Despite these challenges, the author remains optimistic that autonomous trucking will eventually be realized, although not as soon as initially expected. Companies like Aurora, Kodiak, and Gatik are anticipated to make some form of driverless deployment by the end of the year, but a large-scale deployment is not expected in 2024. The author concludes that achieving this will require advances in sensing, machine learning, and a significant amount of hard work.
Key takeaways:
- Driverless trucking, despite seeming simpler due to predictable freeway scenarios, is actually more complex than driverless rideshare due to the need for longer range sensing and more complex controls.
- Freeways, while simpler in terms of traffic and intersections, require a higher level of reliability in autonomous vehicles due to the high speeds and the need for advanced planning in case of emergencies.
- Current sensor technology does not meet the requirements for autonomous trucks, which need to detect objects at a greater distance than passenger vehicles due to their longer stopping distance.
- Despite the challenges, the author believes that autonomous trucking will eventually become a reality, but it will require significant advances in sensing technology and machine learning.