An experimental ant colony approach for the geolocation of verbal route descriptions
Knowledge-Based Systems
Evaluating and minimizing ambiguities in qualitative route instructions
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Automated feeding of POI base for the generation of route descriptions
Proceedings of the 6th Euro American Conference on Telematics and Information Systems
On qualitative route descriptions: representation and computational complexity
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Moving beyond the map: automated landmark based pedestrian guidance using street level panoramas
Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services
Qualitative constraint satisfaction problems: An extended framework with landmarks
Artificial Intelligence
Flexible route guidance through turn instruction graphs
Proceedings of the 1st ACM SIGSPATIAL International Workshop on MapInteraction
Interactive cartographic route descriptions
Geoinformatica
| Hi-index | 0.00 |
This article addresses the problem of incorporating cognitively salient landmarks in computer-generated navigation instructions. On the basis of a review of the existing literature in the domain of navigation with landmarks, the article develops algorithms for generating routing instructions that include references to landmarks. The most basic algorithm uses a new weighting model to annotate simple routes with references to landmarks. A key novel feature of this algorithm is that it depends only on commonly available data and generic capabilities of existing web mapping environments. A suite of extensions are also proposed for improving the cognitive ergonomics of the basic landmark instructions. A case study, implemented within a national online routing system, demonstrates practicality of the approach. The article then concludes by reviewing a range of further issues for future work.