TuSimple, UPS maps new autonomous driving routes in southern US states
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An autonomous TuSimple truck can be seen in this undated photo. TuSimple / Document via REUTERS
Nov. 3 (Reuters) – Autonomous truck technology company TuSimple Holdings Inc (TSP.O) said on Wednesday it is mapping new freight lanes with UPS (UPS.N) from Arizona to Florida and has completed significant fuel savings for corporate parcel delivery at highway speed.
TuSimple said that since 2019, it has flown 160,000 freight miles for the North America Air Freight (NAAF) division of UPS – which is part of its supply chain business – and has achieved 13% of fuel savings at speeds between 55 miles (88.5 km) and 68 miles per hour. Routes for this UPS unit typically run between an airport and a UPS facility.
TuSimple said it shares data from its operations with UPS, which also owns a stake in the autonomous truck technology company.
According to the American Transportation Research Institute, fuel accounts for 24% of the cost per kilometer for heavy trucks, the second largest item after driver salaries and benefits, which account for 42% of costs.
“Reducing fuel costs by more than ten percent would translate into billions of dollars in savings for the entire US trucking industry,” TuSimple CEO Cheng Lu told Reuters.
“We cannot lose sight of the environmental and efficiency gains that this technology is already showing,” he said. “It shows that our technology drives more efficiently than human drivers.”
TuSimple’s network started in Arizona and the company has grown in the Southeastern United States. Read more
It plans to roll out a national self-sustaining freight network in the United States by 2024.
Self-driving technology for freight trucks has caught the attention of investors because it is expected to be easier and cheaper to deploy than in self-driving cars and robot-axes, while providing a clearer route to the road. profitability.
Autonomous freight services operate on fixed routes between pre-defined points – mostly on major highways with no intersections or pedestrians – requiring less mapping than shuttling customers between random points in the robotic axis.
Reporting by Nick Carey; Editing by Steve Orlofsky
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