In autonomous and self-driving vehicle news are Gatik, Cummins and North Carolina State University.
Gatik Partners with Cummins
Gatik announced today that it will collaborate with Cummins Inc. to facilitate the integration of Gatik’s autonomous driving system with Cummins’ advanced powertrain solution in Gatik’s fleet of medium-duty trucks. Cummins delivers powertrain solutions that provide leading performance and fuel economy through the integration of hardware and software. Gatik is the market leader in autonomous middle mile logistics, and in 2021 launched the world’s first fully driverless commercial delivery service with Walmart.
Under the collaboration, Cummins will utilize its suite of advanced software features to integrate its powertrain solution to enable Drive-by-wire (DbW) for Gatik’s industry-first medium-duty (class 6) Isuzu FTR fleet with the Cummins B6.7 engine. The integration of Gatik’s commercial-grade autonomous technology with Cummins’ powertrain increases functional safety and enhances reliability of the autonomous system, while improving fuel efficiency and offering superior vehicle performance on Gatik’s short-haul, B2B delivery routes. Cummins will work closely with Gatik’s engineering team to provide additional technical expertise.
“As we commercialize our product offerings at scale across North America, ensuring that we integrate our technology with the world’s leading Tier 1 companies is critical to meeting intensifying demand for our solution safely and quickly,” said Arjun Narang, CTO and co-founder, Gatik. “Cummins’ technological leadership in developing the world’s leading powertrains for over 100 years, and deep commitment to developing customer-centric solutions for the future of logistics mean the tangible benefits of our work together will be felt immediately across our customer base.”
“Cummins is excited to integrate its powertrain solution with Gatik’s automated driving system,” said Michael Taylor, General Manager Global Powertrain Integration, Cummins Inc. “Cummins powers nearly every type of application globally, so integrating our powertrain with automated driving systems like Gatik’s will allow our customers to choose the newest technologies to meet their needs.”
This announcement comes on the heels of rapid commercial and technical progress at Gatik. Gatik has one of the largest commercially deployed autonomous fleets in North America, operating for Fortune 500 customers across multiple markets including Texas, Arkansas, Louisiana and Ontario, Canada. In the past 12 months, Gatik announced its industry-first partnership with Isuzu to implement OEM-grade redundancies for medium-duty trucks, collaboration with Goodyear to equip its fleet with tire intelligence technology to improve stopping distances and monitor tire pressure in real time for enhanced safety, and a strategic partnership with Ryder to leverage Ryder’s national leasing, servicing and fleet maintenance expertise.
Gatik’s collaboration with Cummins represents a key component of Gatik’s platform-agnostic commercialization strategy, enabling Gatik to seamlessly integrate its autonomous driving system with multiple OEMs, and across a range of vehicle platforms powered by Cummins, further refining a safe, unique, and efficient autonomous solution for the commercial middle mile market.
North Carolina State University Improve Autonomous Vehicle Calculations
If autonomous vehicles are ever going to achieve widespread adoption, we need to know they are capable of navigating complex traffic situations, such as merging into heavy traffic when lanes disappear on a highway. To that end, researchers from North Carolina State University have developed a technique that allows autonomous vehicle software to make the relevant calculations more quickly – improving both traffic and safety in simulated autonomous vehicle systems.
“Right now, the programs designed to help autonomous vehicles navigate lane changes rely on making problems computationally simple enough to resolve quickly, so the vehicle can operate in real time,” says Ali Hajbabaie, corresponding author of a paper on the work and an assistant professor of civil, construction and environmental engineering at NC State. “However, simplifying the problem too much can actually create a new set of problems, since real world scenarios are rarely simple.
“Our approach allows us to embrace the complexity of real-world problems. Rather than focusing on simplifying the problem, we developed a cooperative distributed algorithm. This approach essentially breaks a complex problem down into smaller sub-problems, and sends those to different processors to solve separately. This process, called parallelization, improves efficiency significantly.”
At this point, the researchers have only tested their approach in simulations, where the sub-problems are shared among different cores in the same computing system. However, if autonomous vehicles ever use the approach on the road, the vehicles would network with each other and share the computing sub-problems.
In proof-of-concept testing, the researchers looked at two things: whether their technique allowed autonomous vehicle software to solve merging problems in real time; and how the new “cooperative” approach affected traffic and safety compared to an existing model for navigating autonomous vehicles.
In terms of computation time, the researchers found their approach allowed autonomous vehicles to navigate complex freeway lane merging scenarios in real time in moderate and heavy traffic, with spottier performance when traffic volumes got particularly high.
But when it came to improving traffic and safety, the new technique did exceptionally well. In some scenarios, particularly when traffic volume was lower, the two approaches performed about the same. But in most instances, the new approach outperformed the previous model by a considerable margin. What’s more, the new technique had zero incidents where vehicles had to come to a stop or where there were “near crash conditions.” The other model’s results included multiple scenarios where there were literally thousands of stoppages and near crash conditions.
“For a proof-of-concept test, we’re very pleased with how this technique has performed,” Hajbabaie says. “There is room for improvement, but we’re off to a great start.
“The good news is that we’re developing these tools and tackling these problems now, so that we’re in a good position to ensure safe autonomous systems as they are adopted more widely.”
The paper, “Distributed Cooperative Trajectory and Lane changing Optimization of Connected Automated Vehicles: Freeway Segments with Lane Drop,” appears in the journal Transportation Research Part C. First author of the paper is Mehrdad Tajalli, a recent PhD graduate of NC State. The paper was co-authored by Ramin Niroumand, a PhD student at NC State.