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Regional travel demand models are an institutionalized element of the transportation planning process, requiring a multiyear investment from collaborating agencies that rely on model outputs to assist with project prioritization and community visioning. This paper reports on lessons learned in making modest modifications to one region’s legacy planning model to consider how driverless vehicles (DVs) may affect concerns expressed by regional stakeholders. An outreach exercise suggested four congestion and emissions concerns: DVs might (1) initially reduce capacity (if operators choose comfortable acceleration rates);(2) later increase capacity (as platoons result);(3) increase travel by persons without access to a vehicle; and (4) increase zero occupant vehicles (as commuters avoid parking fees). The regional model incorporated these impacts through altering capacity, nonwork trips by persons age 65+, and commute travel. The results suggested that the concerns have different impacts on transportation performance. A capacity decrease yielded the greatest risk of congestion, increasing vehicle hours traveled (VHT) by 46% to 134%. By contrast, additional trips (to avoid parking charges) increased VHT by 22% to 30% and travel by persons age 65+ presently without access to a vehicle increased VHT by 1% to 2%. Because nitrogen oxide (NOₓ) emissions are parabolic with respect to speed, avoidance of parking charges increased NOₓ emissions by 10.8% to 1712.2% whereas a capacity reduction increased NOₓ emissions by 5% at the most. These results suggest that smaller metropolitan planning organizations can initially consider DVs …