Safe　driving　and　effective　collision　avoidance　are　critical　challenges　in　the　development　of　autonomous　driving　technology.　As　the　dynamic　interactions　between　vehicles　and　pedestrians　become　increasingly　complex,　making　rational　decisions　and　accurately　executing　planning　and　control　in　emergency　situations　has　become　a　core　issue　for　sustainable　development　relating　to　traffic　mobility　and　safety.　This　paper　proposes　an　active　collision-avoidance　control　strategy　based　on　emergency　decisions　and　planning　in　the　context　of　vehicle-pedestrian　interactions.　A　safety-distance　model　is　developed　with　consideration　given　to　the　dynamic　interactions　between　these　two　entities,　and　an　emergency-decision　mechanism　is　designed　using　the　integration　of　priority　rules.　To　generate　smooth　collision-avoidance　trajectories,　a　quintic　polynomial　method　is　employed　to　construct　trajectory　clusters　that　meet　the　desired　specifications.　Moreover,　a　multi-objective　optimization　value　function　which　considers　multiple　factors　comprehensively　is　used　to　select　the　optimal　path.　To　enhance　collision-avoidance　control　accuracy,　an　RBF　(radial　basis　function)-optimized　SMC　(sliding　mode　control)　algorithm　is　introduced.　Additionally,　an　FD-SF　(force　demand-based　speed　feedback)　algorithm　is　designed　to　accurately　track　the　longitudinal　braking　path.　The　results　indicate　that　the　proposed　strategy　can　generate　efficient,　comfortable,　and　smooth　optimal　collision-avoidance　paths,　significantly　improving　vehicle　response　speed　and　control　accuracy.