Mars Auto has initiated its U.S. operations in Texas, focusing on automating long-haul Class 8 trucks. The company offers vertically integrated trucking services powered by their proprietary self-driving technology and competes within the Texas freight transport hub while expanding across the Sunbelt region.
(Photo courtesy of Mars Auto)
AUSTIN, Texas, Nov. 06, 2024 (GLOBE NEWSWIRE) -- Mars Auto, specializing in autonomous trucking technology, has launched its U.S. operations, focusing on automating Class 8 trucks. With a cost-effective system priced at $7,000 per truck, the company aims to streamline freight transport and expand operations across the Sunbelt.
"We're pleased to bring our technology to the U.S.,” says Ilsu Park, CEO of Mars Auto. "Our model enables us to automate up to 99% of highway routes, lowering costs for companies while addressing driver shortages.”
Expansion in the Texas Logistics Hub
The Texas Triangle is a key freight corridor linking Dallas, Houston, and San Antonio. It is now experiencing an influx of autonomous trucking operations. Companies like Aurora Innovation and Kodiak Robotics are already active in the area. Their entry into this space offers a more affordable and efficient solution for automating truck fleets.
The company chose Texas as its starting point due to its central role in the movement of U.S. goods. Combining autonomous driving with transport management provides a seamless and cost-effective solution for companies aiming to improve their supply chains.
"We simplify the entire process, from route planning to truck operation, easing the load for our clients,” says Park.
The company's system eliminates the need for expensive high-definition maps and Light Detection and Ranging (LiDAR) technology. This provides a quicker and cheaper way to deploy autonomous trucks on routes requested by customers.
Entering a Competitive Market
In the trucking industry, where profit margins are tight, cost efficiency is critical. Mars Auto is entering this competitive market alongside several self-driving truck startups expanding across Texas.
These companies rely on high-definition maps and complex sensor systems for their self-driving technologies. This traditional approach results in system costs that exceed the price of the truck itself, pushing per-mile trucking costs above those of human drivers. These limitations not only create fundamental constraints in obtaining data to train self-driving AI but also present significant cost barriers to commercialization.
In contrast, Mars Auto is embracing a new generation of technology. It employs a mapless, vision-based, end-to-end approach that, similar to Tesla, maximizes the potential of AI on an affordable system.
Mars Auto's goal is to provide a streamlined, full-service, for-hire carrier service for long-haul trucking. "We are focusing not on selling systems but on providing our customers with more efficient trucking services at a more affordable price through self-driving technology," says Park. "With our ongoing efforts, our customers will soon be able to cut their per-mile trucking costs in half."
Future Prospects for Autonomous Trucking
Mars Auto's entry into the U.S. represents a significant expansion after completing over one million miles of autonomous driving for major firms in South Korea. The company is now focusing on scaling its operations in the U.S., with all necessary registrations secured.
Mars Auto plans to expand its autonomous trucking technology across the Sunbelt. This innovative direction reflects the industry's growing focus on sustainability and automation.
"We're looking forward to increasing our presence in the U.S. market,” says Park. "Our technology will support companies as they adapt to future challenges.”
For more information, visit Mars Auto.
Contact Information:
Contact Person's Name: Jaekyoung Roh
Organization / Company: Mars Auto
Company website: https://marsauto.com
Contact Email Address: [email protected]
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/245799c2-f414-4ba0-8754-02ae8178378f
