<p>Technological advancements have facilitated the emergence of robotaxis, which allow customers to request rides that are served by automated (i.e., driverless) vehicles. Due to the novelty of these services, and a relative dearth of publicly available information, relatively little is known about the factors influencing robotaxi demand. To address this gap, this study uses publicly available information to examine the determinants of robotaxi demand in San Francisco from September 2023 through August 2024. Specifically, pooled spatial lag models are estimated to investigate the impacts of socioeconomic characteristics, built environment attributes, points-of-interest, and transit network attributes on the monthly number of robotaxi trips starting from and ending in a given census tract. The results highlight the substantial growth in robotaxi use during the study period and suggest that the demand for these services is highest in the downtown area and areas that tend to be popular among tourists. The pooled spatial lag models suggest that land-use mix, walkability, and median income are positively associated with robotaxi demand, which echoes the results of studies on ride-hailing demand. Conversely, robotaxi demand was lower in census tracts that were classified as <i>disadvantaged</i> or <i>equity priority communities</i> and census tracts with higher population density. Overall, the results of this study offer insights into the attributes of locations where robotaxi demand tends to be higher, which provides a foundation from which the potential impacts of these services can be further analyzed. To the authors’ knowledge, this is the first study to examine the determinants of observed robotaxi demand.</p>