Abstract: Powered wheelchairs provide essential mobility and independence for individuals with motor impairments, yet the skills required for driving and prevalence of safety risks, such as collisions and drop-offs, limit access for users with high levels of disability. Robotic driver assistance systems have the potential to mitigate these risks, unlocking access to powered wheelchairs for a broader population of users. This paper presents REACT, a shared control algorithm for powered wheelchairs built atop the LUCI driver assistance system, that performs minimal, deterministic control arbitration and action selection under safety constraints, and is robust to user, environment, and task variability. Additionally, we introduce a novel evaluation protocol designed to capture longitudinal, task-dependent, and user-specific effects of shared control. We implement REACT on a LUCI-equipped commercial powered wheelchair and conduct case studies using our proposed evaluation method. We find that the effects of REACT assistance vary substantially across participant impairment types, control interfaces, tasks, and timescales, and in many evaluated scenarios, lead to improved driving control input behavior. Users also consistently report positive perceptions of using the system. Our findings underscore the importance of analyzing not only task performance but also user–assistance interaction when evaluating shared control for powered wheelchairs, and additionally motivate longitudinal, multi-task assessment frameworks for assistive mobility systems.