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.