A Dynamic Bayesian Network-Based Real-Time Crash Prediction Model for Urban Elevated Expressway

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Variable</td><td class="align_center">Description</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">TPI</td><td class="align_center">The average TPI of the whole expressway within 5 min interval</td></tr><tr><td class="align_left">V</td><td class="align_center">The average speed of current segment within 5 min interval (km/h)</td></tr><tr><td class="align_left">U_V</td><td class="align_center">The average speed of upstream segment within 5 min interval (km/h)</td></tr><tr><td class="align_left">D_V</td><td class="align_center">The average speed of downstream segment within 5 min interval (km/h)</td></tr><tr><td class="align_left">Q</td><td class="align_center">The volume of current segment within 5 min interval (pcu/h)</td></tr><tr><td class="align_left">U_Q</td><td class="align_center">The volume of upstream segment within 5 min interval (pcu/h)</td></tr><tr><td class="align_left">D_Q</td><td class="align_center">The volume of downstream segment within 5 min interval (pcu/h)</td></tr><tr><td class="align_left">Visibility</td><td class="align_center">The horizontal visibility within one hour (km)</td></tr><tr><td class="align_left">Weather</td><td class="align_center">The weather type in one hour, rainy or sunny</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Information of the nine alternative variables.</div>

Journal of Advanced Transportation

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Table 1

Table 1: A Dynamic Bayesian Network-Based Real-Time Crash Prediction Model for Urban Elevated Expressway 