Transportation Analytics in the Era of Big Data by Satish V. Ukkusuri & Chao Yang
Author:Satish V. Ukkusuri & Chao Yang
Language: eng
Format: epub
ISBN: 9783319758626
Publisher: Springer International Publishing
5.2.2 Radio-Frequency Identification Data
Travel information extracted by mobile phone data is greatly improved in terms of timeliness and practicability but has shortcomings in terms of accuracy and real-time performance. RFID data, which records vehicular locations through RFID equipment, could better overcome these deficiencies and serve as a kind of high-resolution data. RFID sensing equipment can accurately record the exact time and location when an RFID-equipped vehicle passes [11]. Densely distributed RFID sensing equipment can record information at a high frequency. Usually, the vehicle’s ID, the ID of the RFID station the vehicle passes, and the exact time the vehicle passed the station are recorded, so the RFID-equipped vehicles can be traced and the required traffic information collected.
With the advantage of high resolution, the recording of vehicles’ spatiotemporal information is more accurate and captured with relatively high frequencies, and the RFID data are more useful for generating dynamic travel demands and developing real-time traffic management systems. Khateeb et al. [11] proposed dynamic traffic light sequence algorithm using RFID, which could improve the efficiency of traffic management. Yang [12] employed Complex Event Processing technology based on RFID to improve real-time event detection, while Wen et al. [13] presented an intelligent traffic management expert system using RFID technology that provided traffic data collection and control information. However, there is one current limitation of RFID data, namely that RFID devices are not installed in all vehicles, which means that only some of the vehicles passing an RFID sensing station can be detected and recorded. With the installation of RFID devices in more vehicles, traffic demand information could be obtained on a larger scale.
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