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After years of research and development, testing, and multiple regional tests, the first cross-country autonomous haul has finally happened. And according to multiple reports, the test went off without a hitch.
The autonomous haul was completed by Plus.ai – a Silicon Valley-based technology firm that has been working on improving self-driving solutions for the trucking industry. The shipment included moving 40,000 pounds of Land O’Lakes butter over a 2,800-mile distance from Tulare, CA. to Quakertown, PA. In total, it took only three days to complete the autonomous haul with multiple scheduled breaks as it traveled down Interstate 70 and 15.
To ensure safety during transit, the autonomous trucks were staffed by a safety driver. Also on-board was a company engineer to monitor performance throughout the trip. The safety driver was never used to take over manual control throughout the entire trek. Of course, this is except for federal-mandated driver breaks or to refuel the vehicle.
Most of the transit was handled by Plus.ai’s self-driving platform called SLAM – being an acronym for the lengthier “multimodal sensor fusion, deep-learning visual algorithms, and simultaneous locating and mapping.
Although this cross-country movement was a monumental accomplishment, it certainly was not the first rodeo for Plus.ai. In fact, the firm has been testing its autonomous technology on a weekly basis, with freight trips traveling within the region for about a year.
Other autonomous technology providers have been testing self-driving solutions in the Southwestern United States for quite some time as well. Namely, the United States Postal Service has been testing truck movements from Texas to Arizona, a popular trucking lane that is traveled by thousands of shipping trucks each day.
As these tests begin to expand their distance, and the technology improves, it’s likely that more of these cross-country trips will occur throughout 2020.
One of the biggest hurdles to the full integration of autonomous driving is accounting for various road conditions. These trucks have multiple sensors and cameras that collect data and permit the AI technology to receive the route information, guide the truck along the said route, and safely react to emergency situations. When the vehicle travels during daylight hours, and in perfect weather conditions, visibility issues are not common.
However, the cross-country trip encountered various weather conditions including rain, snow, and the need to handle multiple operations during the night or low light hours. It was expected that the changing weather patterns would cause multiple delays during the trip, as sensors could be blocked by ice and snow, which would make the vehicle unsafe to operate.
This didn’t occur. Plus.ai reported that their SLAM system handled the diverse traveling conditions with very little trouble. The effectiveness of this test provided a significant positive step in the future of self-driving commercial trucks – as having the ability to adapt to evolving conditions, operating 24-hours per day, and with reduced human interaction is the long-term objective of this technology.
In fact, one of the most publicized accidents involving self-driving vehicles occurred in Tempe, Arizona, when a self-driving rideshare vehicle operated struck a pedestrian at night, killing them in the process. While there was a human operator in the vehicle, the reduced visibility at night was determined to be a contributing factor.
A major reason why companies like Plus.ai are actively testing these self-driving commercial trucks is to help bridge the gap with a current truck driver shortage that plagues the supply chain industry. It is estimated that there are more than 60,000 open truck driver positions in the United States alone. While the initial self-driving solutions will include a human occupant or CDL truck driver, that can take over in case of emergency situations.
Many industry experts suggest that once the industry converts to fully autonomous solutions, shipping rates with LTL and FTL freight movements will drop significantly. However, on the other side of the coin, the costs to integrate this technology into trucking fleets comes with the inevitability of recouping the investment.