Trajectory Estimation From Sparse Cellular Network Data Based on the Historical Vehicular Data (CROSBI ID 726282)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Mardešić, Nikola ; Erdelić, Tomislav ; Tišljarić, Leo ; Carić, Tonči
engleski
Trajectory Estimation From Sparse Cellular Network Data Based on the Historical Vehicular Data
By coupling data-mining techniques with historical cellular and vehicular data, it is possible to find a certain spatiotemporal logic in the observed data. The primary motivation for combining multiple data sources derives from the fact that origin-destination matrices, extracted from cellular data sets, represent only the route's start and end-point without the information about the complete trajectory. This paper proposes a method to estimate sparse cellular data trajectories by reconstructing possible paths from the historical vehicular data. The possible routes are generated by solving the shortest-path problems for given origin- destination pair. A spatiotemporal similarity value is computed to evaluate the paths relative to the ground-truth origin-destination pair. In the end, the path with the highest similarity value is selected. Three criteria for the computation of the spatiotemporal similarity are used: length-based, modified length-based and time-based. The results show the application of proposed methods on the collected historical data, with average percentage similarity ranging from 39.85% to 56.11% (depending on the transport mode and criteria used) with modified-length criteria producing the best results - in some cases producing a trajectory with 98% similarity to the actual cellular trajectory.
FCD ; big data ; traffic data analysis ; trajectory estimation
Transportation Research Procedia Volume 64, Issue C
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Podaci o prilogu
166-173.
2022.
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objavljeno
10.1016/j.trpro.2022.09.020
Podaci o matičnoj publikaciji
Transportation research procedia
Petrović, Marjana ; Dovbischuk, Irina ; Cunha, André Luiz
Elsevier
2352-1457
2352-1465
Podaci o skupu
International Scientific Conference “The Science and Development of Transport - Znanost i razvitak prometa” (ZIRP 2022)
predavanje
28.09.2022-30.09.2022
Šibenik, Hrvatska
Povezanost rada
Tehnologija prometa i transport