Pedestrian　detection　is　an　important　part　of　assisted　driving　and　automatic　driving.　This　paper　proposes　a　pedestrian　detection　method　based　on　improved　SSD　(Single　Shot　MultiBox　Dectector)　algorithm　for　the　problem　of　the　detection　accuracy　in　pedestrian　test　tasks.　We　reconstructed　the　feature　extraction　network　of　the　SSD　model.　The　MobileNet　and　ResNet　(Residual　Network)　were　used　as　the　basic　network　of　SSD　to　build　the　SSD　model　and　improve　the　detection　capability　of　the　algorithm.　We　conducted　experiments　on　public　pedestrian　detection　data　sets.　The　results　were　evaluated　using　mAP　and　FPS.　The　experimental　results　show　that　the　mAP　of　the　SSD　algorithm　after　introducing　the　residual　network　reaches　85.00%,　which　is　11.92%　higher　than　the　original　SSD　algorithm,　and　the　FPS　reaches　39.31%,　which　effectively　improves　the　accuracy　and　speed　of　pedestrian　detection.　©　2021　IEEE.