Lane　change　operation　is　widely　used　in　numerous　traffic　scenarios;　to　minimize　lane　change　time　and　avoid　collisions　with　other　vehicles　required　by　intelligent　vehicles,　an　optimal　lane　change　motion　is　proposed　for　the　shortest　time　free　lane　change　and　emergency　obstacle　avoidance　lane　change.　First,　two　optimal　lane　change　motion　models　are　constructed　based　on　a　3-degree-of-freedom　dynamical　vehicle　model.　Because　of　uncertain　parameters　in　the　vehicle　model,　the　optimal　lane　change　motion　problem　is　an　uncertain　optimal　control　problem.　Subsequently,　targeted　at　nonlinearity　and　uncertain　parameters,　an　extended　adaptive　pseudo-spectral　method　is　also　presented　on　the　basis　of　approximate　and　numerical　integration　of　parameter　space.　Finally,　solving　the　optimal　lane　change　motion　problem,　optimization　results,　control　results　based　on　the　nonlinear　model　predictive　control　algorithm,　and　experimental　results　are　shown　under　circumstances　of　certain　vehicle　mass　and　uncertain　vehicle　mass.　As　for　uncertain　parameters,　optimization　results　are　featured　with　robustness.　Thus,　uncertain　parameters　need　not　be　measured,　and　optimization　calculation　need　not　be　carried　out　in　real　time.　The　algorithm　put　forward　here　could　be　adopted　to　solve　an　uncertain　optimal　control　problem.　The　optimal　lane　change　motion　can　be　extended　to　apply　in　more　complex　operations　like　merging,　double-lane　change,　entering/exiting　highways,　or　overtaking　another　vehicle.