Abstract

This study integrates welfare, a measure of the impact of road network disruption on individual commuters' well-being, with a probabilistic seismic risk assessment framework in a computationally tractable way. Welfare is a network performance measure that reflects the differential impacts of changes in commute time on various groups. For a case study of the San Francisco Bay Area, welfare loss is computed by augmenting an origin-destination matrix with publicly available information about commuters' income levels, residences, and workplaces. While commuters from all income groups have similar risk of drivers' delay due to road network disruption, commuters with low incomes have a substantially higher risk of welfare loss than those with high incomes. A comparison of bridge retrofit policies shows that disaggregation of welfare loss by income group is necessary to examine whether such policies reduce risk equitably. While a retrofit policy determined using drivers' delay reduces the expected drivers' delay, it increases the disparity in the per-capita welfare loss of commuters with low and high incomes relative to the network's baseline state. In contrast, a retrofit policy that prioritizes low-income commuters reduces the difference in welfare loss of commuters with low and high incomes compared to the baseline network state.