“Our work revolves around two key areas—engineering and IT (information technology). Within engineering, we focus on two major pillars: conventional mechanical engineering (chassis, cabin, aerodynamics and computer-aided engineering, or CAE) and software and electronics, which power our trucks and buses,” Raghavendra Vaidya, managing director and chief executive officer (CEO) of DTICI, told Mint in a recent interview.
DTICI, according to Vaidya, has been investing in IT infrastructure since its separation from Mercedes-Benz in 2021. It is also using data analytics and AI, and exploring GenAI “not just for the sake of technology, but to solve business problems.”
What are software-defined vehicles?
It’s not that Daimler Truck no longer sees value in hardware improvements. “We are still working on aerodynamics, fuel efficiency and on reducing emissions for our diesel trucks, which is all hardware,” Vaidya said. But implementing new truck features often requires hardware changes, which at times can even take up to three years, limiting the ability to innovate fast. SDVs, on the other hand, promise to change this by decoupling software from hardware, allowing for rapid, over-the-air updates like it’s done in smartphones.
The key challenge, of course, is balancing cost and value. “The hardware platform cost must decrease, while software-driven features—such as cross-traffic assist—will bring additional value,” Vaidya said. “Whoever wins this (SDV) battle will be able to make their trucks more valuable for customers, and acquire a competitive advantage.”
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Vaidya underscored the “crucial role” of the group’s joint venture (JV) with Volvo in this software transformation. Last May, Daimler Truck and Volvo announced a 50:50 JV to develop a common SDV platform and dedicated truck operating system. “Volvo will deliver a next-generation hardware and software platform, allowing both companies to customize their applications while maintaining a common foundation,” he explained. The company recently launched its next-generation electrical/electronic (E/E) architecture—a system that connects in-vehicle electronic control units (ECUs), sensors, actuators, etc.,—and is “now developing SDVs, set to hit the market early next decade,” Vaidya said.
As vehicle manufacturers like Daimler Truck, Volkswagen, BMW, Hyundai, Renault, Stellantis and Mercedes-Benz transition towards SDVs, the market for such vehicles is expected to grow from $213.5 billion in 2024 to $1.23 trillion by 2030, according to Research and Markets.
Further, with improved connectivity (3G to 4G, and now 5G), trucks are being constantly linked to the internet through a telematics system. This system helps monitor and manage truck performance in real time. With “nearly 90 mini-computers onboard,” Daimler Truck likens it vehicles to “data centres on wheels”, continuously streaming data—about 30 billion messages are processed by the connectivity platform every month.
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However, while this introduces benefits like remote diagnostics and updates, it also creates major cybersecurity risks. Since trucks send and receive data—sometimes even controlling vehicle functions—they must be protected like data centres. The risks are real, but with proper security, they can be managed, according to Vaidya, which makes cybersecurity another critical focus area for the group.
Use of AI, GenAI
DTICI is also integrating AI into software development, using tools like GitHub Copilot to boost coding efficiency. “It’s improving developer productivity, though we’re still measuring the exact impact,” Vaidya said. He added that AI is also aiding contract analysis and product documentation, reducing complexity for new employees. “We recently introduced the RAG (Retrieval-Augmented Generation) architecture with OpenAI’s GPT-4.0 model, integrating it into our embedded software development process,” Vaidya said.
Currently, this move is helping the company generate test cases. Product documentation is another example since “many of our products are built to order, each one comes with extensive documentation”, according to Vaidya. New after-sales and sales team members often find it overwhelming to navigate. To address this, DTICI has implemented RAG to ensure that proprietary data remains private, not permitting OpenAI to access it for training. This allows engineers to ask questions like, “A customer wants this variant—is there something similar?” The system then retrieves relevant information, making it easier to find answers quickly.
To maintain accuracy, DTICI has set the hallucination (when an AI model confidently provides false information) index to zero, limiting the model’s responses. “This also makes us hesitant to adopt a more autonomous agent-based model. Our goal is to augment engineers, not replace them,” Vaidya said. Hence, even with tools like GitHub Copilot, all AI-generated code and text are still reviewed by engineers.
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In production, Daimler uses robotics “selectively” because the trucks need a lot of customisation. It is also working with digital twins and machine learning models to improve efficiency. DTICI also partners with institutions like the Indian Institute of Science (IISc) and the Indian Institute of Technology (IIT) Bombay on research projects, including battery chemistry and simulation techniques. “We’re also setting up two dedicated research labs—one for hardware, another for software. Beyond research, we engage with academia through tear-down workshops, expert lectures, and mentorship programs. There’s no formal course on assembling an electric truck or hydrogen combustion engines. Our experts help bridge that gap by sharing real-world insights with students,” Vaidya explained.
Future of transportation
Vaidya believes the future of transportation involves hydrogen trucks, autonomous driving, and evolving connectivity. “I wish we knew exactly where to place our bets, but the reality is, the industry is evolving rapidly,” he added.
For now, DTICI is focusing on Advanced Driver Assistance Systems (ADAS), specifically Level 2 automation. This includes features like lane-keeping assist, emergency braking, and cross-traffic assist. “We don’t believe in Level 3 automation (where the vehicle can drive itself in certain conditions but still needs a human driver to take over when required) but strongly support Level 4, particularly for hub-to-hub operations on highways,” Vaidya said.
He added that this effort is being led by US-based Torc Robotics—a Daimler Truck unit. “We provide them with trucks equipped with Level 2 software and electronics, and they (Torc Robotics) integrate additional hardware—sensors, actuators, and computing systems—to achieve Level 4 automation,” he explained.
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Daimler Truck has also partnered with Waymo, a unit of Alphabet Inc., to equip its trucks “with radars, cameras, and computing technology”. Waymo’s goal is to operate these trucks as a service, renting them to fleet operators on a per-kilometer basis, with a portion of the revenue shared with Daimler, according to Vaidya.
According to him, “while full autonomy is still years away due to various challenges, we believe hub-to-hub automation is achievable”. Vaidya reasoned that while many of the necessary technologies—adaptive cruise control, lane changes, braking, and acceleration—already exist, removing the driver entirely is a significant step. “But at Level 4, there is no onboard driver, only potential remote intervention to guide the truck to safety when needed. While this vision will take time to materialize, we are committed to making it a reality,” Vaidya concluded.
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