Work

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

Year: 2013

Type: article

Abstract: 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.

Source: Mathematical Problems in Engineering

DOI: 10.1155/2013/306783

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

Institutions: Hwa Hsia University of Technology, National Yang Ming Chiao Tung University, Chunghwa Telecom (Taiwan)

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,550