  Smart Cities and Communities (SCC) constitute a new paradigm in urban
development. SCC ideates on a data-centered society aiming at improving
efficiency by automating and optimizing activities and utilities. Information
and communication technology along with internet of things enables data
collection and with the help of artificial intelligence (AI) situation
awareness can be obtained to feed the SCC actors with enriched knowledge. This
paper describes AI perspectives in SCC and gives an overview of AI-based
technologies used in traffic to enable road vehicle automation and smart
traffic control. Perception, Smart Traffic Control and Driver Modelling are
described along with open research challenges and standardization to help
introduce advanced driver assistance systems and automated vehicle
functionality in traffic. To fully realize the potential of SCC, to create a
holistic view on a city level, the availability of data from different
stakeholders is need. Further, though AI technologies provide accurate
predictions and classifications there is an ambiguity regarding the correctness
of their outputs. This can make it difficult for the human operator to trust
the system. Today there are no methods that can be used to match function
requirements with the level of detail in data annotation in order to train an
accurate model. Another challenge related to trust is explainability, while the
models have difficulties explaining how they come to a certain conclusion it is
difficult for humans to trust it.
