Spatially Clustered Autonomous Vehicle Malware: Producing New Urban Geographies of Inequity

Abstract

Malicious software (malware) is both a hurdle to autonomous vehicle (AV) adoption and a serious threat to AV occupant safety. Yet, to date, the topic of how subnational transportation decision makers should handle this cybersecurity threat has been underexplored. This paper describes how malware can spread through vehicle-to-X networks and infect AVs to a non-technical planning audience. It then explains how AV malware can cluster spatially in linguistic, socioeconomic, and political enclaves of American cities. Since AVs can identify new indicators of safety imperceptible to humans, malware clusters can produce new geographies of accessibility, mobility, economic, and environmental inequity across a city. In provisioning the inherently localized technical malware prevention tools available to them, subnational transportation planners have the capacity to reproduce or overcome historical and current transportation system inequities.