Control Strategy of Frequent Overflow at Intersection Based on Remote Sensing of Unmanned Aerial Vehicle and Vehicle Trajectory Data

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static-preview.hindawi.com/articles/js/volume-2022/5214240/figures/5214240.fig.009a.svgz" name="5214240.fig.009a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Road network</td></tr><tr class="fig-image" id="b"><td><object data="https://static-preview.hindawi.com/articles/js/volume-2022/5214240/figures/5214240.fig.009b.svgz" name="5214240.fig.009b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Road network topology</td></tr><tr class="fig-image" id="c"><td><object data="https://static-preview.hindawi.com/articles/js/volume-2022/5214240/figures/5214240.fig.009c.svgz" name="5214240.fig.009c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Moving trajectory data</td></tr></table>

<div>Simulation Model of Changping District in Beijing (Road network comes from Baidu’s open source map. 9(a)).</div>

Journal of Sensors

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Figure 9

Figure 9: Control Strategy of Frequent Overflow at Intersection Based on Remote Sensing of Unmanned Aerial Vehicle and Vehicle Trajectory Data 