We present a routing paradigm called PBR that utilizes steepest gradient search methods to route data packets. More specifically, the PBR paradigm assigns scalar potentials to network elements and forwards packets in the direction of maximum positive force. We show that the family of PBR schemes are loop free and that the standard shortest path routing algorithms are a special case of the PBR paradigm. We then show how to design a potential function that accounts for traffic conditions at a node. The resulting routing algorithm routes around congested areas while preserving the key desirable properties of IP routing mechanisms including hop-by-hop routing, local route computations and statistical multiplexing. Our simulations using the ns simulator indicate that the traffic aware routing algorithm shows significant improvements in end-to-end delay and jitter when compared to standard shortest path routing algorithms. The simulations also indicate that our algorithm does not incur too much control overheads and is fairly stable even when traffic conditions are dynamic.