Abstract
The origin-destination (OD) demand is a critical information source used in the traffic strategic planning and management. The Radio Frequency Identification (RFID) is an advanced technique to collect traffic data. In this paper, daily origin-destination trips were inferred from the RFID data. Locations of RFID readers are considered as the origins and destinations. However, the sparseness of RFID data leads uncertainty to the destination of trip. To handle this problem, an approach was proposed to estimate the OD matrix. At first, the driving time of trip-legs in all trajectories are calculated by the driving time of taxis, which can be distinguished from the RFID data. And then, the stay, the last pass-by RFID reader of a trip, is inferred based on the calculated driving time. Finally, we extracted daily origin-destination trips for all vehicles. Using the proposed method, a case study was developed employing the real-world data collected in Chongqing, China, which demonstrated the effectiveness of our proposed approach.
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Chen, C., Zheng, L., Cui, C., Liu, W. (2019). Estimating Origin-Destination Flows Using Radio Frequency Identification Data. In: Li, S. (eds) Green, Pervasive, and Cloud Computing. GPC 2018. Lecture Notes in Computer Science(), vol 11204. Springer, Cham. https://doi.org/10.1007/978-3-030-15093-8_15
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