Both stochastic and gradual sea level rise (SLR) from anthropogenic climate change threatens coastal communities and infrastructure world-wide. The major consequences of SLR to shoreline highway systems are twofold: 1) a degraded supply of transportation infrastructure; and 2) travel demand reduction induced by land/infrastructure flooding. There have been several recent and important studies of region-scale impacts of SLR on transportation systems and travel. These previous studies unilaterally use excessive delay to measure network degradation, which is effective only in large-scale areas. In this study, we introduce a trip-based assessment process to quantify the SLR impact on fine-scale urban highway networks. By integrating highway network models with SLR flood data and microscopic land use data, we built scenarios representing changes on both the demand and supply sides of travel. We used micro-simulator Simulation of Urban MObility (SUMO) to model traffic interactive outcomes. We defined the trip-based exposure and accessibility indices to aggregate the simulation output into zonal performance measures. We applied this method to two typical urban highway networks in the San Francisco Bay Area, California: 1) the waterfront zone of Suisun City, which is primarily composed of a small urban area accessed along the inland edge from a state highway that has a low probability of being affected by SLR within 50 years; 2) and the City of San Rafael, which includes both urban and freeway segments likely to flood from SLR within 50 years. We found different patterns of SLR impacts on travel on each highway network. In Suisun City, the impact was demand-dominant, meaning that the land inundation causes more significant travel demand reductions than travel time increases from highway flooding. In San Rafael, the impact is supply-dominant, showing that the disrupted highway corridors result in more significant accessibility reduction than exposure induced travel demands reduction. Meanwhile, results from San Rafael network also demonstrated significant benefits of vertically adapting the freeway corridor for local and commuting travelers. This modeling approach could be used in any shoreline city or developed area to predict potential changes in travel time and supply of open highways.