This　paper　focuses　on　the　path　following　control　problems　for　autonomous　driving　vehicles.　Aiming　at　enhancing　the　robustness　and　attenuating　the　chattering　phenomenon,　a　super-twisting　sliding　mode　control　algorithm　(STA)　is　developed　based　on　Lyapunov　theory,　where　the　proof　of　the　stability　of　the　control　system　is　presented　by　applying　the　backstepping　technique.　Moreover,　co-simulation　between　Matlab/Simulink　and　Carsim　is　carried　out　to　verify　the　path　following　control　performance.　In　this　research,　Stanley　controller,　conventional　sliding　mode　control　(SMC),　and　model　predictive　control　(MPC)　are　used　as　the　benchmark　controllers　for　evaluating　the　proposed　STA　performance.　Two　driving　scenarios　are　considered　in　the　simulations,　including　normal　driving　and　flerce　driving.　To　comprehensively　assess　the　control　performance　and　control　effort　(i.e.　magnitude　of　steering),　an　integrated　and　weighted　performance　evaluation　index　(IWPEI)　is　novelly　provided.　Simulation　results　show　that　the　IWPEI　of　the　proposed　STA　can　be　reduced　by　40.5%,　25.8%,　10.9%　in　the　normal　driving　scenario;　and　62.5%,　24%,　6.8%　in　the　flerce　driving　scenario　as　compared　with　Stanley　controller,　conventional　SMC,　and　MPC,　respectively.　The　results　also　indicate　that　the　proposed　STA　outperforms　the　conventional　SMC　in　terms　of　the　chattering　attenuation,　resulting　in　a　smoother　front　steering　wheel　angle　input　and　a　smoother　yaw　rate　performance.　As　compared　with　MPC,　the　advantage　of　the　proposed　STAlies　in　its　much　lower　computational　complexity.　Furthermore,　the　robustness　of　the　controllers　is　verified　by　changing　the　vehicle　mass　and　tire　parameters.　The　proposed　STA　can　reduce　the　fluctuation　of　the　IWPEI　by　22.6%,　22.3%,　and　5.9%　compared　with　the　benchmark　approaches.　These　results　imply　that　the　consideration　of　system　perturbations　is　very　critical　in　the　design　of　the　super-twisting　sliding　mode　controller　which　can　improve　the　robustness　of　the　autonomous　vehicle　path　following　system.