The advent of autonomous and ubiquitous co-robot technologies presents an opportunity to recalibrate current automobile transportation infrastructure in dense urban cores. This research investigates the trade-offs between navigation safety, functionality, and experiential conditions to understand the impact of driverless vehicles on urban design. The result will be a framework of forecast scenarios to advise urban designers, policymakers, stakeholders, and the autonomous vehicle industry on critical factors to consider when deploying these technologies. The research examines how cities can leverage upcoming mobility technologies to retrofit late-nineteenth-century automobile transportation infrastructure into human infrastructure for the twenty-first century. This excerpt establishes a system for using passive landscape objects as reference points to improve the navigation ability of driverless cars while addressing environmental issues like Urban Heat Island. The research builds a technical framework based on current driverless technologies and IIT's interdisciplinary Driverless City project methodology to understand the limitations of GPS availability and landmarkbased navigation. The final component incorporates speculative scenarios to increase the localization safety of autonomous cars by using landscape objects in a binary error-correcting code in State Street (Chicago). The results of these scenarios suggest an increase in landscape elements as landmarks that can be translated into an increase in canopy coverage, maximizing the benefits of the urban tree canopy. By employing our findings in a 3D simulation of State Street, we determined that our system improves not only navigation accuracy but also environmental benefits like outdoor thermal comfort.