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

Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities