The Daimler Truck Innovation Center India (DTICI) is established in Bangalore, India, as one of Daimler Truck’s largest innovation and development centers outside Germany. DTICI in Bangalore plays a pivotal role as the backbone for driving innovations and technological advancements across all brands under Daimler Truck’s umbrella worldwide, with a focused emphasis on Product Engineering and IT. Leveraging profound software expertise, DTICI spearheads the development of a dedicated Truck Operating System, showcasing its strategic importance in shaping the future of commercial vehicle technology on a global scale.
In a recent interview, Abdullah interacted with Mr. Raghavendra Vaidya, MD & CEO, DTICI in which he discussed about the future of automotive driving technology in the commercial vehicle sector, DTICI Addressing the Unique Challenges of Deploying Automated Driving Technologies in India, safety and reliability of automated driving systems in diverse Indian road conditions, AI being leveraged to enhance the capabilities of the ADAS, key benefits of implementing connected truck technology.
Could you please give me an overview of the firm and its objectives?
Well, DTICI, as we call it, is an engineering center based in Bangalore, exclusively set up to handle engineering and IT work for Daimler Truck AG. Daimler Truck AG is a global manufacturer of commercial vehicles, and we are the largest commercial vehicle manufacturer in Stuttgart for Europe and South America. Additionally, we have a business called DT&A, which is part of Daimler Truck, based in Portland, Oregon, USA, focusing on North America. We also manage operations in the Asia Pacific region and China.
The purpose of DTICI is to work on engineering for all these geographies and products. Our products vary across regions because the requirements for commercial vehicles differ by geography. Competitors, logistics industries, and market needs are unique to each area, necessitating tailored solutions. DTICI serves as the melting pot of engineering, integrating efforts across regions and products to meet these diverse demands. This is what we do here at DTICI.
What is DTICI’s vision for the future of automotive driving technology in the commercial vehicle sector?
Let me first explain that there are different levels of autonomous driving: Level One, Level Two, Level Three, and Level Four. Level Four is fully autonomous, where there is no driver. At DTICI, we predominantly work on what is known as Level Two autonomy. This involves the presence of a driver and is referred to as Advanced Driver Assistance Systems (ADAS) in the industry.
Our focus is on creating active safety systems. Unlike passive safety, which involves making the truck safer through reinforcements, braking, and other measures, active safety means the truck actively makes the environment safer. For example, if an obstacle is detected, the truck will automatically brake. Teams at DTICI work on these active safety systems.
We do not work on Level Four autonomy. For that, we have a wholly-owned subsidiary called TORC, based in the US. TORC has the mandate to create Level Four autonomous trucks. Although they are a wholly-owned subsidiary, TORC operates as an independent company, and we do not engage in Level Four autonomous trucking solutions here at DTICI.
How is DTICI Addressing the Unique Challenges of Deploying Automated Driving Technologies in India?
Well, in India, I don’t think commercial vehicles are aiming for fully autonomous operation. However, we are seeing an increasing number of features related to active assistance being integrated into trucks and commercial vehicles, such as Advanced Driver Assistance Systems (ADAS) and active braking. This trend aligns with the development of the logistics industry in India.
The highway network in India has significantly improved over the past 5 to 10 years, with the construction of four-lane and six-lane highways connecting different parts of the country. As the infrastructure improves, the opportunity to travel at higher speeds increases, necessitating safer vehicles. Consequently, there are emerging regulations mandating certain safety features.
As these regulations come into effect and the logistics industry evolves, we are incorporating active safety systems into our trucks. However, until now, we have not implemented these systems in our products in India. Predominantly, our engineers are working on products sold in North America, Central Europe, Southeast Asia, and China.
How does DTICI ensure the safety and reliability of automated driving systems in diverse Indian road conditions?
As I mentioned, we are not working on Indian products for Indian road conditions. In the Indian automotive industry, active safety and advanced ADAS systems are just beginning to emerge and are not yet widely available. Currently, our engineers are primarily focused on working on global products, such as those we sell in Europe and North America, rather than on Indian products.
How is AI being leveraged to enhance the capabilities of the Advanced Driver Assistance System (ADAS)?
We must be careful when we talk about AI because there is a distinction between AI and machine learning, and the two are different. Level two autonomous systems are predominantly deterministic systems. For example, consider a feature like lane-keeping assist, which is part of ADAS. This feature ensures that if you attempt to change lanes and it is not safe, the truck will prevent you from doing so, keeping you in the same lane even if you, as the driver, try to change lanes because it detects a vehicle approaching from behind.
There is no AI or machine learning used here; it is a completely deterministic system. It relies on radars and cameras, coupled with advanced software that determines the safety of a lane change. If it is not safe, the system controls the truck to prevent the lane change.
AI and machine learning become more prevalent and are increasingly used in level three and level four autonomous systems. In these higher levels of autonomy, the vehicle drives itself, requiring perception and sensor fusion. The system uses cameras, radars, and lidars, combining their data to decide the best way to drive the truck.
In level two autonomous systems, the technology is very close to deterministic, and we do not use much AI. However, we do use a lot of machine learning in testing scenarios. For instance, we simulate road conditions to test the software. If we want to simulate and test lane-keeping assist on a German autobahn compared to a U.S. highway, we employ machine learning systems to replicate those conditions. The software that keeps the vehicle in the same lane is deterministic; it processes sensor data and determines whether it is safe to change lanes, keeping the vehicle in the current lane if necessary.
What are the key benefits of implementing connected truck technology, such as platooning, in commercial fleets?
Well, I think connected truck technology is the future. Platooning is just one example; it is a simple method of automated driving on a highway where you have trucks following each other, maintaining a certain distance, speed, and velocity. This improves fuel efficiency, and it is a straightforward system, at least compared to the complexities of autonomous driving. However, this technology goes way beyond platooning.
Some of the active safety systems are designed to make the environment safer. These are 40-ton trucks, and they can be very dangerous. Ensuring their safety requires precise and careful engineering. The software for these systems is developed under strict frameworks and processes, undergoing extensive testing and validation, including regulatory validation, before being deployed on the road. All the active safety systems we have are very advanced, taking a significant amount of time to develop, test, and certify to ensure they are roadworthy.
Can you provide an example of how connected truck technologies have improved safety in the roads?
Take, for example, what we call predictive powertrain control. This technology comes into play when a truck is navigating a highway and encounters an upcoming traffic jam, perhaps two kilometers ahead. Unlike cars that can quickly accelerate or decelerate, trucks, given their size and weight, require more time to adjust speed. Predictive powertrain control integrates map data, terrain information, and real-time traffic updates—some processed in the cloud, some on-board the truck itself. By analyzing this data, the system anticipates the traffic congestion ahead and proactively slows down the truck well in advance. This preemptive slowing ensures that when the truck reaches the congested area, it can safely come to a stop without sudden maneuvers. This capability is crucial for maintaining road safety, especially when a heavy truck traveling at high speeds encounters unexpected obstacles like a traffic jam. By leveraging a combination of cloud-based and onboard data exchange, predictive powertrain control exemplifies how connected truck technologies enhance safety on the roads.