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Adverse weather has been recognized as an important factor to affect travelers’ activity plans in departure time, transport mode, route taken, or cancellation. In the storm, road waterlogging degrades the capacity of road networks and the service quality of transit systems, which further may affect the supply and demand for transit. Based on a typical case in Shanghai that commuters have no easy access to metro service, this paper aims to explore how transit passengers adapt to different situations in the storm and what emergency plans should be taken accordingly. Derived from the revealed preference (RP) and stated preference (SP) survey results for experienced transit commuters, a nested logit (NL) model was developed to describe the travel behavior of transit commuters. Six alternatives, Direct Bus, Bus + Bus, Metro, Bus + Metro, Taxi, and Cancel Trip, and three storm scenarios were set for transit commuters in this case. Estimated parameters indicate that, in storm weather, crowdedness is less considered by transit commuters, and transfer times, walking time, in-vehicle time, and waiting time have negative effects on the selection of the corresponding alternative, whereas the impact of taxi fare is positive since the higher fare is usually accompanied by worse weather and traffic condition. Sensitivity analysis shows that walking time to metro station, in-vehicle time, and waiting time at a bus stop are the most critical factors leading to transit ridership reduction in the storm. According to this, three possible plans for the transit operator, shuttle bus to the metro station (P1), information announcement (P2), and route adjustment (P3), are simulated and compared. We recommend adopting P2, P2 + P3, and P1 + P2 + P3 in turn with the increase of road waterlogging. These findings have important practical implications for developing transit emergency management plans and serve as references for the transit agencies and operators.

Commuting in the Storm: Adaptation of Transit Riders and Measures for Transit Operator—A Case in Shanghai