Indoor Routing for Individuals with Special Needs and Preferences

Recently much research has been focused on developing techniques and systems for providing routes within buildings. While outdoor routing is based on criteria such as shortest, fastest and least turns, indoor routing is primarily based on accessibility and safety criteria, and while outdoor routing could adversely be impacted by weather and traffic, among other conditions, such conditions do not affect indoor routing. However, developing techniques that meet user's indoor routing preferences, especially those with special needs, is a challenging task. An example is development of a set of techniques that avoids a hallway with a protruding object to allow safe passage by the visually impaired or that avoids stairs for the mobility impaired. In this article, we present and analyze new techniques based on the Americans with Disabilities Act (ADA) standards that provide routes within buildings and meet user's special needs and preferences.

[1]  Thomas Ertl,et al.  Design and development of an indoor navigation and object identification system for the blind , 2003, ASSETS.

[2]  Grantham K. H. Pang,et al.  Intelligent Route Selection for In-vehicle Navigation Systems , 2002 .

[3]  Andreas Butz,et al.  A hybrid indoor navigation system , 2001, IUI '01.

[4]  Vassileios Tsetsos,et al.  Semantic Location Based Services for Smart Spaces , 2007, MTSR.

[5]  Ming-Hei Chu,et al.  Route Selection for Vehicle Navigation and Control , 2007, 2007 5th IEEE International Conference on Industrial Informatics.

[6]  Martin Raubal,et al.  An Indoor Routing Algorithm for the Blind: Development and Comparison to a Routing Algorithm for the Sighted , 2009, Int. J. Geogr. Inf. Sci..

[7]  Stefan Schlott,et al.  Semantic Information Retrieval in the COMPASS Location System , 2006, UCS.

[8]  Stathes Hadjiefthymiades,et al.  Environments , 2006, 2006 ACS/IEEE International Conference on Pervasive Services.

[9]  Michael Byron,et al.  Satisficing and Maximizing: Moral Theorists on Practical Reason , 2004 .

[10]  M. Raubal Cognitive Engineering for Geographic Information Science , 2009 .

[11]  Shannon Dawn Moeser Cognitive Mapping in a Complex Building , 1988 .

[12]  Martin Raubal,et al.  Comparing the Complexity of Wayfinding Tasks in Built Environments , 1998 .

[13]  Birgit Elias,et al.  Pedestrian Navigation - Creating a tailored geodatabase for routing , 2007, 2007 4th Workshop on Positioning, Navigation and Communication.

[14]  Stathes Hadjiefthymiades,et al.  OntoNav: A Semantic Indoor Navigation System , 2005, MCMP@MDM.

[15]  Hassan A. Karimi,et al.  Universal Navigation through Social Networking , 2009, HCI.

[16]  Hassan A. Karimi,et al.  Universal Navigation: Concept and Algorithms , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.

[17]  Joel Barnes,et al.  High Precision Indoor and Outdoor Positioning using LocataNet , 2003 .

[18]  L. Mcclain,et al.  Shopping center wheelchair accessibility: ongoing advocacy to implement the Americans with Disabilities Act of 1990. , 2000, Public health nursing.

[19]  Hassan A. Karimi,et al.  ONALIN: Ontology and Algorithm for Indoor Routing , 2009, 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware.

[20]  Markus Knauff,et al.  Up the down staircase : Wayfinding strategies in multi-level buildings , 2006 .

[21]  Srinivas Peeta,et al.  A Hybrid Model for Driver Route Choice Incorporating En-Route Attributes and Real-Time Information Effects , 2003 .