Conference Presentation, Panel
To Infinity and Beyond: What's Cool in Transportation
- Timeline Consensus: Industry leaders project the initial rollout of autonomous ride-share fleets in major cities within approximately five years (specifically targeting 2021), though widespread suburban expansion and individual ownership are expected to follow a slower trajectory.
- Kyle Voigt (Cruise/GM) notes that "five years" is the current consensus but suggests the technology may progress faster than anticipated, with the first deployments occurring in high-utilization urban ride-share environments.
- Richard Wilson (Center for Automotive Research) observes that some companies (e.g., Navia, Neutronomy, Tesla) have already achieved constrained autonomy, with 2018–2021 expected to see Level 4 deployments, while Level 5 remains a distinct, later leap.
- Operational Strategy (Level 4 vs. Level 5): The industry prioritizes constrained "Level 4" autonomy over immediate "Level 5" universal capability.
- Lior Iran (Uber) and James Hilliard Garcia (Toyota) argue that success requires "constraining" the operating environment (e.g., specific neighborhoods, highways, good weather) to manage technical complexity.
- Toyota defines Level 5 as a system requiring no human intervention under any condition (weather, traffic), whereas Level 4 allows for human take-over in extreme failure scenarios.
- James Garcia highlights that "one million miles in South Dakota" is not equivalent to "one million miles in Manhattan rush hour," necessitating new validation metrics based on scenario complexity rather than distance alone.
- Technology and Regulatory Hurdles:
- Technical: The primary remaining challenge is "polishing" technology to ensure reliability over hundreds of thousands of miles without failure; current demonstrations often rely on scripted paths or safety drivers.
- Regulatory: The U.S. faces a fragmented regulatory landscape where licensing is a state function, though the NHTSA has issued a voluntary 15-point plan covering cybersecurity and data sharing; states are cautioned against rushing legislation to maintain consistency.
- Infrastructure: Cruise (GM) states that current vehicle systems are designed to operate independently of Vehicle-to-Vehicle (V2V) communication, as infrastructure upgrades cannot be guaranteed in the near term.
- Business Model Shifts: The transition to autonomy is viewed as a shift from product ownership to service provision ("Mobility as a Service").
- Uber Vision: Uber aims to reduce private vehicle ownership, predicting that families will likely retain only one car while utilizing on-demand, shared autonomous fleets for affordability and convenience.
- Asset Ownership: While Uber initially may bear ownership costs, the long-term model predicts a "wealth of asset owners" (third parties, OEMs) seeking predictable returns, resembling an airline or real estate yield model.
- Maintenance: Autonomous fleets will require airline-style preventative maintenance with daily inspections and component swaps to maximize 24/7 utilization, rather than the 15-year lifecycle of a privately owned car.
- Microsoft's Ecosystem Approach: Microsoft is not manufacturing vehicles but is providing the cloud, cybersecurity, and productivity software infrastructure to enable third-party in-car experiences.
- Revenue Opportunity: With drivers freed from operating tasks, Microsoft aims to monetize the average 300 hours Americans spend in cars annually via productivity tools, voice assistants, and entertainment (e.g., in-car Skype, email dictation).
- Data & Security: Microsoft emphasizes that data is the new "fuel," requiring robust cloud infrastructure to protect against cybersecurity threats (citing hundreds of thousands of weekly attacks) and to enable personalized services.
- Societal Impact and Urban Planning:
- Land Reuse: Experts estimate that significant urban land currently dedicated to parking (e.g., 13 square miles in LA County) could be repurposed for green spaces, residential, or commercial use as vehicle utilization rises and private ownership drops.
- Congestion: The net effect on traffic is debated; while shared rides and platooning could increase efficiency, the lower cost and increased comfort of autonomous travel may induce higher demand, potentially offsetting congestion relief.
- Safety: The primary driver for adoption is safety; with ~36,000 U.S. traffic fatalities annually (largely due to distraction or impairment), even a 90% reduction would be socially acceptable, addressing the "trolley problem" as a low-priority edge case compared to saving lives.
- Labor and Economic Disruption:
- Job Evolution: Panelists acknowledge the displacement of driving jobs but cite the historical shift from telephone operators to IT services as a model for new employment opportunities in a service economy.
- Aging Society: Toyota is exploring robotics derived from autonomy technology to assist elderly populations, supporting the concept of "aging in place" and maintaining mobility for those with declining physical skills.
- Work Hours: Speculation exists that if automation handles basic infrastructure labor, society may transition to shorter workweeks (e.g., 20 hours) with robots filling remaining labor gaps.
- Ethical Decision-Making:
- Consensus: The panelists agree that ethical dilemmas (the "trolley problem") are extremely rare in practice due to sensors' superior reaction times and 360-degree visibility compared to humans.
- Current Priority: The immediate focus is on proving the system is statistically safer than a human driver; ethical hierarchies are viewed as secondary societal questions to be addressed only after safety benchmarks are met.