This paper examines alternative regulatory strategies for decarbonizing private transportation in the presence of congestion co-benefits. To capture the behavioral responses of heterogeneous households to regulation and consistently value the monetary and time costs of commuting, we integrate (1) spatial household-level data on the location of residence and work, (2) road network and traffic data from Google, and (3) household survey data on expenditure and income into a dynamic general equilibrium model which features pre-existing fuel taxes and technology choice between internal combustion engine and electric vehicles. Ignoring co-benefits, an emissions intensity standard outperforms carbon pricing because it is a smaller implicit tax on factors of production. With co-benefits, carbon pricing yields aggregate efficiency gains. Moreover, only high-income households with short- to medium-distance commutes or low congestion exposure prefer a standard over carbon pricing. Under both policies, low-income households with long commutes incur the largest costs. Our analysis suggests that carbon pricing, along with targeted measures to alleviate the burden for low-income households, can be an efficient and equitable instrument for decarbonizing private transport.