This　study　addresses　a　new　lane　reservation　problem　in　a　transportation　network　with　task　merging　and　residual　capacity　constraints　called　the　CLRP-TM.　It　aims　to　optimally　convert　some　general-purpose　lanes　in　the　transportation　network　to　be　reserved　and　design　reserved　lane-based　routes　for　some　time-efficient　transportation　tasks　emerging　in　large-scale　special　events.　Once　reserved,　the　lanes　can　only　be　used　by　the　special　tasks　and　their　travel　times　can　be　reduced.　However,　the　general-purpose　vehicles　on　adjacent　non-reserved　lanes　will　burden　travel　delay　due　to　the　reduction　of　available　lanes.　To　pre-merging　some　tasks　that　are　geographically　close　can　greatly　reduce　such　negative　impact　because　the　required　number　of　time-efficient　transport　routes　is　reduced.　Besides,　each　road　segment　has　a　limited　residual　capacity　for　task　vehicles　if　no　lanes　are　reserved　on　it.　The　objective　of　the　CLRP-TM　is　to　minimize　the　total　negative　impact　caused　by　all　reserved　lanes.　For　this　problem,　an　integer　linear　programming　model　is　developed　and　solved　using　existing　commercial　solver　CPLEX.　Computational　results　for　a　real-life　example　from　the　Guangzhou　Asian　Games　in　2009　confirm　the　effectiveness　and　efficiency　of　the　proposed　approach.