Abstract
Vehicle mobility in urban traffic systems is complex, partly because it reflects mobility of a human who drives a vehicle, and partly because it depends on many roles which the vehicle plays. Previous studies on human mobility revealed that it includes Lévy-flights-like motions and memoryless deterministic walks as well as random walks, but the mobility of vehicles may be more biased due to their functions. Focusing our research target on a sightseeing vehicle with sufficiently limited functions, we show a method to measure regularity of visitation patterns, quantified by order(s) of Markov chains in their mobility. Graphs of higher-order Markov chains, which are representatives of mobility in a network style, possess statistical properties; in our observation dataset, they include degree distributions similar to scale-free networks. The detection of mobility in real social experiments, which is also assumed on these graphs, yields the order of Markov chains inside it with its comparison with the results of agent-based simulations. Centrality indices of the mobility networks well coincide with prediction of these analytical and numerical results.
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
References
Tamagawa, D., Taniguchi, E., Yamada, T.: Evaluating city logistics measures using a multi-agent model. Procedia Soc. Behav. Sci. 2, 6001–6012 (2010)
Peng, C., Jin, X., Wong, K.C., Shi, M., Lio, P.: Collective human mobility pattern from taxi trips in urban area. PLoS One 7, e34487-1–e34487-8 (2012)
Sagarra, O., Szell, M., Santi, P., Díaz-Guilera, A., Ratti, C.: Supersampling and network reconstruction of urban mobility. PLos One 10, e0134508-1–e0134508-15 (2012)
Crainic, T.G., Montreuil, B.: Physical internet enabled hyperconnected city logistics. Transp. Res. Procedia 12, 383–398 (2016)
Tachet, R., Sagarra, O., Santi, P., Resta, G., Szell, M., Strogatz, S.H., Ratti, C.: Scaling law of urban ride sharing. Sci. Rep. 7, 42868-1–42868-6 (2017)
Makse, H.A., Havlin, S., Stanley, H.E.: Modelling urban growth patterns. Nature 377, 608–612 (1995)
Caceres, N., Wideberg, J.P., Benitez, F.G.: Review of traffic data estimations extracted from cellular networks. IET Intell. Transp. Syst. 2, 179–192 (2008)
González, M.C., Hidalgo, C.A., Barabási, A.-L.: Understanding individual human mobility patterns. Nature 453, 779–782 (2008)
Brockmann, D., Hufnagel, L., Geisel, T.: The scaling laws of human travel. Nature 439, 462–465 (2006)
Viswanathan, G.M., Afanasyev, V., Buldyrev, S.V., Murphy, E.J., Prince, P.A., Stanley, H.E.: Lévy flight search patterns of wandering albatrosses. Nature 381, 413–415 (1996)
Klafter, J., Shlesinger, M.F., Zumofen, G.: Beyond Brownian motions. Phys. Today 49, 170601-1–170601-4 (1997)
Lima, G.F., Martinez, A.S., Kinouchi, O.: Deterministic walks in random media. Phys. Rev. Lett. 87, 010603-1–010603-4 (2001)
Sasaki, T.: Estimation of person trip patterns through Markov chains. In: Newell, G.F. (ed.) Traffic Flow and Transportation, pp. 119–130. Elsevier, Amsterdam (1972)
Adler, T., Ben-Akiva, M.: A theoretical and empirical model of trip chaining behavior. Transp. Res. B 13B, 243–257 (1979)
Song, C., Koren, T., Wang, P., Barabási, A.-L.: Modelling the scaling properties of human mobility. Nat. Phys. 6, 818–823 (2010)
Yamamoto, K., Yoshida, J., Miyagi, S., Minami, S., Minami, D., Sakai, O.: Mobilities in network topology and simulation reproducibility of sightseeing vehicle detected by low-power wide-area positioning system. Electron. 9, 116-1–116-16 (2020)
Sen, J.: The Sha Fu of Calcutta: the past, the present, and the future of the hand-rickshaw pullers of Calcutta. Is a civilized and progressive transition possible? Bull. Concerned Asian Sch. 30, 37–49 (1998)
Cover, T.M., Thomas, J.A.: Elements of Information Theory, 2nd edn. John Wiley & Sons, Hoboken (2006)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction, 2nd edn. MIT Press, Cambridge (2018)
Liu, F., Janssens, D., Cui, J.X., Wets, G., Cools, M.: Characterizing activity sequences using profile Hidden Markov models. Expert Syst. Appl. 42, 5705–5722 (2015)
Liu, Z., Barahona, M.: Geometric multiscale community detection: Markov stability and vector partitioning. J. Complex Networks 6, 157–172 (2017)
GAT Hikone Association: How about “Jinriki-Sha”, Japanese traditional taxi by a self-running driver? https://www.gat-hikone.net/rikisha/index.php. Accessed 21 Oct 2019
Albert, R., Barabási, A.-L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)
Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Comput. Netw. ISDN Syst. 30, 107–117 (1998)
Mizui, Y., Nobuto, K., Miyagi, S., Sakai, O.: Complex reaction network in Silane plasma chemistry. In: Complex Networks VIII, pp. 135–140. Springer International Publishing, Cham (2017)
Acknowledgements
All the authors thanks the members of the GAT Hikone Association for their useful comments on this study, and also the Hikone-Kirakusha Association for their corporation during the device’s installation on the rickshaws. All the authors also thank K. Enomoto, S. Matsuyama and J. Yoshida at the University of Shiga Prefecture and D. Minami and S. Minami at Eagle Electronics Corporation for their useful comments. This work is partially supported by Regional ICT Research Center of Human, Industry and Future at The University of Shiga Prefecture, and by Cabinet Office, Government of Japan.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Yamamoto, K., Miyagi, S., Sakai, O. (2021). Order Estimation of Markov-Chain Processes in Complex Mobility Network Embedded in Vehicle Traces. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-65351-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-65351-4_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-65350-7
Online ISBN: 978-3-030-65351-4
eBook Packages: EngineeringEngineering (R0)