  Autonomous Vehicles (AVs) are increasingly embraced around the world to
advance smart mobility and more broadly, smart, and sustainable cities.
Algorithms form the basis of decision-making in AVs, allowing them to perform
driving tasks autonomously, efficiently, and more safely than human drivers and
offering various economic, social, and environmental benefits. However,
algorithmic decision-making in AVs can also introduce new issues that create
new safety risks and perpetuate discrimination. We identify bias, ethics, and
perverse incentives as key ethical issues in the AV algorithms' decision-making
that can create new safety risks and discriminatory outcomes. Technical issues
in the AVs' perception, decision-making and control algorithms, limitations of
existing AV testing and verification methods, and cybersecurity vulnerabilities
can also undermine the performance of the AV system. This article investigates
the ethical and technical concerns surrounding algorithmic decision-making in
AVs by exploring how driving decisions can perpetuate discrimination and create
new safety risks for the public. We discuss steps taken to address these
issues, highlight the existing research gaps and the need to mitigate these
issues through the design of AV's algorithms and of policies and regulations to
fully realise AVs' benefits for smart and sustainable cities.
