Future Tense Getting up to speed with autonomous vehicles
15 snips
Oct 23, 2025 
Join experts Michael Milford, a robotics director at Queensland University of Technology, Milad Haghani, an urban resilience associate professor, and sociolinguist Abdesalam Soudi from the University of Pittsburgh. They dive into the current state and commercial uses of autonomous vehicles, touching on Tesla’s camera-based approach versus LiDAR systems. They discuss the social language of driving, how contextual cues can confuse AI, and consumer reluctance towards driver-assist technologies, revealing the complexities of acceptance and regulation in the evolving landscape of self-driving cars.
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Consolidation Reveals Real Leaders
- Waymo and a few credible operators lead the field after long consolidation and heavy costs.
- Real deployments let companies gather safety and financial data to judge viability.
Sensor Choice Shapes Strategy
- Tesla relies primarily on cameras while many rivals use LiDAR and range sensors.
- The sensor choice reflects different technical strategies and trade-offs in perception.
Scale Enables Real Statistics
- Some robo-taxi operators run hundreds or thousands of vehicles in city areas, not just single prototypes.
- That scale produces real-world safety and usage statistics previously unavailable.
