In geographic routing, nodes need to maintain up-to-date positions of their immediate neighbours for making effective forwarding decisions. Periodic broadcasting of beacon packets that contain the geographic location coordinates of the nodes is a popular method used by most geographic routing protocols to maintain neighbour positions. We contend that periodic beaconing regardless of network mobility and traffic pattern does not make optimal ulilisation of the wireless medium and node energy. For example, if the beacon interval is too small compared to the rate at which a node changes its current position, periodic beaconing will create many redundant position updates. Similarly, when only a few nodes in a large network are involved in data forwarding, resources spent by all other nodes in maintaining their neighbour positions are greatly wasted. To address these problems, we propose the Adaptive Position Update (APU) strategy for geographic routing. Based on mobility prediction, APU enables nodes to update their position adaptively to the node mobility and traffic pattern. We embed APU into the well known Greedy Perimeter Stateless Routing Protocol (GPSR), and compare it with original GPSR in the ns-2 simulation platform. We conducted several experiments with randomly generated network topologies and mobility patterns. The results confirm that APU significantly reduces beacon overhead without having any noticeable impact on the data throughput of the network. This result is further validated through a trace driven simulation of a practical vehicular ad-hoc network topology that exhibits realistic movement patterns of public transport buses in a metropolitan city.