The first day of May 2025 is set to become a landmark in the history of the National Highways Authority of India (NHAI) as the Fastag Authentication System (FASTag) ends.

The FASTag electronic toll collection system in India, which uses Radio Frequency Identification (RFID) technology, was introduced to enable seamless toll payments without stopping at toll plazas. This is set to be replaced with Global Navigation Satellite System (GNSS) that will collect toll through a device, possibly fitted in the vehicle number plate. This system will calculate tolls through GPS and GPS-aided GEO Augmented Navigation (GAGAN) as per the actual distance travelled.

This will eliminate the need to pay tolls for the entire highway if one is getting off earlier. With its introduction, toll transactions are expected to see a reduction in technical glitches, helping clear long queues faster. The government of India has received feedback for a more efficient upgrade to FAStag, the bank-based digital wallet system that has been in use since 2016.

So far, users crossing a single toll plaza multiple times a month are issued monthly passes worth INR 340, which means INR 4,080 a year. On the other hand, a yearly pass for INR 3,000 is being proposed for the whole year, allowing unlimited travel across various national highways of India. As per Nitin Gadkari, Minister of Road Transport & Highways (MoRTH), GNSS with annual and lifetime passes for private cars is the solution to decongest Indian highways.

Though originally slated for 1 April, the launch of the new toll collection system has now been scheduled for 1 May. As per media reports, a better network of India’s satellites are being activated for it. GNSS will be in operation alongside FAStag during the initial stages, with select lanes receiving technology for the new system.

The trials with the new technology are already underway on Panipat-Hisar and Bengaluru-Mysore national highways.    

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Open-source autonomous driving software company TIER IV has joined the Next-Generation Edge AI Semiconductor Research and Development Programme, led by the Japan Science and Technology Agency (JST). The initiative focuses on the development of a software-defined system-on-chip (SoC) designed for Level 4 autonomous driving applications.

As part of the programme, a team led by Professor Yoshihiro Kawahara at the University of Tokyo is researching physical AI chip design based on specific use cases. Concurrently, TIER IV is developing the logic design for an AI chip aimed at processing inference for end-to-end autonomous driving systems. TIER IV plans to open-source the resulting logic design, compiler, and software toolchain to allow semiconductor manufacturers and developers to modify and build upon the hardware architecture.

The project focuses on developing hardware architectures tailored for Transformer AI models, which process sensor data from cameras and point clouds for perception and motion planning.

The chip design incorporates dedicated circuits for matrix multiplication and attention mechanisms, aiming to reduce power consumption from external memory transfers. To maintain software adaptability, TIER IV is integrating the Tensor Operator Set Architecture (TOSA) as an intermediate representation layer between AI frameworks such as PyTorch and the chip hardware.

The initiative also applies formal verification techniques to mathematically trace numerical consistency during AI model compilation.

Shinpei Kato, Founder and Chief Executive Officer, TIER IV, said, “Advances in AI have been accelerated by powerful computing platforms, including GPUs, which have enabled rapid progress across the industry. As Level 4 autonomous driving moves toward broader deployment, we believe the next step is to complement these platforms with computing architectures designed for real-world and real-time requirements. Through this initiative, we are introducing a software-defined and open approach to AI chip design that combines power efficiency, adaptability, transparency and verifiability. In particular, the ability to understand how an AI model is transformed for execution and to verify the correctness of that processing will be increasingly important as autonomous driving systems are deployed in safety-critical environments. By extending the open-source philosophy behind Autoware from software to AI chip design and related toolchains, we aim to create an open ecosystem in which automakers, semiconductor manufacturers and developers can build upon the technology and continue advancing their own systems. This represents an important step toward a scalable, adaptable and reliable computing foundation for Level 4 autonomous driving.”

Professor Yoshihiro Kawahara stated, “In physical AI applications such as robotics and autonomous driving, GPU power consumption has long been a major bottleneck for deployment on battery-powered devices. This project aims to fundamentally overcome this constraint through a functionally differentiated chip design backward-mapped from specific use cases. I look forward to TIER IV developing chips responsible for high-level decision-making – specifically, the high-level behavioural layer that handles the thinking process essential for end-to-end physical AI and autonomous driving. As the leading force behind Autoware, the global standard open-source software for autonomous driving, TIER IV is democratising design, with an approach spanning application requirements to hardware. This enables applied researchers to shape their ideal semiconductors. This initiative, supported by an open ecosystem, has the potential to lay the foundations for a steady stream of Japanese startups creating high-value semiconductors.”

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American automotive supplier Stoneridge, Inc. has announced details of its EVO ECU Platform, which will debut at IAA Transportation 2026 in Hanover, Germany.

The electronic control unit (ECU) is engineered for commercial vehicles, buses, coaches and off-highway applications to consolidate system architecture and support software-defined capabilities.

The platform replaces multiple individual control units with a centralised processing architecture designed to manage vehicle data, enable remote software updates and facilitate diagnostics.

The ECU is developed in collaboration with technology partner Renesas Electronics using its R-Car system-on-chip technology and the hardware is built to withstand operating conditions involving temperature variations, vibration and dust exposure.

Christian Leblanc, Global Vice-President of Product and Project Management, Stoneridge, said, “Commercial vehicles are becoming increasingly connected and intelligent, but traditional vehicle architectures were not designed to support the pace of innovation happening today. EVO provides a scalable platform that helps simplify integration, improve vehicle performance and give our customers the flexibility they need to adapt as technology continues to evolve.”

“Fleet customers were at the centre of our development process. EVO helps enable faster troubleshooting, fewer service interruptions and the ability to continuously improve vehicle capabilities throughout the vehicle lifecycle,” added Leblanc.

The software structure was developed alongside Green Hills Software to segregate safety-critical operations while allowing system updates. Additionally, Stoneridge partnered with indie Semiconductor to produce the platform's image processor, supporting camera integration and driver assistance systems.

Natalia Noblet, President and CEO, Stoneridge, said, “Our industry is undergoing a significant transformation, driven by increasing connectivity, automation and evolving regulatory requirements. EVO represents our commitment to helping customers navigate that transformation with a flexible platform designed to support innovation today and tomorrow.”

Aish Dubey, Vice-President and Head of the HPC SoC Division, Renesas Electronics, commented, “Stoneridge’s EVO ECU Platform demonstrates how commercial-vehicle manufacturers can modernise vehicle electronics for demanding operating environments. Our collaboration brings together Stoneridge’s commercial-vehicle expertise and Renesas’ R-Car system-on-chip, power-management and programmable mixed-signal technologies to create a scalable, automotive-grade foundation for connected and software-defined commercial vehicles.”

The system has undergone field testing within the Stoneridge Innovation Truck demonstrator vehicle, which will be exhibited alongside the platform at the Hanover trade show.

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Roppen Transportation Services, which operates under the brand name Rapido, has received an aggregator license from the Karnataka State Transport Authority under the Karnataka On-Demand Transportation Technology Aggregators Rules, 2016.

The licence authorises the platform to operate cab services in the state for a period of five years, remaining valid until August 2031.

The regulatory approval affects Rapido's operations across 21 cities in Karnataka, where the platform reports 314,000 drivers, referred to by the company as captains and over 20.4 million registered users.

According to company figures, more than 6.9 million users have taken cab rides via the platform within the state. The company's operations span urban centres including Bengaluru, Mysuru, Mangaluru, Hubballi-Dharwad, Belagavi, Davangere, Shivamogga, Ballari, Kalaburagi and Tumakuru.

Pavan Guntupalli, Co-Founder, Rapido, said, “Karnataka is our home state and one of our most important markets. Over the years, Rapido has become a trusted mobility platform for millions of customers in the state, while creating earning opportunities for lakhs of captains. We welcome the grant of the licence under the Karnataka On-Demand Transportation Technology Aggregators Rules, 2016, for cab services. This development gives us the opportunity to strengthen our cab offering within a formal regulatory framework, while continuing to work closely with the Government of Karnataka and the Transport Department to support safe, reliable and accessible mobility for commuters.”

In addition to securing the operational licence, Rapido has been included in the Urban Mobility Mission initiated by the Government of Karnataka. The initiative aims to align private platform operations with state transport priorities, focusing on multimodal connectivity, transit technology integration and transport infrastructure in urban centers.

“Rapido’s ambition is to be a long-term mobility partner for Karnataka as the state builds the next generation of urban transport. Clear and predictable regulation benefits the entire mobility ecosystem, commuters, captains, platforms and the government. Our priority is to operate in full compliance with the state framework, while continuing to strengthen safety, service reliability and meaningful earning opportunities for captains,” added Guntupalli.

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L&T Technology Services has introduced AgenticIQ, a comprehensive Agentic AI platform tailored for engineering and manufacturing sectors. The end-to-end system is designed to facilitate the shift from isolated AI experiments to full-scale operational deployment. It achieves this by enabling autonomous, multi-agent workflows that span product development, manufacturing and customer experience, thereby promoting widespread Engineering Intelligence adoption.

Despite rising corporate AI investments, many projects remain stalled at the pilot phase due to fragmented engineering systems and manual processes. Highly regulated environments further complicate scalability, as organisations struggle to balance autonomous operations with strict governance and security protocols. AgenticIQ directly addresses these hurdles by embedding a planning-first architecture into existing production workflows.

Built upon LTTS’ existing Engineering Intelligence portfolio, the platform converts proven capabilities into reusable, specialised AI agents that function within enterprise governance frameworks. It ensures the protection of critical data and intellectual property while supporting a new agentic delivery model. With a cloud-agnostic design, the platform serves R&D-heavy industries like automotive, healthcare and semiconductors, allowing clients to deploy solutions anywhere without losing control over proprietary knowledge and workflows.

Amit Chadha, Chief Executive Officer & Managing Director, L&T Technology Services, said, “The next phase of Engineering Intelligence will be defined by how effectively autonomous AI agents collaborate to solve complex industry challenges across engineering, production and customer experience. Over the years, LTTS has built AI-powered engineering solutions that address domain-specific business problems across industries. With AgenticIQ™, we are transforming these proven capabilities into reusable AI agents on a unified Agentic AI platform that enables enterprises to rapidly build, orchestrate and deploy next-generation agentic solutions at scale.”

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