As the adoption of Intelligent Transport Systems (ITS) grows worldwide, so does the need for lost-cost, fast-deployment vehicle detection systems. SAVeD is a low-cost acoustic detection system developed by the authors which works by fitting a curve indicating vehicle passage to a sound map depicting the difference in arrival time of a passing vehicle's sound at two microphones installed on the roadside. This paper expands on the SAVeD method by proposing a Two-Stage Acoustic Vehicle Detection System for use in high-traffic environments, where multiple simultaneously and successively passing vehicles cause interference in the detection process. To solve this problem, the sound map fitting process is divided into two stages: the detection range is narrowed based on information estimated during the Pre-Fitting stage, and neighborhood point extraction is performed during the Post-Fitting stage to improve vehicle detection accuracy. Initial evaluation performed on a four-lane, two-direction road showed a vehicle detection F-measure of 0.63, a 12-point increase over SAVeD.