This study explores the implications of post-smart urbanism on digital mapping, with a specific focus on autonomous vehicle perception systems, centering on Lidar technology. By analyzing visual materials from industry stakeholders, it bridges the gap between engineering and cultural geography, examining the cybernetic landscapes shaping contemporary urban areas. The research critically evaluates the role of Lidar imaging in supporting an algorithmic imaginary and addresses black-boxing issues through media archaeology, filmic analysis, and a materialist examination of Lidar data elaboration. Additionally, it scrutinizes Lidar-informed spatial and temporal dynamics, highlighting potential risks associated with crowd analysis applications. Framing Lidar imaging within the context of driverless car development and urban digitalization, the study charts the discourse surrounding Lidar, analyzes the relationship between data collection and visual representation, and describes spatial and temporal constructs generated by Lidar imaging production and deployment. Methodologically, it circumvents issues of secrecy by creating an archive of ephemeral online Lidar imaging appearances, conducting content and discourse analysis, and employing video analysis to reconstruct hidden spatial geometries and temporal modulations. By positioning Lidar sensors as optical machines shaping data flows, this research contributes to geographical debates within surveillance studies, critical data studies, and the image-data complex, shedding light on issues of control and discipline within data governance.