Robust and safe self-driving in complex and dynamic environments is quite challenging due to the requirement of scalable driving policies against the wide variety of traffic scenarios (e,g., road topologies, traffic rules and interaction with road agents). In this area, traditional modular frameworks scale poorly in new environments, and require tremendous and iterative hand-tuning of rules and parameters to maintain  performance in all foreseeable scenarios.
<coherence> Robust and safe self-driving in complex and dynamic environments is quite challenging due to the requirement of scalable driving policies against the wide variety of traffic scenarios (e,g., road topologies, traffic rules and interaction with road agents). In this area, traditional modular frameworks scale poorly in new environments, and require tremendous and iterative hand-tuning of rules and parameters to maintain  performance in all foreseeable scenarios.
Robust and safe self-driving frameworks scale poorly in new environments, and require tremendous and iterative hand-tuning of rules and parameters to maintain performance in all foreseeable scenarios.