Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic

摘要: The COVID-19 pandemic has severely affected many aspects of people's daily lives. While countries are in a re-opening stage, some effects the on behaviors expected to last much longer, including how they choose between different transport options. Experts predict considerably delayed recovery public options, as people try avoid crowded places. In turn, significant increases traffic congestion expected, since likely prefer using their own vehicles or taxis opposed riskier and more options such railway. this paper, we propose use financial incentives set tradeoff risk infection achieve safe efficient transportation networks. To end, formulate network optimization problem optimize taxi fares. For our framework be useful various cities times day without designer effort, also data-driven approach learn human preferences about which is then used fare optimization. Our user studies simulation experiments show able minimize infection.