Examining the possibility of short-term prediction of traffic volume in smart city control systems with the use of regression models
Abstract
This article deals with issues related to the optimization of traffic management in modern cities, the so-called Smart City. In particular, the article presents the process of evolution of the traffic flow prediction model at a selected crossroads in a selected city in Poland - the city of Rzeszów. Rzeszow is an example of a smart city equipped with an extensive system of real-time data collection and processing from multiple road points in the city. The research was aimed at a detailed analysis of the feasibility and degree of fit of different variants of the regression model: linear, polynomial, trigonometric, polynomial-trigonometric, and regression-based Random Forest algorithm. Several studies were carried out evaluating different generations of models, in particular, an analysis was carried out based on which the superiority of the trigonometric model was demonstrated. This model had the best fit and the lowest error rate, which could be a good conclusion for widespread use and implementation in Smart City supervisory systems.
References
J.A. Bondy, U.S.R. Murty. Graduate Texts in Mathematics 244: Graph Theory. Springer, 2008.
Dymora, P., Mazurek, M., Jucha, M. (2023). Regression Models Evaluation of Short-Term Traffic Flow Prediction. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Dependable Computer Systems and Networks. DepCoS-RELCOMEX 2023. Lecture Notes in Networks and Systems, vol 737. Springer, Cham. https://doi.org/10.1007/978-3-031-37720-4_5
Dieter Jungnickel. Algorithms and Computation in Mathematics, vol. 5: Graphs, Networks and Algorithms. Springer, 2005.
Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining. Introduction to Linear Regression Analysis, 5th edition. John Wiley & Sons, Inc., 2012.
Frank E. Harrell, Jr. Regression Modeling Strategies with Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis, 2nd edition. Springer, 2015.
Polynomial Regression, https://online.stat.psu.edu/stat462/node/158/ (access: 20.12.2022).
Fourier Series and Integrals, https://math.mit.edu/~gs/cse/websections/ cse41.pdf (access: 22.12.2022).
Robin Genuer, Jean-Michel Poggi. Random Forests with R. Springer, 2020.
Linear regression analysis in Excel, https://www.ablebits.com/office-addins-blog/linear-regression-analysis-excel/ (access:15.10.2022).
Conrad Carlberg. Regression Analysis Microsoft Excel. Pearson Education, Inc., 2016.
Pearson Correlation Coefficient, https://online.stat.psu.edu/stat501/ lesson/1/1.6 (access: 7.12.2022).
Adjusted R Squared Formula, https://www.educba.com/adjusted-r-squared-formula/ (access: 8.01.2023).
P. Dymora, M. Mazurek, Influence of Model and Traffic Pattern on Determining the Self-Similarity in IP Networks. Appl. Sci. 2021, 11, 190. https://doi.org/10.3390/app11010190.
M. F. Huber, “Chebyshev polynomial kalman filter,” Digital Signal Processing, vol. 23, no. 5, pp. 1620–1629, 2013.
P. Wachel and P. Śliwiński, "Aggregative Modeling of Nonlinear Systems," IEEE Signal Processing Letters, vol. 22, no. 9, pp. 1482-1486, Sept. 2015, doi: 10.1109/LSP.2015.2405613.
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