Inceptio and Ambarella to Deliver SAE Level 3 as Industry Focuses on Making Autonomous Trucking Work at Scale

Ambarella, an edge Artificial Intelligence (AI) semiconductor company, and Inceptio Technology, an autonomous driving truck technology and operation company, announced that Inceptio selected two each of Ambarella’s CV2FS and CV2AQ edge AI Systems-on-Chip (SoCs)—a total of four CVflow SoCs—for its automotive-grade central computing platform. This platform is at the core of Inceptio’s full-stack XUANYUAN autonomous driving system for trucks, with Ambarella’s SoCs providing high-performance and low-power processing simultaneously for seven 8 Megapixel (MP) cameras, including AI compute, for surround camera perception and front Automotive Driver-Assistance Systems (ADAS) safety features like collision avoidance.

The autonomous trucking market has been gaining a lot of traction in recent times. Lowell, Arkansas-based carrier J.B. Hunt Transport Services Inc. recently reported metrics of a pilot program to move freight autonomously on Interstate 45 between Dallas and Houston. The autonomous trucks, developed by autonomous driving technology development company Waymo will be delivering home goods for retail giant Wayfair using its fleet of autonomous semi-trailer trucks. The deliveries will take place in Texas, with Waymo’s Class 8 autonomous truck hauling goods along Interstate 45 between facilities in Houston and Dallas, which was the route used by Waymo and J.B. Hunt during the original pilot last year. The trucks will operate autonomously, but will be supervised by two Waymo employees, a commercially licensed driver, and a software engineer from the cab of the vehicle.

Similarly, Swedish autonomous truck startup Einride AB announced that it will test its self-driving freight vehicles on public roads in the United States in an operation with GE Appliances after receiving approval from federal regulators. Einride plans to put one of its chunky Electric Vehicles (EVs), which have no cabs for drivers, on a 1-mile stretch of road between two warehouses in Tennessee for GE Appliances, a subsidiary of home appliances company Haier. The National Highway Traffic Safety Administration (NHTSA) recently greenlighted the company’s test run.

Autonomous truck developers are making continual developments toward commercialization and mainstream use, but these companies and their future fleet end users will need to address a range of technical issues and other operational concerns to fully integrate this technology into the freight transportation industry. Beyond regulatory hurdles surrounding autonomous driving on roads for commercial use, autonomous trucks should be well equipped to smoothly interact with law enforcement and connect with smart trailers to make way for mainstream deployment.

One of the biggest barriers with regard to streamlining the operations seems to be a lack of actionable data. The success of autonomous trucking would require a fundamental shift in how data are looked at and treated in businesses. Behind a truck’s autonomous driving system are software and compute power processing massive amounts of data from cameras and sensors. In the current landscape, more actionable data have been proven to be essential in enabling a vehicle’s safe operations and decision-making on the road. Beyond this, sensors can also generate additional types of information, such as location data, that would be critical for the broader ecosystem. Many stakeholders would depend on data integration to complete typical day-to-day functions without a driver.

The data collected from autonomous vehicle systems could also unlock new opportunities for consumers—and could serve as enhanced input to Transportation Management Systems (TMSs) for further enhanced load, carrier, and route scheduling optimization and real-time tracking and visibility. Autonomous system providers and fleets using autonomous trucks should consider how real-time data around variables like construction on roads, traffic, and weather conditions can be leveraged to improve their own fleet operations and even be commercialized to external parties and stakeholders by providing updated visibility into routes. The advancement of connected trucks can also support machine performance with data for better processes like predictive maintenance and manufacturing quality control. Data access and data quality are the major challenges to unlocking a range of opportunities for autonomous driving technology providers. Decision makers should act swiftly to reap the potential benefits from data platform integration.