Ett produktutvecklingsprojekt som behandlar hur problemen kring en förarmiljös formspråk, reglage och kombinationen av dessa i högre grad kan utformas på ett kognitivtergonomiskt och estetiskt vis med anknytning till varumärke. I projektet utfördes en omfattande studie över nutidens förarmiljöer där flera tydliga trender upptäcktes.  I parallellkurs utfördes ett kognitiv ergonomiskt praktikfall tillsammans med litteratur som förankrat arbetet i att forma tekniken efter människan.  Sedan har projektet fördjupat i estetiska principer och olika studier kring förarmiljöer behandlas.  Konceptframtagningen bestod av tre faser. Där det initialt togs fram en mängd övergripande formspråk. Sedan lades de åt sidan för att utforma manöverdon. Slutligen kombinerades resulterande formspråk med manöverdon till en helhet och ett slutkoncept valdes ur dem. Projektet leder fram till ett konceptförslag genom formspråk, ratt och mittreglage till förarmiljön. Konceptförslag med återkoppling till varumärket, målgrupp, kognitiv ergonomi och estetik. / A product development project that deal with the problem of how a driver environment's design language, controls, and the combination of these to a greater extent can be designed in a cognitive ergonomic and aesthetic way related to the brand. The project was carried out a comprehensive study of contemporary operator environments where several clear trends were detected. In parallel course was conducted a cognitive ergonomic case study together with literature that secured the work in shaping technology for humans. The project has immersed in the aesthetic principles and various studies on driver environments have been treated. The development concept consisted of three phases. Initially a wide range of comprehensive design language was developed. Then they were put aside to design the actuators. Finally the resulting design with actuators combined into a whole which an end concept was chosen from. The project leads to design documentation through form-language, steering wheel and center controls for a driving environment. Design documentation with feedback to the brand, audience, cognitive ergonomics and aesthetics.

Indianapolis / E-scooters are ubiquitous and their number keeps escalating, increasing their interactions with other vehicles on the road. E-scooter riders have an atypical behavior that varies enormously from other vulnerable road users, creating new challenges for vehicle active safety systems and automated driving functionalities. The detection of e-scooter riders by other vehicles is the first step in taking care of the risks. This research presents a novel vision-based system to differentiate between e-scooter riders and regular pedestrians and a benchmark dataset for e-scooter riders in natural environments. An efficient system pipeline built using two existing state-of-the-art convolutional neural networks (CNN), You Only Look Once (YOLOv3) and MobileNetV2, performs detection of these vulnerable e-scooter riders.

E-scooters are ubiquitous and their number keeps escalating, increasing their interactions with other vehicles on the road. E-scooter riders have an atypical behavior that varies enormously from other vulnerable road users, creating new challenges for vehicle active safety systems and automated driving functionalities. The detection of e-scooter riders by other vehicles is the first step in taking care of the risks. This research presents a novel vision-based system to differentiate between e-scooter riders and regular pedestrians and a benchmark dataset for e-scooter riders in natural environments. An efficient system pipeline built using two existing state-of-the-art convolutional neural networks (CNN), You Only Look Once (YOLOv3) and MobileNetV2, performs detection of these vulnerable e-scooter riders.<br>