Objectives: Multiple sclerosis (MS) is a neurological disease that commonly results in physical and cognitive dysfunction. Accordingly, MS might impact the ability to safely cross the street. The purpose of this study was to examine the feasibility of a simulated street-crossing task in persons with MS and to determine differences in street-crossing performance between persons with MS and non-MS controls. Methods: 26 participants with MS (median Expanded Disability Status Scale [EDSS] score = 3.5) and 19 controls completed 40 trials of a virtual street-crossing task. There were 2 crossing conditions (i.e., no distraction and phone conversation), and participants performed 20 trials per condition. Participants were instructed that the goal of the task was to cross the street successfully (i.e., without being hit be a vehicle). The primary outcome was task feasibility, assessed as completion and adverse events. Secondary outcomes were measures of street-crossing performance. Results: Overall, the simulated street-crossing task was feasible (i.e., 90% completion, no adverse events) in participants with MS. Participants with MS waited longer and were less attentive to traffic before entering the street compared with controls (all P <.05). Participants with MS also took longer to cross the street and were closer to oncoming vehicles when exiting the street compared to controls (all P <.05). When distracted, all participants took longer to initiate crossing, took longer to cross the street, and made more head turns while crossing (all P <.05). There were no significant group by condition interaction effects (all P >.05). Conclusions: A virtual street-crossing task is feasible for studying street-crossing behavior in persons with mild MS and most individuals with moderate MS. Virtual street-crossing performance is impaired in persons with MS compared to controls; however, persons with MS do not appear to be more vulnerable to a distracting condition. The virtual reality environment presents a safe and useful setting for understanding pedestrian behavior in persons with MS.