Catalyst with Shayle Kann
Catalyst with Shayle Kann

Cracking the code on autonomous trucking

May 7, 2026

AI Summary

5 min read

Ayal Cohen, founder and CEO of Humble Robotics, explains why autonomous trucking has lagged behind passenger vehicles like Waymo despite early promise, and details his clean-sheet approach at Humble to accelerate progress using current AI advances.

Highway Trucking's Unexpected Difficulties

Autonomous trucking efforts began in 2016 with companies like Otto (where Cohen worked early) and Starsky Robotics, drawn by the apparent simplicity of highways over chaotic city streets. Initial demos, such as Otto's 100-mile driverless beer run, suggested quick progress. However, highways proved harder due to rare but severe edge cases at high speeds with 80,000-pound vehicles—long stopping distances, inability to safely pull over (unlike Waymo cars that can stop without hazard), and infrequency of events limiting data collection for learning. Passenger vehicles benefit from structural advantages: lower stakes allow stopping in confusion, while trucking demands near-zero error margins. A decade later, no regular driverless highway service exists, though firms like Aurora and Bot Auto have done limited driverless runs, often with safety observers.

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What you'll learn

  • 1 (00:02) **Intro to Autonomous Trucking Landscape** - Host sets context on Waymo's success vs trucking lag, introduces Ayal Cohen of Humble Robotics
  • 2 (04:17) **Ayal's Background and Early Autonomous Efforts** - Cohen recounts joining Otto in 2016 after Apple, initial optimism for highways over cities
  • 3 (06:33) **Why Highways Prove Harder for Trucking** - Details edge cases at high speeds, long stopping distances for 80k lb trucks
  • 4 (09:28) **Current State of Autonomous Trucking** - No regular driverless highway service 10 years in, despite demos by Aurora, Bot Auto
  • 5 (11:40) **Tech Evolution: Pre-LLM to VLM Era** - Early hand-coded algorithms evolved; companies re-engineer stacks multiple times
  • 6 (15:02) **Vision Language Models (VLMs) Explained** - VLMs interpret images like LLMs do text, providing edge case understanding out-of-box
  • 7 (17:22) **Sensor Strategy for Trucking Safety** - Recommends camera+lidar+radar fusion; no dogma, prioritize per condition (e.g., lidar night, radar weather)

+ Full timestamped outline available in the app

Show Notes

Even though autonomous passenger vehicles have entered the mainstream in cities across the country, autonomous trucks still lag behind. But Humble Robotics thinks it has cracked the code with a new design that completely does away with the tractor-trailer model we see on the highway every day.

In this episode, Shayle speaks to Eyal Cohen, founder and CEO of Humble. The company built its electric trucks from the ground up. Fully cabless, they combine the tractor and trailer into a single platform designed to optimize energy efficiency, unit economics, and roadway safety.

Shayle and Eyal explore topics including:

  • The differences between autonomous passenger and freight vehicles
  • The challenge of transporting heavy payloads at high speeds
  • Why Humble has shifted away from LiDar in favor of a camera-centric approach offered by visual language models (VLMs)
  • The unit economics of electric and autonomous freight
  • Why Humble is embracing a "hub-to-hub" model for its trucks
  • The evolving regulatory landscape for autonomous trucking

Resources

Credits: Hosted by Shayle Kann. Produced and edited by Max Savage Levenson. Original music and engineering by Sean Marquand. Stephen Lacey is our executive editor.

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