers to provide GNSS accuracy in the process of surveying especially for the cases which cannot be surveyed directly by the satellite navigation systems (GPS-GNSS), such as closely packed residential areas, tall buildings, trees, etc., and also places which GNSS receivers cannot be work efficiently due to signal interferences. In this technique, all the survey instruments are installed on a bed of a pick-up truck whereas in present techniques they are installed on the ground, therefore it is called Motorized GPSSIT. Study area was chosen within the housing area of our campus. In this area, classical surveying, GPSSIT and Motorized GPSSIT were performed to collect data for comparison and for the analysis of this technique's usability and reliability. Stop and Go and RTK surveying techniques were performed with GPSSIT and Motorized GPSSIT concepts. It is shown that the Motorized GPSSIT technique is applicable as other present techniques in terms of accuracy and reliability.

scholarly journals Predictive Monitoring with Logic-Calibrated Uncertainty for Cyber-Physical Systems

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-25
Author(s):  
Meiyi Ma ◽  
John Stankovic ◽  
Ezio Bartocci ◽  
Lu Feng
Keyword(s):  
Neural Networks ◽  
Real World ◽  
Recurrent Neural Networks ◽  
Cyber Physical Systems ◽  
Uncertainty Estimation ◽  
Physical Systems ◽  
Confidence Levels ◽  
Novel Approach ◽  
Infinite Set

Predictive monitoring—making predictions about future states and monitoring if the predicted states satisfy requirements—offers a promising paradigm in supporting the decision making of Cyber-Physical Systems (CPS). Existing works of predictive monitoring mostly focus on monitoring individual predictions rather than sequential predictions. We develop a novel approach for monitoring sequential predictions generated from Bayesian Recurrent Neural Networks (RNNs) that can capture the inherent uncertainty in CPS, drawing on insights from our study of real-world CPS datasets. We propose a new logic named Signal Temporal Logic with Uncertainty (STL-U) to monitor a flowpipe containing an infinite set of uncertain sequences predicted by Bayesian RNNs. We define STL-U strong and weak satisfaction semantics based on whether all or some sequences contained in a flowpipe satisfy the requirement. We also develop methods to compute the range of confidence levels under which a flowpipe is guaranteed to strongly (weakly) satisfy an STL-U formula. Furthermore, we develop novel criteria that leverage STL-U monitoring results to calibrate the uncertainty estimation in Bayesian RNNs. Finally, we evaluate the proposed approach via experiments with real-world CPS datasets and a simulated smart city case study, which show very encouraging results of STL-U based predictive monitoring approach outperforming baselines.

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