Autonomous trucking is a promising technology that can greatly impact modern logistics and the environment. Ensuring its safety on public roads is one of the main duties that requires an accurate perception of the environment. To achieve this, machine learning methods rely on large datasets, but to this day, no such datasets are available for autonomous trucks.

Waabi and Volvo announce partnership integrating Waabi Driver AI technology with Volvo VNL Autonomous trucks, marking major milestone in autonomous freight.

AI-powered driving will help with a growing shortage of drivers, rising costs and relentless demand for faster deliveries. Artificial intelligence-powered self-driving trucks are no longer a distant concept. They are quickly becoming a real solution to some of the logistics industry's biggest challenges. As supply chains face growing pressure and the driver shortage deepens across the U.S. and Europe, Plus Automation is stepping up with bold ambitions and powerful AI. Recently, the Santa Clara, California-based startup announced it will go public through a merger with Churchill Capital Corp IX.

Autonomous trucking is a promising technology that can greatly impact modern logistics and the environment. Ensuring its safety on public roads is one of the main duties that requires an accurate perception of the environment. To achieve this, machine learning methods rely on large datasets, but to this day, no such datasets are available for autonomous trucks. MAN TruckScenes allows the research community to come into contact with truck-specific challenges, such as trailer occlusions, novel sensor perspectives, and terminal environments for the first time. It comprises more than 740 scenes of 20 s each within a multitude of different environmental conditions.

Driverless semitrucks raise questions about safety, reliability and the future of the trucking industry. Aurora, a leader in autonomous vehicles, has officially deployed its driverless trucks on Texas roads, marking a key milestone in the evolution of transportation. This development raises important questions about safety, reliability and the future of the trucking industry. Aurora's autonomous trucks now operate on routes between Dallas and Houston, hauling commercial loads. Join the FREE "CyberGuy Report": Get my expert tech tips, critical security alerts and exclusive deals, plus instant access to my free "Ultimate Scam Survival Guide" when you sign up!

Autonomous trucking is a promising technology that can greatly impact modern logistics and the environment. Ensuring its safety on public roads is one of the main duties that requires an accurate perception of the environment. To achieve this, machine learning methods rely on large datasets, but to this day, no such datasets are available for autonomous trucks. In this work, we present MAN TruckScenes, the first multimodal dataset for autonomous trucking. MAN TruckScenes allows the research community to come into contact with truck-specific challenges, such as trailer occlusions, novel sensor perspectives, and terminal environments for the first time. It comprises more than 740 scenes of 20 s each within a multitude of different environmental conditions. The sensor set includes 4 cameras, 6 lidar, 6 radar sensors, 2 IMUs, and a high-precision GNSS. The dataset's 3D bounding boxes were manually annotated and carefully reviewed to achieve a high quality standard. Bounding boxes are available for 27 object classes, 15 attributes, and a range of more than 230 m. The scenes are tagged according to 34 distinct scene tags, and all objects are tracked throughout the scene to promote a wide range of applications. Additionally, MAN TruckScenes is the first dataset to provide 4D radar data with 360{\deg} coverage and is thereby the largest radar dataset with annotated 3D bounding boxes. Finally, we provide extensive dataset analysis and baseline results. The dataset, development kit and more are available online.

We develop a deep reinforcement learning framework for tactical decision making in an autonomous truck, specifically for Adaptive Cruise Control (ACC) and lane change maneuvers in a highway scenario. Our results demonstrate that it is beneficial to separate high-level decision-making processes and low-level control actions between the reinforcement learning agent and the low-level controllers based on physical models. In the following, we study optimizing the performance with a realistic and multi-objective reward function based on Total Cost of Operation (TCOP) of the truck using different approaches; by adding weights to reward components, by normalizing the reward components and by using curriculum learning techniques.

California Gov. Gavin Newsom has blocked a bill that would have required autonomous trucks weighing more than 10,000 pounds (4,536kg) to have human safety drivers on board while operating on public roads. The governor said in a statement that the legislation, which California Senate members passed in a 36-2 vote, was unnecessary. Newsom believes existing laws are sufficient to ensure there's an "appropriate regulatory framework." The governor noted that, under a 2012 law, the state's Department of Motor Vehicles collaborates with the National Highway Traffic Safety Administration, California Highway Patrol and other relevant bodies "to determine the regulations necessary for the safe operation of autonomous vehicles on public roads." Newsom added that the DMV is committed to making sure rules keep up with the pace of evolving autonomous vehicle tech.

California governor Gavin Newsom worked late last night, vetoing a law that would have banned self-driving trucks without a human aboard from state roads until the early 2030s. State lawmakers had voted through the law with wide margins, backed by unions that argued autonomous trucks are a safety risk and threaten jobs. The bill would have seen California, which in 2012 became the first state to clear a regulatory path for autonomous vehicles, turn against self-driving technology just as driverless taxis are starting to serve the public. Autonomous truck developers now hope the freight-heavy state--home to two of the largest US ports--will one day become a critical link in an autonomous trucking network spanning the US. Companies developing the technology say it will save freight shippers money by enabling trucks to run loads on highways 24 hours a day, and by eliminating the dangers of distracted human driving, which could bring down insurance costs.