Towards fully-automated driving: challenges and potential solutions
There are three key drawbacks of current sensing, mapping, and localization technologies that prevent global deployment of Highly Automated Driving (HAD). Firstly, the creation of the required HAD maps is extremely complex and requires careful and time consuming human verification, making this socio-economically non-viable at global scales. Secondly, no effective technologies are available to regularly, automatically, and cost effectively update these HAD maps, although road networks and other dedicated transport infrastructures are subject to daily changes, allowing life-threatening situations. Thirdly, the HAD map is only useful when the vehicle is able to accurately position itself in this map. This requires specific sensing technologies, which are currently not robust enough to be deployed safely in all types of environments and in all types of adverse weather conditions.
The challenge to unlock the societal benefits of Highly Automated Driving is therefore to: 1) improve the scalability and robustness of HAD mapping and localization technology, and 2) make the vehicle less dependent on these HAD maps by advancing Artificial Intelligence. In this presentation, possible solutions to solve these challenges are put forward and current results are presented.Download slides