Attention-deficit/hyperactivity disorder (ADHD) is a commonly diagnosed neuro-developmental disorder that is chronic, persists into adulthood, and causes impairment in social, educational, and occupational functioning. While the educational and social impairments of ADHD are well understood, far less is known about the occupational impairments that affect young adults with ADHD, who are known to earn less and change jobs more frequently than their typical peers. Thus, it is vital to understand the type and intensity of functional problems within workplace settings with a goal of reducing occupational impairment. To analyze this critical human performance deficiency, we have developed an analog single-Laboratory restaurant setting: a hybrid Live-Virtual “pizza place� training environment. A total of forty-nine young adults (24 ADHD, 25 Typical) were recruited to participate in a simulated workday doing typical job tasks: receive food requests, provide customer service (using confederates), prepare food orders, plan the most efficient driving route to make food deliveries, “deliver� the orders, and make appropriate change, and settle up finances once “returned� to the restaurant. Stated tasks require working memory, sequencing, sustained attention, direction-following, cognitive flexibility, and problem-solving. To identify specific areas of impairment for food order deliveries, we have computationally modeled a residential neighborhood to be endeavored upon a high-fidelity driving simulator. During the delivery cycle, the efficiency of the route, an evaluation of correct delivery and money management, and quantifiable simulator metrics (e.g., speeding, failure to stop at signs and signals) are observed as dependent variables. We likewise solicit feedback on the fidelity/usability of the analog setting (i.e., user experience), including suggested improvements for future work. In this paper, our discussion will emphasize critical Modeling & Simulation (M&S) engineering details of the simulator environment design and implementation. Likewise, our multi-measure data analysis methods will focus on measuring human performance and effectiveness within the Live-Virtual environment, and comparing preliminary observations from both cohorts.