This study aims to evaluate the performance of an extended floating car data (xFCD)-based traffic state estimation method proposed by Seo et al. (2015), which does not rely on any strong assumptions such as Fundamental Diagram, using high-resolution complete trajectory data, viz. Zen Traffic Data (ZTD). Traffic state estimated by this method, considering randomly sampled trajectories of ZTD as those of probe vehicles with known penetration rates, are compared with ones obtained by complete ZTD by applying Edie’s generalized definitions. The variation in estimation errors and covering percentages are analyzed for varying settings: spatiotemporal resolution and probe penetration rates.
Exploring the Performance of Streaming-Data-Driven Traffic State Estimation Method Using Complete Trajectory Data
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 19 , 3 ; 572-586
2021-09-01
15 pages
Article (Journal)
Electronic Resource
English
Traffic states estimation , Vehicle trajectory data , Big data and naturalistic datasets , Probe penetration rate , Statistical and theoretical analysis , Spatiotemporal resolution Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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