Inproceedings
Book title :
11th International Conference on Ambient Systems, Networks and Technologies (ANT'2020)
Series :
Procedia Computer Science
Address :
Warsaw, Poland
Publisher :
Information
Period : April 2020
Volume : 170
Pages : 522-529
Details
An Efficient Learning Assistant for a Contextual Road Navigation
Jean-Michel Ilié Karim Lahiani Ahmed-Chawki Chaouche François Pêcheux
Due to traffic conditions that are very context dependent, the computation of optimized or shortest paths is a very complex problem for both drivers and autonomous vehicles. In this paper, we introduce a learning mechanism that is able to efficiently evaluate path durations based on an abstraction of the available traffic information. We demonstrate that a cache data structure allows a permanent access to the results whereas a lazy politics taking new data into account is used to increase the viability of those results. Our measures highlight the performance of each mechanism, according to different learning strategies.
Key words :
Context awareness Intelligent transportation systems Learning systems Cache memory Path planning Clustering
Ref. laboratory citation :
misc-lab-259
DOI :
10.1016/j.procs.2020.03.119
Link :
Texte intégral
ACM :
J.-M. Ilié, K. Lahiani, A.-C. Chaouche and F. Pêcheux. 2020. An Efficient Learning Assistant for a Contextual Road Navigation. In Proceedings of the 11th International Conference on Ambient Systems, Networks and Technologies (ANT'2020), Warsaw, Poland. Procedia Computer Science, 170 (April 2020), Elsevier, 522-529. DOI: https://doi.org/10.1016/j.procs.2020.03.119.
APA :
Ilié, J.-M., Lahiani, K., Chaouche, A.-C. & Pêcheux, F. (2020, April). An Efficient Learning Assistant for a Contextual Road Navigation. In Proceedings of the 11th International Conference on Ambient Systems, Networks and Technologies (ANT'2020), Warsaw, Poland. Procedia Computer Science, 170, Elsevier, 522-529. DOI: https://doi.org/10.1016/j.procs.2020.03.119
IEEE :
J.-M. Ilié, K. Lahiani, A.-C. Chaouche and F. Pêcheux, "An Efficient Learning Assistant for a Contextual Road Navigation". In Proceedings of the 11th International Conference on Ambient Systems, Networks and Technologies (ANT'2020), Warsaw, Poland. Procedia Computer Science, vol. 170, Elsevier, pp. 522-529, April, 2020. DOI: https://doi.org/10.1016/j.procs.2020.03.119.
BibTeX :
@inproceedings{misc-lab-259,
author = {Ili\'{e}, Jean-Michel and Lahiani, Karim and Chaouche, Ahmed-Chawki and P\^{e}cheux, François},
title = {An Efficient Learning Assistant for a Contextual Road Navigation},
volume = {170},
booktitle = {11th International Conference on Ambient Systems, Networks and Technologies (ANT'2020)},
series = {Procedia Computer Science},
location = {Warsaw, Poland},
pages = {522--529},
publisher = {Elsevier},
year = {2020},
month = {April},
doi = {10.1016/j.procs.2020.03.119},
url = {http://www.sciencedirect.com/science/article/pii/S1877050920305573},
keywords = {Context awareness, Intelligent transportation systems, Learning systems, Cache memory, Path planning, Clustering}
}
RIS :
TY  - CONF
TI - An Efficient Learning Assistant for a Contextual Road Navigation
AU - J.-M. Ilié
AU - K. Lahiani
AU - A.-C. Chaouche
AU - F. Pêcheux
PY - 2020
VL - 170
BT - 11th International Conference on Ambient Systems, Networks and Technologies (ANT'2020), Warsaw, Poland
SP - 522
EP - 529
PB - Elsevier
AB - Due to traffic conditions that are very context dependent, the computation of optimized or shortest paths is a very complex problem for both drivers and autonomous vehicles. In this paper, we introduce a learning mechanism that is able to efficiently evaluate path durations based on an abstraction of the available traffic information. We demonstrate that a cache data structure allows a permanent access to the results whereas a lazy politics taking new data into account is used to increase the viability of those results. Our measures highlight the performance of each mechanism, according to different learning strategies.
KW - Context awareness
KW - Intelligent transportation systems
KW - Learning systems
KW - Cache memory
KW - Path planning
KW - Clustering
DO - 10.1016/j.procs.2020.03.119
UR - http://www.sciencedirect.com/science/article/pii/S1877050920305573
ID - misc-lab-259
ER -