Edge　computing　technology　emerges　as　a　novel　computing　paradigm　that　makes　use　of　resources　closed　to　the　devices　of　smart　rail　system.　However,　it　is　difficult　to　support　data　offloading　to　the　stations　directly　from　different　trains,　due　to　the　limited　coverage　of　the　stations　equipped　with　MEC　servers.　Therefore,　multi-hop　ad　hoc　network　is　considered　and　introduced　in　this　case.　In　this　article,　we　propose　an　improved　optimization　framework　for　MEC-enabled　smart　rail　system　by　multi　hop　data　communication　and　blockchain　technology.　The　tasks　can　be　offloaded　to　the　MEC　servers　through　multi-hop　transmission　between　trains,　even　requesting　trains　are　not　covered　by　servers.　Moreover,　blockchain　technology　is　utilized　to　ensure　the　security　and　reliability　of　the　data　during　multi-hop　transmission.　Then　the　offloading　routing　path　and　offloading　strategy　are　co-optimized　to　minimize　both　delay　and　cost　of　the　system.　We　formulate　the　proposed　optimization　problem　as　a　Markov　decision　process　(MDP),　and　adopt　deep　reinforcement　learning　(DRL)　to　solve　it.　Simulation　results　show　that　the　proposed　scheme　can　improve　system　performance　significantly　compared　with　other　existing　schemes.　©　2022　IEEE.