An Incentive Based Road Traffic Control Mechanism for Covid-19 Pandemic Alike Emergency Preparedness and Response

The Covid-19 pandemic has hit hard on the highly-organised yet risk-vulnerable modern societies, and has introduced new characteristics to large-scale emergencies, which feature long persistence in duration, high frequency in occurrence, large sensitivity to individual behaviours, and extreme high hazard propagation rate owing to the highly-efficient transport networks. This has raised new challenges on long-term emergency preparedness of urban transportation systems in terms of safety, efficiency, robustness and sustainability. Non-cooperative behaviours of transport participants could result in severe performance degradation in emergency preparedness, and mandatory restrictions in human activities can be economical costly and difficult in operation. In addition, current arrangement models for the disaster financial assistance have not been elaborately designed for civilian behaviour optimisation although with great potential as an economical instrument. Hence, in this paper, we propose a reward based traffic control mechanism to generate cooperative behaviours and optimise resource allocation in an urban transportation system for emergency preparedness via distributing credit coins, which can also be treated as a financial assistance approach during long-term disasters. A queueing theory based analytic model is employed to mimic the behaviours of civilians in the transportation system under the emergency preparedness state and a probability choice model is utilised to optimise the emergency preparedness strategies of the system. The experimental results show that the introduction of the incentive based traffic control mechanism can significantly reduce hazard response time, travel delay as well as the energy usage of the urban transportation system at the expense of monetary rewards.