In this paper, we present a driverless taxi system for autonomous campus mobility services. College campuses have unique mobility requirements in terms of layout, population, and demand and patterns. It is typically recommended to minimize the presence of private automobiles on campuses due to teaching and research disturbances, visual degradation from parking provision, environmental pollution, and negative health effects. As an alternative to private automobiles, shared mobility systems have been considered for both campus and urban transportation. Conventional shuttle systems suffer from the first and last mile problem. A bicycle and pedestrian friendly policy is not a generalizable solution for all geographic locations and campus layouts. We suggest a driverless taxi service as an alternative point-to-point shared mobility system for campuses. We have demonstrated the feasibility of this service on a 4.5-km campus road at Seoul National University. The service has covered over 10 000 km autonomously since the first public demonstration was made in November 2015.

The dynamics of multi-agent in nature have been largely studied for a long time to investigate how the aggregation of agents can move smoothly in complex environments without collision. The main insights can be summarized such that the aggregated dynamics of animals and particles can be explained by an individual's simple rules. In a similar vein, we conjecture that such simple rules for vehicle maneuvering can accommodate the fluid flow of traffic and reduce car accidents in highway and urban areas. In this paper, we first show the Reynolds' three rules are applicable to autonomous driving on a single lane. Moreover, we provide additional requirements and algorithms for multiple lanes. Based on these results, we show that the proposed nature-inspired driving maneuver can increase traffic flow by 1) mitigating shockwave at bottlenecks and 2) extending the perception range for better path planning, which requires the support of the vehicle autonomy and wireless communication, respectively. Finally, we prove the feasibility of our work with experiments using multiple UAVs.

Although lots of research efforts have focused on group key management (GKM) for secure multicast, existing GKM schemes are inadequate for vehicle communication (VC) systems since they incur unnecessary rekeying overhead without considering the characteristics of VC systems such as Vehicle-to-Infrastructure communications and a great number of high mobility vehicles. Therefore, we propose a GKM scheme, called RSU-based decentralized key management (RDKM), dedicated for the multicast services in the VC systems. The RDKM scheme significantly reduces the rekeying overhead through delegating a part of the key management functions to the road-side infrastructure units (RSUs) and through updating the key encryption keys (KEKs) within a RSU. The performance of the RDKM scheme is analyzed in terms of communication overhead and storage overhead each of which has a strong impact on the performance of GKM. Furthermore, we propose an optimization algorithm that minimizes the weighted sum of the communication and the storage overhead, called the GKM overhead (GKMO), by appropriately determining the design parameters. The numerical results from the extensive analysis demonstrate that the RDKM scheme outperforms the existing GKM schemes in terms of the GKMO.