The　ongoing　growth　of　green　vehicles　had　led　to　an　increase　in　demand　of　cost-effective　and　driver-satisfactory　hydrogen/electric　vehicle　aggregators　(HEVAs).　However,　existing　approaches　for　cost　minimization　of　HEVA　can　lead　to　poor　performance　due　to　the　inaccurate　modelling　of　power-gas　exchange　system　and　neglection　of　schedulable　characteristics　of　loads.　Furthermore,　the　behaviour　of　drivers　was　rarely　considered　from　a　psychological　perspective.　To　resolve　these　limitations,　the　optimal　dispatch　scheme　of　HEVA,　equipped　with　reversible　solid　oxide　cell　(rSOC),　is　investigated　by　quantifying　drivers＇　charging　decision　response　toward　pricing　stimuli.　As　the　core　of　the　bi-directional　energy　conversion,　rSOC　is　modelled　by　considering　the　climbing　power　constraints　and　time-dependent　restartup　cost.　At　the　driver　side,　EVs　are　aggregated　as　clusters　for　efficient　computation.　Two　charging　modes　are　designed　for　drivers　with　incentive　discounts.　To　measure　the　relationship　between　external　factors　and　charging　decision　response,　the　stimuli-responsive　charging　decision　estimation　is　proposed　by　introducing　Weber-Fechner　law　(W-F　Law).　To　minimum　operation　cost,　a　mixed　integer　nonlinear　programming　(MINP)　method　is　presented.　The　results　validate　that　the　operation　cost　of　HEVA　can　be　decreased　by　19.37%,　and　the　maximum　utilization　of　energy　is　realised　in　the　proposed　scheme.　Additionally,　the　impacts　of　sizes　of　power-gas　exchange　devices　are　investigated　for　practical　reference.　Under　a　given　charging　demand,　the　proposed　dispatch　scheme　can　realise　installation　of　smaller　devices,　and　thereby,　resulting　in　lower　construction　cost.　(c)　2021　Hydrogen　Energy　Publications　LLC.　Published　by　Elsevier　Ltd.　All　rights　reserved.