To　improve　the　tracking　efficiency　of　the　platoon　during　driving　and　ensure　the　spacing　safety　between　vehicles,　a　platoon　tracking　control　strategy　based　on　the　adaptive　neural　network　algorithm　is　developed.　In　this　method,　the　nonlinear　term　in　the　vehicle　model　is　estimated　by　the　adaptive　neural　network,　and　the　estimated　value　is　used　to　compensate　for　the　control　input　and　enhance　the　tracking　performance　of　the　vehicle　platoon.　In　addition,　the　estimation　update　law　of　target　trajectory　and　adjacent　vehicle　acceleration　is　designed　through　the　adaptive　method,　which　relaxes　the　trajectory　generation　requirements　of　virtual　vehicles,　improves　the　tracking　performance　of　vehicle　platoon,　reduces　the　measurement　and　communication　burden　in　the　platoon,　and　ensures　the　security　and　stability　of　vehicle　platoon　system.　After　constructing　the　vehicle　and　desired　path　model,　the　control　objective　is　formulated,　and　the　adaptive　neural　network　algorithm　controller　is　designed.　Meanwhile,　the　stability　of　the　controller　is　verified　by　the　Lyapunov　method.　The　feasibility　of　the　proposed　method　is　proved　by　simulation　and　experiment.　Rigorous　theoretical　derivation　and　experiments　confirm　that　the　proposed　strategy　has　obvious　advantages　over　other　existing　strategies.