This article provides an overview of the use of inertial and visual sensors and discusses their prospects in the Arctic navigation of autonomous vehicles. We also examine the fusion algorithms used thus far for integrating vehicle localization measurements as well as the map-matching (MM) algorithms relating position coordinates with road infrastructure. Our review reveals that conventional fusion and MM methods are not enough for navigation in challenging environments, like urban areas and Arctic environments. We also offer new results from testing inertial and optical sensors in vehicle positioning in snowy conditions. We find that the fusion of Global Navigation Satellite System (GNSS) and inertial navigation systems (INSs) does not provide the accuracy required for automated driving, and the use of optical sensors is challenged by snow covering the road markings. Although extensive further research is needed to solve these problems, the fusion of GNSS, INSs, and optical sensors seems to be the best option due to their complementary nature.