As　one　of　the　primary　sources　of　carbon　emissions,　transportation　sector　has　proposed　various　measures　to　reduce　its　carbon　emissions.　Introducing　energy-efficient　and　low-carbon　autonomous　trucks　into　freight　transportation　is　highly　promising,　but　faces　various　challenges,　especially　safety　issues.　This　study　addresses　eco-friendly　lane　reservation-based　autonomous　truck　transportation　network　design　for　transportation　safety　and　low　carbon　emissions.　It　aims　to　optimally　implement　dedicated　truck　lanes　in　an　existing　network　and　design　dedicated　routes　for　autonomous　truck　transportation　to　simultaneously　minimise　the　negative　impact　caused　by　dedicated　truck　lanes　and　carbon　emissions　of　the　entire　transportation　system.　We　first　formulate　this　problem　into　a　bi-objective　integer　linear　program.　Then,　an　epsilon-constraint-based　two-stage　algorithm　(ETSA)　is　proposed　to　solve　it　based　on　explored　problem　properties.　A　case　study　based　on　the　well-known　Sioux　Falls　network　is　conducted　to　demonstrate　the　applicability　of　the　proposed　model　and　algorithm.　Computational　results　for　310　instances　from　the　literature　demonstrate　that　the　proposed　algorithm　significantly　outperforms　the　epsilon-constraint　combined　with　the　proposed　ILP　in　obtaining　the　Pareto　front.　Moreover,　helpful　managerial　insights　are　derived　based　on　sensitivity　analysis.