Abstract
In the last decade, mobility prediction has played a crucial role in urban planning, traffic forecasting, advertising, and service recommendation. This paper addresses the prediction of mobility and emphasizes an essential step that is trajectory modeling (better the modelling is, better is the prediction). First, we propose a context-based and prediction-oriented trajectory model. Our model is based on a grid-oriented trajectory description technique that allows overcoming low precision and ambiguity issues. Second, our model is compared to some related trajectory models. Third, an application of the model in intelligent transportation domain is illustrated. Finally, to evaluate our model, we experiment it on a data mining-based prediction algorithm and show the results in terms of prediction accuracy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Boc, M., Amorim, D.M.D., Fladenmuller, A.: Near-zero triangular location through time-slotted mobility prediction. Wireless Netw. 17(2), 465–478 (2011)
Samaan, N., Karmouch, A.: A mobility prediction architecture based on contextual knowledge and spatial conceptual maps. IEEE Trans. Mob. Comput. 4(6), 537–551 (2005)
Chardonnel, S., Du Mouza, C., Fauvet, M.C., Josselin, D., Rigaux, P.: Patrons de mobilité : proposition de définition, de méthode de représentation et d’interrogation. In : Colloque Cassini’04–7ème conférence du GDR Sigma” Géomatique et Analyse Spatiale, pp. 19–23 (2004)
Buard, E., Devogele, T., Ducruet, C.: Trajectoires d’objets mobiles dans un espace support fixe. Revue Internationale de géomatique 25(3), 331–354 (2015)
Bogorny, V., Heuser, C.A., Alvares, L.O.: A conceptual data model for trajectory data mining. In: Fabrikant, S.I., Reichenbacher, T., van Kreveld, M., Schlieder, C. (eds.) Geographic information science, pp. 1–15. Springer Berlin Heidelberg, Berlin, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15300-6_1
Bogorny, V., Renso, C., de Lucca Siqueira, F., Alvares, L.O.: Constant–a conceptual data model for semantic trajectories of moving objects. Trans. GIS 18(1), 66–88 (2014)
Brakatsoulas, S., Pfoser, D., Tryfona, N.: Modeling, storing and mining moving object databases, In Proceedings. International Database Engineering and Applications Symposium, IDEAS'04, pp. 68–77. IEEE (2004)
Kontarinis, A., Zeitouni, K., Marinica, C., Vodislav, D., Kotzinos, D.: Towards a semantic indoor trajectory model: application to museum visits. GeoInformatica 25(2), 311–352 (2021)
Cayèré, C., Sallaberry, C., Faucher, C., Bessagnet, M.N., Roose, P.: Proposition d'un modèle de trajectoires multi-aspects et multi-niveaux appliqué au tourisme. In: IC, pp. 56–64 (2021)
Spaccapietra, S., Parent, C., Damiani, M.L., et al.: A conceptual view on trajectories. Data Knowl. Eng. 65(1), 126–146 (2008)
Raimond, A.M.O., Ouronné, T., Fen-Chong, J., Smoreda, Z.: Le Paris des visiteurs étrangers, qu’en disent les téléphones mobiles-Inférence des pratiques spatiales et fréquentations des sites touristiques en Île-de-France. Revue internationale de géomatique 22(3), 413–437 (2012)
Wang, J., Kong, X., Xia, F., Sun, L.: Urban human mobility: data-driven modeling and prediction. ACM SIGKDD Explor. Newsl. 21(1), 1–19 (2019)
Yan, X.Y., Wang, W.X., Gao, Z.Y., Lai, Y.C.: Universal model of individual and population mobility on diverse spatial scales. Nat. Commun. 8(1), 1–9 (2017)
Wang, Y., Li, G., Li, K., Yuan, H.: A deep generative model for trajectory modeling and utilization. Proc. VLDB Endowment 16(4), 973–985 (2022)
Göndör, S., Uzun, A., Rohrmann, T., Tan, J., Henniges, R.: Predicting user mobility in mobile radio networks to proactively anticipate traffic hotspots. In: 2013 international conference on MOBILe wireless MiddleWARE, operating systems, and applications, pp. 29–38, IEEE (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Boukhedouma, H., Meziane, A., Hammoudi, S., Benna, A. (2024). A Grid-Based and a Context-Oriented Trajectory Modeling for Mobility Prediction in Smart Cities. In: Ben Ahmed, M., Boudhir, A.A., El Meouche, R., Karaș, İ.R. (eds) Innovations in Smart Cities Applications Volume 7. SCA 2023. Lecture Notes in Networks and Systems, vol 906. Springer, Cham. https://doi.org/10.1007/978-3-031-53824-7_14
Download citation
DOI: https://doi.org/10.1007/978-3-031-53824-7_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-53823-0
Online ISBN: 978-3-031-53824-7
eBook Packages: EngineeringEngineering (R0)