Vehicle Driving Risk Prediction Based on Markov Chain Model

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/ddns/volume-2018/4954621/figures/4954621.fig.0011a.svgz" name="4954621.fig.0011a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Cluster 1</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/ddns/volume-2018/4954621/figures/4954621.fig.0011b.svgz" name="4954621.fig.0011b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Cluster 2</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/ddns/volume-2018/4954621/figures/4954621.fig.0011c.svgz" name="4954621.fig.0011c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Cluster 3</td></tr></table>

<div>Driving risk level time window clustering results.<i> Note</i>. The random observed time window samples were sorted according to the average value of iTTC within the time window for easier understanding.</div>

Discrete Dynamics in Nature and Society

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Figure 11

Figure 11: Vehicle Driving Risk Prediction Based on Markov Chain Model 