GPS Data in Urban Online Car-Hailing: Simulation on Optimization and Prediction in Reducing Void Cruising Distance

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left" colspan="4">Statistic</td></tr><tr class="thead"><td class="align_center">Metric</td><td class="align_center">Original dataset (%)</td><td class="align_center">Baseline greedy algorithm (s)</td><td class="align_center">Proposed method with optional constraint (s)</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">AWT</td><td class="align_center"> </td><td class="align_center">447.47</td><td class="align_center">215.41</td></tr><tr><td class="align_left">AVCDP</td><td class="align_center">29.34</td><td class="align_center">11.24</td><td class="align_center">3.73</td></tr><tr><td class="align_left">PCO</td><td class="align_center">0.00</td><td class="align_center">1.64</td><td class="align_center">0.00</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr><tr class="table-fn"><td><div>AWT: average waiting time of passenger; AVCDP: average void cruising distance proportion; PCO: proportion of canceled orders.<br/></div></td></tr></table>

<div>Comparison of the greedy algorithm and proposed method by metric in high travel demand region.</div>

Mathematical Problems in Engineering

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Table 3: GPS Data in Urban Online Car-Hailing: Simulation on Optimization and Prediction in Reducing Void Cruising Distance 