Congestion Costs and Scheduling Preferences of Car Commuters in California : Estimates Using Big Data

In this paper, we construct commuters’ travel-time profiles, namely, the menu of travel times that each individual will likely face according to alternate trip timing choices, to measure congestion delays for morning commutes in California and explore a new trip scheduling pattern of commuters under congestion. We find that commuters adapt to the congestion dynamics they face, specifically by choosing to arrive at work at an inconvenient time when they face a higher congestion level. We also confirm that the shape of our estimated scheduling utility is much steeper than commuters’ travel-time profiles, which has not been featured in the standard bottleneck analysis. Thus, we question the accuracy of the existing bottleneck models in quantifying the economic costs of congestion and the optimal toll to ameliorate congestion