Age　-related　changes　and　frailty　are　reasons　for　the　high　proportion　of　older　drivers　in　certain　types　of　crashes,　such　as　giving　right　of　way　at　intersections　and　turning　left.　The　identified　crash　causes　include　the　driver　＇　s　demographics,　driving　style,　cognitive　function,　and　mental　workload.　This　study　aimed　to　explore　the　associations　of　demographics　and　scale　measures　with　cognitive　driving　behavior.　Thirty-nine　drivers,　consisting　of　twenty　younger　drivers　(18　-　60　years　old)　and　nineteen　older　drivers　(above　60　years　old),　participated　in　driving　simulation　experiments　after　completing　scale　tests.　The　selected　scale　measures　included　the　demographic　questionnaire,　Multidimensional　Driving　Style　Inventory　(MDSI-C),　Mini　-Mental　State　Examination　(MMSE),　Trail　Making　Test　Part　A　(TMT-A)　and　Part　B　(TMT-B),　and　the　National　Aeronautics　and　Space　Administration　Task　Load　Index　(NASA-TLX)　for　obtaining　subjective　information　from　drivers.　Driving　scenarios　were　developed　based　on　the　driving　characteristics　of　older　adults　to　investigate　age　-related　driving　ability.　The　driving　behavior　parameters　included　reaction　time,　lateral　stability,　and　driving　speed,　corresponding　to　reaction,　perception,　and　execution.　Three　stepwise　regression　models　showed　that　NASA-TLX,　the　interaction　between　age　and　driving　experience,　and　the　interaction　between　age　and　TMT-A　significantly　explained　53.3　%　of　reaction　time　variance;　TMT-A,　risk　driving　style,　anxiety　driving　style,　and　gender　significantly　explained　53.5　%　of　lateral　stability　variance;　TMT-A,　NASA-TLX,　and　MMSE　significantly　explained　60.6　%　of　driving　speed　variance.　Subsequently,　the　impact　of　four　age　-related　predictor　variables　on　driving　behavior　was　further　discussed.　It　is　worth　noting　that　a　rich　driving　experience　may　compensate　for　driving　performance.　However　cognitive　impairment　impairs　this　compensation.　Driving　behavior　is　influenced　by　a　combination　of　various　factors.　Age,　as　a　physiological　indicator,　is　not　sufficient　to　be　a　strong　predictive　factor　for　lateral　stability　and　driving　speed.　The　results　provide　a　reference　for　traffic　safety　management　departments　to　streamline　driving　suitability　test　procedures　and　propose　targeted　training　methods　for　older　drivers.