Although not as widespread as their use in other settings, there is a growing realization that distributed acoustic sensing (DAS) systems are suitable for traffic monitoring applications. One such application is demonstrated here using data from a surface DAS array recorded at Brady Hot Springs, Nevada, USA. Although this data set was acquired with the original intent of monitoring changes in a geothermal reservoir, it is shown that the data can also be used to identify and monitor vehicle movements on a nearby highway. Analysis of moveout patterns and recorded amplitudes confirm that this data set is dominated by signals generated by passing vehicles. During nighttime periods, the reduced traffic levels provide isolated signals that are more straightforward to analyze and interpret. During the day, however, increased traffic levels result in the signals from multiple vehicles overlapping to create a complex pattern of amplitudes recorded on the DAS array, making analysis and interpretation more challenging. Nonetheless, these signals can be separated and multiple vehicles identified along with their speeds and timings through the application of an automated workflow based on velocity stacking. The use of DAS for traffic monitoring purposes is an emerging technology, and despite challenges stemming from the nature of the measurement and the signals recorded, it can provide valuable information for the effective management of a transport network.