Specialized in optical systems, Zehra Adil worked in lasers, vision & thermal cameras for the defence industry before moving to Magna Electronics (former Veoneer).
Originally from Turkey, Zehra was headhunted to move to Sweden. “A decision that changed her life,” as she puts it. She started as a technical coordinator in optical testing and now works as a Research and Innovation Leader. In the company, she has already managed several concepts related vehicle sensing, such as cameras, lidars, radars, and sensors both inside and outside of the car cabin. She is also representing Magna Electronics in MobilityXLab – a collaboration hub that enables right matching between automotive companies and brilliant start-ups like a bridge, connecting startups with companies.
Zehra likes looking at the big picture and offers us her futuristic view on autonomous driving.
I have heard that you are very proud of the MobilityXLab initiative. How important are these types of collaborations in your industry, and what do you expect in the future?
The culture is changing to embrace more collaboration. Previously, the top OEMs, which are the Original Equipment Manufacturers of cars under their own brand names, used to decide and specify the requirements for certain car components. They would approach companies asking, ‘Can you do this for us?’ However, now they are asking, ‘What do you have to offer? What ground-breaking advancements do you have in your hands?’ The industry is becoming more open to innovation. For example, we are seeing lots of opportunities and new ideas coming through startups, and MobilityXLab promotes these interactions. This is because of the exponential changes in the field; we are more likely to work together and make decisions collectively. Collaboration is important, but it is even more crucial to find the right match.
Speaking of collaborations, what is your view on the GRAPH-X project?
GRAPH-X provides a great opportunity for us to work with academic and industrial collaborators. My former colleague, Olof Eriksson, had the idea to use fiber optics cables for both communications and radar signals, and we want to test its feasibility. Currently, from the Magna team, I am working together with Carina Marcus and Victor Pettersson. We have a strong team 😊
Could you tell us more about it?
Our aim is to address short-range sensing both inside and outside of the vehicle. We aim to achieve comprehensive 360-degree coverage around the car. In the automotive industry, it is common to use one forward-looking radar and four corner radars to gather information about the vehicle’s surroundings. However, this approach presents a couple of challenges. Firstly, it incurs high costs. Secondly, aligning these radars mechanically to simulate a single source with a 360-degree view is not possible, and methods based on software algorithms introduce errors. To overcome these challenges, GRAPH-X introduces a coherent signal approach with multiple antennas behaving as one, acting like a single source. Our role is to provide the requirements and specifications, contribute to the prototype and demo testing, and continue market monitoring and dissemination activities.
Since you mentioned market monitoring, let me ask you: What are the needs that the automotive industry wants to address?
Doing market monitoring in this area, one can appreciate that needs come quite naturally. Imagine a situation where someone falls on the road or an animal suddenly crosses the road, requiring you to brake abruptly. It is natural for a driver to want to inform others. At the moment, people can signal danger with their head beam lights or hazard lights. But wouldn’t it be great if we could inform the other in a more accurate way? This is where the concept of car-to-car communication comes into play: collective perception means that cars can sense and share what they observe. If a car senses a potential risk, this information can be made available to other cars.
Turning our attention to in-cabin applications, monitoring the driver’s position and behaviour will be useful for self-driving cars. We can determine whether the driver is engaged, has their hands on the wheel, or if they’re distracted. Even in a full autonomous car, we might want to change between the driver driving and autonomous driving, and the car could estimate if the driver is engaged and able to get the control. Furthermore, we can ensure seatbelt usage and monitor the number of occupants in the car. This information becomes invaluable in post-accident scenarios, as it can activate emergency calling systems. Additionally, for normal driving, it helps optimize seat heating, in-cabin settings, and airbag deployment.
Child detection in vehicles is another critical aspect. Sometimes, parents may unintentionally leave their child in the car, leading to potentially tragic consequences. By issuing warning alerts and taking appropriate measures, like opening the windows, we can protect the child from harm. Similar concerns arise for pets, such as cats and dogs, which may be left inside cars. People often underestimate the risks, assuming the animals will be fine.
Additionally, we can now collect health-related information, such as breathing rate and heartbeat. To further enhance this concept, we can leverage in-cabin technology. As most of us use cars daily, we can now monitor the cabin and the people inside it. By doing so, we can easily detect any changes or anomalies related to our health, such as skin conditions. For instance, if a disease manifests on the skin, our monitoring system can alert us to seek medical attention. While we don’t aim to diagnose medical conditions, this continuous monitoring can provide recommendations to the driver or occupants, urging them to consult a healthcare professional. Moreover, this data can be utilized for various purposes, such as developing an occupancy health system.
Monitoring the status of cabin doors and windows is equally important. When doors or windows are open, the car’s software needs to be aware of it. Achieving all these functionalities brings complexity to our systems. However, as we strive towards autonomous driving, we are simultaneously developing algorithms that mimic the human brain. These algorithms need to comprehend which doors are open and detect any unusual occurrences that may indicate potential problems.
Thank you for your visionary outlook into the future of the automotive industry!