In intensity-modulated radiotherapy (IMRT), the quality of the treatment plan, which is highly dependent upon the treatment planner's level of experience, greatly affects the potential benefits of the radiotherapy (RT). Furthermore, the planning process is complicated and requires a great deal of iteration, and is often the most time-consuming aspect of the RT process. In this paper, we describe a methodology to automate the IMRT planning process in lung cancer cases, the goal being to improve the quality and consistency of treatment planning. This methodology (1) automatically sets beam angles based on a beam angle automation algorithm, (2) judiciously designs the planning structures, which were shown to be effective for all the lung cancer cases we studied, and (3) automatically adjusts the objectives of the objective function based on a parameter automation algorithm. We compared treatment plans created in this system (mdaccAutoPlan) based on the overall methodology with plans from a clinical trial of IMRT for lung cancer run at our institution. The 'autoplans' were consistently better, or no worse, than the plans produced by experienced medical dosimetrists in terms of tumor coverage and normal tissue sparing. We conclude that the mdaccAutoPlan system can potentially improve the quality and consistency of treatment planning for lung cancer.