The vehicular sensor network (VSN) is emerging as a new solution for monitoring urban environments such as intelligent transportation systems and air pollution. One of the crucial factors that determine the service quality of urban monitoring applications is the delivery delay of sensing data packets in the VSN. In this paper, we study the problem of routing data packets with minimum delay in the VSN by exploiting 1) vehicle traffic statistics, 2) anycast routing, and 3) knowledge of future trajectories of vehicles such as busses. We first introduce a novel road network graph model that incorporates the three factors into the routing metric. We then characterize the packet delay on each edge as a function of the vehicle density, speed, and the length of the edge. Based on the network model and delay function, we formulate the packet routing problem as a Markov decision process (MDP) and develop an optimal routing policy by solving the MDP. Evaluations using real vehicle traces in a city show that our routing policy significantly improves the delay performance compared with existing routing protocols. Specifically, optimal VSN data forwarding (OVDF) yields, on average, 96% better delivery ratio and 72% less delivery delay than existing algorithms in some areas distant from destinations.