This Autonomous Trucking Company Is Beating Waymo and Tesla

 

Founded in 2015, San Diego- and Beijing-based TuSimple has captured the attention of supply chain managers, as well as investors.

About 15 months ago, the company received $55 million in funding, which it used to open a new R&D facility in Tucson, Arizona, and initiate revenue-generating services in the state. Recently, the company received another infusion of $95 million in Series D funding, giving it a valuation of $1 billion.

The new funds will go toward expanding TuSimple’s fleet, with the goal of hitting 50 trucks by June, making it the largest autonomous trucking company in the world.

While a number of startups continue to test their autonomous technology, TuSimple currently has five revenue-generating routes and plans to expand to Texas later this year. The company’s progress can be attributed to a couple of key differentiators.

First, TuSimple is not interested in manufacturing vehicles. It is currently working with semi OEMs to integrate their platforms, and is only running a fleet of trucks to validate the company's autonomous technology.

TuSimple's business model focuses on the hardware, the software updates needed to properly utilize the autonomous system, and monitoring of the system while it’s in use.

The company is not focused on long-distance routes. While this could be an application down the road, TuSimple’s primary focus is the last mile (e.g., local warehouses close to the actual buyer instead of state-to-state transportation).

This is where the final defining factor comes into play. Instead of LiDAR or radar-based systems, TuSimple relies on a collection of 10 or more mounted cameras that provide a 360° view from up to 10 football fields away. A systems engineer and driver are currently in the vehicle at all times.

These cameras are used with TuSimple’s algorithms and artificial intelligence to detect and track the truck’s environment in real time in order to make operational adjustments.

Next steps for TuSimple include working with state DOTs to adjust operators' hours of service rules in order to accommodate those who are merely supervising, rather than driving.

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