The essential need to maintain roadway structures makes encountering work zones an inevitable part of today’s driving. The corresponding changes in traffic dynamics directly affect the drivers’ mobility and safety. Accordingly, a closer look into driver’s interaction with work zones’ geometrics and activity features may be helpful. The overall objective of this study is to examine the longitudinal characteristics of driver behavior in different work zone conditions. Based on existing literature, the variables defining these work zone conditions were specified as the work zone length, the barrier type and the level of activity. Eight different scenarios were designed by changing these three variables in a driving simulator and 40 trajectory data sets were recorded. Using a genetic algorithm, these data sets were used to calibrate a prospect theory-based acceleration model. The calibrated parameter values helped quantify the driver’s perception of the surrounding environment, his/her risk-attitudes and the corresponding judgment process.