Vehicular content downloading via open WiFi access points (APs) can be challenging due to sparse AP deployment with bounded communication range and the rapid movement of traveling vehicles. For drive-thru networks, resource allocation and scheduling closely interrelate to and interact with each other, collectively affecting the performance of content downloading. However, none of the previous work has tackled this problem as a whole. This paper discusses joint resource allocation and scheduling problem for efficiently content downloading considering channel contention and scarce AP resource utilized effectively. It formalizes optimization selection problem of node set to maximize the total quantity of data downloaded, and proves that it is NP-hard. Further, it presents a solution with a joint resource allocation and scheduling approximate algorithm (JAS). Theoretical analysis and simulation results both verify that the presented implementation achieves higher throughput and delivery ratio than the existing algorithms.