As　an　essential　component　of　China＇s　comprehensive　transportation　network,　freeways　play　an　irreplaceable　role　in　promoting　regional　economic　integration,　improving　logistics　efficiency,　and　serving　public　travel.　However,　the　development　of　freeways　faces　challenges　such　as　the　underutilization　of　road　resources,　significant　financial　pressure　for　construction　and　maintenance,　and　imbalanced　revenue　and　expenditure　leading　to　heavy　debt　burdens,　which　severely　impact　the　sustainable　development　of　freeways.　Optimizing　freeway　toll　rates　is　an　effective　measure　to　alleviate　these　issues,　playing　a　crucial　role　in　enhancing　the　operational　efficiency　of　the　road　network　and　increasing　the　revenue　of　freeway　operating　enterprises.　Existing　studies　have　focused　on　finding　the　optimal　toll　rates　for　freeways　based　on　bi-level　programming　models,　neglecting　the　dynamic　relationships　among　individual　travel　behavior　preferences,　toll　rates,　travel　demand,　and　toll　revenue.　Grounded　in　bounded　rationality　theory,　the　research　employs　microscopic　traffic　simulation　technology　to　analyze　the　dynamic　relationships　among　freeway　toll　rates,　travel　demand,　and　toll　revenue.　The　results　confirm　that　travel　demand　decreases　as　toll　rates　increase,　while　toll　revenue　exhibits　asymmetric　＂synchronization＂　and　＂asynchronization＂　phases,　peaking　at　CYN　58.9　thousand　(USD　8246)　when　the　toll　rate　reaches　CYN　0.45/km　(USD　0.06/km).　Additionally,　users＇　rationality　levels　significantly　affect　the　stabilization　time　of　toll　revenue,　and　the　speed　difference　between　freeways　and　parallel　roads　demonstrates　a　threshold　effect　on　travel　demand　and　revenue.　These　findings　provide　theoretical　and　technical　support　for　optimizing　freeway　toll　strategies,　enhancing　operational　efficiency,　and　promoting　sustainable　transportation　development.