City-Scale Holographic Traffic Flow Data based on Vehicular Trajectory Resampling

• URL: http://arxiv.org/abs/2108.13376v2
• Date: Sat, 29 Jan 2022 09:35:23 GMT
• Title: City-Scale Holographic Traffic Flow Data based on Vehicular Trajectory Resampling
• Authors: Yimin Wang, Yixian Chen, Guilong Li, Yuhuan Lu, Zhi Yu, and Zhaocheng He
• Abstract summary: We constructed one-month continuous trajectories of daily 80,000 vehicles in Xuancheng city with accurate intersection passing time. With such holographic traffic data, it is possible to reproduce every detail of the traffic flow evolution. We presented a set of traffic flow data based on the holographic trajectories resampling, covering the whole 482 road segments in the city round the clock.
• Score: 4.899517472913586
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Despite abundant accessible traffic data, researches on traffic flow estimation and optimization still face the dilemma of detailedness and integrity in the measurement. A dataset of city-scale vehicular continuous trajectories featuring the finest resolution and integrity, as known as the holographic traffic data, would be a breakthrough, for it could reproduce every detail of the traffic flow evolution and reveal the personal mobility pattern within the city. Due to the high coverage of Automatic Vehicle Identification (AVI) devices in Xuancheng city, we constructed one-month continuous trajectories of daily 80,000 vehicles in the city with accurate intersection passing time and no travel path estimation bias. With such holographic traffic data, it is possible to reproduce every detail of the traffic flow evolution. We presented a set of traffic flow data based on the holographic trajectories resampling, covering the whole 482 road segments in the city round the clock, including stationary average speed and flow data of 5-minute intervals and dynamic floating car data.

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