eNav navigation system
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| Route planner | |
| languages | 9 |
| editorial staff | RWTH Aachen University |
| On-line | 2016 (currently active) |
| http://enav.embedded.rwth-aachen.de | |
The project eNav - Navigation system for electric wheelchairs integrates different methods and ideas with embedded systems in order to better measure the battery capacity of electric wheelchairs and to use them more effectively. In addition, possible barriers that can be bypassed are discovered. As a special feature, the user can choose between the shortest possible route or the most energy-efficient route possible . eNav can currently be accessed as a route planner via a browser. In the future, a free navigation app should be available in the Google Play Store .
eNav is a project of RWTH Aachen , led by " computer science - Chair I11 - Embedded Software" has been established to enhance the quality of life of people with limited mobility.
idea
The original idea for eNav arose from the fact that previous navigation systems provided little support to people in electric wheelchairs. A normal navigation system can neither provide information about how steep the route to be traveled is, nor whether the planned route can even manage with the current battery level. Based on the wheelchair routing project, the idea arose to specify a corresponding navigation system. The fact that the built-in battery level detection of electric wheelchairs is imprecise and unreliable gave rise to the motivation to develop a corresponding system to improve the battery level detection. In addition, new methods are to be used to calculate an energy-efficient route by considering the topographical location.
Maps
In addition to barrier information, which is necessary to evaluate the navigability of a route, a 3D map with floor covering information is required to calculate the energy-efficient route . In addition, the accessibility of the individual buildings ( POI ) is interesting. In order to ensure all of these map properties, the eNav map material consists of four layers.
1. OpenStreetMap
The first layer uses OpenStreetMap as a basis. The entire road network and information about accessibility are taken from this. The latter is either explicitly present or is derived from other information, such as e.g. B. stairs or ramps.
2. Laser scan
For the second shift, the Cologne District Government provided laser scan data with an accuracy of ± 20 cm. A three-dimensional map can be created with this, and the gradient of the road is calculated from these 3D coordinates . This has a significant influence on the energy consumption of an electric wheelchair.
3. Flooring
Flooring information forms the third layer. These are supplemented by the information from the Aachen city region , from which it can be seen whether a street is cobbled or asphalted. With the help of volunteer employees ( Crowdsourcing or Volunteered Geographic Information (VGI) or Contributed Geographical Information (CGI) ), information about flooring is continuously collected and entered into the database. The technique used is the vertical acceleration of the acceleration sensor of a smartphone . Based on the measured values, it can be concluded whether the vehicle was driven over cobblestones or asphalt. If the route is located using GPS , a surface can then be assigned to it.
4. POI
In the last layer, a link is made to Wheelmap.org so that the user can get information about the accessibility of buildings while navigating . Visually, the goals ("point of interest" or POI) are displayed in green (barrier-free), orange (limited barrier-free), red (not barrier-free) or gray (unknown).
Most energy efficient route
A weighted graph is required for routing. To calculate the shortest route, the length of the road is used as the edge weight . With energy-efficient routing, the power consumption of an electric wheelchair forms the edge weight. The power consumption of an electric wheelchair on an edge is currently determined by the following influencing factors:
The following consumption function follows from this:
Due to the exponential weighting function, a special A * algorithm - heuristic was developed, which accelerates the route calculation.
profitability
As part of the project, an evaluation has shown that in 41% of all tested cases there is a route that is more efficient than the shortest route.
Individual evidence
- ↑ MÜLLER, Astrid, et al. A route planner for wheelchair users based on OpenStreetMap data conception, implementation and perspectives. Applied Geoinformatics, 2010. ( full text )
- ↑ Cologne district government on ALS
- ↑ DŽAFIĆ, Dzenan, et al. Modification of the A * algorithm for energy-efficient 3D routing. 2013. ( full text )
- ↑ FRANKE, Dominik, et al. Concept of a mobile OSM navigation system for electric vehicles. Applied Geoinformatics, 2011, pp. 148–157. ( Full text )
- ↑ a b DŽAFIĆ, Dženan, et al. Integration of flooring information for energy-efficient routing of electric wheelchairs. 2014. ( full text )