To　improve　the　traffic　safety　of　highway　bridge　sections　in　foggy　environments,　this　paper　considered　the　influence　of　variable　speed　limit　signs　on　driving　behavior.　To　obtain　the　best　effect,　it　put　forward　a　quantitative　evaluation　method　from　the　perspective　of　the　obedience　effect.　Taking　E’dong　Yangtze　River　Bridge　as　the　prototype,　this　paper　selected　the　lowest　visibility（100　m）and　free　flow　service　level　of　the　bridge　in　recent　years　as　the　test　environment.　Three　speed　limit　strategies　were　designed,　namely,　the　control　group　SI　(no　speed　limit　strategy）,　the　experimental　group　SII　(90~70　km/h　speed　limit　strategy),　and　the　experimental　group　SIII　(90~70~　50　km/h　step-by-step　speed　limit　strategy）.　Relying　on　the　driving　simulator,　the　micro-driving　behavior　data　of　foggy　bridge　scenes　with　different　speed　limit　conditions　were　realized.　The　action　mechanism　of　variable　speed　limit　signs　and　driver　characteristics　were　analyzed　from　the　rapidity,　stability,　and　accuracy　of　driver　response　by　repeated　measure　analysis　of　variance,　and　the　effectiveness　of　different　speed　limit　strategies　was　evaluated　using　the　fuzzy　comprehensive　evaluation　method.　The　results　show　that　the　variable　speed　limit　sign　can　make　the　driver　take　deceleration　measures　earlier,　and　the　vehicle’s　stability　in　the　fog　area　is　better.　When　the　visibility　is　100　m　in　fog,　the　steady-state　frequency　of　90~70~50　km/h　step-by-step　speed　limiting　strategy　is　more　significant,　the　spatial　stability　is　better,　the　speed　overshoot　and　the　following　ratio　are　more　minor,　and　the　response　accuracy　is　higher.　The　results　of　the　fuzzy　comprehensive　evaluation　show　that　the　90~70~50　km/h　step-by-step　speed　limit　strategy,　as　the　optimal　scheme,　can　effectively　improve　the　adaptability　of　driving　behavior　in　fog　areas,　reduce　driving　risk,　and　improve　the　stability　of　vehicle　operation.　The　research　results　provide　a　solution　for　setting　variable　speed　limit　signs　for　bridges　on　foggy　days　and　can　provide　adequate　support　for　the　active　safety　prevention　and　control　of　bridges　on　foggy　days.　©　2024　South　China　University　of　Technology.　All　rights　reserved.