Planning safer autonomous driving by guessing multiple futures

Self-driving cars must guess what other vehicles will do, then plan safely anyway. This work combines two proven techniques—stochastic model predictive control and branching decision trees—so the planner generates different trajectory options for different likely intentions while staying safe under trajectory uncertainty. A clustering method merges similar scenarios to keep computation tractable. Highway tests show it cuts excessive caution while maintaining safety and real-time speed.