The development of autonomous vehicles and smart transportation systems rapidly up the digital transformation processes in the transportation sector. The initial trials of such transformations could be easily facilitated on campus sites due to a noncomplex and safe environment compared to city centres. Integrating digital technologies into campus infrastructure will improve transportation efficiency and the overall user experience, especially for students, faculty, and visitors. It will also provide a test environment for developing and utilizing the latest technologies related to autonomous vehicles and intelligent transportation systems. One of the crucial components of this transformation is the generation of a High-Definition Map (HD Map) that is essential for autonomous vehicles to interact with their surroundings, as they allow them to navigate safely and accurately. Hence, this study aims to facilitate the safe and efficient operation of autonomous vehicles on campus roads by facilitating HD maps. Data acquisition is a critical step for this production, where the necessary data is obtained through mobile mapping systems. These are generally vehicles equipped with a Global Navigation Satellite Systems receiver, panoramic camera, Inertial Measurement Unit, Light Detection and Ranging device, and odometer sensors. For this study, the Ayazağa Campus of Istanbul Technical University served as the pilot area for data acquisition using such a novel system. The data obtained from this process include point cloud data, panoramic photos, 3D coordinates, and timestamps for each point. 4267 panoramic photos and 55 point cloud data (60 million points per file) were collected along a road network of about 19 kilometres. However, some challenges remain, such as the vast amount of data, different types of data, and data fusion. These challenges, possible solutions, and lessons learned will be discussed in this paper. Overall, aiding the operation of driverless vehicles represents an important step towards a smart campus. The digital infrastructure generated through this study will serve as a model and a test field for other campuses and cities that will follow a similar approach to improve the overall transport experience for their users.