The Rivian and Volkswagen Group Technologies (RV Tech) joint venture has completed winter testing of its production-intent zonal architecture for the first generation of software‑defined vehicles (SDVs). Over the course of several months of testing in Phoenix, Arizona, and Arjeplog, Sweden, a joint team from Volkswagen, Audi, Scout and RV Tech validated the functionality and performance of the electronics and software.

The partnership is developing SDV technology, from operating systems to zonal controllers to cloud and connectivity solutions.

Oliver Blume, CEO of the Volkswagen Group, said, “We are accelerating toward the future. With the successful completion of the winter tests, our joint venture once again demonstrates the speed and precision of its work.

Continue reading Rivian-Volkswagen joint venture completes SDV architecture winter testing at ADAS & Autonomous Vehicle International.

WeRide has announced that Grab, a superapp in Southeast Asia, has committed to a strategic equity investment in WeRide. The investment is part of a strategic partnership between the two companies to accelerate the deployment and commercialization of Level 4 robotaxis and shuttles in Southeast Asia, and will see the integration of WeRide’s autonomous vehicles (AVs) into Grab’s network.

Grab’s investment is expected to be completed by the first half of 2026, subject to customary closing conditions and WeRide’s preferred timing.

The partnership will establish a framework for deploying autonomous solutions across Grab’s network, to enhance operational efficiency and scalability.

Continue reading Grab invests in WeRide to advance robotaxi and shuttle deployment in Southeast Asia at ADAS & Autonomous Vehicle International.

Gatik has launched Arena, its next-generation simulation platform designed to accelerate the development and validation of autonomous vehicle systems. The platform has been developed in collaboration with Nvidia and integrates Nvidia Cosmos World Foundation Models (WFMs).

As Gatik scales freight-only driverless operations in 2025, Arena is designed to enable safe and efficient training for its autonomous systems on a wide range of driving scenarios, reducing reliance on on-road testing.

Arena uses high-fidelity synthetic data generation, combining real-world logs, trajectory editing, agent modeling and multi-sensor simulation pipelines, to deliver full closed-loop simulations.

“As the AV industry pushes toward scaled deployments, the bottleneck isn’t just better algorithms – it’s better, smarter data,” said Gautam Narang, Gatik’s CEO and co-founder.

Continue reading Gatik unveils next-gen simulation platform built on Nvidia Cosmos at ADAS & Autonomous Vehicle International.

Nvidia has launched a comprehensive, industry-defining autonomous vehicle (AV) software platform to accelerate the large-scale deployment of safe, intelligent transportation innovations for auto makers, truck manufacturers, robotaxi companies and startups worldwide.

The full-stack Nvidia Drive AV software platform is combined with Nvidia’s accelerated compute, designed to provide the industry with a robust foundation for AI-powered mobility.

Full-stack software approach

Nvidia Drive offers a modular and flexible approach, allowing customers to scale by adopting either the full technology stack or selected components based on their requirements. The software architecture supports real-time sensor fusion and continuous improvement through over-the-air updates.

Continue reading Nvidia Drive full-stack autonomous vehicle software rolls out at ADAS & Autonomous Vehicle International.

Simulation software specialist rFpro has developed a highly detailed digital model of a rural road network near the village of Harbury in Warwickshire in the UK. The model offers a multi-functional simulation solution for vehicle development, ranging from vehicle dynamics and automated driving to powertrain and headlight tuning.

The digital twin spans 17.5km and includes more than 230 buildings, 190 selectable parking locations, 660 drain covers and over 2,000 roadside objects, such as lampposts, road signs and traffic lights. This creates a highly immersive experience for both human drivers and vehicle sensor systems.

The Harbury model has been created using survey-grade lidar data, ensuring a road surface accuracy of 1mm in height, making the model suitable for vehicle dynamics tuning.

Continue reading rFpro launches digital twin of rural UK road at ADAS & Autonomous Vehicle International.

Neural Concept has announced that its 3D AI platform will leverage the Nvidia Omniverse Blueprint. This integration enables Neural Concept customers to create real-time interactive digital twins at scale for computer-aided engineering (CAE) product development.

Conventional OEM engineering workflows — from physics simulation to visualization — can take weeks or even months. By using Neural Concept’s 3D AI platform with the Nvidia Omniverse Blueprint, OEMs can get real-time predictions on performance, make design iterations faster and more efficiently, and make the best design decisions out of tens of millions of simulated options.

Neural Concept’s AI platform accelerates CAE with engineering intelligence by using generative AI and data-driven design at the core of the OEM product development.

Continue reading Neural Concept unveils digital twin solution with Nvidia Omniverse Blueprint at ADAS & Autonomous Vehicle International.

AV Elevate is a fully integrated simulation solution designed to accelerate the development of autonomous vehicles.

rFpro states that it is “the industry’s most advanced platform to provide both closed-loop perception testing and the creation of engineering-grade synthetic training data”. The solution also enables the tuning of sensors, the training of perception and control algorithms and testing of the full AV technology stack.

“AV Elevate is a game-changing simulation platform, it is the most advanced solution to enable the complete AV technology stack to be tuned, trained and tested,” said Matt Daley, technical director at rFpro.

Continue reading rFpro introduces AV Elevate simulation solution for AV development at ADAS & Autonomous Vehicle International.

Ansible Motion and MdynamiX have established a partnership to enhance the development of steering, braking and advanced driver assistance systems (ADAS). They hope to enable engineers to experience and evaluate vehicle systems early and often during the development process by combining real, deployable hardware and software with virtual assessment capabilities.

Ansible Motion is already experiencing steady demand for its driving simulators from OEMs and Tier 1 suppliers across China, Korea, the USA and Europe. Thanks to the versatility and capabilities of its DIL simulators, engineers are finding new ways to refine and validate vehicle features much earlier in the development phase.

Continue reading Ansible Motion and MdynamiX partner to enhance remote vehicle development at ADAS & Autonomous Vehicle International.

When the world’s fastest autonomous race cars take to the starting line at the Indianapolis Motor Speedway this Friday (September 6), the 10 university teams of the Indy Autonomous Challenge will begin a new chapter in the development of their vehicle controllers. From now on, the university teams can use the extended functionality of dSPACE’s software-in-the-loop (SIL) solutions and use the cloud racing services to race virtually against other teams at any time. With the SIL simulations from dSPACE, the racing teams can further develop their AI drivers on virtual racetracks to make the cars faster, safer and more reliable. 

Continue reading dSPACE enables Indy Autonomous Challenge virtual racing at ADAS & Autonomous Vehicle International.

WorldGen-1, a multisensor generative AI foundation model designed for simulating an entire autonomous vehicle stack, has been introduced by Helm.ai, a provider of AI software for ADAS, autonomous driving and robotics.

The model has been designed to synthesize realistic sensor and perception data across multiple modalities and perspectives. It can also extrapolate sensor data from one modality to another, and predict the behavior of the ego vehicle and other agents in the driving environment. These simulation capabilities will simplify the development and validation of autonomous driving systems, according to Helm.ai.

WorldGen-1 leverages generative deep neural network (DNN) architectures and deep teaching, an unsupervised training technology.

Continue reading Helm.ai develops AI model for autonomous vehicle simulation at ADAS & Autonomous Vehicle International.