When most people imagine self-driving cars, they think of Silicon Valley highways or city streets packed with sensors and traffic lights. But the bigger challenge may be in rural America, where nearly half of roadway fatalities occur despite carrying far less traffic. At the University of Wisconsin–Milwaukee (UWM), Muhammad Fahad is working to bring autonomy to these overlooked environments as part of the $15 million TRAVELS Center (Tribal and Rural Autonomous Vehicles for Efficiency, Livability, and Safety), funded by the U.S. Department of Transportation.
UWM, which manages a $1.4 million share of the grant, is focused on adapting self-driving technologies to roads with limited infrastructure, harsh weather, and unique mobility needs. Muhammad Fahad leads the design of scaled AV testing platforms, simulating rural conditions and evaluating how perception and control systems respond where reliability matters most.
1) Please tell us more about yourself.
My name is Muhammad Fahad, and I’m a graduate research assistant at the University of Wisconsin–Milwaukee. My expertise lies in artificial intelligence, robotics, and intelligent transportation systems, with a focus on making autonomy safe and practical. At UWM, I design and lead projects that integrate AI-based perception with experimental testing. My role in the TRAVELS Center is to build and validate scaled autonomous vehicle platforms that replicate rural driving challenges, bridging the gap between lab development and real-world deployment.
2) What inspired you to focus on rural autonomy?
Muhammad Fahad: Rural roads are often invisible in technology discussions, yet they account for a disproportionate number of serious crashes. Long, dark stretches with no lighting, gravel roads, faded markings, and limited emergency response make accidents more dangerous than in cities. At the same time, mobility options for rural residents especially seniors and tribal communities are extremely limited. I wanted to focus my skills where the need is greatest. Autonomy should not be a luxury for urban centers; it should be a tool for equity and safety everywhere.
3) What makes rural environments harder for AVs than cities?
Muhammad Fahad: In urban areas, AVs benefit from dense infrastructure: connected traffic signals, clear lane markings, and high-definition maps. Rural environments often lack those supports. You can have long stretches of road with no markings, patchy GPS or cellular coverage, and conditions like snow, fog, or sudden wildlife crossings. Farm equipment may appear unexpectedly, and many roads are completely unlit at night. For autonomy to work here, vehicles must be able to operate safely even with incomplete or unreliable data. That resilience is what we are testing.
4) How do you conduct this research in practice?
Muhammad Fahad: I lead the design of 1/10th-scale robotic cars that model rural driving in controlled environments. These vehicles are equipped with panoramic cameras, inertial sensors, and RTK-GNSS, and they stream telemetry in real time. We run them through scenarios like GNSS dropouts, low-light highways, foggy intersections, and unmarked roads. I also develop the algorithms that process the data combining YOLO-based detection, DeepSORT tracking, and trajectory analysis to evaluate how the vehicle “perceives” and reacts. This approach lets us test edge cases safely and affordably before larger field pilots.
5) What challenges stand out as the toughest so far?
Muhammad Fahad: Two stand out. The first is perception in poor visibility cameras and sensorsDriving struggle when there’s no lighting or when snow and fog obscure the scene. The second is connectivity: AVs must continue to function safely even if GPS or cellular coverage drops out. Designing for those realities is far harder than programming for a city street. And beyond the technical side, we also need to build trust. Rural communities may be cautious about adopting AVs, so the technology must prove itself as both safe and reliable.
6) How do you see this research benefiting people in rural and tribal areas?
Muhammad Fahad: The impact is very human. For a senior living mile from the nearest doctor, an autonomous shuttle could mean access to healthcare without depending on family. For tribal communities, shared AV services could improve access to schools, jobs, and groceries. And for all rural drivers, advanced driver-assistance features tuned for unlit highways and gravel roads could prevent life-threatening crashes. This isn’t just about convenience it’s about safety, mobility, and equity.
7) What role do you personally play in the TRAVELS Center project?
Muhammad Fahad: I am responsible for creating the scaled AV testbed and experimental framework at UWM. That means I design the hardware platform, program the control systems, run the test scenarios, and build the data pipeline that analyzes results. I also work with local county partners to make sure our test cases reflect real-world conditions. My role is to ensure the research is not just theoretical, but reproducible and directly useful to communities and agencies.
8) What’s next in the project timeline?
Muhammad Fahad: We’re moving toward pilot demonstrations. The scaled testing results will feed into larger deployments in rural counties. I am also developing toolkits for local governments and tribal agencies, so they can evaluate AV systems independently before investing in them. Our goal is to make these tools accessible, affordable, and scalable, so rural communities can adopt autonomy with confidence.
9) Where do you see rural autonomy five years from now?
Muhammad Fahad: I believe rural autonomy will evolve into a public utility. Shared AV shuttles could provide essential mobility for seniors and nondrivers. Collision-avoidance and emergency response systems will make rural highways safer. And counties will have simple frameworks to test technologies before rollout. In five years, I hope to see rural and tribal communities leading in adoption, showing that autonomy is not just for high-tech cities but for every community that values safety and access.
10) What motivates you personally to pursue this work?
Muhammad Fahad: For me, engineering is most meaningful when it addresses real human needs. Rural safety statistics aren’t just numbers they represent families and lives impacted by preventable accidents. Knowing that my work can reduce those risks and give mobility back to people who currently have few options, is what drives me. I see autonomous technology not as a futuristic luxury, but as a tool to create fairness and safety where it’s needed most.
Media Contact
Muhammad Fahad •
https://www.linkedin.com/in/iamfahadusa/
Website: https://www.fahadmuhammad.com/
