A web-based visual analytics system for traffic intersection datasets Online publication date: Thu, 04-Nov-2021
by Ke Chen; Tania Banerjee; Xiaohui Huang; Zhaowen Ding; Venkata Sai Varanasi; Anand Rangarajan; Sanjay Ranka
International Journal of Big Data Intelligence (IJBDI), Vol. 8, No. 1, 2021
Abstract: The efficiency of a road network may be improved by making the traffic intersections more efficient. A smart traffic intersection is equipped with different sensors from which it is possible today to collect streaming data feed and run data analysis algorithms to identify potential inefficiencies, near-miss incidents, and anomalous traffic behaviour. In this paper, we present a visual analytics framework which may be used by traffic engineers to analyse the events and performance at an intersection. The tool ingests streaming videos collected from a fisheye camera, cleans the data, and runs analytics on it. The tool presented here has two modes: a streaming mode and a historical mode. The streaming mode may be used to analyse data close to real-time with a latency set by the user. In the historical mode, the user can run a variety of trend analysis on historical data.
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