Pan, Zheng, Yan, Lei, Winstanley, Adam C., Fotheringham, Stewart and Zheng, Jianghua (2009) A 2-D ESPO Algorithm and Its Application in Pedestrian Path Planning Considering Human Behavior. In: Third International Conference on Multimedia and Ubiquitous Engineering, 2009. MUE '09. IEEE, pp. 485-491. ISBN 9780769536583
Preview
AW-2-D-ESPO-2009.pdf
Download (1MB) | Preview
Abstract
A 2-D Euclidean shortest path with obstacles (ESPO) algorithm for pedestrian navigation is developed. ESPO is a classical algorithm in the field of computational geometry. We describe some common ESPO algorithms and discuss their application in pedestrian shortest path determination based on the generation of a network of paths within a polygon with interior obstacles. This algorithm can be applied to pedestrian navigation in open spaces, such as squares, parks and big halls. Path generation is based on the Dijkstra algorithm, which is extended to solve the path planning problem not only for path and road networks but also for open spaces. The algorithm takes human preferences based on walking conditions into account and can find different paths with minimum cost for different conditions. The results of this approach are illustrated through an experimental system. Further work to integrate the algorithm into a practical pedestrian navigation system is proposed.
Item Type: | Book Section |
---|---|
Keywords: | Pedestrian behavior; ESPO Algorithm; pedestrian path planning; |
Academic Unit: | Faculty of Science and Engineering > Computer Science |
Item ID: | 8096 |
Identification Number: | 10.1109/MUE.2009.86 |
Depositing User: | Dr. Adam Winstanley |
Date Deposited: | 30 Mar 2017 14:35 |
Publisher: | IEEE |
Refereed: | Yes |
Funders: | Science Foundation Ireland (SFI) |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/8096 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
Downloads
Downloads per month over past year