The Optimal Sampling Period of a Fingerprint Positioning Algorithm for Vehicle Speed Estimation

Ding Yuan Cheng*, Chi-Hua Chen, Chia-Hung Hsiang, Chi-Chun Lo, Hui-Fei Lin, Bon-Yeh Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Using cellular floating vehicle data is a crucial technique for measuring and forecasting real-time traffic information based on anonymously sampling mobile phone positions for intelligent transportation systems (ITSs). However, a high sampling frequency generates a substantial load for ITS servers, and traffic information cannot be provided instantly when the sampling period is long. In this paper, two analytical models are proposed to analyze the optimal sampling period based on communication behaviors, traffic conditions, and two consecutive fingerprint positioning locations from the same call and estimate vehicle speed. The experimental results show that the optimal sampling period is 41.589 seconds when the average call holding time was 60 s, and the average speed error rate was only 2.87%. ITSs can provide accurate and real-time speed information under lighter loads and within the optimal sampling period. Therefore, the optimal sampling period of a fingerprint positioning algorithm is suitable for estimating speed information immediately for ITSs.
Original languageEnglish
Article number306783
JournalMathematical Problems in Engineering
StatePublished - 2013

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