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{{PAGETITEL:eNav-Navigationssystem}}
{{Infobox Website
 | name = eNav
 | url = http://enav.embedded.rwth-aachen.de
 | logo = [[File:ENav-Logo.svg|200px|zentriert]]
 | type = [[Route planning software]]
 | language = 8 Languages
 | launch_date = 2016
 | owner = [[RWTH Aachen University]]
 | current_status = Active
}}
[[file:ENav-Planner.png|thumbnail]]
The project '''eNav – A navigation system for electric wheelchairs''' uses several distinct methods and ideas concerning embedded systems to better measure as well as utilize the battery capacity of [[Motorized wheelchair| electric wheelchairs]]. Furthermore, barriers are detected, which can then be avoided. The hallmark of the navigation system is the calculation of a energy efficient [[Route]], which is conducted additionally to the calculation of the shortest route. The user has the option, to choose between both. eNav can be accessed as [[route planner]] using a web browser. In the near future, an free navigation app should be available in the [[Google Play|Google Play Store]].

eNav is a project at the [[RWTH Aachen]], which has been launched by the [[informatics]] chair I11 to increase the life quality of people with an impairment.

== Idea ==
The initial idea for eNav originated because of the lack of support from present Navigation systems for electric wheelchair users. A common navigation system can neither provide information about the incline of the to be travered route, nor can it estimate whether the planned [[Route]] can be overcome with the current battery level. Inspired by the project RollStuhlrouting<ref>MÜLLER, Astrid, et al. Ein Routenplaner für Rollstuhlfahrer auf der Basis von OpenStreetMap-Daten-Konzeption, Realisierung und Perspektiven. Angewandte Geoinformatik, 2010. ([https://www.vde-verlag.de/proceedings-en/537495033.html Full text])</ref> an idea originated, to specify a according navigation-system. Because of the fact that battery level indicators of electric wheelchairs are inaccurate and unreliable, the motivation arises to develop a system with improved battery level detection. Additionally, emerging technologies should be used to calculate a energy efficient route by consideration of topographical characteristics. The user of the navigation system can choose between the shortest and a energy efficient route.

== Map-data ==
[[file:Kartenquellen.png|thumb|Map layers]]
For the calculation of the energy-efficient route, a [[Cartesian coordinate system | 3D]]-map with road surface information is required for the eNav-system. Furthermore, information about accessibility is required to assure 
practicability of the calculated route for an electric wheelchair user. Additionally, the accessibility information of individual buildings ([[Point of Interest|POI]]) is of interest. The map-data of eNav consists of four layers to warrant all these map-properties.

=== 1. OpenStreetMap ===
The first layer is formed by [[OpenStreetMap]] as basis. From it, the complete road network is extracted. Moreover, information about accessibility can be directly extracted or derived from other information like, for example, stairs or ramps.  

=== 2. Laserscan ===
For the second layer, the [[Bezirksregierung| district government]] of [[Köln | Cologne]] provided [[Lidar|Laserscan-data]]<ref>[http://www.bezreg-koeln.nrw.de/brk_internet/geobasis/hoehenmodelle/index.html District government of cologne about ALS]</ref>. The accuracy of this data is ±20 cm. The data provides a possibility to create a three-dimensional map for the system. The incline of a road can be derived from the [[Cartesian coordinate system | three-dimensional coordinates]] of the map. The incline has a significant influence on the energy consumption of a electric wheelchair<ref>DŽAFIĆ, Dzenan, et al. Modifikation des A*-Algorithmus für energieeffizientes 3D-Routing. 2013. ([http://gispoint.de/fileadmin/user_upload/paper_gis_open/537533019.pdf Full text])</ref>.

=== 3. Route surface ===
Route surface information forms the third layer. These are partly enriched by the information provided by the [[Städteregion Aachen]]. This information contains accurate details about the surface of a road, for example, the surface is [[asphalt]] or [[cobblestone]]. Moreover, by using [[crowd-sourcing]] or more specifically  [[Volunteered geographic information]] (VGI) and Contributed Geographical Information (CGI), road surface information is permanently accumulated and incorporated. This is done by measuring the vertical acceleration of an [[accelerometer]] of a [[smartphone]]. Based on the measured values, the road surface type can be retrospectively deduced, whether it consisted out of cobblestone or asphalt. By using [[GPS]], an road surface type can be assigned to a traveled route.

=== 4. POI ===
In the last layer a connection with [[Wheelmap.org]] is made, to enable the user to obtain information about [[accessibility]] of buildings during navigation. That means, the POI are indicated to the user as Green (Accessible), Orange (Limited accessible), Red (Not accessible) or grey (unknown). An [[Point of Interest|Point Of Interest]] can be directly selected as a route target.

== Energy-efficient Route ==
[[file:Verbrauchfunktion.png|thumb|upright=1.1|right|Exponential consumption function]]
For routing a [[weighted graph]] is necessary. For calculating the shortest route, the length of the road is used as edge weight. During energy-efficient routing, the [[Electric energy consumption | energy consumption]] of an [[Motorized wheelchair | electric wheelchair]] forms the edge weight <ref>FRANKE, Dominik, et al. Konzept eines mobilen OSM-Navigationssystems für Elektrofahrzeuge. Angewandte Geoinformatik, 2011, S. 148–157. ([http://gispoint.de/fileadmin/user_upload/paper_gis_open/537508024.pdf Full text])</ref>. Currently, the energy consumption of an electric wheelchair is determined by following influencing faktors:
* Length of the edge
* [[Incline]] of the edge
* [[Friction]] on the edge (Road surface) <ref name="Agit2014">DŽAFIĆ, Dženan, et al. Integration von Bodenbelagsinformationen zum energieeffizienten Routen von Elektrorollstühlen. 2014. ([http://gispoint.de/fileadmin/user_upload/paper_gis_open/537543014.pdf Full text])</ref>
From this the following consumption function can be derived:
:<math>Normal consumption \times Length \times 1{,}16^{Incline} \times friction coefficient</math>
Because of the exponential weighting function an special [[A*]]-[[heuristic]] has been developed, which accelerates route calculation.

== Viability ==
[[file:Efficient vs. shortest.png|thumb|200px|right]]
An [[evaluation]] as part of the eNav-Project found, that in 41 % of all tested cases a route exists, which is more [[Efficient energy use | energy-efficient]] than the shortest<ref name="Agit2014" />.

== References ==
<references />

[[category:Automotive electronics]]
[[category:Navigation device]]
[[Category:Travel- and routeplanning]]
[[Category:Barrier freedom]]