"Friction between the road and vehicle tires plays a key role in defining how a vehicle should be controlled and maneuvered in winter conditions. To enable safe automated driving in winter, our research group is developing computer vision-based methodology for estimating the friction properties of the road. This is achieved with deep learning techniques."  Ojala Risto

”Storing electrical energy from renewable sources onboard the ship represents a promising zero-emission pathway for coastal maritime shipping. The key technical challenge for battery-electric ships arises from the extra volume and weight of the battery system, propulsion motor, and power electronics relative to combustion engines and tanks of conventional ships. Our group is developing modeling techniques to accelerate the design space exploration of novel battery-electric ship concepts. These techniques, known as convex transformations, can accelerate solution times of design problems from hours or days to only a few seconds.” Ritari Antti

"In the field of autonomous driving, targeted external perception is a key component in executing optimum control strategies to ensure the safety of vulnerable road users. The research focuses on developing an attention mechanism in the form of utilizing scene-flows to obtain moving road users in the neighborhood of an ego-vehicle in different driving scenarios. The work revolves on the underlying concepts of sensor integration, dynamic background refinement, pattern analysis and vision-based prediction models."   Jayawickrama Nilusha

"I have been a doctoral candidate in the autonomous mobility laboratory since early 2022. My research focuses on autonomous driving in adverse conditions. I specialize in solutions to mitigate weather effects such as snowfall on sensor data using deep learning tools"  Alvari Seppänen

"Detection of the drivable area in all driving conditions is extremely important for autonomous vehicles and advanced driver assistance systems. My research concentrates on drivable area detection in demanding winter driving conditions with deep learning methods. For better scalability, I try to find ways to automatize the learning process that usually requires human supervision." Alamikkotervo Eerik

Mapping in dynamic environments, produces dynamic points, adversely effecting localization. This study aims to remove the dynamic points by leveraging the observation that stationary points, over multiple scans, have a smaller convex hull volume compared to dynamic ones. Habibiroudkenar Pejman 

"Vehicular energy-efficiency plays a pivotal role in reducing the carbon footprint in the world, especially for long-haul vehicles. To achieve such energy-efficiency in hybrid vehicles, our research group is focused on developing robust controllers which decide when to use internal combustion engines and when to use electric motors fitted with electric batteries in such vehicles. The robust controllers are developed using model-based and convex optimization techniques."  Sahoo Subhadyuti