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Traffic demand estimation using path information from Bluetooth data
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AI
DOI：10.1016/j.trc.2021.103443.png)
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Recent advances in technology have made available numerous new monitoring systems that collect updated traffic measurements both in fixed locations and over specific corridors or paths. Such recent technological developments point to challenging and promising opportunities for Origin-Destination (OD) traffic demand estimation and forecast. Therefore, the aim of this paper is to study how to exploit available information detected by new monitoring devices in the estimation of traffic demand. Starting from the formulation proposed by Spiess (1987, 1990), in this paper a new method to estimate the traffic demand by means of Bluetooth data is proposed. It explores inherent properties of this information in an off-line (and static) context, where mathematical formulation of the estimation problem can be derived. The effectiveness of the proposed method has been investigated in an extensive plan of experiments carried out both on test networks and on a study network consisting in a part of the city of Rome, Italy, obtaining promising results in both applications.
Keyword:
Analytical models
Bluetooth Data
Demand Estimation
Path Information
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4.9K
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