LAUSR

Automated driving will have a big impact on society, creating new possibilities for mobility and reducing road accidents. Current developments aim to provide driver assistance in the form of conditional and partial automation. Computer vision, either alone or combined with other technologies such as radar or lidar, is one of the key technologies of advanced driver assistance systems (ADAS). The presence of vision technologies inside the vehicles is expected to grow as the automation levels increase. However, embedding a vision-based driver assistance system supposes a big challenge due to the special features of vision algorithms, the existing constrains and the strict requirements that need to be fulfilled. The aim of this study is to show the current progress and future directions in the field of vision-based embedded ADAS, bridging the gap between theory and practice. The different hardware and software options are reviewed, and design, development and testing considerations are discussed. Additionally, some outstanding challenges are also identified.