This Autonomous Vehicles collection houses innovations from Stanford investigators enabling the next generation of self-driving transportation systems. These technologies promise to revolutionize mobility by enhancing safety, efficiency, and user experience through advanced perception, decision-making, and control. The collection includes state-of-the-art software for imitation learning, game-theoretic planning for interactive agents, and pedestrian intent prediction to enable safer navigation in complex environments. Additionally, the collection features sensor and camera systems including LIDAR technologies with phased arrays, Doppler time-of-flight imaging, and holographic beam steering for precise environmental sensing. Vehicle components round out the portfolio with adaptive steering controls and novel human-machine interfaces for seamless transitions between autonomous and manual driving. Together, these innovations contribute to safer, more intelligent, and more reliable autonomous vehicles for transportation, logistics, and mobility services. Key investigators leading these advances include Sebastian Thrun, Silvio Savarese, Mac Schwager, Jelena Vuckovic, Mark Brongersma, Olav Solgaard, and David Miller.