Working　from　home　becomes　the　norm;　this　trend　has　put　added　pressure　on　urban　logistics,　as　large　volumes　of　goods　and　services　are　required　for　domestic　use.　Meanwhile,　public　transport　operators　face　a　big　challenge　and　trade-off　due　to　higher　labour　and　frequent　cleaning　costs,　with　lower　passenger　revenue　over　a　longer　period.　Considering　the　collaborative　urban　public　transport　services　achieve　a　seamless　movement　for　both　passengers　and　goods,　and　could　reduce　the　adverse　effects　of　the　existing　urban　public　transport　systems.　Therefore,　a　mixed-integer　linear　programming　model　introducing　the　concept　of　capacity　matching　is　proposed　to　assist　this　collaborative　urban　freight　service　network　in　minimising　total　freight　transport　time　at　station　hubs　and　not　affecting　passenger　transportation　in　this　paper.　Moreover,　an　efficient　improved　optimisation　algorithm　based　on　the　Artificial　Bee　Colony　Algorithm　(ABC)　is　designed,　and　the　numerical　examples　and　real　cases　are　illustrated　to　demonstrate　the　feasibility　and　effectiveness　of　the　proposed　model　and　algorithm.　The　performance　evaluations　suggest　that　the　coordinated　operating　strategy　of　the　collaborative　freight　transportation　system　supports　increasing　mobility　demands　for　freight,　resulting　in　declining　congestion　levels　and　reducing　transport　emissions,　while　no　influence　in　passenger　transport,　notably　in　urban　areas.